FINITE ELEMENT MODELLING OF SMART STRUCTURES

A dissertation submitted in partial fulfillment of the requirement for the award of the degree of

MASTER OF TECHNOLOGY

in

STRUCTURAL ENGINEERING

Submitted by

V.S.N.MURTHY KOLLEPARA

ENTRY NO -2004CES2066

Under The Guidance of

Dr. SURESH BHALLA

DEPARTMENT OF CIVIL ENGINEERING INDIAN INSTITUTE OF TECHNOLOGY DELHI

MAY 2006

CERTIFICATE

This is to certify that the dissertation entitled “FINITE ELEMENT MODELLING

OF SMART STRUCTURES” which is being submitted by

V.S.N.MURTHY.KOLLEPARA (ENTRY NO: 2004CES2066) in the partial

fulfillment of the requirements for the award of degree of Master of Technology in

“STRUCTURAL ENGINEERING” is a record of the student’s own work carried out

at Indian Institute of Technology Delhi under my supervision and guidance. The

matter embodied in this thesis has not been submitted elsewhere for the award of any

other degree or diploma.

Dr. SURESH BHALLA

Assistant professor

Department of Civil Engineering

Indian Institute Of Technology Delhi New Delhi May 2006

ACKNOWLEDGMENT

I have great pleasures and privilege to express my deep sense of gratitude and

thankfulness towards my supervisor, Dr. SURESH BHALLA, for his invaluable

guidance, constant supervision and continuous encouragement and support throughout

this work. Timely guidance and valuable suggestions have steered me in clearing out

difficulties at every juncture.

I am thankful to all staff members of Computation Laboratory, Computer Service

Centre for their co-operation while carrying out the analysis work. I am equally grateful

to all my classmates, friends and family for their encouragement, support and help.

(V.S.N.MURTHY.KOLLEPARA) New Delhi, May, 2006. 2004CES 2066

ABSTRACT Structural health monitoring is gaining importance day by day. Failure of any

infrastructure causes severe loss of life and economy. Therefore, critical structures should

be monitored at frequent intervals. Even though visual inspection is the most common

appropriate at the present, it is very tedious, and needs experienced people. Over the last

two decades, many researchers have tried to find the alternative solution for visual

inspection.

This study concentrated on high frequency because of the limitations of

low frequency techniques, in locating incipient damages. Unique properties of direct and

converse piezoelectric effects enable piezo electrio-ceramic (pzt) patch to act both as an

actuator and as a sensor simultaneously. Making use of the sensing capability the of PZT

patch, conductance signature of the structure can be obtained against which health

monitoring of the structure can be done. Signature of the structure in healthy state is

called the base line signature. It is compared with signature obtained after a time lapse,

which is called secondary state conductance signature. The characteristic feature of the

EMI technique is that it activates higher frequency modes of the structure.

The present study was performed on a lab sized RC model frame.

Numerical simulation of the frame was carried out using finite element approach with

ANSYS 9 software. Results were compared the experimental data obtained by Bhalla

and Soh ( 2004 ). So far, researchers developed numerical solution at frequency of less

than 25 kHz. In this case, numerical simulation was done in a frequency range of 100 to

150 kHz. Conductance signatures of experimental and simulation method compare

reasonably well. Peak conductance found in two curves at identical frequencies.

Magnitude wise, these signatures are better correlated compared to those of other

researchers. Conductance signatures for the damaged frame were also obtained by

simulating different type of damages numerically. Cracks were simulated by reducing

the Young’s modulus of elements at the location of damage. Numerically obtained

conductance signatures followed the same trend as that of experimental signatures for

these damages. Influence of cracks on the conductance signature was clearly identified.

Percentage of variation of the numerical results with respect to the experimental results

are very less compared to Giurgiutiu and Zagari (2002), Tseng and Wang(2004) results.

These results will be helpful for further research in smart structures area. Purpose of this

research is to minimize the necessity of tedious experimental work and to save the

economic resources. The successful numerical modelling will enabled researchers to

carry out further work in the area of smart structures. Challenging tasks like modeling of

piezo electric coupling in shell or plate structures can be performed in this manner.

Fracture analysis in the presence of coupled behavior is another critical aspect to be

studied with help of numerical modeling.

TABLE OF CONTENTS

CONTENT PAGE

CERTIFICATE i

ACKNOWLEDGEMENT ii

ABSTRACT iii

TABLE OF CONTENTS v

LIST OF FIGURES vii

LIST OF TABLES viii

CHAPTER1: INTRODUCTION 1

1.1 General 1

1.2 Need for health monitoring 2

1.3 Objective and scope of study 3

1.4 Organisation of thesis 3

CHAPTER 2: STRUCTURAL HEALTH MONITORING 4

2.1 Structural health monitoring : An over view 4

2.1.1 Passive sensing diagnostics 5

2.1.2 Active sensing diagnostics 5

2.1.3 Self –healing-self –repairing 6

2.2 Techniques of health monitoring 7

2.2.1 Conventional techniques for structural health monitoring 7

2.3 Techniques using smart materials and smart structure concepts 11

2.3.1 Smart structure 12

2.3.2 Components of smart structures 12

2.3.3 Potential applications of smart materials in Civil Engineering 14

2.3.4 Research needed in smart structures 15

2.3.5 Necessity of Modelling 15

2.4 Summary 15

CHAPTER3: STRUCTURAL HEALTH MONITORING WITH

PIEZO ELECTRIC ACTUATOR/SENSOR PATCHES. 16

3.1 Piezoelectricity and piezo electric materials 16

3.2 Fundamental piezoelectric relations 17

3.3 Principle and method of application 18 3.3.1 Description of EMI technique 18

3.3.2 Damage quantification 20

3.3.3 Improvements in EMI technique in recent years. 20

3.4 Advatages of EMI technique 21

3.5 Limitations of EMI technique 22

3.6 Conclusions 22

CHAPTER4 :FINITE ELEMENT MODELING OF SMART STRUCTURE

4.1 Importance of Numerical simulation 23

4.2 Finite element modeling of Rc frame 27

4.3 Results 30

4.4 Comparative study 32

4.5 Conductance signature with flexural damage 33

4.6 Study of conductance signature pattern by inducing different

damages to the numerical model 33

4.6.1 Determination of damping constants 34

4.7. Study of effect of damage on conductance signature of numerical

model RC frame 35

4.7.1. Study of effect of flexural crack 35

4.7.2. study of effect of shear crack 37

4.7.3. Effect of both flexural and shear crack 39

4.8comparison of experimental and simulated results 42

CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS

5.1 Conclusions 44

5.2 Recommendations 45

5.3 Remarks 45

5.4 Advantages of numerical modeling 46

5.5 Limitations 46

REFERENCES 47

LIST OF FIGURES:

Fig 3.1 (a) a PZT bonded to the structure 17

(b) Interaction model of one half pzt and host structure 17

Fig 4.1.a Pristine conductance signature on specimen 1 (Tseng and Wang) 24

Fig 4.1.b Pristine conductance signature on specimen 2 (Tseng and Wang) 24

Fig 4.2 Experimental and calculated Impedance Vs Frequency 25

Fig 4.3 Details of the test frame 28

Fig 4.4 Finite element model of lab sized frame. 29

Fig 4.5 Conductance signature using 10mm, 5mm, 3mm size of the elements 30

Fig 4.6 Numerical conductance signature of the pristine frame model 31

Fig 4.7 Experimental conductance signature of the pristine frame model 32

Fig 4.8 Simulated conductance signature of frame for healthy & damaged state 33

Fig 4.9 conductance signature with different damping constants 34

Fig 4.10 Numerical conductance signature with modified damping constants 35

Fig 4.11 simulated RC frame with Flexural cracks. 36 Fig 4.12 Effect of flexural crack on conductance signature 37 Fig 4.13 RC frame with shear crack near PZT location 38 Fig 4.14 Effect of shear crack on conductance signature of numerical model 39 Fig 4.15. Simulated frame with both flexural and shear cracks 40

