SECTION 7 DESIGN & MANUFACTURING

SECTION 7

DESIGN & MANUFACTURING

ASME District F - ECTC 2013 Proceedings - Vol. 12 223


ASME District F - Early Career Technical Conference Proceedings ASME District F - Early Career Technical Conference, ASME District F – ECTC 2013

November 2 – 3, 2013 - Birmingham, Alabama USA

INVESTIGATION INTO THE BENEFITS OF USING ASME BPVC SECTION VIII DIVISION 2 IN LIEU OF DIVISION 1 FOR PRESSURE VESSEL DESIGN

James William Becker Burns & McDonnell

Kansas City, Missouri, USA

ABSTRACT ASME Boiler and Pressure Vessel Code Section VIII

Division 1 [1] is one of the most commonly used pressure vessel codes in the world. The Division 1 rules were originally written before the age of computers; they were intended to be solved by simple hand calculations. This simplification led to rules with a high safety margin and a conservative technical basis. In 2007, ASME published a completely rewritten edition of ASME BPVC Section VIII Division 2 [2], intended to lower the safety margin by introducing more complex, technically accurate pressure vessel design rules, and make the Code more cost-competitive in an international market.

The Division 2 Code saves the user money on materials with the use of higher allowable stresses and more accurate design formulas. However, in order to justify the increase in allowable stress, Division 2 mandates additional NDE and a Professional Engineer’s stamp, which raise the vessel price. At a certain thickness, the material savings outweigh the additional cost, and Division 2 becomes cost-effective. Six years after publication of the new Division 2, the industry has yet to identify the thickness at which the transition from Division 1 to Division 2 becomes cost-competitive. Division 2 is still most commonly used only for very high pressure, high thickness applications. This investigation compares Division 2 to Division 1 to determine a reasonable set of design conditions by which Division 2 will yield a more cost-effective pressure vessel, even on some lower pressure applications.

NOMENCLATURE = weld consumable cross section area

ASME = American Society of Mechanical Engineers BPVC = Boiler and Pressure Vessel Code

= corrosion allowance = vessel diameter = joint efficiency

°F = degree Fahrenheit FEA = finite element analysis ksi = 1,000 x psi MDR = manufacturer’s data report MT = magnetic particle testing NDE = non-destructive examination

= design pressure

psi = pounds per square inch PE = Professional Engineer

= vessel radius RT = radiographic testing

= allowable stress = safety factor on tensile strength = safety factor on yield strength

= minimum required thickness = Division 1 calculated minimum thickness = Division 2 calculated minimum thickness ∆ = change in thickness due to Division 2 = design temperature = allowable tensile stress = minimum tensile strength

UT = ultrasonic testing = minimum cost effective weight

= allowable yield stress = minimum yield strength at design temperature

BACKGROUND Pressure vessels, boilers and other pressurized equipment

can contain an abundance of energy and can be dangerous should one fail. Prior to pressure vessel and boiler safety laws, boiler explosions claimed thousands of lives. The single worst maritime disaster in the history of the United States occurred in 1865 when the boiler on the steamboat Sultana exploded, killing more than 1,600 of the 2,300 Union prisoners of war on board. [3] The Sultana explosion was more deadly than the sinking of the Titanic in 1912. At the beginning of the 20th century there were over 1,200 deaths caused by more than 1,600 boiler explosions in the United States. [4] In 1905, at the climax of the boiler explosions, the R.B. Grover & Company Shoe Factory’s boiler exploded, killing 58 and injuring 150 in Brockton, Massachusetts. [5] The Commonwealth of Massachusetts, along with the American Boiler Manufactures Association, persuaded the American Society of Mechanical Engineers to start work on a safety code for the construction and inspection of boilers. [6] This first boiler code was published in 1914, and an updated edition is still used today, published as ASME Boiler and Pressure Vessel Code Section I.

After the first boiler code was published, ASME published the first pressure vessel code in 1925, still updated and published today as ASME BPVC Section VIII Division 1. Since


its inception in the early 20th century, Section VIII Division 1 has contained simple pressure vessel calculations that can quickly and easily be solved by hand. For simplicity, conservative assumptions form the technical basis of Division 1; therefore, Division 1 also contains a relatively high factor of safety. In 1975, ASME BPVC Section VIII Division 2 was first published as a more accurate, less conservative, pressure vessel code, with a slightly lower factor of safety. [4]

INTRODUCTION By the mid-1990s, pressure vessel technology and research

had advanced to a point where neither Division 1 nor Division 2 incorporated the latest research or technological advancements. Computers and the advent of FEA allowed engineers to study pressure vessel behavior more in depth and obtain complex, rigorous results quickly. Division 1 was always intended to house simple pressure vessel rules that, while conservative, could be solved easily by hand. The advancement in pressure vessel technology and computation speed provided the opportunity for more rigorous and accurate calculations to be included in the Code; however, since Division 1 was one of the most commonly used pressure vessel codes in the world, the decision was made to leave Division 1 as-is, a “simple” pressure vessel code that the industry could continue to implement without major change. In 1998, the ASME Boiler and Pressure Vessel Standards Committee commissioned a project to rewrite Division 2 that would update the Code with the latest technology and lower the safety margin to make it more cost-competitive in an international market. [7]

The new, completely rewritten Division 2 was published by ASME in 2007, only nine years after it was commissioned. The current Division 2 is a better defined Code than Division 1 from a technical viewpoint, with more accurate and rigorous formulas, a lower factor of safety on tensile strength, and a more user friendly structure. [7] In general, the lower factor of safety on tensile strength in Division 2 leads to higher allowable stress values and, therefore, a reduced cost for the pressure-retaining materials of construction. Alternately, Division 2 mandates a Professional Engineer’s stamp and requires an increase in non-destructive examination that among other factors contribute as cost adders compared to Division 1. [2] Due to general uncertainty surrounding the relatively new Division 2, as well as the conflicting cost implications of higher allowable stresses versus increased NDE, no clear guideline exists for when a Division 2 pressure vessel might become cost-effective over a Division 1 design. This investigation attempts to analyze the cost implications resulting from different allowable stress values in the two divisions, as well as the variable and fixed cost adders for Division 2 as seen by the vessel fabricator, to propose a set of parameters over which Division 2 might become the more cost-effective pressure vessel code. The focus of this investigation is on carbon steel, ASME material specification SA-516-70 [8], as this is one of the more commonly used materials in the fabrication of pressure vessels. Other material specifications may yield different results, and the decision to use Division 2 is typically

much easier to determine with high cost, high chrome-type materials. As in any investigation with a focus on cost, factors such as market fluctuations, labor agreements and material surcharges can greatly influence the results.

ALLOWABLE STRESS AND MINIMUM THICKNESS Division 2 is a more accurate and technically complex

Code, therefore the safety factor on tensile strength is reduced and the allowable stress for each type of material is generally higher than Division 1. Before the relative thicknesses of a pressure vessel built to either Division 1 or Division 2 can be compared, first the calculated allowable stress from each Division must be understood. ASME BPVC Section II Part D Tables 1A and 1B list the Division 1 allowable stress values for each material specification at varying temperatures. [9] Section II Part D Tables 5A and 5B list the allowable stress values for Division 2. [9] These allowable stress values are calculated by applying safety factors to both the minimum tensile strength and the minimum yield strength and setting the lower of these two values as the maximum allowable stress at each temperature, as shown in equations 1 through 3. Table 1 indicates the different safety factors for Division 1 and Division 2, which lead to the different allowable stress values in each Division.

= (1)

= (2)

= minimum (3)

Table 1 Safety Factors [10]

As indicated in Section II Part D Table Y-1, the minimum

yield strength of SA-516-70 decreases as the design temperature increases [9]. In both Division 1 and Division 2, the safety factor on the yield strength, , is 1.5. [10] In other words, the maximum allowable yield stress, , is two-thirds of the yield strength, , at the design temperature in both Divisions. The Division 2 safety factor on tensile strength, , is 69% of the Division 1 safety factor, leading to a Division 2 allowable tensile stress, , approximately 1.45 times greater than Division 1 at room temperature. As indicated in Equation 3, the allowable stress of the material from Section II Part D is the minimum of the allowable yield stress and allowable tensile stress. [9]

At a given temperature, a material for which the allowable yield stress is lower than the allowable tensile stress is

Division 1 Division 2 3.5 2.4

1.5 1.5


considered governed by yield strength and a material for which the allowable tensile stress is lower than the allowable yield stress is considered governed by tensile strength. Division 2 provides no general material savings benefit for a yield strength governed material, such as stainless steel. The greatest benefit from Division 2 is realized for a material that is tensile governed up to a relatively high temperature. Figure 1 indicates the allowable stress values for SA-516-70 for both Division 1 and Division 2 at a variety of temperatures. [9]

Below 600°F, carbon steel is governed by tensile strength, and above 600°F carbon steel is governed by yield strength. Because the higher allowable stress values in Division 2 result in the majority of the cost savings, this study focuses on design temperatures significantly less than 600°F where the margin on allowable stress between Division 1 and Division 2 is most prominent. [11] When SA-516-70 becomes governed by yield strength, the allowable stress values between the two Divisions are identical and there is no financial incentive to choose Division 2 over Division 1.

The minimum required thickness of the pressure vessel is inversely proportional to the allowable stress for the material of construction. Equations 4 and 5 are the minimum thickness equations for Division 1 and Division 2, respectively. [1] [2] While these equations appear vastly different at first glance, they supply very similar results when using the same input parameters and allowable stress values.

= − 0.6 + (4)

= 2 − 1 + (5)

DIVISION 2 VS. DIVISION 1 PRICING The pricing of a pressure vessel is dependent on so many

factors that, when competitively bid, the same pressure vessel

could be quoted at much different prices from different vessel fabricators. This investigation studies the pricing of pressure vessels on a percentage basis, because total cost becomes arbitrary as the input parameters are changed. Regardless of the total magnitude of cost savings, Division 2 does become cost-effective when the percent difference between the Division 1 and Division 2 costs is zero. In general, as the size and thickness of a pressure vessel increase, so does the total amount saved by switching to Division 2; however, the percent difference in cost may be the same for either large or small vessels at the same design temperature, regardless of size and thickness. For small pressure vessels, a 5% cost savings may only be a few thousand dollars, whereas for very large pressure vessels, a 5% savings may amount to hundreds of thousands of dollars. In either case, Division 2 would be more cost-effective, and the decision to use Division 2 should not be limited by the total dollar amount saved but by the percentage reduction in the cost of the pressure vessel when using Division 2. This investigation analyzes the four cases, provided by Curtis Kelly Inc. shown in Table 2. [12] The thickness shown is the Division 1 minimum required thickness.

These four cases cover a variety of pressure vessel sizes,

thicknesses and volumes. All four of these cases would probably be considered “large” relative to an average-sized pressure vessel. Traditionally, Division 2 has only been used for large, thick pressure vessels, because until the Division 2 Code was rewritten in 2007, there wasn’t much cost advantage for anything on the average side of the vessel spectrum. [10] In Figure 1, the Division 2 allowable stresses were plotted with respect to the design temperature. The design temperature and corresponding allowable stress for the four test cases are shown in Table 3. As the design temperature decreases, the allowable stress increases and therefore the benefit for using Division 2 in lieu of Division 1 increases. Figure 2 shows the percent cost savings as a function of the percent weight savings for each vessel. In Figure 3, the percent cost and percent weight savings for each of the four test cases is plotted against the allowable stress. . Both Figure 2 and 3 apply for “large” pressure vessels, which are defined as vessels whose material cost savings greatly outweigh the fixed cost of a calculated Division 2 design, stamped by a PE. It should be noted that Figure 2 was used in this investigation to determine the maximum cost-effective design temperature; however, other factors, such as market demand, supplier availability and volatile labor costs, can affect the total cost of both Division 1 and Division 2 pressure vessels.

10,000

15,000

20,000

25,000

30,000

0 100 200 300 400 500 600 700 800

Allo

wab

le S

tres

s (p

si)

Design Temperature (°F)

Division 1Division 2

Figure 1 Allowable Stress vs. Design Temperature for SA-516-70 [9]

Case Diam Length Thickness % Weight

Savings % Cost Savings

1 10’ 80’ 3.75” 21% 12% 2 10’ 60’ 2.75” 18% 10% 3 8’ 64’ 3” 12% 6% 4 11’ 100’ 1.5” 6% 2%

Table 2 Division 2 Pricing Data [12]


RESULTS In contrast to the material savings realized by switching to

Division 2 from Division 1, there are also cost adders associated with Division 2, most notably the cost of a PE’s design and certification, and the cost of additional NDE. In order to use Division 2, a PE must prepare the MDR, which is a fixed cost regardless of the pressure vessel size. In this investigation, the cost of a PE to prepare and stamp the MDR is estimated at $2,000 per pressure vessel. [12] There are also variable costs associated with Division 2, which manifest in additional NDE requirements. In most cases, Division 2 requires RT, UT and MT, in addition to the minimum requirements in Division 1.