Fig 4.16 Effect of different types of damages on conductance signature of

numerical model frame 40

Fig 4.17 Effect of PZT distance from the damage location. 41 Fig 4.18 Experimental results 42 Fig 4.19 Results obtained from Numerical model 43

LIST OF TABLES:

Table 4.1 Material properties of concrete 27

Table 4.2 Mechanical and electrical properties of PZT 28

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CHAPTER1

INTRODUCTION

1.1 GENERAL

Health monitoring is the continuous measurement of the loading environment

and the critical responses of a system or its components. Health monitoring is typically

used to track and evaluate performance, symptoms of operational incidents, anomalies

due to deterioration and damage as well as health during and after an extreme event

(Aktan et al, 2000). Health monitoring has gained considerable attention in civil

engineering over the last two decades. Although health monitoring is a maturing concept

in the manufacturing, automotive and aerospace industries, there are a number of

challenges for effective applications on civil infrastructure systems. While successful

real-life studies on a new or an existing structure are critical for transforming health

monitoring from research to practice, laboratory benchmark studies are also essential for

addressing issues related to the main needs and challenges of structural health

monitoring. Health monitoring offers great promise for civil infrastructure

implementations. Although it is still mainly a research area in civil infrastructure

application, it would be possible to develop successful real-life health monitoring systems

if all components of a complete health monitoring design are recognized and integrated.

A successful health monitor design requires the recognition and integration of

several components. Identification of health and performance metric is the first

Component which is a fundamental knowledge need and should dictate the technology

involved. Current status and future trends to determine health and performance in the

context of damage prognosis are reported by Farrar et al. in a recent study (2003).

New advances in wireless communications, data acquisition systems and

sensor technologies offer possibilities for health monitoring design and implementations

(Lynch et al, 2001, Spencer, 2003). Development, evaluation and use of the new

technologies are important but they have to be considered along with our “health” and

“performance” expectations of the structure. Yao (1985) defined the term damage as a

deficiency or deterioration in the strength of the structure, caused by external loading or

environmental conditions or human errors. So far visual inspection has been the most

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common tool to identify the external signs of damage in buildings, bridges and industrial

structures. These inspections are made by trained personnel. Once gross assessment of

the damage location is made, localized techniques such as acoustic, ultrasonic,

radiography, eddy currents, thermal, or magnetic field can be used for a more refined

assessment of the damage location and severity. If necessary, test samples may extract

from the structure and examined in the laboratory. One essential requirement of this

approach is the accessibility of the location to be inspected. In many cases critical parts of

the structure may not be accessible or may need removal of finishes. This procedure of

health monitoring can therefore be very tedious and expensive. Also, the reliability of the

visual inspection is dependent, to large extent, on the experience of the inspector. Over

the last two decades number of studies have been reported which strive to replace the

visual inspection by some automated method, which enable more reliable and quicker

assessment of the health of the structure. Smart structures was found to be the alternative

to the visual inspection methods from last two decades, because of their inherent

‘smartness’, the smart materials exhibit high sensitivity to any changes in environment.

1.2 NEEDS FOR HEALTH MONITERING

Appropriate maintenance prolongs the life span of a structure and can be used to

prevent catastrophic failure. Higher operational loads, greater complexity of design and

longer life time periods imposed to civil structures, make it increasingly important to

monitor the health of these structures. Economy of a country depends on the

transportation infrastructures like bridges, rails, roads etc., Any structural failure of

buildings, bridges and roads causes severe damage to the life and economy of the nation.

The U.S. economy is supported by a net work of transportation infrastructures like

highways, railways, bridges etc., amounting to about US$ 2.5 trillion worth (Wang et al.,

1998). Every government is spending many crore of rupees every year for the

rehabilitation and maintenance of large civil engineering structures. Failure of civil

infrastructure to perform may effect the gross domestic production of the country.

These facts underline the importance of an automated health monitoring system,

which cannot only prevent an incipient damage included collapse, but can also make an

assessment of structural health, as and desired, at a short notice. These automated systems

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hold the promise for improving the performance of the structure with an excellent

benefit/cost ratio, keeping in view the long term benefits.

1.3 OBJECTIVE AND SCOPE OF PROJECT

The objective of this project was to develop methodologies for finite element

analysis of smart structures. In specific, the project attempted to compare experimental

results obtained for health monitoring of lab sized Reinforced concrete (RC) frame with

of numerical simulations, using finite element analysis. The study made use of high

frequency dynamic response technique employing smart piezoceramic (PZT) actuators

and sensors. They can excite the structure to vibrate at high frequencies, thus activating

the local modes, which have higher sensitivity to incipient damage (Giurgiutiu and

Rogers, 1997). Numerical results matched reasonably well with the experimental

signatures, especially the peak frequencies. As second part of the project, appropriate

damping constants were found by trial and error. Different damages were simulated into

the numerical model and the effects of those damages on the conductance signature were

studied and compared with the experimental results. Purpose of Numerical simulation

was to avoid tedious experimental work of subjecting the structure to numerous fractures

in future research, thereby and saving time and money in future research.

1.4 ORGANISATION OF REPORT

This report consists of total of five chapters including this introductory chapter.

Chapter 2 presents detailed review of research in the area of health monitoring of

structures. In Chapter 3, the fundamental relations of the piezoelectric patches and

structural health monitoring using PZT patches and the recent developments in EMI

technique are discussed. Chapter 4 presents procedure of the numerical simulation of RC

model frame. Results are described and discussions are made. Chapter 5 presents the

conclusions and scope of the work.

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.CHAPTER 2

STRUCTURAL HEALTH MONITORING

2.1 STRUCTURAL HEALTH MONITORING (SHM): AN OVER VIEW

Increase in population necessitated the more civil infrastructural facilities in

every country. Wealth of the nation can be represented by well conditioned infrastructure.

Civil engineering structures under go damage and deterioration with age and due to

natural calamities. Nearly all in-service structures require some form of maintenance for

monitoring their integrity and health condition. Collapse of civil engineering structures

leads to immense loss of life and property. Appropriate maintenance prolongs the

lifespan of a structure and can be used to prevent catastrophic failure. Current schedule-

driven inspection and maintenance techniques can be time consuming, labor-intensive,

and expensive. SHM, on the other hand, involves autonomous in-service inspection of the

structures. The first instances of SHM date back to the late 1970s and early 1980s. The

concept of SHM originally applied to aerospace and mechanical systems is now being

extended to civil structures.

Objectives of health monitoring are as follows.

a) To ascertain that damage has occurred or to identify damage

b) To locate the damage

c) To determine the severity of damage.

d) To determine the remaining useful life of the structure.

SHM consists of both passive and active sensing and monitoring. Passive sensing and

monitoring is used to identify the location and force–time–history of external sources,

such as impacts or acoustic emissions. Active sensing and monitoring is used to localize

and determine the magnitude of existing damages. An extensive literature review of

damage identification and health monitoring of structural and mechanical systems from

changes in their vibration characteristics is given by Doebling et al. (1996).

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2.1.1 PASSIVE SENSING DIAGNOSTICS

For a passive sensing system, only sensors are installed on a structure. Sensor

measurements are constantly taken in real time while the structure is in service, and this

data is compared with a set of reference (healthy) data. The sensor-based system

estimates the condition of a structure based on the data comparison. The system requires

either a data base, which has a history of prestored data, or a structural simulator which

could generate the required reference data.

Passive sensing diagnostics are primarily used to determine unknown inputs from

changes in sensor measurements. Choi and Chang (1996) suggested an impact load

identification technique using piezoelectric sensors. They used a structural model and a

response comparator for solving the inverse problem. The structural model characterised

the relation between the input load and the sensor output. The response comparator

compared the measured sensor signals with the predicted model.

2.1.2 ACTIVE SENSING DIAGNOSTICS

Active sensing techniques are based on the localized interrogation of the

structures. They are used to localize and determine the magnitude of an existing

damages. Local or wave propagation-based SHM is therefore advantageous since much

smaller defects can be detected. Chang (2000) concentrates his research on wave-

propagation-based SHM. He developed Lamb-wave-based techniques for impact

localization /quantification and damage detection. Wilcox et al. (2000) examined the

potential of specific Lamb modes for detection of discontinuities. They considered large,

thick plate structures (e.g. oil tanks) and thin plate structures (e.g. aircraft skins). They

showed that the most suitable Lamb mode is strongly dependent on what the plate is in

contact with. Bhalla and Soh (2005) presented the technique using wave propagation

approach for NDE using surface bonded piezoceramics. They utilized simple, economical

and commercially available hardware and sensors, which can be easily employed for real

time and online monitoring of critical structures, such as machine parts and aircraft

components. Lemistre and Balageas(2001) presented a robust technique for damage

detection based on diffracted Lamb wave analysis by a multire solution wavelet

transform. Berger et al. (2004) employed fibre optic sensors in order to measure Lamb

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waves. Benz et al. (2003) and Hurlebaus et al.(2002) developed an automated, non-

contact method for detecting discontinuities in plates. Laser ultrasonic techniques were

used to generate and detect Lamb waves in a perfect plate and in a plate that contains a

discontinuity. The measured signals were first transformed from the time–frequency

domain using a short-time Fourier transform (STFT) and subsequently into the group–

velocity–frequency domain. The discontinuity is then located through the use of a

zzcorrelation in the group–velocity–frequency domain. The smart layer presented by Lin

and Chang (1998) makes use of a PZT-sensing element, whereas the smart layer

presented by Hurlebaus et al.(2004) uses PVDF-sensing elements. Finally, in the study by

Lin and Chang (2002) PZT transducers were placed at a few discrete points on the smart

layer; and in the study by Hurlebaus et al. (2004), the PVDF polymer covers the entire

surface of the smart layer.

2.1.3. SELF–HEALING & SELF–REPAIRING

Peairs et al. (2004) presented a method for the self-healing of bolted joints based

on piezo electric &.shape memory alloys . The loosening of a bolted joint connection is a

common structural failure mode. They reported a real-time condition monitoring and

active control methodology for bolted joints in civil structures and components. They

used an impedance-based health-monitoring technique which utilizes the

electromechanical coupling property of piezoelectric materials to identify and detect bolt

connection damage. When damage occured, temporary adjustments of the bolt tension

could be achieved actively and remotely using shape memory alloy actuators.

Specifically, when a bolt connection became loose, the bolted members can moved

relative to each other. The heat produced by this motion caused a Nitinol washer to

expand axially, thereby leading to a tighter, self-healed bolt connection.

Hagood and von Flotow(1991) established the analytical foundation for general

systems with shunted piezoelectrics. Their work characterised the electromechanical

interactions between a structure and the attached piezo network, and offers some

experimental verification. Davis and Lesieutre(1995) extended previous studies by using

the modal strain energy approach to predict the structural damping produced by a

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network of resistively shunted piezoceramic elements. Using this approach, the amount

of added damping per mode caused by an individual ceramic element can be computed.

It was also demonstrated that increased damping could be achieved in several modes

simultaneously via proper placement of the piezoceramics. demonstrates the effectiveness

of shunted piezoelectricity for three different resistance values. A structural vibration

control concept using piezoelectric materials shunted with real-time adaptable electrical

networks has also been investigated by Wang et al. (1994). Instead of using variable

resistance only, they implemented variable resistance and inductance in an external RL

circuit as control inputs. They created an energy-based parametric control scheme to

reduce the total system energy while minimising the energy flowing into the main

structure. Furthermore, they proved stability of the closed-loop system and examined the

performance of the control method on an instrumented beam. Hagood and von Flotow

presented a passive damping mechanism for structural systems in which piezoelectric

materials are bonded to the structure of interest.

In previous days health monitoring concept was limited to electrical and

mechanical systems. In present days, it is extended to large civil structures also. Civil

engineering structures are huge, heavy, expensive and more complex than electrical and

mechanical systems. The need for quick assessment of state of health of civil structures

has necessitated research for the development of real time damage monitoring and

diagnostic systems.

2.2 TECHNIQUES OF HEALTH MONITORING

2.2.1 Conventional Techniques for Structural Health Monitoring (a) Static response based techniques

This technique was formulated by Banan et. al. (1994). In this method

static forces applied on structure and corresponding displacements are measured. It is not

necessary to select the entire set of forces and displacements. Any subset could be

selected, but a number of load cases may be necessary in order to obtain sufficient

information for computation. Computational method based on least scale error function

between model and actual measurement is used. The resulting equations are to be solved

to arrive at a set of structural parameters. Any change in the parameters from the base

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line healthy structure is an indicator of damage. The short comings of this technique are

measurement of displacements is not an easy task. It requires establishment of frame of

reference. Employing a member of load cases can be very time consuming. Besides, the

computational effort required by the method is enormous.

Sanayei and Saletnik (1996) proposed a technique based on static strain method.

The advantage of this technique is strain measurement can be made accurately compared

to displace measurement. Although the method has some advantages over the static

displacement method, its application on real life structures remains tedious.

(b) Dynamic response based techniques

In this method structure is subjected to low frequency vibrations, and dynamic

response of the structure are measured and analysed. By this analysis a suitable set of

parameters such as modal frequencies, and modal damping, and mode shapes associated

with each modal frequency. changes also occur In structural parameters namely the

stiffness matrix and damping matrix. In this method structure is exited by appropriated

means and the response data processed to obtain a quantitative index or a set of indices

representative of the condition of the structures.

These techniques have advantageous over static response since they are

comparatively easier to implement. Few methods using low frequency dynamic technique

are described below.

Casas and aparcio (1994) presented a method of localizing and quantifying

cracks in bridges based on the first few natural frequencies and mode shapes extracted

from the dynamic response measurements.

Zimmerman and kaouk (1994) developed this damage detection method based

on changes in the stiffness matrix. The stiffness matrix is determined from mode shapes

and modal frequencies derived from the measured dynamic response of the structure.

The stiffness matrix matrix [K] may be expressed in terms of mode shape matrix [φ ],

the mass matrix [M], and the modal stiffness matrix [Ω ].

[K] = [M][φ ][Ω ]T[M] (2.1)

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Change in flexibility method.

This method of damage detection and localization in beams was proposed by

Pandey and Biswas (1994). The basic principle used in this approach is that damage in a

structure alters its flexibility matrix which can be used to identify damage. Secondly,

damage at a particular loation alters the respective elements differently. The relative

amount by which different elements are altered is used to localize the damage. Like

change in stiffness method, mode shape vectors and resonant frequencies obtained from

the dynamic response data (collected before damage and after damage) are used to obtain

the flexibility matrix [F], which may be expressed as

[ ] [ ][ ][ ] [ ]1F φ φ−= Ω (2.2)

As can be seen from Eq. (2.2) [F] is proportional to the square of the inverse of the modal

frequencies. Therefore it converges rapidly with increasing frequencies. Hence only few

lower modes are sufficient for an accurate estimation of [F].

The technique is an improvement over the change in stiffness method but the

researchers did not investigate the case of multiple damage locations.

This method is based on low frequency dynamic response of structure

involving only the first few low frequency modes of vibration. Therefore only a limited

number of modal frequencies and corresponding mode shape vectors can be extracted.

This limited number of modal vectors may not provide sufficient information to detect

damage at all possible locations. These techniques rely on the global properties to

identify local changes. Global parameters do not change significantly when a small order

local damage occurs. At local frequencies, small cracks cannot significantly affect the

global parameters to permit effective damage detection.. Therefore, the low frequency

techniques are not dependable for the detection of relatively small cracks.

Techniques using neural networks

Recently neural networks are entered the domain of structural health

monitoring after their success in other areas of research. In many areas of application,

neural networks have to be robust, especially when a clear mathematical relation ship is

not easily discernible among various parameters. These advantages made their presence

in structural health monitoring.

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Marsi et al (1996) presented a time domain method of damage detection in

structure unknown single degree of freedom systems using neural network approach.