By extrapolating the cost curve in Figure 3, the allowable stress when the percent cost savings becomes zero is approximately 21,800 psi. When the Division 2 allowable stress is less than 21,800 psi, there is no cost benefit for using Division 2 in lieu of Division 1, regardless of the pressure vessel size. At 21,800 psi, there remains a 1,800 psi gap, or an approximate 3% weight difference, between Division 1 and Division 2 in which material savings can be realized; however, the fixed and variable costs of a PE stamp and additional NDE offset the material savings at that low of an allowable stress. Even for large pressure vessels, when a 3% weight offset alone could result in tens of thousands of dollars in material savings, the amount of additional NDE increases as the vessel size increases, and the additional savings are absorbed by the increasing variable cost. As shown in Figure 1, the design temperature associated with a Division 2 allowable stress of 21,800 psi is 380°F. [9] For conservatism, the highest design temperature for which Division 2 is cost-effective is approximated as 350°F, which results in an allowable stress of 22,100 psi. As shown in Figures 2 and 3, for large pressure vessels, an allowable stress of 22,100 psi will result in an approximate 6% weight savings and 2% cost savings by switching to Division 2.

As the size and weight of a pressure vessel decreases, so does the material required for fabrication, and therefore the amount of money saved by switching to Division 2 also decreases. The correlations shown in Figure 3 are only applicable for relatively large pressure vessels, where the material cost savings greatly outweigh the fixed cost. This same curve would not be linear for small pressure vessels, because as a vessel decreases in size the fixed cost of the PE stamp begins to overwhelm the cost savings from using less material. For example, the $2,000 PE stamp does not have much effect on a large pressure vessel from which tens of thousands of dollars can be saved by switching to Division 2; however, for a small pressure vessel, where only a few thousand dollars in material savings exist, a $2,000 PE stamp takes away a relatively large percentage of the savings. Carbon steel built to the ASME SA-516-70N material specification [9] typically costs approximately 75 cents per pound. [12] SA-516-70N is one of the most common pressure vessel material specifications for thicknesses greater than 1 inch, which is the case for most Division 2 pressure vessels. [13]

The minimum weight of a pressure vessel for which Division 2 becomes cost-effective is not as simple as dividing the fixed cost, $2,000, by 75 cents per pound and then dividing by the minimum percent weight savings. There are cost advantages from reducing the material thickness beyond material savings alone, most notably weld labor time. As shown in Figure 4, as the thickness of a pressure vessel decreases by ∆ , the amount of consumable material used decreases on the order of ∆ . This also reduces the amount of weld time on the order of ∆ .

Figure 3 Percent Savings vs. Allowable Stress [12] [9]

0

5

10

15

20

25

21 22 23 24 25 26

Perc

ent S

avin

gs

Allowable Stress (ksi)

Cost

Weight

Figure 2 Percent Cost Savings vs. Percent Weight Savings

02468

101214

0 5 10 15 20 25

Perc

ent C

ost S

avin

gs

Percent Weight Savings

Table 3 Division 2 Allowable Stress Values [9] Case 1 Case 2 Case 3 Case 4

Design Temp

100 °F 150 °F 250 °F 350 °F

Allowable Stress

25.3ksi 23.8 ksi 22.8 ksi 22.1 ksi


In reality, the fabricated savings of a Division 2 pressure

vessel per pound is greater than the 75 cent material cost, partly due to the reduction in consumable volume and weld labor indicated in Figure 4. For large vessels, the fabricated cost of a pressure vessel is close to $3 per pound, and for small pressure vessels it can escalate to $6-7 per pound. This investigation assumes the additional cost for Division 2 NDE requirements will offset the savings realized from reduced weld consumables and weld labor hours. To be conservative, a fabricated cost, or savings, of 75 cents per pound is assumed on the marginal weight difference between the two Divisions. Also, because the weight savings percentages shown in Figures 2 and 3 apply to “large” pressure vessels, as the size of a pressure vessel decreases, the weight savings percentage by switching to Division 2 also decreases. A small vessel will have a slightly lower weight savings percentage at each allowable stress than indicated in Figure 3. In Equation 6, the minimum weight of a pressure vessel with a design temperature of 350 F is calculated with a “small vessel” margin of 2 in order to get into a less volatile weight savings percentage range. This “small vessel” margin helps move the curve away from the fixed cost of a PE stamp. At the maximum cost-effective design temperature of 350°F, the minimum fabricated weight at which Division 2 becomes cost effective is 88,622 pounds, as outlined in Equation 6.

= (2)($2,000)$0.75 (6%) = 88,622 , (6)

A pressure vessel large enough or thick enough to weigh

90,000 pounds at a design temperature of 350°F will be approximately the same cost as either a Division 1 or a Division 2 design. Figure 2 shows a 2% cost benefit at 350°F; however, 90,000 pounds is a small enough pressure vessel at 350°F that the fixed cost begins to govern and the savings is offset. For each design temperature within the recommended Division 2 range (-20 to 350°F) there is a minimum required fabricated weight in order to overcome the fixed cost, as shown in Figure 5. To develop Figure 5, Equation 6 was used and the respective weight savings percentage for each allowable stress was substituted into the denominator, shown as 6% in Equation 6 for 350°F. A pressure vessel that falls in the range above the curve in Figure 5 will be more cost-effective as a Division 2

design. As the vessel design moves further above and away from the curve in Figure 5, the cost savings will approach the values shown in Figure 2. The curve in Figure 5 represents an estimated cost savings of 0%, or the break-even point for Division 2.

Figure 5 Division 2 Cost-Effective Range

= 1.1341 − 271.67 + 42842 100 350 = 27016 − 20 100 (7) The polynomial curve fit equation shown on Figure 5 and

in Equation 7 represents the minimum weight at each design temperature for which Division 2 may become cost-effective. The price of any pressure vessel is highly dependent on more factors than were analyzed in this study, including market supply, demand, labor rates and material surcharges. The design temperature is bounded on the low side by -20°F, and bounded on the high side by 350°F, which is the highest temperature at which Division 2 remains reasonably cost-effective. If a pressure vessel design falls within the blue shaded region of Figure 5 or above, a Division 2 design should be considered. At design conditions close to the curve, the cost savings may be minimal or nonexistent due to market fluctuations; however, the equation shown in Figure 5, Equation 7, provides an easily identifiable set of design conditions under which Division 2 should be explored for cost-effectiveness.

OTHER DIVISION 2 BENEFITS The possibility of a lower pressure vessel cost is not the

only benefit of using the new Division 2 for pressure vessel design. Unlike Division 1, all of the rules in Division 2 have a strong technical basis. Some of the Division 1 rules were written to be very conservative, and the technical basis has been forgotten over the years. These rules, such as the reinforcement area replacement or the 2-inch nozzle exclusion for reinforcement continue to be published in Division 1 because they have been around for almost 100 years. Although there isn’t a technical basis for these rules, they have been proved through experience to work, so they continue to be accepted. Division 2 was written with a strong technical basis for all of

Figure 4 Weld Consumable Cross-Section Area


the rules, which is one of the reasons the safety factor on tensile strength is reduced.

Another major benefit from using Division 2 is weight savings. Some vessel applications, such as offshore oil rigs, demand the lightest construction possible. In these situations, Division 2 may be used even when it isn’t necessarily cost-effective. Shell thickness is not the only avenue for weight savings in Division 2. The opening reinforcement produce smaller reinforcement pads, the external pressure calculations require fewer stiffener rings, and the elliptical head formulas generally calculate thinner than Division 1, even at the same allowable stress values.

CONCLUSION In response to numerous deaths resulting from boiler

explosions around the turn of the century, ASME published the first pressure vessel safety code in 1925. This first code was intended to be simple and conservative to enable the solving of vessel equations by hand. It continues today in the form of Division 1. In 2007, ASME published a completely rewritten, more technically accurate code, known as Division 2. Division 2 is more technically sound, the equations are more rigorous, and therefore the safety factor is lower than Division 1. The lower safety factor in Division 2 leads to additional cost savings by reducing the minimum required thickness of a pressure vessel. There are also additional costs associated with Division 2, most notably the cost of a PE stamp and additional NDE requirements. As the size of a pressure vessel increases, the material savings begin to outweigh the additional costs.

At higher design temperatures, the Division 2 allowable stress values decrease and the cost advantage of Division 2 is diminished. Figure 3 and Table 2 show that the maximum design temperature at which Division 2 is still cost-effective is 350°F. At a constant design temperature, even as the size of the pressure vessel increases, the cost savings percentage does not increase. The variable cost of additional NDE as the size of the pressure vessel increases is offset by additional variable savings. The main driving factor that causes Division 2 to be cost-effective is the raw material savings. Even with the advantageous Division 2 allowable stress values, a small pressure vessel may not be cost-effective due to the fixed cost of a PE stamp. Figure 5 and Equation 7 show the minimum required fabricated vessel weight in order for Division 2 to be cost-effective at each design temperature. The cost of a pressure vessel is dependent on many more parameters than outlined in this investigation, such as market supply, demand, and labor rates. Vessel design conditions that fall above the curve bounded by -20°F, 350°F and Equation 7 should be explored for Division 2; however, due to the many parameters that affect the price of a pressure vessel, pressure vessels that fall above but near the curve should be evaluated for both Division 1 and Division 2.

Cost benefits are not the only advantage of using the new ASME BPVC Section VIII Division 2. It is more accurate, has a stronger technical basis and employs better design principles than Division 1. Today’s market is slow to adapt to the new

Division 2, partly because the line at which it becomes cost-effective has been unclear. This investigation — and Equation 7 in particular — serve to better define the boundary at which Division 2 should be analyzed, with hope that industry will become more comfortable and confident using Division 2.

ACKNOWLEDGMENT This investigation would not have been possible without

the strong technical and commercial support from Curtis Kelly Inc. Many thanks are extended to the management team at Curtis Kelly for their continued support and advice. Curtis Kelly Inc. is a vessel fabricator in the Houston area.

REFERENCES

[1] ASME Boiler and Pressure Vessel Committee on Pressure Vessels, ASME Boiler and Pressure Vessel Code: Section VIII Division 1, New York: ASME, 2011. [2] ASME Boiler and Pressure Vessel Committee on Pressure Vessels, ASME Boiler and Pressure Vessel Code: Section VIII Division 2, New York: ASME, 2011. [3] S. Ambrose, "Remembering Sultana," National Geographic, 1 May 2001. [Online]. Available: http://news.nationalgeographic.com/news/2001/05/0501_river5.html. [Accessed 14 July 2013]. [4] K. Mokhtarian, Participant Workbook - ASME Boiler and Pressure Vessel Code: Section VIII Division 1, Las Vegas, Nevada: ASME Training & Development, 2012. [5] D.H. Cook, "The R.B. Grover & Company Shoe Factory Boiler Explosion," USGen Web, Brockton, Massachusetts, 2002. [Online]. Available: http://plymouthcolony.net/brockton/boiler.html. [Accessed 14 July 2013]. [6] S.F. Harrison, "Development, Relationship of the ASME Boiler-and-Pressure Vessel Committee and the National Board of Boiler and Pressure Vessel Inspectors," in International Compressor Engineering Conference, Paper 73, 1972. [7] David A. Osage et al, "Section VIII: Division 2 - Alternative Rules," in Companion Guide to the ASME Boiler & Pressure Vessel Code, New York, ASME, 2009, p. Chapter 22. [8] ASME Boiler and Pressure Vessel Committee on Materials, ASME Boiler & Pressure Vessel Code: Section II Part A, New York: ASME, 2011. [9] ASME Boiler and Pressure Vessel Committee on Materials, ASME Boiler & Pressure Vessel Code: Section II Part D, New York: ASME, 2011. [10] K. T. Lau, "A Brief Discussion on ASME Section VIII Divisions 1 and 2 and the New Division 3," in 3rd Annual Pressure Industry Conference, Banff, 2000. [11] The B&PV Taskforce on the new ASME Section VIII Division 2 Code, "A Proposal for the Use of the New (2007) ASME Section VIII Division 2 Code in Alberta," 2007. [12] C. K. Kyle Kotzebue, Interviewee, Division 2 Cost Comparison. [Interview]. 31 December 2012. [13] E. F. Megyesy, Pressure Vessel Handbook, Oklahoma City: PV Publishing Inc., 2008.