Vibration measurement from a healthy structure is used to train a neural network. The

input consists of system displacement and velocity at suitable intervals in the time

domain. The output is the restoring force calculated. at a later time, when the health of a

structure is required to be assessed, the network is fed with vibration measurements from

the structures. The deviation between the actual output of the system and output from the

trained neural network provides a measure of changes in the physical system relative to

its healthy condition.

Neural network based techniques has the following advantages over the

conventional methods of health monitoring.

1. Neural networks have the ability to develop generalized solutions to a problem from a

set of examples, to continue the development , and to adapt to changes. This enables them

to be used for problems other than the training set. This also makes them fault tolerant

and capable of working with incomplete and noisy data (Flood and karantm, 1994a)

2. They do not require prior information concerning phenomenological nature of the

structure ( Marsi et al., 1996). They can tackle linear as well as non-linear problems.

The limitations of neural networks are lack of precision, limited ability to rationalize

solutions, and most importantly lack of a rigorous theory to assist their design.

(d)Local SHM techniques

These techniques rely on the localized structural interrogation for

detecting damages. Ultrasonic techniques, acoustic emission, eddy currents, impact echo

testing, magnetic field analysis, penetrant dye testing, and x-ray analysis.

The ultrasonic methods are based on elastic wave propagation and reflection within the

material for non-destructive strength characterization and identifying for field

inhomogeneities caused by damages. These techniques require experienced persons and

need to interpret the data.

Acoustic emission methods make use of waves generated by plastic deformations,

moving dislocations and disbonds in detection of damages. The main draw back of this

method is the existence of multiple travel paths from the source to sensors.

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The eddy currents perform a steady state harmonic interrogation of structures for

detecting surface cracks. A coil is employed to induce eddy current in the main coil and

and this induction current undergoes variations on the development of damages, which

serves as indication of damage. This method can employed only for conductive materials.

In impact echo testing, a stress pulse is introduced into the interrogated

component using an impact source. As a result wave propagates through the structure, it

is reflected by cracks and disbonds. This method can not detect small sized cracks.

In magnetic field methods, a liquid containing iron powder is applied on

the object to be interrogated, subjected to magnetic field, and then observed under ultra

violet light. Cracks are detected by presence of magnetic fields lines along their positions.

This method can be used only for magnetic materials. And component must be

dismounted and inspected inside a special cabin.

Penetration dye test involves, a coloured liquid is brushed on the surface of

the component under inspection, allowed to penetrate into the cracks, and then washed

off the surface. There after a quick drying chalk is applied which act as a developer and

causes coloured lines to appear along the cracks.

X-ray method involves, the object structure is exposed to X-rays, which

are then observed on film, where the cracks are depicted as black lines. Even though

moderate sized cracks can be detected ,very small cracks are difficult to captured.

2.3 TECHNIQUES USING SMART MATERIALS AND SMART STRUCTURES

CONCEPT

Smart materials: smart materials are materials which have ability to change their

physical properties such as shape, stiffness, viscosity, etc. in a specific manner according

to certain specific type of stimulus input. Smart materials are one of components of

smart structures .Examples of smart materials are Electrostrictive materials,

magnetostrictive materials, shape memory alloys, magneto- or electrorheological fluids,

polymer gels, and piezoelectric materials, optical fibers .These are explained in detailed

manner later.

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2.3.1 Smart Structures

The terms smart structures, intelligent structures, adaptive structures, active

structures, adaptronics, and structronics all belong to the same field of study. All these

terms refer to the integration of actuators, sensors in structural components, and the usage

of some kind of control unit or enhanced signal processing with a material or structural

component. The goal of this integration is the creation of a material system having

enhanced structural performance, but without adding too much mass or consuming too

much power.

Smart structures/materials are generally created through synthesis, by not only

combining sensors, processing, and actuators but also through their integration with

conventional structural materials such as steel, concrete, or composites.

According to Ahmad (1988), A system is termed as ‘smart’ if it is capable of

recognizing an external stimulus and responding to it with in a given time in

predetermined manner. In addition it is supposed to have the capability of identifying its

status and may optimally adapt its function to external stimuli or may give appropriate

signal to the user. Smart structures that can moniter their own condition, detect

impending failure, control, or heal damage and adapt to changing environment. Because

of their inherent capability of detecting the any change in structure, smart materials,

systems and structures are being used for SHM and NDE from past two decades.

Research on smart civil structural system is focused on two areas. They are

1. Control of structural response to external loading, such as wind and earth quake.

2. Detection of damage and flaw in the system, and its severity.

2.3.2 Components Of Smart System

Sensors: A smart system must have embedded intrinsic sensors to recognize And

measure the intensity of stimulus (stress or strain) or its effect on the structure

Actuators: A smart system may additionally have embedded or bonded actuators,

Which respond to stimulus in predetermined manner.

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Control mechanism: A smart system must have a mechanism for integrating and

Controlling the actions of the sensors and actuators.

Some of smart materials are described as follows.

(a)Piezoelectric materials: Piezoelectric materials are the material that generates a

surface charge in response to an applied mechanical stress. Conversely they under go a

material deformation in response to an applied electric field. This unique capability

enables the material to be used both as a sensor and as an actuator. Smart system

applications of these material range from developing a skin like sensor to robotic

applications.

(b)Shape memory alloys (SMA): A shape memory (SMA) alloys have the ability to

remember a specified memorized shape. Below a specific temperature called transition

temperature. SMA can be plastically deformed from its memorized shapes. when it is

heated above transition temperature, the SMA will return to its memorized shape if not

constrained from doing so. SMAs can generate force through changing the temperature

across a transition state. eg.Nitinol (an Alloy of Nickel and titanium) is a commercial

SMA

(c)Electro–Rheological (ER) fluids: ER fluids are typically the suspensions of micron

sized particles in suitable hydrophobic carrier liquids. They have an inherent ability to

undergo an abrupt and reversible change in viscosity when subjected to electrostatic

potential. vibration control using ER fluids has been demonstrated using hollow graphite

epoxy cantilever beams filled with various ER fluids

(d)Optical fibres: These are made up of glass and silica and utilize fibre properties to

provide optoelectric signals, which are indicative of external parameters to be measured.

They have a wide range of applications including measurements of temperature, pressure,

strain, displacement, and chemical composition.

- 14 -

2.3.3 Potential Applications Of Smart Materials In Civil Engineering

One idea is to place capsules or hollow fibers filled with crack-sealing material

into concrete which if cracked would break the fiber releasing the sealant.

Optical fibers which change in light transmission due to stress are useful sensors.

They can be embedded in concrete or attached to existing structures.Brown University

and the University of Rhode Island investigated the fundamentals and dynamics of

embedded optical fibers in concrete.

Japanese researchers recently developed glass and carbon fiber reinforced concrete which

provides the stress data by measuring the changes in electrical resistance in carbon fibers.

Semi-active vibration absorbers

A smart micro-controller coupled With hydraulic systems reduces large

vibration amplitudes over 50% produced by heavy trucks passing through a highway

bridge, adding 15% more load capacity and extending bridge life over 20 years.

Fibre optic sensors in bridges

Fiber-optic cables are etched by laser with 5-mm-long internal gauges, spaced

about 2 m apart. These cables, strung under the bridge with epoxy, will be able to detect

the stresses by sending light beams down the cable at regular intervals and by measuring

the bending of the light beams. These gauges can also be used to monitor general traffic

patterns. The sensors serve as a data collector as well as a wireless transmitter.

Bhalla and Soh (2004) obtained high frequency piezoelectric signatures for diagnosis of

seismic induced structural damages. Bhalla , Soh and Liu (2005) presented wave

propagation approach for NDE using surface bonded piezoceramics, can be employed for

real time and online monitoring of critical structures,such as machine parts and aircraft

components. Tseng and Wang (2003) used smart piezoelectric transducers for in situ

health monitoring of concrete. They quantified the damage using root mean square

deviation index. The experimental results are confirmed with numerical simulation.

- 15 -

2.3.4 RESEARCH NEEDED IN SMART STRUCTURES

The research needed in smart structures is as follows.

Among the topics requiring study are innovative energy sources for wireless

sensors, energy absorbing and variable-damping structural properties as well as

those having a stiffness that varies with changes in stress, temperature or

acceleration.

reliable accelerated tests for long-term durability behavior

improved computers, microprocessors and information technology

More accurate/complete modeling of lifetime predictions

New sensors and control systems; Non Destructive Technology ; new materials

Innovative, lightweight and reliable energy sources

Electrorheological fluids, shape memory alloys, etc.

Understanding corrosion better at the detail level

2.3.4 NECESSITY OF MODELLING

The integration of smart (active) materials with the traditional (passive) ones is a

key aspect in the behavior of the structures and their modelling. Modelling should be

such that stiffness and inertial mass of the structure not effected by transducers or

sensors. The above considerations give an idea of the motivations that drive the research

effort in modelling smart structures, and the reason why this is a very challenging and

open research field. The modeling of full material nonlinearities and the modelling of full

coupling between smart structures and fluids might be mentioned as possible examples

for future research.

2.4 SUMMARY This chapter has described the concepts of structural health monitoring in recent

years. Various SHM techniques and their advantages and disadvantages have been

discussed. Latest research done in SHM and research needed in future also discussed. In

this particular project , conductance &susceptance signatures are obtained using finite

element modeling.

- 16 -

CHAPTER3

STRUCTURAL HEALTH MONITORING WITH PIEZO ELECTRIC

ACTUATOR/SENSOR PATCHES

3.1 PIEZOELECTRICITY AND PIEZO ELECTRIC MATERIALS

The unique property of piezoelectric materials to play the dual roles of

actuators and sensors is utilized in this particular application.

Piezo electricity is the effect of interaction between electrical and mechanical

systems. it occurs in certain type of anisotropic crystals, in which electrical dipoles are

generated upon applying mechanical deformations. The same crystals also exhibit the

converse effect, that is, they under go mechanical deformations when subjected to electric

fields. This phenomena was discovered by Pierre and Paul-Jacques Curie in 1880.

Present research is “FINITE ELEMENT MODELLING OF SMART

STRUCTURES”. Particularly working of structure with piezo electric patch was studied.

That’s why these things were discussed in detailed manner as follows.

The prinicipal commercially available piezoelectric materials are

1. Piezoceramics, such as Lead Zirconate Titanate(PZT).

2. Piezopolymers, such as Polyvinvylidene Fluoride(PVDF).

- 17 -

3.2 FUNDAMENTAL PIEZOELECTRIC RELATIONS

Fig 3.1 (a) A PZT bonded to the structure (b) Interaction model of one half of

PZT and host structure. (Bhalla and Soh (2002)).

Consider a piezoceramic actuator bonded to host structure as shown in fig 3.1

by means of high strength epoxy adhesive and electrically excited by means of

impedance analyzer .It is assumed that the patch expands and contracts in direction 1

only when the electric field is applied in direction 3. ha, la and wa are the thickness,

length, and width respectively of the PZT patch. T is stress applied in direction 1, and E3

is the electric field applied in direction 3.

Fundamental relationships of the PZT patch may be expressed as (Ikeda, 1990)

S1 = 131

11E

T d EY

+ (3.1)

3 33 3 31 1TD E d Tε= + (3.2)

where

S1 = strain

D3 = electric charge density over PZT

11EY = Y11

E (1+ηj) is the Young’s modulus of the PZT patch at zero electric field.

η = mechanical loss factor T

33ε = T33ε (1-δj) is the complex permittivity of the PZT material at zero stress

δ = dielectric loss factor

- 18 -

for d31 first subscript signifies the direction of electric field and second subscript signifies

the direction of the resulting stress or strain.

3.3 PRINCIPLE AND METHOD OF APPLICATION

As suggested by Sun et al(1995) by inducing an alternating current source, pzt

patch Imposes a dynamic force on the structure it is bonded to. The structural response in

turn modulates the current flowing through the PZT i.e. affects the electrical Admittance.

The electrical admittance is therefore is a unique function of the mechanical impedance

of the structure at the point of attachment. Any variation in mechanical impedance will

alter the electrical admittance, which can be used as an indicator of damage. A frequency

range is selected for extracting conductance as a function of frequency. This is called

conductance signature. This frequency is kept typically high, in the order of kHz using an

impedance analyzer. The conductance signature is recorded for the healthy structure as

a bench mark. At any subsequent state, when structure health is required to be assessed,

the procedure is repeated. If any change in signatures is found, it is an indication of

damage.

The surface bonded piezoelectric patches, because of their inherent direct and

converse mechatronic coupling, can be effectively utilized as mechatronic impedance

transducers(MITs) for SHM. The MlT –based technique has evolved during the last 8

years and is commonly called the electro mechanical impedance (EMI) technique in the

literature.

3.3.1 Description of EMI Technique

The PZT patch is assumed to be infinitesimally small and possessing negligible

mass and stiffness as compared to host structure. When an alternating electric field is

applied to PZT patch it expands and contracts dynamically in the direction ‘1’. As shown

in fig 3.1 (b) Hence two end points of the patch can be assumed to encounter equal

mechanical impedance Z from the host structure.

- 19 -

Liang et al.(1994) solved the governing equilibrium equation for the system

shown in fig3.1(b), using impedance approach. Using Liang’s derivation following

equation can be written for the complex electro mechanical admittance Y (inverse of

electrical impedance), of the coupled system shown in figure 3.1.

2 2

33 31 11 31 11tan2 T E Ea a a

a a

w l klZaY j d Y d Yh Z Za kl

ω ε = + − +

(3.3)

31d = piezoelectric strain coefficient,

11EY =complex Young’s modulus of the PZT patch at constant electric field.

33T∈ =complex electric permittivity of the PZT material at constant stress.

Z =mechanical impedance of the structural system

aZ =mechanical impedance of the PZT patch

ω = angular frequency

k =wave number.

Equation (3.3) is used in the damage detection in the EMI technique .The

mechanical impedance Z in the equation is a function of structural parameters i.e. the

stiffness, the damping and mass. Any damage to the structure will cause these

parameters to change, and hence changes the mechanical impedance Z. consequently,

electro mechanical admittance Y ,will under go change, and serves as an indicator of state

of health of the structure. Z cannot be measured easily but Y can be measured easily by

using an electrical impedance analyzer. The measured admittance is a complex quantity

consists of real and imaginary parts, the conductance(G ) and the suceptance (B ),

respectively. The real part actively interacts with the structure and is therefore preferred

in SHM applications. A plot of G over frequency serves as a diagnostic signature of the

structure and is called the conductance signature.

- 20 -

3.3.2 Damage quantification

Health of the structure can be known by visualizing the healthy signature and

signature obtained after some period when health monitoring is needed. But to quantify

changes in signature due to damage, there are few techniques such as wave form chain

code (WCC) technique, the signature assurance criteria (SAC), adaptive template

matching (ATM), equivalent level of degradation system, root mean square deviation

technique (RMSD) etc.

R.M.S.deviation of the signature was defined by Giurgiutu and Roger (1998a )

RMSD(%)=( )2

1

2

1

100

i n

i ii

i n

ii

w u

u

=

==

=

−×

∑

∑ ( 3.4)

where,

ui i-1,2,3,….,N is a base line signature and

wi i=1, 2,3,….,N is the signature obtained after a period of time.

3.3.3 Improvements of EMI technique in recent years

Major developments and contributions made by various researchers in the field of EMI

technique during last ten years are summarized as follows. (Park et al., 2003b)

(1) Application of EMI technique for SHM on a lab sized truss structure was first

developed by Sun et al.(1995). This study was then extended to a large scale

prototype truss joints by Aryes et al.(1998).

(2) Lopes et al. (1999) trained neural networks using statistical damage quantifiers

(Area under the conductance curve, root mean square (RMS)of the curve, rooy

mean square deviation (RMSD) between damaged and undamaged curves and

correlation coefficients ) using experimental data from a bolted joint structure.