STRAIN SENSING PROPERTY OF GLASS MICROBALLOONS/CNF

NANOCOMPOSITE EMBEDDED IN SYNTACTIC FOAM

Ephraim F. Zegeye, Ali Kadkhoda Ghamsari NextGen Composite CREST Center Mechanical Engineering Department

Southern University and A & M College Baton Rouge, LA , USA

Eyassu Woldesenbet Mechanical Engineering Department

Louisiana State University Baton Rouge, LA , USA

ABSTRACT The strain sensing property of a nanocomposite fabricated

from a free standing structure consisting of glass microballoons (GMB) and carbon nanofibers (CNF) (GMB-CNF nanocomposite) has been reported [1]. The strain measurement was performed by attaching the nanocomposite on the surface of a tensile specimen. In this study, the GMB-CNF nanocomposite is embedded in compression test sample fabricated from syntactic foams to measure internal strain. The electrical resistance of the nanocomposite when subjected to a compressive strain is investigated. It is found that the average change in normalized electrical resistance decreases at lower strain. After about 6.5 % of strain, a sharp increase in the average change in normalized resistance is observed. The possible reasons for these behaviors are explained. Results provide significant information in the use of the nanocomposite for determining the onset of microballoons fracture or indicating the initiation of a crack in syntactic foam structures.

INTRODUCTION The application of composite materials in aircraft,

spacecraft, marine vessels, and automobile structures has been increasing in recent years. A structural health monitoring (SHM) system with the ability to detect and monitor the changes in the structure of composites used for these applications is very important in order to improve the reliability of using composite materials, and to reduce the risks associated with their failure. SHM basically involves embedding a sensing element (or a set of sensing elements) into a composite structure for continuous remote monitoring of damage in the structure. SHM systems are advantageous over traditional inspection systems, as they can reduce down-time, eliminate component tear-down inspections, and potentially prevent failure during operation [2]. Due to their excellent piezoresistive properties, carbon nanotubes (CNTs) and carbon nanofibers (CNFs) may enable a new generation of sensors in nano or micro scales and can be used to develop novel SHM systems. Consequently, several studies have been carried out to investigate the use of CNTs and CNFs for SHM applications [3-7].

In order to fabricate sensors for macro-strain measurements, the CNTs/CNFs were either stacked to form a thin film (buckypaper) or dispersed in polymeric materials [7-12]. In buckypaper and CNT/CNF polymer nanocomposite sensors, the CNTs/CNFs may have direct physical contact or may be separated with small gaps so that the electrons tunnel (hop) across the gaps [13]. Application of load or deformation on the nanocomposites can increase/decrease the gap between the conductive fillers. This gap variation affects the electrical properties of the nanocomposite system. Accordingly, buckypapers and CNT/CNF polymer nanocomposites have been investigated for macro-strain measurement and damage sensing applications [12, 14]. One of the benefits of CNT/CNF based strain sensors over metallic alloy foil based sensors is their use as embedded sensors for multidirectional sensing at multiple locations [15].

Embedded sensors could help in identifying internal defects and determining the extent and propagation rate of cracks in the hosting composite. They could also provide information for maintenance and replacement of the structural members before catastrophic failure. However, sensing elements that are embedded and used for SHM systems need to have closely similar properties with the hosting composite. This is because embedded sensors may create possible structural strength degradation of the host material and can be considered as defects if they have mechanical properties that are different than the host composite [16].

Recently, the strain sensing properties of a nanocomposite fabricated from a paper like structure consisting of glass microballoons (GMBs) and CNFs (GMB-CNF structure) was investigated [1]. The strain measurement was performed by attaching the nanocomposite on the surface of tensile specimens. In order to fabricate the nanocomposite (GMB-CNF nanocomposite), epoxy was infiltrated into the GMB-CNF structure. Due to the presence of the glass microballoons in the GMB-CNF nanocomposite, the nanocomposite has been reported to have similar properties with syntactic foams, which are also fabricated by dispersing microballoons in polymeric matrices [17]. Hence it is anticipated that embedding the GMB-CNF nanocomposite in a syntactic foam structure would not affect the mechanical properties of the hosting structure.


Therefore, in this paper, the potential use of the nanocomposite as embedded sensor in syntactic foams was investigated.

EXPERIMENTAL

Fabrication of GMB-CNF nanocomposite sensors Multilayered GMB-CNF nanocomposite sensors were

fabricated using a vacuum infiltration technique. Four GMB-CNF structures were laid-up, one over the other, before the infiltration process (Fig. 1a and b). A high purity bisphenol A diglycidylether epoxy resin (D.E.R. 332) and an aliphatic polyamine hardener (D.E.H. 24), both from DOW Chemical Company, USA, were mixed at a volume ratio of 87:13. Sufficient resin system was then poured around the region represented by the green rectangle in Fig. 1a. After sealing the vacuum bag, the resin system was infiltrated into the GMB-CNF structures by applying a vacuum. The resin system was sucked along the direction indicated in Fig. 1a. In order to avoid warping of the nanocomposite, the structures were kept between Teflon sheet covered plates. The bag was maintained in vacuum for about 12 hours. The nanocomposites were then removed from the bag and cured for 12 hours at room temperature and post cured for 3 hours at 100 oC. Fabrication of compression test samples

The multilayer sensor was embedded in samples prepared for compression testing. The test samples fabricated were syntactic foams containing 50 % by volume of S22 glass microballoons. The matrix of the samples was composed of the same epoxy resin system that was used to fabricate the GMB-CNF nanocomposites. The dimension of the compression test samples was 24.83 × 24.83 × 12.61 mm. In order to embed the sensors, 5 mm wide strip of nanocomposite was first placed across the length, in the middle of a mold prepared from Dow corning 3120 RTV silicone rubber (Dow Corning Corporation, USA) (Fig. 2a). A slurry prepared for compression test samples was then poured into the molds and cured for 24 hours at room temperature and post-cured for 3 hours at 100 οC. The fabricated sensor-embedded syntactic foam samples are shown in Fig. 2b. Compression test samples that did not contain sensors were also fabricated using the same materials and curing procedure.

Installation of electrical connections to the sensors

The procedures used for making electrical connections to the embedded sensors are shown in Fig. 3. The exposed edges of the sensor were first painted with PELCO conductive Silver 187 paste. Single stranded tinned-copper wires (Micro-Measurements, USA) were affixed at conductive silver painted ends of the sensor. In order to avoid wire pulling during the test, M-bond 200 (Micro-Measurements, USA) was used to attach the wires at the locations indicated by the arrows as shown in Fig. 3a. Conductive sliver paste was then applied on top of the wire to minimize contact resistance as shown in Fig. 3b. Finally, a plastic tape was wrapped around the sample in

order to maintain the wires on the sample surface and isolate the electrical connections from the crosshead during the test.

Figure 1. Vaccum infiltration process; (a) figure showing how the process was performed, (b) a magnified image of

the rectangular region in part (a). Testing

Compression tests were conducted on the samples using QTEST 150 universal testing equipment. The tests were performed at the crosshead speed of 0.5 mm/min. Mechanical strain (ε) developed along the thickness of the sample was measured as the crosshead displacement normalized by the gauge length (or platen separation) of the test specimen. The samples that did not contain sensors were tested up to 60 % of strain. Whereas, samples with the sensors were compressed up to 15 % of strain while measuring the electrical resistance of the sensors embedded in the samples. In order to record the resistance, FLUKE 83 digital millimeter (Fluke Corporation, USA) was used. Both the resistance and mechanical strain were captured during the test and the change in resistance (∆R) corresponding to the strain was obtained from the video. Fig. 4 shows the test setup and the orientation in which electrical measurements were performed with respect to the applied strain direction.

Sucking direction

(a)

(b)


Figure 2. (a) Strip of sensors placed in a silicone rubber

mold, (b) sensor-embedded syntactic foam sample.

Figure 3. Steps for making electrical connections; (a) painting silver paste and bonding the wire, (b) applying

silver paste on the wire and wrapping with a plastic tape.

Figure 4. Test setup showing strain direction and the orientation of sensor in the compression test sample.

RESULTS AND DISCUSSION

Nanocomposite Characterization A SEM micrograph of an edge of a fractured GMB-CNF

nanocomposite sensor is shown in Fig. 5. The average thickness of the fabricate nanocomposite was 0.65 ± 0.16 mm. In Fig. 5, white thin regions (see the arrows in the figure) are observed on the opposite surfaces of the nanocomposite. Such an artifact on an SEM image is attributed to a charging effect that appears when a non-conductive material is scanned by high voltage

electron beam. These white regions are resin dominated thin layers on the surface that hinder the transport of electrons to the conductive fillers in the nanocomposite. When these regions were carefully removed with 600 grit paper, the nanocomposite was shown to have consistent electrical property. The resistances of the nanocomposite sensors were measured using FLUKE 83 digital multimeter. The average no load resistance of the nanocomposite sensors (Ro) was 10.87 ± 2.29 KΩ.

Figure 5. SEM micrograph of an edge of a GMB-CNF

nanocomposite.

Figure 6. Normalized change in resistance versus strain plot.

Electromechanical Property and Sensitivity Fig. 6 presents the average normalized change in resistance

(∆R/Ro) plot of the embedded sensors with respect to the applied strain. As it can be observed in figure, the normalized change in resistance versus strain curve has two distinct regions. For the strains less than 6.5 %, the average normalized change in resistance is observed to reduce with strain. This can be explained by the decrease in the tunnel junction gap width between the CNFs upon the compressive strain. A decrease in the tunnel junction gap width between the CNFs reduces the contact resistance between adjacent CNFs. Consequently, the

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volume resistance of the sensors reduces. After about 7.0 % strain, the resistance of the embedded sensors is observed to increase with strain. In Fig. 7, the average normalized change in resistances for the two regions are plotted separately. The data can be fitted with straight lines having coefficient of determination (R2) values greater than 0.90. For the strains less than 6.5 %, the sensors have a gauge factor of about -0.48. The gauge factor is negative since the resistance decreases with applied strain in this region. Negative gauge factor is not unique to GMB-CNF nanocomposite sensors. Previous works have also reported negative gauge factors for CNT based sensors [18]. Commercial semiconductor strain sensors with n-type doping material have also a negative gauge factor [19]. The gauge factor of the sensors embedded in samples for strains 7.0 – 15 % is 2.6.

The behavior seen at strain about 6.5 % is credited to the evolution of damage in the sensor as a result of microballoons crushing in the sensor. The effect of such damage caused loss of contact and widening of the adjacent CNFs and significantly increased the contact resistance after this strain. It is important to note that both the nanocomposites and the syntactic foam samples were fabricated using the same type of microballoons. Hence, application of 6.5 % strain could also fracture microballoons in the syntactic foam samples. However, from Fig. 8, yielding of the syntactic foam samples when subjected to a compressive stress appears at about 12 % of strain. This yielding is also attributed to the crushing of microballoons in the syntactic foam sample. It can be noted that strain at which change in slope of the normalized resistance versus strain plots of the sensor (6.5 %) is much less than the yield strain of the hosting syntactic foam sample (12 %). This is because the electrical resistance changes are more sensitive to microballoons crushing than the yield stress. In the nanocomposite sensors, increase in the electrical resistance can be instigated by the fracture of only few microballoons and keep increasing as more microballoons are crushed. On the other hand, in the syntactic foam samples, although microballoons start crushing at lower strain, yielding may not be seen until a certain number of microballoons are fractured. The fact that the electrical resistance of the sensor is sensitive to the fracture of a few microballoons would be advantageous, as the embedded sensor could be used to identify structural defects or cracks prior to failure.

In order to identify cracks or defects prior to failure, series studies at different external conditions could be done to investigate the electrical resistance response of the embedded sensor due to the applied strain. From the study, a relationship between the applied strain and the generated electrical resistance could be obtained for structural member with known microstructural property. Once this is determined, any peculiar electrical resistance generated in the sensor could be attributed to cracks or defects in the structural member. The extent and propagation rate of cracks in the structure could also be determined based on the measured electrical resistance. Since the electrical resistance of the GMB-CNF nanocomposite sensor is sensitive for the fracture of few microballoons, it

could have a strong potential to be used as embedded sensor for investigating cracks in a syntactic foam structure. Being seamlessly integrated with the hosting structural member, it could provide information for maintenance or replacement of the structural members before failure. Consequently, the GMB-CNF nanocomposite sensors developed in this study could have significant importance for in-situ health monitoring applications in syntactic foam structures.

Figure 7. Normalized change in resistance versus strain plots with best fitting curves, (a) for 0 – 6.5 % strain, (b)

for 7.0 – 15.0 % strain.

REFERENCES [1] Zegeye, E., Ghamsari, A., Jin, Y., and Woldesenbet, E.,

2013, "The strain sensing property of carbon nanofiber/glass microballoon epoxy nanocomposite," Smart Mater. Struct., 22 (2013), pp. 065010.

[2] Kessler, S. S.,2002, "Piezoelectric-based in-situ damage detection of composite materials for structural health monitoring systems," PhD thesis, Massachusetts Institute of Technology, Cambridge, MA.

[3] Zhao, Q., Wood, J. R., and Wagner, H. D., 2001, "Stress fields around defects and fibers in a polymer using carbon nanotubes as sensors," Appl. Phys. Lett., 78 (12), pp. 1748-1750.