(3) Park et al.(2000a) reported significant proof of concept applications of EMI

technique on civil structural components such as composites reinforced

- 21 -

massonary walls, steel bridge joints and pipe joints. The technique was found to

be very tolerant to mechanical noise and also to small temperature fluctuations.

(4) Park et al. (2000a) extended the EMI technique to high temperature applications

(typically>5000c), such as steam pipes and boilers in power plants. Besides he

also developed practical statistical cross section correlation based methodology

for temperature compensation.

(5) Soh et al. (2000) established the damage detection and localization ability of

piezo impedance transducers on real life RC structures by successfully

monitoring a 5m span RC bridge during its destructive load testing.

(6) Park et al.(2000b) were integrated the EMI technique with wave propagation

modeling for thin beams (1Dstructures) under ‘free-free’ bopundary conditions,

by utilizing axial modes. The conventional statistical indices of the EMI

technique were used for locating damage in the frequency range 70-90 KHz.

(7) After the year 2000, numerous papers appeared in the literature demonstrating

successful extension of the technique on sophisticated structural components such

as restrengthened concrete members and jet engine components under high

temperature conditios (Winston et al., 2001).

(8) Inman et al. (2001)proposed a Novel technique to utilize a single PZT patch for

health monitoring as well as for vibration control.

(9) Abe et al.(2002) developed a new stress monitoring technique for thin structural

elements (such as springs, bars and plates) by applying wave propagation theory

to the EMI measurement data in the moderate frequency range (1-10KHz).

(10) Giurgiutu et al.(2002) combined the EMI technique with wave propagation

approach for crack detection in aircraft components. While EMI technique was

employed for near field damage detection, the guided ultrasonic wave

propagation technique (pulse echo) was used for far field damage detection.

3.4 ADVANTAGES OF EMI TECHNIQUE

(1) EMI technique shows greater damage sensitivity than the global SHM techniques.

It does not need expansive hard wares like the ultrasonic techniques.

- 22 -

(2) The PZT patches possess negligible weight can be bonded non-intrusively on the

structure. No need to dismantle the structure.

(3) As PZT can be used both as actuator and sensor, reduces the number of

transducers and eliminates complicated wiring .

(4) The PZT patches are available at very low costs, hence can be used at any

number of locations.

(5) This technique does not need to interfere the functioning of structures.

(6) The method can be implemented at any time in the life of a structure.

(7) Since PZT patches are commercially available and portable, there are used in

wide range of applications.

3.5 LIMITATIONS OF EMI TECHNIQUE

1. since the sensing zone PZT patch is limited to 0.4 to 2m only, thousands of PZT

patches are required for real life monitoring of civil engineering structures like

bridges and multi storied buildings.

2. This technique does not give the over all stability of structure. Since civil

engineering structures are of indeterminate in nature, occurrence of cracks at

some places may not affect the overall stability of structure.

3.6 CONCLUSION

In this chapter fundamental piezoelectric relations, structural health monitoring

using piezoelectric actuator or sensor patches, recent developments in EMI technique and

advantages and limitations of EMI technique were briefly discussed.

- 23 -

CHAPTER4

FINITE ELEMENT MODELLING OF SMART STRUCTURES

4.1 IMPORTANCE OF NUMERICAL SIMULATION

Since the last two decades, the use of smart structures in area of structural

monitoring has been increased tremendously. Research in area of smart structures need to

be developed to meet the future requirements in civil engineering field. In research it is

not preferable to built the structures to under go damages to study the behaviour of smart

structures. This necessitates finite element modelling of smart structures. Numerical

modeling of structures eliminates the tedious and time consuming laboratory work. It is

necessary to determine the conductance signatures by numerical simulation at high

frequencies in addition to experimental methods. In addition to develop robust pattern

recognition algorithms that can classify situations other than those in the laboratory,

numerical simulation at high frequency are needed to study the signatures associated with

additional type of damage. As the experimental work are tedious and expansive,

numerical simulations can significantly reduce R&D cost.

Tseng and Wang (2004) conducted numerical study on a concrete beam with a

progressive damage on its surface. They investigated signature in a frequency range of

20-25 kHz, considering only one dimensional vibration. They are concluded that PZT

patch are not capable of detecting damage, when damage is located 500 mm from the

damage. Results of Tseng and Wang are shown in fig 4.1. From the figures 4.1(a) and

4.1(b) it could be observed that peak conductance was not obtained at the same frequency

in experimental and simulation cases.

- 24 -

(a)

(b)

Fig 4.1(a) Pristine conductance signatures on specimen 1. (Tseng and Wang 2004).

(b) Pristine conductance signatures on specimen 2 (Tseng and Wang 2004).

Giurgiutiu and Zagari (2002) numerically studied a beam structure with PZT

patch on its surface. They made an attempt to study the effect of PZT patches in

comparison with conventional sensors. Numerical study was conducted on four types of

beams narrow thin, narrow thick, wide thin , wide thick. Results obtained for double

thickness beams were found to be less precise due to in homogeneity introduced by the

layer of glue between single thickness beams. This inhomogeneity altered the electro

- 25 -

mechanical impedance response of a beam. They conducted the study at ultrasonic

frequency range. The results of their study are reproduced in fig 4.2.

Fig 4.2 Experimental and calculated impedance vs frequency(Giurgiutiu and Zagari

2002).

From fig 4.2 it is observed that the calculated impedance (or conductance) values

are deviated more than 100 times from the experimental impedance (or conductance).

The reason was given as nonhomogeneity introduced by the material.

In the present study, for understanding the conductance signature of the RC

frame, a numerical simulation study was carried out, using the finite element method. The

frequency range was kept as 100 to 150 kHz, since the experimental study by Bhalla and

soh (2004) confined to this range only.

Liang’s impedance equation (Liang et al.) is used to determine electrical

admittance spectrum measured at the terminals of the PZT patches. From the literature it

is know that closed form solutions are available for structural impedance at low

frequency techniques only. In this study it is intended to compare experimental results

with numerical solutions at high frequencies typically in kHz.

When PZT patch is bonded on a structure and harmonic voltage used to

activate, dynamic force of the PZT patch on the host structure is represented as pair of

self -equilibrating harmonic forces of constant amplitude is given by

- 26 -

( ) i tF t Fe ω= (4.1)

Where,

F = Amplitude of the harmonic exciting force,

ω = exciting angular frequency

t = time

The structural impedance Z at the location of the PZT patch is defined as the force

acting on the driving point divided by the response velocity of the transducer v(t)

( )( )

F tZ

v t= (4.2)

In response to harmonic excitation the displacement of PZT patch is given by

X= i tXe ω (4.3)

where,

X is the amplitude of the response displacement of PZT at the exciting frequency ω.

The response velocity of the transducer can be written as

v = dXdt

= iwti Xeω (4.4)

The structural impedance at the location of the PZT patch at the exciting frequency ω

can thus be expressed as

Z = Fi Xω

(4.5)

- 27 -

After getting structural displacement response from the finite element method,

structural impedance can be obtained from the equation (4.5), and the electrical

admittance for the PZT patch can be obtained using Liang’s equation (3.3).

4.2 FINITE ELEMENT MODELLING OF RC FRAME

In the present work numerical investigations were conducted on a lab sized RC

frame using finite element for which experimental study was done by Bhalla. and Soh

(2004).

Part-1 of the major project, preliminarily conductance signature of the numerical

RC lab sized frame was obtained. In part -2, further refinement of the model has been

carried out and various types of damages have been simulated.

The properties of the concrete are listed in the table 4.1. Properties of the PZT patch is

shown in Table 4.2

Table 4.1 Material properties of concrete

Table 4.2 Mechanical and electrical properties of PZT.