∆R/Ro = -0.48ɛ - 0.66 R² = 0.909

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Figure 8. Typical stress-strain plot of syntactic foam samples.

[4] Wood, J. R., Zhao, Q., Frogley, M. D., Meurs, E. R., Prins,

A. D., Peijs, T., Dunstan, D. J., and Wagner, H. D., 2000, "Carbon nanotubes:From molecular to macroscopic sensors," Phys. Rev. B, 62 (11), pp. 7571-7575.

[5] Zhang, W., Suhr, J., and Koratkar, N., 2006, "Carbon Nanotube/Polycarbonate Composites as Multifunctional Strain Sensors " J. Nanosci. Nanotech, 6 (4), pp. 960-964.

[6] Rein, M. D., Breuer, O., and Wagner, H. D., 2011, "Sensors and sensitivity: Carbon nanotube buckypaper films as strain sensing devices," Compos. Sci. Technol., 71 (3), pp. 373-381.

[7] Su, C. C., Chang, N. K., Wang, B. R., and Chang, S. H., 2012, "Two Dimensional Carbon Nanotube Based Strain Sensor," Sensors Actuat. A-Phys., 176 (0), pp. 124–129.

[8] Li, X., Levy, C., and Elaadil, L., 2008, "Multiwalled carbon nanotube film for strain sensing," Nanotech., 19 (4), pp. 045501.

[9] Kang, I., Schulz, M. J., Kim, J. H., Shanov, V., and Shi, D., 2006, "A carbon nanotube strain sensor for structural health monitoring," Smart Mater. Struct., 15 (3), pp. 737–748.

[10] Loh, K. J., Kim, J., Lynch, J. P., Kam, N. W. S., and Kotov, N. A., 2007, "Multifunctional layer-by-layer carbon nanotube–polyelectrolyte thin films for strain and corrosion sensing," Smart Mater. Struct., 16 (2), pp. 429–438.

[11] Hu, N., Karube, Y., Arai, M., Watanabe, T., Yan, C., Li, Y., Liu, Y., and Fukunaga, H., 2010, "Investigation on sensitivity of a polymer/carbon nanotube composite strain sensor," Carbon, 48 (3), pp. 680-687.

[12] Hu, N., Karube, Y., Yan, C., Masuda, Z., and Fukunaga, H., 2008, "Tunneling effect in a polymer/carbon nanotube nanocomposite strain sensor," Acta. Mater., 56 (13), pp. 2929–2936.

[13] Zhang, W., Dehghani-Sanij, A. A., and Blackburn, R. S., 2007, "Carbon based conductive polymer composites " J. Mater. Sci., 42 (10), pp. 3408–3418.

[14] Park, J., Kim, D., Kim, S., Kim, P., Yoon, D., and DeVries, K., 2007, "Inherent sensing and interfacial evaluation of carbon nanofiber and nanotube/epoxy composites using electrical resistance measurement and micromechanical techniquque.," Composites B, 38 (7-8), pp. 847–861.

[15] Pham, G. T., Park, Y. B., Liang, Z., Zhang, C., and Wang, B., 2008, "Processing and modeling of conductive thermoplastic/carbon nanotube films for strain sensing," Comp. Part B, 39 (1), pp. 209-216.

[16] Proper, A., Zhang, W., Bartolucci, S., Oberai, A. A., and Koratkar, N., 2009, "In-Situ Detection of Impact Damage in Composites Using Carbon Nanotube Sensor Networks," Nanosci. Nanotechnol. Lett., 1 (1), pp. 3-7.

[17] Zegeye, E., Pennington, K., Jin, Y., Abera, A., and Woldesenbet, E., 2012, "Dynamic Mechanical Analysis of Conductive Foam Films Fabricated From Free Standing Glass Microballoon-CNF Structure," ECTC Proceedings ASME Early Career Technical Conference, Baton Rouge, LA, pp. 1-6.

[18] Grow, R. J., Wang, Q., Cao, J., Wang, D., and Dai, H., 2005, "Piezoresistance of carbon nanotubes on deformable thin-film membranes," Appl. Phys. Lett., 86 (9), pp. 093104.

[19] Beeby, S., Ensell, G., Kraft, M., and White, N., Mems Mechanical Sensors, Artech House, Inc., Norwood, MA,Chap. 5.

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COGNITIVE EVIDENCE IN ENGINEERING DESIGN DOCUMENTATION

Sophoria Westmoreland United States Naval Academy

Annapolis, Maryland, USA

Linda Schmidt University of Maryland – College Park

College Park, Maryland, USA

ABSTRACT In order to process knowledge during the engineering

design process certain cognitive tools are necessary. At a surface level those tools are creativity, scientific, and process knowledge. While some progress has been made recently in exploring cognitive processes, reading between the lines, and thinking about design thinking – much more work is yet to be done in this expansive field.

The purpose of this paper is to present a method of extracting cognitive evidence from engineering design documentations-specifically capstone design journals from undergraduate students-and the results from its application. Attempting to reveal cognitive processes is a complex science, as such methods and tools should be created to explore the unknown realms of the engineer’s mind. Using different types of engineering design documentation is one path to retrieving cognitive information.

Capstone design journals are examined as part of a larger study that partially fulfilled the requirements for the author’s dissertation research. A Cognitive Coding Scheme was created by the author to explore evidence of design thinking and behavior. This paper seeks to identify patterns of behavior found in a capstone design team using hand written design journals.

INTRODUCTION A wide array of engineering design studies on cognition

exist in literature that combine research from the engineering and psychology domains [1-5]. This present work effort is a part of a larger work which includes the authors’ dissertation [6]. The goal of this work is to contribute to the understanding of cognitive processes during engineering design.

The mixture of art and engineering is what design is all about. Designers use what they know to create some “new” artifact. Executing this skill requires the use of cognitive activities that are the evidence of the process of a designers thinking. Some examples of cognitive activities are analogical thinking, questioning, and inquiry. The mind’s arrangement of this information is used to energize the art of innovation.

This study proposes a method for understanding those cognitive methods and seeing how they are organized. The results would support good design education and training needed to produce quality engineers prepared to lead a global society. According to one source promoting innovative thinking can “drive future economic growth and continue to lead on the global stage” [7].

Many things can be revealed by studying written documentation. Thomas Jefferson’s letters, Albert Einstein’s paper, and Leonardo da Vinci’s mirror writings are examples of famous written documentation [8-10]. Visualizing the design process can result in many forms of design documentation such as design journals, final reports, presentations, notes, and sketches. Using cognitive research techniques (i.e. a cognitive coding scheme on students’ engineering design journals), this study seeks to understand what happens in the mind during the design process.

LITERATURE REVIEW: COGNITIVE PSYCHOLOGY AND ENGINEERING DESIGN

According to Cross et al. design activities are among those occurring at the highest possible human cognitive levels [11]. One definition of design from the engineer’s perspective is to pull together something new or arrange existing things in a new way to satisfy a recognized need of society [12]. A general understanding of cognition and engineering design activities is needed in the creation of a cognitive coding scheme.

Cognition Research begins with starting with what we know. William

James says it clearly “the first fact is that thinking of some sort goes on” [13]. Cognitive processes are a part of everyday life, from the smallest tasks to the larger ones. Studying cognitive processes reveals how people organize and use knowledge in daily life and work situations. Many researchers have successfully studied the mysteries of the mind, knowledge, and thought processes [14-16]. These studies increase our understanding of human thinking processes and maximize usefulness of the tools created to promote learning methods and learning metacognitive strategies. Common researcher questions are, what is knowledge and where does it come from?


According to Alexander et al., knowledge is “an individual’s personal stock of information, skills, experiences, beliefs, and memories”[17].

It is important to note the interdisciplinary nature of the fields of study that examine cognition. They include cognitive science, cognitive psychology, and educational psychology. These fields all have their foundation in psychology. Studies in these fields can be complementary and are all focused on the central theme of understanding the mind. Studying the mind creates a path to understanding human behaviors.

Cognition in Design The original way to learn about cognitive activities in

design was to study designer behavior. Studying designer behavior can be done using a variety of methods such as verbal protocol analysis [18], design prompts [19], direct observation [20], coding design journal content [21, 22], and interviewing designers [23]. Different methodologies were used in each study based, at least partially, on the anticipated results. It is useful to note that studying design does not solely belong to the field of engineering. Of the studies mentioned above some are from architecture, industrial design, and other engineering disciplines that have design as a central tenant. Some of these studies have focused on designer behavior and in the process uncovered cognitive findings. The studies detailed below focus on students’ design activities because they are the subjects used in this current paper.

ABET requires students in engineering undergraduate programs to take a course in capstone design towards the end of their course studies[24]. Each engineering discipline is different in how they present the course, but the goal is generally for students (working in a team) to create an original design product using the culmination of engineering subject knowledge acquired during the previous years of study. This course provides the perfect opportunity to study student design behavior in a natural design setting. A deeper understanding of team behavior is often also a result of these types of studies.

Grenier et al. analyzed design journal sketches and notations of capstone design students to learn “how students are learning and practicing design” [25]. Twelve student design journals were used from a senior design course. The results showed that positive links exist between sketching and cognitive processes. Two cognitive operators were displayed in the student sketches, generation and exploration; both are critical for solving complex problems. Grenier’s study presents promise for learning more about the cognitive processes of engineering design students.

Another important study was done on team communication by Stempfle [26]. The goal was to examine the thinking processes of student design teams. Teams of mechanical engineering design students were recorded (4-6 students per team) designing a sun planetarium for six consecutive hours. A coding system was created to analyze the team communication in order to create a model of design team activity. Four basic operations of design thinking were identified: generation, exploration, comparison, and selection.

A study by Shah fully integrated traditional engineering based design with traditional psychology based labs [27-29]. The goal was to study the cognitive processes that happen during the engineering design process through an ideation experiment to create a cognitive model of the design process. Models were pulled from cognitive psychology related to information processing such as human problem solving, mental imagery, and visual thinking. The resulting preliminary cognitive model included six ideation components: provocative stimuli, suspended judgment, flexible representation, frame of reference shifting, incubation, and example exposure. The design teams in the study were exposed to the six ideation components, and the results were recorded. The study concluded that introducing ideation components has a positive effect on divergent thinking during idea generation. This created a basis for linking cognitive psychology with engineering design studies through a cross-disciplinary study using terms from both fields.

Sobek implemented design journals for a senior capstone design course at Montana State University in order to find the correlation between thoughts and written documentation during the design process[21, 22]. The students kept a design journal and received a portion of their course grade for the contents. Each member of the design team was required to keep a journal documenting the process. A coding scheme was created and applied to the design journals to find out what design process variables affect the design outcome. It was concluded that design process models do not suit novice designers as well as they do expert designers. Sobek noted the importance of the potential cognitive benefits students gain from using a design journal.

This current study utilizes written documentation to create a cognitive coding scheme for engineering design documentation.

A COGNITIVE CODING SCHEME A cognitive coding scheme is defined as a system

developed for the classification of design documentation content for quantitative analysis. Many researchers have created cognitive coding schemes for application to other types of design documentation such as verbal protocol analysis and design interviews [20, 30, 31]. A good cognitive coding scheme is one suitable for extracting evidence to imply cognitive activities from design documentation. Application of such a coding scheme can benefit design researchers progress towards developing design competency tools and help clarify the differences between novice and professional design engineers.

The development of the coding scheme began with a detailed literature search (both cognitive psychology and engineering design) using an iterative process. A series of 4 design journal studies were conducted with students in senior design courses at the University of Maryland- College Park to apply and refine the coding scheme. The cognitive codes were validated against similar coding schemes found in literature [20, 32, 33]. We have confidence that our final version of the coding scheme, as shown in Table 1, is useful for revealing the


cognitive activities that occur during the design process. The individual cognitive codes are grouped into larger classes.

Table 1: Cognitive Coding Scheme Class and Related

Codes Cognitive Codes

INFORMATION SEEKING AND NOTING Search (1), References (2), Questioning (3), Price Quotes (4), and Definitions (5) PROBLEM UNDERSTANDING Customer Requirements (6), Problem Statement Clarification (7), Criteria Lists (8), and Engineering Characteristics (9) IDEA GENERATION Project Ideas(10), Analogical Reasoning (11), and Material Options (12) ANALYSIS Estimate (13), Assumptions (14), Calculations (15), Testing Procedures (16), Variables (17), and Explanations (18) DECISIONS Recommendations (19), Conclusions (20), and Design Changes (21) PROJECT MANAGEMENT To Do Lists (22), Meeting Notes (23), Task Assignment (24), Inventory (25), Task Completion (26), Project Milestones (27), and Field Trip Notes (28) REFLECTION Personal Notes(29), Design Process Notes (30), Revelations (31), Mistakes (32), and Cross References (33) OTHER Illegible Entries (34), Designer Signature (35), and No Evidence of Cognitive Activity (36)

METHODOLOGY: STUDENT DESIGN TEAMS STUDY A design journal study was conducted in fall 2011 with a

team of students in Mechanical Engineering at the University of Maryland. This study is one out of a larger group of similar studies done for a larger work. The team presented in this paper consisted of 5 members with only N=4 participating in the study. The students were given a design journal at the beginning of the course to capture the complete design process experienced by each student (1 semester lasted 15 weeks). A one page “Design Journal Guidelines” gave a brief overview of the journaling process in the event that a team member was not familiar with the process. A short presentation was given on the first day of class introducing the study and giving details about the journaling process and expectations. The students participating in this study were volunteers but were compensated for their time with gift cards to the local college bookstore.

A journal is defined for this study as a bound notebook with lined pages used as a permanent record of what happened

during the design process. A sample design journal page is shown in the Appendix as Figure 6.

The journals were reviewed weekly, and feedback was given to the study participants. Dates of entries in the journal are important for correlating them with course due dates and team meeting times. Hence when the journals were checked this was a priority and feedback was given to the students if dates were missing from entries. The content of the journals was left entirely up to the students in order to give them control over how they utilize their journals to benefit them in the design course. Students who participated in this study completed an exit survey through e-mail.

Coding the Design Journals Coding the design journals produces a design string

(Figure 1) which is an order of numbers that relate to components in the coding process. The cognitive code presented previously represents only one component in the design string. For breadth and depth this study all captures other important information from the students design journals.

The design session includes all the written records found to

have occurred on a single date or during a single period of concentration. The design segment is a section of work within each session in the journal that is focused on the same design thought, which can be described by a single cognitive code. The design phases are conceptual design, embodiment design, detailed design, and re-design in accordance with the course text [12]. The cognitive codes are from Table 1. The concept code indicated the concept (if any) to which the segment is referring. The visual types classify a visual representation found in the design segment such as sketches and free body diagrams. A sample coded example is shown in Figure 2.

The main coder is the author of this paper and a trained undergraduate assistant also coded a representative set of the design journals in order to perform an inter-coder reliability study. The Cohen’s Kappa was calculated at 64.7% at the cognitive code level, which is a good strength of agreement.

RESULTS AND DISCUSSION The students reported on in this study are all from the same

capstone design team. The team was made up of five students, and four out of five of the students participated in the study. Their project was to design a dynamic coring system, which is a drill bit stand, over a 15 week period. Detailed information about the students on this team is given below in Table 2.

Figure 1: Elements of the design string assigned to each segment of a coded journal page


Figure 2: Coding Example

Table 2: Detailed Team Information

ID Number of

Journal Pages

Recorded

Design Sessions

Design Segments

Activity Density

3 32 20 69 3.45 5 28 11 123 11.18 6 20 20 101 5.05 7 20 9 119 13.22

Variation between the number of design sessions and the

number of design segments is expected. Activity density is defined as a measure of the amount of journaling activity within a design session. A lower activity density indicates that students were writing about a specific topic or had a narrower focus during some of their design sessions. A higher activity density indicates a wider range of cognitive activities each time they sat for a design session.

The design phase coding results are shown in Figure 3. The students in this study found the design journals to be most useful during the conceptual design and embodiment design phases of the design process. These stages involve activities such as gathering information, conceptualization, concept development, product architecture, and parametric design.

The cognitive coding results from the study are shown in Table 3.

For spacing purposes cognitive codes that were not found in this team’s design journals were omitted. These codes are Definition, Estimates, Analogical Reasoning, Assumptions, Variables, Meeting Notes, Task Assignments, Inventory, Field Trip Notes, Task Completion, Design Changes, Mistakes, and Designer Signature. These results present a good representation of the cognitive codes across the students design journals. Student 3 produced the lowest number of different types of cognitive activities with only 9 (out of a possible 36). Student 7 produced the highest number of different types of cognitive activities with 15 (out of a possible 36).

All 4 students in this study used their design journals for Project Ideas more than anything else. It is clear that the journal provided a convenient space to document their creativity and share ideas for solutions to the problem amongst the group

members. A deeper understanding of the benefits of using a design journal for a project like this would likely even out these

Figure 3: Design Phase Results

Table 3: Cognitive Code Results as a Percent

Students Cognitive Code 3 5 6 7 Search 0% 0% 0% 0.84% References 0% 13.82% 0% 0% Questioning 4.35% 2.44% 3.88% 0% Price Quotes 0% 0% 0% 0.84% Customer Requirements 1.45% 3.25% 2.91% 3.36%

PS Clarification 1.45% 1.63% 0% 2.52% Criteria List 0% 0.81% 0% 7.56% Engineering Characteristics 0% 4.88% 0% 0%

Project Ideas 65.2% 29.2% 61.1% 53.78% Material Options 7.25% 0% 1.94% 0% Calculations 1.45% 2.44% 0.97% 0.84% Testing Procedures 5.80% 9.76% 5.83% 1.68%

Explanations 0% 5.69% 5.83% 0% Recommendations 0% 0% 4.85% 0% Conclusions 0% 6.50% 5.83% 5.04% To Do Lists 10.14% 7.32% 0.97% 1.68% Project Milestones 0% 0% 0% 0.84%

Personal Notes 0% 0% 2.91% 1.68% Design Process Notes 0% 0% 0.97% 0%

Revelations 0% 0% 0.97% 0% Cross References 0% 0% 0% 2.52% Illegible Entries 0% 1.63% 0% 2.52% None 2.90% 8.94% 0.97% 14.29%

results. It would have been expected to see Engineering Characteristics appear more in these design journals because of the course requirement to make a House of Quality that

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includes an engineering characteristics room. Only 1 student had engineering characteristics entries in their design journal.

Figure 4: Cognitive Codes by Class

Figure 4 is suggestive of the behavior of the students, in that they mostly used the journals the same. With the exception of student 5, they all show a peak during idea generation. The cognitive codes corresponding to each of the classes can be found in Table 1. Understanding time constraints for the design project, other course requirements, and the voluntary nature of this study these are definitely promising results.

Student 3

Student 5

Student 6

Student 7

Figure 5: Cognitive Codes during Conceptual Design Taking a closer look at the students’ design journal

behavior during the conceptual design phase is shown in Figure 5. The numbers in the figure correspond with the cognitive

code classes found in Table 1. The conceptual design phase is mirrored for 3 of the 4 students participating in this study.

Students’ use of visual representations in the design journals is important for this work because visuals are tools used for understanding, explaining, modeling, and creating during the design process. All the visuals found in the 4 students design journals were sketches, which is not surprising. Sketching in engineering design is vital to innovation and the outpouring of ideas from the mind. Many of these sketched ideas become the final design or at least a subsystem.

The comprehensive cognitive coding scheme presented here is shown to be a prescriptive method for extracting cognitive evidence from engineering design journals. The use of the design string coding method allows for quantitative analysis and the collection of a rich data set. One of the benefits to having students journal in a non-prescriptive manner is to be able to see the differences in their behavior.

This research reveals the patterns of journaling behavior in different phases of the design process. The larger study generated a large amount of data that will provide research results into the future. Working with educational psychologist these results can be used to create tools for teaching innovative strategies in engineering design courses.

FUTURE WORK An important next step is combining the cognitive coding

scheme results with a design performance measure to understand the relationship between “good” design and cognitive activities. It would be essential to involve professional design experts in this process to identify student projects that are of high quality. Creating a design performance measure can effectively codify innovation early in the design process. This path will lead to an increased understanding of innovative design thinking.

ACKNOWLEDGEMENT This material is based in part on work done for the author’s

dissertation. The authors are grateful for the student volunteers, coding assistants, and the Mechanical Engineering department at the University of Maryland for their support and assistance with this work.

REFERENCES

[1] Atman, C.J., Kilgore,D., And Mckenna, A., Characterizing Design Learning: A Mixed-Methods Study Of Engineering Designers' Use Of Language Journal Of Engineering Education, 2008. 97(3): P. 309-326. [2] Ball, L.J., J.S.B.T. Evans, And I. Dennis, Cognitive Processes In Engineering Design: A Longitudinal Study Ergonomics, 1994. 37(11): P. 1753-1786. [3] Cross, N. The Expertise Of Exceptional Designers In Creativity And Cognition Conference: Expertise In Design 2003. Sydney, Australia [4] Liang, J., Et Al. A Meta-Cognition Modeling Of Engineering Product Designer In The Process Of Product

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Design In International Conference On Human-Computer Interaction Proceedings Part 1 2007. Beijing, China. [5] Williams, C.B., Et Al. Exploring The Effect Of Design Education On The Design Cognition Of Mechanical Engineering Students In Asme 2011 International Design Engineering Technical Conferences & Computers And Information In Engineering Conference 2011. Washington, Dc, Usa [6] Westmoreland, S., Design Thinking: Cognitive Patterns In Engineering Design Documentation In Mechanical Engineering2012, University Of Maryland - College Park: University Of Maryland Digital Repository In College Park, Maryland. [7] Obama, B. A Strategy For American Innovation: Securing Our Economic Growth And Prosperity 2011 [Cited 2011 October 12]. [8] Da Vinci, L., Leonardo's Notebooks Ed. H.A. Suh2005, New York.: Black Dog & Leventhal Publishers, Inc. . [9] Gorman, M. And W.B. Carlson, Interpreting Invention As A Cognitive Process: The Case Of Alexander Graham Bell, Thomas Edison, And The Telephone. Science, Technology, & Human Values, 1990. 15(2): P. 131-164. [10] Gorman, M., Confirmation, Disconfirmation, And Invention: The Case Of Alexander Graham Bell And The Telephone. Thinking And Reasoning, 1995. 1(1): P. 31-53. [11] Cross, N., Christiaans, H., And Dorst, K. , Analysing Design Activity 1996, West Sussex, England: John Wiley & Sons Ltd. [12] Dieter, G.E. And L. Schmidt, Engineering Design 5th Edition. 4 Ed. Vol. 5. 2012, New York, New York.: Mcgraw-Hill Higher Education [13] James, W., The Principles Of Psychology: Edited By Christopher Green, Ed. C. Green1890, Toronto.: Self Published. [14] Vygotsky, L.S., Thought And Language 1986, Boston: The Mit Press. [15] Lave, J., Cognition In Practice 1988, Cambridge.: Cambridge University Press. [16] American Psychological Association Division 15, A.E.P., Educational Psychology: A Century Of Contributions, Ed. B.J.Z.A.D.H. Schunk2003, Mahwah, New Jersey Lawrence Erlbaum Associates, Inc. . [17] Alexander, P.A., D.L. Schallert, And V.C. Hare, Coming To Terms: How Researchers In Learning And Literacy Talk About Knowledge Review Of Educational Research, 1991. 61(3): P. 315-343. [18] Gero, J.S. And T. Mcneill, An Approach To The Analysis Of Design Protocols Design Studies, 1998. 19(1): P. 21-61. [19] Bogusch, L.L., Turns, J., And Atman, C.J. . Engineering Design Factors: How Broadly Do Students Define Problems. In 30th Asee/Ieee Frontiers In Education Conference. 2000. Kansas City, Mo. [20] Suwa, M., Purcell, T., And Gero, J. , Macroscopic Analysis Of Design Processes Based On A Scheme For Coding Designers' Cognitive Actions Design Studies, 1998. 19(4): P. 455-483.

[21] Sobek, D.K. Use Of Journals To Evaluate Student Design Processes In Asee Annual Conference. 2002. Montreal, Qe. [22] Sobek, D.K. Preliminary Findings From Coding Student Design Journals In Asee Annual Conference 2002. Montreal, Qe. [23] Chimka, J.R., Cynthia, J.A., And Bursic, K.M. . Describing Student Design Behavior In Asee Annual Conference. 1997. Honolulu, Hi. [24] ABET, Criteria For Accrediting Engineering Programs In General Criteria For Baccalaureate Level Programs 2009-2010, Engineering Accredidation Commission Baltimore, Maryland [25] Grenier, A. And L. Schmidt. Analysis Of Engineering Design Journal Sketches And Notations In Asme International Design Engineering Technical Conferences And Computers And Information In Engineering Conference 2007. Las Vegas, Nv. [26] Stempfle, J. And P. Badke Schaub, Thinking In Design Teams- An Analysis Of Team Communication Design Studies, 2002. 23(5): P. 473-496. [27] Shah, J., Kulkarni, S.V., And Vargas-Hernandez, N. , Evaluation Of Idea Generation Methods For Conceptual Design: Effectiveness Metrics And Design Of Experiments Journal Of Mechanical Design, 2000. 122(4): P. 377-384. [28] Shah, J., Vargas-Hernandez, H., And Smith, S., Metrics For Measuring Ideation Effectiveness. Design Studies, 2003. 24(2): P. 111-134. [29] Shah, J., Smith, S., Vargas-Hernandez, H., Gerkins, D. R., And Wulan, M. . Empirical Studies Of Design Ideation: Alignment Of Design Experiments With Lab Experiments In Asme Idetc/Cie Design Theory And Methodology Conference. 2003. Chicago, Il: Asme [30] Atman, C.J., And Turns, J. , Studying Engineering Design Learning: Four Verbal Protocol Studies, In Design Knowing And Learning: Cognition In Design Education C. Eastman, Mccracken, M., And Newstetter, W., Editor 2001, Elsevier: Kidlington, Oxford [31] Adams, R.S., Cognitive Processes In Iterative Design Bahavior In College Of Education 2001, University Of Washington Seattle, Wa. [32] Atman, C.J., Et Al., Engineering Design Processes: A Comparison Of Students And Expert Practitioners. Journal Of Engineering Education, 2007. 96(4): P. 359-379. [33] Jain, V.K. And D.K. Sobek, Linking Design Process To Customer Satisfaction Through Virtual Design Of Experiments Research In Engineering Design, 2006. 17(2): P. 59-71.