Physical parameter value

Young’s modulus (MPa)

Density (kg/m3)

Poison’s ratio

Mass damping factor

Stiffness damping factor

2.74 × 104

2400

0.3

0.001

1.5 × 10−8

- 28 -

Physical parameters value

Density (kg/m3) Dielectric constant, 33

Tε Piezoelectric constant, d31 (m V−1) Young’s modulus, YE

11 (MPa) Dielectric loss factor, δ Mechanical loss factor, η

7800 33 2.124 × 10−8

−2.1 × 10−10 6.667 × 1010

0.015

0.001

The RC frame on which experimental study was carried out is shown in fig4.3

Fig 4.3 Details of the test frame (All dimensions are in mm) (Bhalla and Soh 2004).

As part of the project finite element model of the frame was developed using

plane solid 42 element of 10 mm size using Ansys 9 soft ware. A pair of self

equilibrium harmonic forces of 100 kN are applied at the Location of PZT patch 2 to

- 29 -

simulate the piezoceramic load on the frame. For simplicity PZT patch was located at

the centre of the beam. Boundary conditions are simulated as it is on the experimental

frame. Fig.4.4 shows the 2D finite element model of the symmetric left half of the

experimental frame.

. Fig 4.4 Finite element model of lab sized RC frame.

Harmonic analysis of the frame was carried out by applying self equilibrating

constant axial harmonic forces at the PZT patch in the frequency range of 100 to 150

KHz. Translational displacements in x-direction at the location of PZT patch were

obtained at frequency interval of 1 kHz in between 100 to 150 kHz.

Structural impedance and electrical admittance were calculated at 1 kHz frequency

interval using the equations 4.5 and 3.3 respectively.The process was initially carried

- 30 -

with 10mm element size. The entire procedure was repeated with 5mm, 4mm, 3mm

element sizes. It was observed that convergence of the conductance signature attainedat

an element size of 3mm. Therefore conductance signature with 3mm element size is

considered as healthy signature of the numerical study. Figure 4.5 the conductance

signature corresponding to these three sizes.

Now a flexural damage in the form of vertical crack was introduced at PZT

location and again Harmonic analysis is carried out for the numerical model to obtain

conductance signature at the damaged state. It is assumed that vertical crack occurred at

the PZT location. For introducing damage Young’s modulus of the elements at the

location of damage is reduced to 2×105 N/M2. Deviation of this signature with healthy

signature indicated the presence of damage. Numerical analysis results are compared with

experimental results. The RMSD index with respect to the pristine state signature can

determined by equation (3.4)

4.3 RESULTS The following results were obtained from numerical Analysis of Finite element

model of RC Lab sized frame as part-1 of the project.

Fig.4.5 shows the results of the numerical process when approached with 10mm, 5mm

and 3 mm. sizes of the elements.

- 31 -

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

100000 110000 120000 130000 140000 150000 160000

Frequency (Hz)

Con

duct

ance

(S)

3mm5mm10mm

Fig 4.5 Conductance signatures using 10mm, 5mm and 3mm size of the elements. From the figure 4.5 it is observed that pristine signature using 3mm elements converged

with pristine signature corresponding to the 5mm elements. This is justified by the fact

that most of the curve patterns are similar for these mesh sizes. Hence conductance

signature obtained using 3mm element is considered as conductance signature of the RC

model frame .This can be compared with theexperimental signature shown in Fig

4.7(Bhalla& Soh, 2004)

- 32 -

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

100000 110000 120000 130000 140000 150000 160000

Frequency (Hz)

cond

ucta

nce

(s)

Fig 4.6 Numerical conductance signature of the pristine frame model. Experimental Healthy conductance signature

Signature obtained by Bhalla (2003) is shown in fig. 4.7.

Fig 4.7 Experimental conductance signature of the pristine frame model.(Bhalla and Soh 2003). 4.4 COMPARATIVE STUDY

- 33 -

Discussions: It is observed from the Fig 4.6& 4.7 that simulated and experimental

signatures are more are less similar in nature. Peak conductance in the both signatures

occurs at quite close at same frequencies (117 and 127kHz). Although the magnitudes are

different, the results show much improvement than Tseng(2004) and Giurgiutiu & Zagrai

(2002) results. In case of Tseng (2004), peak conductance in experimental and simulation

curves did not coincide at same frequency. In the case of Giurgiutiu & Zagrai(2002), the

conductance varied by nearly 100 times. But in the present study, conductance varied by

65 times only. The variation is due to high frequency effects which could not be included

in the analysis and variation of damping of concrete. From dynamic analysis point of

view, the damping of concrete might varied from 2% to 6%.

4.5 DEVIATION IN CONDUCTANCE SIGNATURE WITH FLEXURAL

DAMAGE

Healthy conductance signature has been compared with signature obtained by

introducing small vertical flexural crack at PZT location. This is shown in Fig 4.8. From

it can be observed that the conductance signature corresponding to damaged state shifted

vertically and laterally from the healthy conductance signature. In this way structural

health monitoring can be done using piezoceramic actuator/sensor patches.

- 34 -

Fig 4.8 simulated conductance signature of healthy and damaged state.

4.6 STUDY OF CONDUCTANCE SIGNATURE PATTERN BY INDUCING

DIFFERENT DAMAGES TO THE NUMERICAL MODEL.

As a second part of the project various damages at various locations were

induced for the numerical model, and the resulting conductance signature was studied.

4.6.1Determination of damping constants:

Before simulating damaged model an attempt was made to further refine the

model developed during part-1 by determine the appropriate damping constants. For this

purpose, the conductance signatures were obtained for different combinations of the

damping constants α & β. Results are as shown in Fig 4.9

And results are as follows.

- 35 -

Fig 4.9 conductance signatures with different damping constants.

From this figure it can be observed that conductance

signature with α=0, β=1e-09 leads to much better comparable results with experimental

results. The validity of damping constants can be justified as follows.

Mass damping constant (α) = 0, Stiffness damping constant (β) = 1e-09, We have ,

Damping ratio (ξ) = βω / 2, ω= mean frequency= 125×103 ×2π rad/sec.

From the above Damping ratio (ξ) = 6.125%.From the dynamic analysis point of view

damping ratio recommended for reinforced concrete is 3% to 6 %.( A.k.Chopra). hence

the values of α , β used presently are reasonable & hence used in all future work.

.

Heallthy conductance signature (simulated )

0

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.01

100000 110000 120000 130000 140000 150000 160000

Frequency (Hz)

cond

ucta

nce

(s)

Series1

Fig 4.10 Numerical conductance signatures with modified damping constants.

In part-1, numerically obtained results varied by 60 times with the experimental one.

Now it came down to the 15 to 20 times. These results thus show better improvement

compared to Giurgiutiu& Zagrai (2002) work.

- 36 -

4.7 STUDY OF EFFECT OF DAMAGE ON CONDUCTANCE SIGNATURE OF

NUMERICAL MODEL RC FRAME.

4.7.1 Effect of Flexural Crack

A flexural crack at the location of maximum bending moment on the top beam of the

frame was induced by reducing the young’s modulus of the elements at that location from

2.74E 10 to 1E-06. Frame model with flexural crack was shown in Fig 4.11.

Deformations at the location of PZT patch at predetermined frequency range was

obtained and Conductance signature of the damaged numerical frame was obtained

shown in Fig 4.12.

Fig 4.11 simulated RC frame with Flexural cracks.

- 37 -

Fig 4.12 Effect of flexural crack on conductance signature. From the figure 4.11 it can be observed that conductance signature of numerical model

with flexural damage was shifted laterally right and vertically up. Peak conductance also

changed for a considerable amount. Root mean square deviation was found to be 16.82%

4.7.2 Effect Of Shear Crack Now a shear crack at an angle of 450 was introduced near PZT patch’s location

of the top beam, by reducing young’s modulus of elements at that location. RC frame

with shear crack was in Fig. 4.13. Conductance signature changed as shown in Fig 4.14.

Effect of flexural cracks

0

0.002

0.004

0.006

0.008

0.01

0.012

100000 110000 120000 130000 140000 150000 160000

Frequency ( Hz)

cond

ucta

nce

healthywith flexural cracks

- 38 -

Fig 4.13 RC frame with shear crack near PZT location.

Resulting conducting signature was shown below.