APPENDIX

Figure 6: Design Journal Page Example




THE MODELING AND DESIGN OF A SUSTAINABLE PNEUMATIC ENERGY DRIVING AUTOMOBILE SYSTEM

Shaobiao Cai Georgia Southern University

Statesboro, GA, USA

Yongli Zhao St. Cloud State University, MN, U.S.A.

St. Cloud, MN, USA

ABSTRACT Sustainable, clean, efficient energy has become a central

concern with growing interest among industries and academic researchers. This paper presents the modeling and prototyping of an air-powered automobile simulator for field study, using clean pneumatic energy, a potential candidate for a new generation of hybrid-vehicle technologies. The simulator was designed to explore the applications of sustainable, alternative, clean, efficient energy and to gain an in-depth understanding of the engineering processes and methods of modeling such a complex system. A power chain was designed to convert the stored pneumatic energy into torque and deliver the power to a driving wheel. A chassis was designed to meet the loading conditions; it is made of recycled steel and aluminum. The stability and effectiveness of the power transmission are addressed in the prototype. It presents a great potential of new technology development in the relevant areas of application.

INTRODUCTION The car became the primary transportation tool in the

United States soon after its introduction. While enjoying the convenience of it, concerns were raised as well among public. Air pollution due to emission and energy consumption were among the major issues and became even more serious concerns due to the ramping up of gas prices and global warming. According to World Almanac 211 [1] and WRI171

[2], a traditional car’s engine uses about 65 percent of the energy from the fuel just to move all its parts such as the pistons and cams, plus what is wasted generating excess heat. The transmission uses 6 percent of the energy from the fuel, the accessory load 2 percent, and idling losses come to about 11 percent, leaving only about 16 percent of the energy to actually make the wheels turn. Saving energy and increasing energy efficiency thus became very important. In addition to energy efficiency, pollution became another major concern with regard to automobiles. Experimental data show that a gallon of gas

burned produces about 20 pounds of CO2. Relevant work in engine development and automotive performance has been studied by researchers such as [3, 4]. Hybrid vehicles using electrical batteries and hydrogen or various types of fuel cells have been widely studied [5–8]. The studies of applications using solar power [9] and biodiesel fuel [10] are discussed to some extent in the literature. The using of pneumatic air, one of the most promising options to address energy efficiency emissions, is of a great interest among many researchers. Fundamental theories for analysis and modeling, such as thermodynamics, flow mechanics, heat transfer, energy, and energy efficiency can be found in literature [11–13]. The concepts of various pneumatic hybrid engine technologies are proposed and studied based on those theories. For instance, the vehicle may run on petrol but would use its reservoir of compressed air to boost the engine's power through braking energy generated compressed air [14]. Other researchers modeled various types of Hybrid engines, such as the simulation of a pneumatic hybrid motorcycle (which represent the potential application of pneumatic energy to small scale transportation system) [15], and the modeling and optimization of two and four-stroke hybrid pneumatic engines [16]. A significant fuel consumption reduction may be achieved through the combination of engine downsizing, pneumatic hybridization, as well as strategic operation [17]. These works presented some very interesting and encouraging results on hybrid pneumatic engine modeling.

It has been very encouraging that many global industrial companies have adopted industrial ecology and sustainability thinking as part of their practices [18–21]. The use of an air propulsive engine in a purely pneumatic powered car like AirPod has been developed. Energy efficiency at about 39.3% from tank to wheel was reported by MDI [22]. However, skepticism exists among engineers and researchers. Short running distance is still among the major challenges. The tank-to-wheel energy efficiency is yet to be proven or further improved with more robust field data.


The development of field models using pneumatic air with the capability to address sustainable clean energy issues, energy efficiency, and noise and vibration issues is highly in need. This work presents the modeling, design, and prototype of a pneumatic, air-powered automobile simulator for the field, an important stage in new technology development to explore the applications of sustainable clean energy and efficiency in automobiles. It was designed to study the efficiency and the method to increase running distance with integrated energy regeneration functions (not done yet in the current work) using such as gravitational potential. Pneumatic air is chosen as the driven power source for the simulator to address the environmentally friendly applications. The mechanisms utilizing sustainable clean pneumatic energy, with the capability of driving a total of a 300-lb. load, are discussed in detail. A power chain was designed to convert the stored energy to torque and deliver the power to the driving wheel. A chassis was designed to meet the loading conditions. The system consists of recycled steel and aluminum and other metals. The stability and effectiveness of the power transmission were addressed in the prototype. Various supporting mechanisms were engineered. Preliminary field tests were conducted and the effectiveness of the simulator verified.

DESIGN CONSIDERATION The simulator is considered to carry a driver, thus a total of

a 300-lb load due to the weights used. The wheels are 20 inches in diameter. The system is preferable to run at a steady speed of 10 mph with a capability for further expansion and configuration. The specific component design concepts and selections were determined by using the initial preferable loading capacity. The project began with a collection of old unused bicycle frames. These recycled metal frames were carefully examined, dissected, selected, cut, and shaped into the desirable size and shape for the project. Figure 1 shows examples of the lab planning and fabrication.

The design parameters listed above were used to calculate the torque needed to run the system. The torque further determines the capacity of the air motor, the key part for converting pneumatic energy to mechanical energy. The configurations and technical specifications of the air motor were used to specify the energy storage device and pressure tank, which were needed to provide a range of steady airflow and power. The steady airflow with desirable pressure is achieved by using an air regulator with a high-calibration pinpoint control mechanism. The compressed pneumatic air is regulated down to the air motor. The motor, in turn, delivers power through a gear-chain system to the driving wheel. These devices, including the pressure air tank, regulator, air filter, air motor, and gear-chain system, make up the power chain mechanism of the air automobile simulator. A chassis was designed to carry a rider, power chain system, wheels, and other necessary accessories. Supporting mechanisms for the air tank, the air motor, the air filter, and the lubrication system were designed and fabricated. The power chain was installed and secured using the supporting mechanisms. The manufacturing

techniques are not the focus of this paper, the details of which are largely available in the literature [23, 24], and thus are not presented here. The design and modeling are presented in the following sections.

Figure 1. Planning and fabrication of the air-powered

automobile simulator

MODELING AND DESIGN The mechanism design was based on the mentioned

loading conditions and desirable speed. Four wheels were used; however, only two wheels support the total load in driving. The rear one (of the two supporting wheels) serves as the driving wheel. The major considerations were to ensure better manipulation and reduction of energy loss due to friction. The other two wheels (on the side) of the four are used as “training wheels” to maintain stability for safety purposes. These two wheels won’t touch the ground while the vehicle is moving. All of the four wheels are the same size, 20 inches or 1.67 feet in diameter. The two “training wheels” are mounted one inch higher (from the ground) than the others. Thus, they do not support the weight while driving. A gear-chain system is used to reduce direct impact (a major factor known to cause damage and instability to the motor) to the air motor so that a smooth power transmission can be achieved. Loading Condition

It is assumed that the weight of the driver (Wd) and the simulator (Wa) will be 150 lbs., respectively. The total weight (W) is distributed between the two wheels (because only the central two wheels touch the ground while driving). The reaction forces from the ground to the front wheel and the rear wheel are Rf and Rr, respectively. The loading conditions are shown in Figure 2.


Figure 2. Schematic of the loading conditions of the system

The conditions of the force and moment balance of the system at equilibrium give ΣF = Rr + Rf - W = 0 (1) ΣM = Rf (L1 +L2) - WL1 + FdLg = 0 (2) where L1 and L2 are the distances from the line of action of the weight W to the supporting points of the rear wheel and front wheel, respectively. Here, L1 is 11 inches and L2 is 16 inches. Lg is the vertical distance from the mass center of the system to the ground. Because the air-drag force is relatively small at 10 mph, this element may be neglected in the preliminary calculation. Based on the loading conditions, one can readily calculate the reaction forces to the front wheel and the rear wheel, which are Rf = 129 lb and Rr = 171 lb, respectively. Motor Rotational Speed ωm (rpm) Determination

To determine the motor rotational speed, let’s first consider the simulator traveling at a linear velocity of V. To achieve the velocity V, the shaft of the driving wheel needs to run at a rotational speed of ωd, where the subscription d indicates the driving wheel. The linear travel velocity and the rotational speed ωd have a relationship as follows: ωd = V/R (3) where R is the radius of the driving wheel. Because the simulator is meant to run at a speed of 10 mph and all of the wheels are the same size, 20 inches, the rotational speed ωd is 168 rpm. For the gear-chain system, the gear attached to the driving wheel has eighteen teeth, and the gear attached to the motor has forty-four teeth, the gear ratio (GR) is 2.44. The rotational speed of the motor ωm thus can be determined with

GRd

m

(4)

For the application here, the rotational speed ωd is 69 rpm.

Motor Torque and Horsepower Determination

For the system to work as expected, the motor torque needs to be able to overcome the maximum friction torque while rolling. To acquire the rolling friction force, a simple experiment was conducted. A 25-lb. bike with the same size tires was put on straight and level concrete ground with a 160-lb. person on the bike. It is known that any slip can lead to a significant increase in the coefficient of friction. It was pulled as slowly and carefully as possible. It was found that it took a force of six pounds to overcome the rolling resistance. Thus, a rolling coefficient of friction µk can be calculated. It was 0.03 based on the test. This result will be used as the preliminary assumption when rolling. With µk, the friction force fk can be found as follows:

Nfkk

(5) where N is the total normal load, here, the same as the weight. The frictional torque Tf can be determined as follows:

rfTkf

(6)

For this application, the friction force is about 10 lbs., and the friction torque is 100 lb./in. This indicates that the motor needs to provide 100 lb./in. for the system to run at a constant speed. With this information, the power needed can be estimated.

mfTP (7)

For the simulator to move at 10 mph, the motor needs to be

at least 0.11 hp with an output rotational speed of 69 rpm. However, this is the situation of rolling. To start the simulator, higher power is needed because the static friction is higher than the rolling one. The static coefficient of friction varies from 0.2 to 0.6 [25, 26, 27]. Based on these considerations, an air motor with 0.75 hp capacity having a 20:1 gear reducer was chosen to provide enough torque for practical operations and to allow room for future expansion. It also allows for providing slightly larger ranges of velocity and acceleration for field tests. Energy Storage and Regulating Principles

The work-rate output is achieved using the airflow through the motor as shown in Figure 3.

Consider the air flowing in from the inlet of the motor and flowing out from the outlet. The work output rate through the shaft is W . The governing equation for the control volume (CV) (the area indicated by the dash line) is as follows [10]:

WQdAnVgzV

hdet CSCV

)2

(2

(8)


where e is a specific heat term, ρ is the air density, h is the enthalpy of the air, p is the pressure, V is the airflow velocity, g is the gravitational acceleration, z is the elevation from a given reference, n indicates the surface normal of the cross section

area A the air passing through, Q is the net energy passing the CV boundary through heat transfer, and “•” indicates the time rate of the relevant property.

Figure 3. Schematic of the control volume (CV) for airflow energy analysis

In this model, it is assumed the airflow is steady. For

simplicity, the heat transfer across the boundary may be neglected at this point. Because there are rigid guides at the inlet and outlet of the motor, the air flowing in and out can be considered perpendicular to the cross sections of the inlet and outlet. The vertical elevation between the inlet and outlet is only 4 inches; thus, the effect of gravitational potential energy is negligible. Based on these assumptions, equation (8) is reduced to the following:

WdAnVVp

uCS

)2

(2

(9) where u is the internal energy of the air. Equation (9) provides an estimation of the available work output from the motor shaft. Equation (9) is a dynamic equation. The total energy initially stored in the pressure tank can be estimated using a static form of this equation. To estimate it, we may consider the pressure vessel is control volume, and initially, no air passes through the boundary (V = 0, W = 0). The equation for the energy stored in the pressure vessel can be written as follows:

mhd

puE

CV

)( (10)

where E is the total energy at the thermal dynamic state defined by room temperature (T), pressure level (P), and volume (); m is the total mass of the air stored in the tank; and h is the enthalpy of the air at room temperature and designated pressure. For room temperature operations, T1 = T2, and inlet location 1 has a pressure at p1. The outlet location 2 has a

pressure p2 at 1 atm. The simulator is meant to run steadily for about fifteen minutes at 10 mph. To satisfy the design criteria and the boundary conditions, equation (10) is used to estimate the total energy needed. Two standard, carbon-fiber pressure tanks with a total capacity of 46 standard cubic feet (SCF) and a maximum pressure level of 2216 psi are used. A two-stage regulating mechanism is used to provide a better steady flow. The pressure is regulated down to 100 psi. This constant pressure is then regulated down to a desirable pressure level controlled by a pinpoint controller. Energy consumption and analysis will be discussed in the later sections.

MECHANISMS The mechanism design and engineering include component

design, fabrication, and assembly. These involve the power chain, chassis, and core components and their supporting mechanisms. Power Chain

The power chain is made up of two pressure tanks, two regulators, an air filter and a lubrication system, an air motor, a gear-chain system, and relevant adaptors and connectors. shows The power chain arrangement is shown in Figure 4 below. The compressed air from the air tank is regulated to provide reliable air flow. The air flow is guided to pass through an air filter/lubricator before input into the air motor for protection purposes. The energy carried by the airflow is converted to mechanical torque through the air motor. The output torque from the motor is then transmitted through the gear-chain system to the driving wheel of the simulator.

Figure 4. Power chain architecture

Chassis and Major Supporting Mechanisms

The chassis is made out of recycled aluminum and steel bars. It consists of a center triangle frame with two additional triangle frames (steel tubes with a wall thickness of 0.125 in.) welded to each side to stabilize the system and provide the necessary strength. The simulator has a total of four wheels and the center rear wheel is the driving wheel. The major considerations are to achieve better manipulation, stability and safety, and a reduction of energy loss due to friction.


The mount made to hold the pressure tank is made up of a square bar with a 45o chamfer on the bottom. Another smaller square bar with a 45o chamfer is welded to the first bar to create an “L” shape. The two thin pieces of steel metal are welded to the larger square bar and bent around the tank to form two adjustable metal bands. A short piece of angle steel is welded to the end of each band. Lastly, a hole is drilled through each piece of angle iron so that the bands can be adjusted and bolted tightly around the pressure tank to ensure the stability and reliability as shown in Figure 5.

The motor mount consists of a small piece of sheet metal (76.2″ × 104.3″) welded to a piece of channel steel (C80 type). The channel steel is welded to the chassis frame. Five holes are drilled in the sheet metal. The center hole is for the motor’s drive shaft, and the other four smaller holes around the perimeter are for bolting the motor to the bracket. Their function is to keep the motor in the proper position to satisfy the alignment of the driving gear (attached to the motor) and the gear attached to the driving wheel, as shown in Figure 6. The completed air automobile simulator is presented in Figure 1 in the center.

Figure 5. Pressure tank supporting mechanism

Figure 6. Motor supporting mechanism

PRELIMINARY RESULTS AND DISCUSSIONS The simulator was designed to use compressed air without

any other power sources (i.e., batteries). Currently, the air tank is filled by an air compressor powered by a solar station established on campus previously. This makes the system sustainable and environmentally friendly. In addition, the power chain system is designed to maximize the energy efficiency. A multistage regulating system is integrated for accurate and easy airflow control to achieve smooth field driving. An in-line lubrication system is integrated to ensure durability and reliability.

Field-driving tests were conducted on a straight, level concrete road. Firsthand preliminary data were obtained. The performance indicators, average pick-up speed and acceleration, for a 164 feet (or 50 m) distance tested by the same driver are shown in Figure 7 (a) and (b). Figure 7 (a) shows the average speed as a function of time. Average speed is used since the measurements were done manually. It does not sacrifice accuracy (since the system run at low speed), and it gives clearer and more straightforward pictures of the system performance. The average speed used here is defined as the average speed achieved in a cumulative period from 0 to t. The tests show that the simulator can pick up speed very quickly, and all of the rides are smooth. It takes about ten seconds to reach a target speed of 10 mph. Figure 7 (b) shows the acceleration as a function of time for the field test. The acceleration is larger at the beginning. It decreases with time after reaching a certain speed level. The acceleration is reduced to zero after about ten to eleven seconds. The simulator runs at a constant speed of 10 mph when the acceleration is zero. The transition from the start to the constant driving speed of 10 mph is smooth, as one can observe from the figure. This is consistent with the driver’s experiences during the field tests.

Figure 7a. Average picking-up speed vs. time


Figure 7b. Average picking-up speed vs. time

There are many factors that may affect the speed and acceleration performance, such as the loading conditions, operational pressure level, and the airflow rate regulated (amount of air regulated in a certain time period). The smoothness of all the rides is believed to be the result of the well-designed mechanisms. For example, the speed is controlled by regulating the airflow with a high caliper pinpoint control mechanism. This pinpoint control mechanism leads to an even airflow across the whole power chain. Because the motor has a theoretical maximum rotational speed of 3000 rpm with a gear reduction ratio of 20:1, the simulator has a theoretical maximum linear speed of 22 mph. Due to safety considerations, the limit was not tested.

CONCLUSIONS AND FUTURE WORK The combination of pneumatic energy and other available

types of energy has a great potential to be a successful candidate in new generation of hybrid technology applications. This paper presents the design, modeling, and prototyping of an automobile simulator powered purely by clean pneumatic air with goals to investigate energy efficiency and running distance. The mechanisms to utilize the sustainable clean energy air to drive a 300 lb load to run at a steady speed of 10 mph for ten to fifteen minutes with a maximum up to 22 mph were discussed. Engineering design theories and scientific calculations were implemented in the modeling. These theories were also used to guide the technological design and fabrication work. A power chain was designed to convert the stored energy into mechanical torque to deliver the power to the driving wheel. The chassis was designed to meet the loading conditions and was fabricated of recycled metals, such as steel and aluminum. The stability and the effectiveness of power transmission were addressed. Preliminary field tests were conducted.

In addition, the prototype provides a significant field model to further investigate pneumatic air-related clean energy technologies, energy efficiency, and environmental impact. It is worthy to mention that the system is not a “hybrid” system at

its current stage. An energy regeneration mechanism using gravity when running down a slope or hill has been designed but is not installed yet. The system’s on boarding data acquisition system will also be designed and integrated into the system as well in the near future. With both the regeneration function and onboarding data colleting system, the firsthand field data, such as vibration, noise, and environmental impact, can be obtained. Those data will be expected to lead to further insights of the relevant applications. Also, the prototype will serve as an important stage in the process of exploring the applications of sustainable, alternative, clean, and efficient energy. These will also help to gain an in-depth understanding of the engineering processes and methodologies of modeling complex systems.

ACKNOWLEDGEMENT The project was funded by the PSU common campus

research fund. Greg Kurtz, an undergraduate student contributed to the manufacturing of the work.

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W. W., 2009, Fundamentals of Fluid Mechanics. (6th ed.). John Wiley & Sons, Inc. [13] Moran, M. J., Shapiro, H. N., Boettner, D. D. and Bailey, M. B., 2011, Fundamentals of Engineering Thermodynamics. John Wiley & Sons. [14] Anonymous, 2009, "Running on air," Economist. Vol. 391 Issue 8634, special section, p5-6. [15] Lu, C. H., Hwang, Y. R., Shen, Y. T., 2012, "Modeling and Simulation of a Novel Pneumatic Hybrid Motorcycle," International Journal of Green Energy. Vol. 9 Issue 6, p467-486. [16] Dönitz, C., Vasile, I., Onder, C., Guzzella, L., 2009, "Modelling and optimizing two- and four-stroke hybrid pneumatic engines," Proceedings of the Institution of Mechanical Engineers, Part D (Journal of Automobile Engineering). Vol. 223, Issue 2, p. 255-280. [17] Dönitz, C., Vasile, I., Onder, C., Guzzella, L., 2009, "Dynamic programming for hybrid pneumatic vehicles," 2009 American Control Conference. St. Louis, MO, US, 10-12 Jun, 2009. [18] Zhou, Z., Chen, Z. and Li, Y., 2012, “The Adoption Behavior of New Energy Automotive Technology in Chinese Firms: A Knowledge Rigidity Perspective,” J. Renewable Sustainable Energy. 4, 031802. [19] Allenby, B.R., 1999, Industrial Ecology: Policy Framework and Implementation. Upper Saddle River, NJ: Prentice Hall. [20] Tester, J. W., Drake, E. M., Driscoll, M. J., Golay, M. W., Peters, W. A., 2005, Sustainable Energy Choosing Among Options. The MIT press, Cambridge, MA. [21] Socolow, R., Andrews, C., Berkhout, F. and Thomas, V., 1999, Industrial Ecology and Global Change. Cambridge University Press, Cambridge, Great Britain. [22] Fairley, P., 2009, "Driving on air," IEEE Spectrum. Vol. 46 Issue 11, p30-35. [23] Groover, M. P., 2010, Fundamentals of Modern Manufacturing. (4th ed.). John Wiley & Sons. [24] Olumolade, M., Chen, D. M., Chen. H., 2011, “Design Prototyping for Manufacturability,” International Journal of Modern Engineering, 10 (2), 5-9. [25] Müller, S., Uchanski, M., Hedrick, K., 2003, “Estimation of the Maximum Tire-Road Friction Coefficient,” Journal of Dynamic Systems, Measurement, and Control, 125, 607-617. [26] Tipler, P. A., Mosca, G., 2008, Physics for Scientists and Engineers. (4th ed.). W. H. Freedman and Company. [27] Rolling friction and rolling resistance, http://www.engineeringtoolbox.com/rolling-friction-resistance-d_1303.html




DESIGN AND CONTROL OF A LEG PRESS TRAINING MACHINE FOR WHOLE BODY VIBRATION

Adetayo C. Faminu and Yong Zhu

Department of Mechanical Engineering Georgia Southern University

Statesboro, GA 30458

ABSTRACT Whole body vibration is the use of vibrating mediums to

heal, strengthen, and/or increase the flexibility in various parts of the body. A passive leg press device was designed to key these features to parts specifically found in the leg. This study was conducted by controlling a pneumatic bellows cylinder, in fluctuating in its height fast and far enough to be at the required frequency to be considered a useful whole body vibration table. An xPC target based control system was implemented so that the control logic can be easily programmed, parameters can be easily adjusted and good real-time performance can be achieved. Both simulation and experimental results demonstrated that the bellows cylinder position control was feasible. However, the motion frequency was far below what a vibration table would normally require since the thrust force provided by the bellows cylinder far exceeds the intended load. In the future, this might be partially mitigated if the subject were able to bend and press down, which would create a downward force of 2-3 times of body weight.

INTRODUCTION Whole body vibration is the use of vibrating mediums to

heal, strengthen, and/or increase the flexibility in various parts of the body. Whole body vibration has been widely used in training [1][2][3][4][5][7] and rehabilitation [6] research. There are required frequencies and changes in height of the vibrating table for it to be an efficient and effective tool. Various studies have proven that this form of exercise and training can be very beneficial as opposed to traditional ways of exercise such as resistive training for example. The only downside is that there is no cardio involved with passive leg press training in the form of whole body vibration, so a subroutine to include cardio would be needed in the exercise routine of the individual. Below is a look into the various studies that have been done with whole body vibration and passive leg press training.

Previous research indicates that vibration exercise may generally help improve flexibility, jump height, muscle power and range of motion. A passive leg press training machine was designed by Liu et al. [1] using an electrical motor, which provided periodic motions between 0.5 and 2.5 Hz. The study

tried to show that passive high contraction velocity can increase muscle power and speed. Peer et al. [2] studied that biomechanical muscle vibration using a commercial whole body vibration device appeared to have significant acute benefits for improving flexibility in healthy adults with ankle or hamstring injuries. Trans et al. [3] used whole body vibration exercise to improve muscle strength for women with osteoarthritis in the knee. Melnyk et al. [4] showed that whole body vibration appeared to have a positive effect on knee joint stability. Annino et al. [5] further demonstrated that whole body vibration training may be an effective and safe training strategy to improve the muscle power in high-level ballet students. Vargas [6] showed that whole body vibration can be used as a rehabilitation tool for patients recovering from Anterior Cruciate Ligament (ACL) injuries. Van den Tillaar’s research [7] also indicated that whole body vibration may help improve range of motion of hamstrings.

Commercial whole body vibration devices usually operate up to very high frequencies, e.g. 30 Hz with 10 mm amplitude. This study will be conducted by trying to control an actuator, more specifically a bellows cylinder, in fluctuating in its height fast and far enough to be at the required frequency to be considered a useful vibration table. The bellows actuator we will be using is a Festo single-bellows cylinder, which traditionally is used in passive or active suspensions for high-frequency vibration isolation [8]. To the best of our knowledge, there is almost no research that has been done in terms of using a pneumatic bellows cylinder as an active actuator for whole body vibration. This study would try to bridge this gap and explore the possibility and advantages of using a pneumatic bellows cylinder to drive a whole body vibration device for training or rehabilitation purposes.