- 39 -

Effect of shear cracks

0.005

0.0055

0.006

0.0065

0.007

0.0075

0.008

0.0085

0.009

0.0095

100000 110000 120000 130000 140000 150000 160000

Frequency (Hz)

cond

ucta

nce

healthywith shear crackks

Fig 4.14 Effect of shear crack on conductance signature From fig 4.14, it can be observed that because of presence of shear crack signature

moved vertically downward. So presence of such a change in signature indicates us that

structure undergone shear damage.Root mean square index for this case was found to be

15.74%

4.7.3 Effect Of Both Flexural And Shear Cracks

Now both flexural and shear cracks were induced together and the change in signature is

observed. Frame with both flexural and shear cracks are shown in Fig 4.15. Resulting

conductance signature was shown in Fig 4.16

- 40 -

Effect of different damages on conductance signature

0.005

0.006

0.007

0.008

0.009

0.01

0.011

100000 110000 120000 130000 140000 150000 160000

frequency (KHz)

cond

ucta

ncen

(s)

Healthywith flexural crackswith shear cracksshear+ Flexural cracks

Fig 4.15. Simulated frame with both flexural and shear cracks.

Fig 4.16 Effect of different types of damages on conductance signature of numerical

model frame.

- 41 -

From fig 4.16 it can be observed that conductance signature with both flexural and shear

cracks is between signatures with effect of flexural crack and shear cracks

individually.Root mean square index for this case was found to be 10.42%

4.7.4 Effect Of Distance Of PZT From The Damage Location:

The Fig 4.17 shows the change in conductance signature with increase in distance of

PZT from damage location.

effect of distance of PZT from damage location

0

0.002

0.004

0.006

0.008

0.01

0.012

100000 110000 120000 130000 140000 150000 160000

Frequency (KHz)

cond

ucta

nce

(s) Healthy

PZT at damage location

Damage at 200mm away fromPZT

Fig 4.17 Effect of PZT distance from the damage location. From figure 4.17 it was observed that when the damage occurs at the

location of the PZT patch, clear change in the conductance signature occurs. When the

PZT patch is at 150 mm away from the damage location change is observed is very

small. When the damage happened 150 mm away from PZT, it was not able to detect the

presence of damage.

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4.8 COMPARISON OF EXPERIMENTAL AND SIMULATED RESULTS.

Experimental conductance signatures

0.0002

0.0003

0.0004

0.0005

0.0006

0.0007

0.0008

0.0009

0.001

100 105 110 115 120 125 130 135 140 145 150

Frequency (kHz)

Con

duct

ance

(S)

BASELINESTATE:1STATE:2STATE:3STATE:4STATE:5STATE:6STATE:7STATE:8

Fig 4.18 Experimental results (Bhalla &Soh 2004) Fig 4.18 shows the effect of damage experimentally observed on the

conductance signature. In the experiment, the frame was subjected to different dynamic

loads by changing frequency , velocity amplitude, acceleration amplitude, reffering ti

state 1 to state 8. From Experimental results it was observed that there was some

deviation in the signatures as compared to baseline signature, up to state 3. from state 4 to

state 6 there was a prominent and sequential vertical shift in the signature as compared to

the earlier states. At state 7 prominent crack was found around and conductance

signature prominently downwards. At state 8 crack progresses through the PZT patch

and sudden vertical shift of the conductance signature was observed clearly. it was clear

that before visual observation of the damage, change in conductance signature explains

us the presence of minute cracks.

- 43 -

Simulated results

0

0.002

0.004

0.006

0.008

0.01

0.012

100000 110000 120000 130000 140000 150000 160000

FRequency (KHz)

cond

ucta

nce

(s)

HEALTHYwith Flexural cracksShearFlexural+shear cracksAway from PZT

z

Fig 4.19 Results obtained from Numerical model.

From the results obtained numerically, it was observed that conductance

signature followed the same pattern as that of experimental results .Simulated baseline

signatures varied from the experimental signatures by nearly 20 times.With the

occurrence of the flexural cracks at the location of maximum bending moment,

conductance signature shifted vertically upward and laterally right. With the occurrence

of shear cracks conductance signature shifted down wards. With both flexural and shear

cracks, the conductance signature was found to be between above two curves. The

presence of the damage up to a distance of 150 mm from the PZT location was

significantly detected by the conductance signature. However Beyond 150 mm distance,

the PZT patch unable to detect the presence of damage.

- 44 -

Chapter 5

CONCLUSIONS AND RECOMMENDATIOS.

5.1 CONCLUSIONS (1) On this project, Finite element model for an RC lab sized frame was

developed using ANSYS 9 software, for which experimental results are obtained by

Bhalla and Soh (2004). Self equilibrium harmonic forces of 100 kN were applied at PZT

location and Harmonic analysis was carried out at a frequency range of 100 kHz to 150

kHz. Translational displacements were obtained at PZT patches in the direction of

applied forces at an interval of 1 kHz. Electrical admittance was obtained at each 1 kHz

interval. Conductance signature for the PZT patch was drawn and compared with

experimental signature. The patterns of both signatures was observed as same manner.

Both signatures obtained the peak conductance at the identical frequencies. But there is a

variation in magnitude. These variations are due to high frequency analysis, boundary

effects and uncertainty of concrete damping.

(2). By reducing the young’s modulus of elements in some locations the effect

of different types of cracks was introduced. And again procedure was repeated and

conductance signature of damaged state was obtained. Effect of different types of

damages was clearly demarcated by the conductance signatures. Numerically obtained

healthy and damaged signatures followed the same pattern as that of experimental

results. Both experimental and numerical conductance signatures showed the peak

conductance at identical frequencies. It is found that PZT patches can easily detect

damages as far as 150mm.The results obtained by Giurgiutiu and Zagari (2002) are

shown a variation of 100 times with the experimentals. But in the present research, the

deviation t was around 20 times only. Hence, this is the better simulation compared to

earlier researchs.

(3) This numerical simulation is useful in future researches in smart structures

concept. Using these simulations tedious experimental works can be avoided. It leads to

saving of time and economic resourcse. According to Tseng and Wang (2004) detection

of damage by a PZT patch limited to 500 mm from the PZT patch. Therefore for large

- 45 -

civil engineering structures require more number of PZT patches and impedance

analyzers are required .This difficulty can be overcome by using numerical simulation

method. Using simulation method, conductance signature for various damage patterns

can be studied with out subjecting the structure to any cracks.

5.2 RECOMMENDATIONS

1. Research in area of smart structures can be handled at an ease with this numerical

modelling.

2 The conductance signature patterns for various types of damages and for damages

which cannot be studied in laboratory can obtained by numerical modeling.

3. Challenging tasks like modelling of piezo electric coupling in shell or plate structures

can be performed in this manner.

4. Fracture analysis in the presence of coupled behavior is another critical aspect to be

studied with help of numerical modeling

5. The modelling of full material nonlinearities and the modelling of full coupling

between smart structures and liquids might be mentioned as possible examples for future

research.

5.3 REMARKS:

1.Numerical results indicate that location of piezo electric patch have significant

influence on efficiency of smart structure.

2. The validity and efficiency of modeling confirmed by comparing numerical results

with experimental results.

3.It is feasible to model a efficient smart structure using finite element methods.

5.4 ADVANTAGES OF NUMERICAL MODELING:

1. Actual Structure need not be subjected to many damages for research purpose.

2. Experimental and analytical results can be validated with numerical modeling.

- 46 -

3. Since influence zone of PZT patch is limited, experimental study needs thousands

of PZT patch’s required for bridge like structures. It can be avoided in Numerical

modeling.

5.5 LIMITATIONS.

1. In numerical modelling material is assumed as elastic, linear isotropic

2. Temperature was not taken into account. But properties of the PZT patch varies with

the temperature.

3.Effect of initial cracks formed during curing and hardening may not accounted with the

damping constants used.

4. Coupled behaviour of the smart materials cause nonlinear nature. In case of piezo

electric material, the encounter inversion of material characteristics in presence of

sufficient electric field was not taken into account.

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