The paper is organized as follows. First, the mechanical design of the whole body vibration table will be presented. Then, the real time control system will be presented. After that, simulation and experimental results will be given to demonstrate the feasibility and limitation of controlling the pneumatic bellows cylinder. Conclusions are drawn at the end.


MECHANICAL DESIGN A prototype design showing the basic setup for the passive

leg press trainer was created using SolidWorks. It consists of a bellows cylinder with a bottom and top plate attached to it. Both the bottom and top plates consist of four holes each that allow the attachment of a mechanical connector. The top plate has an extra fifth whole to allow for the pneumatic connection to the bellows cylinder. Each hole in the plates consists of a diameter that is greater than the connection to allow for clearance space. From the bottom plate extend two poles that have a bar in between each other connecting them together. The bar acts a support for test subjects to hold on to in order to assist in generating the downward force needed from their legs to make the passive leg press training machine useful. Figure 1 shows the front and isometric views of the basic leg press layout. The first design was created under the thought that the bellows cylinder would need springs to help support any downward force put on it; this can be seen in the four open cylinders connected to the top of the bottom plate and the four open cylinders connected to the bottom of the top plate. To quickly test this proof-of-concept design, the bars were not implemented in this study.

Figure 1: Front view and isometric view of the prototype

design

In order to have a functional prototype, a bottom and top plate were needed. The bottom plate assists in preventing the bellows cylinder from tilt, while the top plate would act as a platform for the placement of feet so test subjects can stand on it. The plates are made out of plexiglass, a material that is durable enough for testing the passive leg press training machine. Plexiglass is easy to manufacture, as it can be easily

drilled and cut through. The pre-final prototype design with plexiglass bottom and top plates is shown in Figure 2.

Figure 2: Pre-final prototype design with plexiglass bottom and top plates

CONTROL DESIGN Control technologies are applied in almost every field of

industry around the world. These control designs are made up of models, simulations, implementations, and evaluations. Systems can be large and complicated, but the use of real-time control allows for control experiments to become simple. In our control system design, Simulink is used as the graphical user interface while the xPC Target supports I/O hardware via its block diagrams that can be integrated to the Simulink models. Real-time environments do an excellent job of bridging the gap between simulation modeling and hardware controlling while maintaining a good performance level.

Figure 3: Overall system design schematic diagram

Simulink model real-time testing environments were created by connecting a host computer, target computer and any hardware that is undergoing the experimental tests together. The advantage of PC usage is in its computing power, flexibility, and expandability. The host computer runs the Simulink models, xPC Target, and a C compiler. The host computer is then linked to the target computer via an Ethernet cable. The target computer is then connected to the hardware via a NI


SCB-68A I/O board. The host computer is the medium used to design and model in Simulink, the target computer runs the Simulink model in real-time with the xPC Target, and then the hardware, i.e. actuators, sensors and valves, are controlled by the system. By creating a real-time control system, the hardware is controlled using the model created in Simulink. The overall real time control system schematic is shown in Figure 3.

xPC Target implements the Simulink model on a target computer for hardware simulation, real-time testing solutions, rapid control prototyping, and any other real-time testing applications. It allows for the hardware in testing to be monitored and for the data to be logged along with parameter tuning.

SIMULATION Soon after we started to look at the force-stroke curves

(Figure 4) of the Festo pneumatic bellows cylinder EB-385-115, we realized that the force provided by the pneumatic bellows cylinder far exceeds our intended load.

Figure 4: Force-stroke curves of the bellows cylinder [10].

A simulation study was first carried out to verify this. If the pressures and volume of the bellows is P and V , the mass flow rate is m , the rate of change of pressure within the bellows can be expressed as:

VVPm

VRTP

−=

(1)

The nonlinear relationship between the valve orifice area vAand the mass flow rate m can be represented as a function of the upstream pressure uP and downstream pressure dP ,

),( duv PPAm ψ= (2)

where Ψ is the area normalized mass flow rate, which can be written as:

<Ψ≥Ψ

=Ψ0for ),(0for ),(

),(vatm

vsdu APP

APPPP (3)

A common mass flow rate model used for compressible gas flowing through a valve [9] is the following:

−

≤=Ψ

− (unchoked) otherwise)(1)(

(choked) if),(

/)1()/1(2

1

kk

u

dk

u

duf

ru

duf

du

PP

PP

T

PCC

CPP

T

PCC

PP

(4)

where fC is the discharge coefficient of the valve, k is the ratio of specific heats, rC is the pressure ratio that divides the flow regimes into choked and unchoked flow and 1C and 2C are constants defined as:

)1/()1(1 )

12( −+

+= kk

kRkC and

)1(2

2 −=

kRkC (5)

According to the force-stroke curves shown in Figure 4, the stroke is a function of the pressure P (gage pressure between 0 and 8 bar) and thrust force F :

),(1 FPfH = (6)

Referring to the volume-stroke curve shown also in Figure 4, we can represent bellows volume V as a function of stroke H:

)(2 HfV = (7)

Simulating Equations 1-7 while assuming quasi-static condition: MgF = , where Mg is the gravitational force of the test subject. Since Mg is so small when compared to the thrust forces from 1 to 8 bar in Figure 4, that it became very challenging to control the stroke with the desired frequency and amplitude.

A simple proportional controller was used to make the bellows actuator track sine wave inputs. Two cases are shown in Figures 5 and 6 with period T = 20 and 10 seconds. Note that 5 Volt input for the valve corresponds to its neutral position, meaning the mass flow rate ideally should be zero at 5V control voltage. Since the valve mass flow rate is limited, to keep up with the command, the amplitude was set to be only 1 mm. It appears in Figure 5 that the stroke position tracking is generally acceptable. When the sine wave period is reduced to T =10 sec, the valve becomes saturated for most of the time and the actual output cannot keep up with the input command as shown in


Figure 6. For both tests shown in Figures 5 and 6, the supply pressure was kept at 40 psi.

Figure 5: Simulation results of bellows actuator sinusoidal

position tracking (T=20 sec)

Figure 6: Simulation results of bellows actuator sinusoidal

position tracking (T=10 sec)

EXPERIMENTAL RESULTS A Festo single-bellows cylinder (Festo EB-385-115) with a

piston diameter of 385 mm and stroke 115 mm was used as the actuator for the whole body vibration device. A pressure sensor

(Festo SPTW-P25R-G14-VD-M12) is attached to the air chamber in order to measure the pressure in the bellows cylinder. The bellows cylinder has a maximum tolerance of 8 bars pressure. An OTE HY3003-3 Triple output DC power supply producing a voltage of 24 volts was used to power the system. A linear potentiometer (Midori LP-100F) with 100 mm maximum travel is used to measure the displacement of the pneumatic bellows cylinder. A proportional valve (Festo MPYE-5-M5-010-B) controls the fluid flow. An xPC Target based real time control system shown in Figure 7 is used to compile the Simulink model into C language. The target application is then downloaded from the host computer via a LAN connection (Ethernet), and the application is then programmatically controlled by running through the target computer. The data produced from the hardware is then transferred back to the host computer to be evaluated as logged signal data.

Figure 7: Testing set up with the controls and basic components

A closer look at the final prototype design with

displacement sensor attached is shown in Figure 8. An open loop simple test was first carried out to analyze how fast the valve was able to charge or discharge the bellows cylinder. The valve was charged and discharged according to a pulse generator input command that was set at an amplitude of 4.5V (centered around 5V neutral position) with a pulse width of 50 percent of the pulse time (T = 20 seconds). This pulse setting allowed for air to be discharged from the bellows cylinder for 10 seconds and then air to be charged back into the bellows cylinder for another 10 seconds. The pulse width acts as a percentage of the pulse time, and because the time was set to 20 seconds with a width of 50 percent the time for charge and discharge was half of the time making them equal to 10 seconds. With this setting the top plate was able to rise approximately two millimeters and decrease in height by 1.5 millimeters. This amplitude is close to being ideal for a

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vibration table, but the frequency of the table was not high enough. This verified our concern that the bellows cylinder would not be able to move fast enough to serve as an effective leg press machine and whole body vibration table.

Figure 8: Final prototype design with displacement sensor

attached. A closed loop PID controller was created in the model to

track sine wave position command similar to the simulation results shown in Figures 5 and 6. The experimental results shown in Figures 9 and 10 are very similar to the simulation results shown in Figures 5 and 6; this proves that our understanding of the bellows cylinder was correct and verifies that its thrust force is indeed too large for our intended load.

Figure 9: Experimental results of bellows actuator

sinusoidal position tracking (T=20 sec)

Figure 10: Experimental results of bellows actuator sinusoidal position tracking (T=10 sec)

As a summary, the purpose of this experiment was to

design a control system that would allow a bellows cylinder to act as vibration table. With the model used in Simulink, the sinusoidal pattern of the bellows cylinder’s fluctuation was created. It is possible to control the bellows cylinder to track small amplitude and slow varying sine waves using the proportional control valve, but not at a high enough frequency to consider it a passive leg press training machine and whole body vibration table. Based on these results, it was determined that the load on the bellows cylinder was not large enough to produce the proper amount of stroke change. The bellows cylinder has a stiffness so large that when a person stands on it, it is as if a miniscule load has been applied. In the future, this might be partially mitigated if the subject were able to bend and press down, which would normally create 2-3 times of body weight. This feature was not implemented in the current design.

CONCLUSION The greatest challenge of this study was trying to control

the bellows cylinder into fluctuating at a high enough frequency to work as a useful leg press trainer. Though we were able to get the actuator to change its height by charging and discharging air into the system, we were unable to do so at a fast enough frequency, one needed to be considered a useful passive leg press trainer. The size of the valves may also need to increase in order to allow enough air to flow in and out the bellows cylinder causing a rapid increase and decrease in the position of the top plate. Another future goal to mitigate this is to implement the vertical bars so that the test subject could bend and press hard downward to create a 2-3 times larger load on the bellows cylinder.

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Overall, it appears that pneumatic bellows actuators, especially the ones with large thrust force like we have been using, may not be a good choice to be used as a relatively high frequency actuator due to its intrinsic natural compliance and requiring large load and large flow rate to achieve a fast stroke change.

REFERENCES [1] Liu, C., Chen C.-S., Ho W.-H., Füle R. J., Chung P.-H., and

Shiang T.-Y., 2013, “The effects of Passive Leg Press Training on Jumping Performance, Speed, and Muscle Power,” J Strength and Conditioning Research, 27(6), pp. 1479-1486.

[2] Peer, K. S., Barkley, J. E., and Knapp, D. M., 2009, “The Acute Effects of Local Vibration Therapy on Ankle Sprain and Hamstring Strain Injuries,” The Physician and Sports Medicine, 37(4), pp. 31-38.

[3] Trans, T., Aaboe, J., Henriksen, M., Christensen, R., Bliddal, H., and Lund, H., 2009, “Effect of Whole Body Vibration Exercise on Muscle Strength and Proprioception in Females with Knee Osteoarthritis,” The Knee, 16(4), pp. 256-261.

[4] Melnyk, M., Kofler, B., Faist, M., Hodapp, M., Gollhofer, A., 2008, “Effect of a Whole-Body Vibration Session on

Knee Stability,” Int J Sports Medicine, 29(10), pp. 839-844.

[5] Annino, G., et al., 2007, “Effect of Whole Body Vibration Training on Lower Limb Performance in Selected High Level Ballet Students,” J Strength and Conditioning Research, 21(4), pp. 1072-1076.

[6] Vargas, S.R., 2011, “Whole Body Vibration in Anterior Cruciate Ligament Rehabilitation,” Master’s thesis in Health and Human Movement, Utah State University.

[7] Van den Tillaar, R., 2006, “Will Whole-Body Vibration Training Help Increase the Range of Motion of the Hamstrings?” J Strength and Conditioning Research, 20(1), pp. 192-196.

[8] Porumamilla, H., 2007, “Modeling, Analysis and Non-linear Control of a Novel Pneumatic Semi-active Vibration Isolator: A Concept Validation Study,” Ph.D. dissertation in Mechanical Engineering, Iowa State University.

[9] Richer, E., and Hurmuzlu, Y., 2000, “A High Performance Pneumatic Force Actuator System: Part I-Nonlinear Mathematical Model,” ASME J Dynamic Systems, Measurement and Control, 122(3), pp. 416-425.

[10] Festo manual of bellows cylinders EB/EBS, available at http://www.festo.com/cat/fi_fi/data/doc_engb/PDF/EN/EB-EBS_EN.PDF



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SECTION 7 DESIGN & MANUFACTURING