Chapter 11

Multiscale Modelling of Hybrid Machining Processes

Dr. J. Ramkumar1 and Ishan Srivastava2

1Professor and 2Research Student

Department of Mechanical Engineering

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Organization of the presentation

• Introduction

• Multiscale Modelling Fundamentals

- Basics of Multiscale Modelling Technologies

- Multiscale Modelling Methodologies and Strategies

- Modelling & Simulation Approaches for Machining Processes

• Multiscale Modelling For Laser-Assisted Hybrid Machining Processes

- Process Work Principle and features.

- Multiscale Modelling Considerations

- Pre- and Postprocessing

• Case Study

• Conclusions

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Introduction

Multiscale modelling refers to the analysis of systems which involves

- wide range of physical/chemical/mechanical/thermal/fluid phenomenon's

- Nano-meso-micro-macro scale coupling

- Different spatial and temporal scales

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Different techniques used for modelling phenomenon of

different length domain.

IntroductionDensity Functional

Theory (DFT)

Molecular Dynamic Simulation (MDS)

Dissipative Particle Dynamics (DPD)

Finite Element Method (FEM)

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Multiscale Modelling Fundamentals

Basics of Multiscale Modelling Technology

• To determine the response of a process chain to specific inputs and boundary conditions.

• Earlier, usually restricted to a specific spatial/temporal scale.

• Now replaced with multiscale-modelling (Spanning over multiple level of space and time)

Multiscale Problems

Type-A

Problems involving local defects and singularities.A macroscale model is sufficient for most physical domain.

Ex- chemical reactions at specific locations, crack defects during machining process, dislocations or boundary layers in deformed materials.

Type-B

Some information is missing from macroscale model, so microscale model is either used everywhere or is coupled with macroscale model.

Ex- heat flow in heat exchangers, mass transport in chemical reactions, swirl formation in fluid flow.

Basics of Multiscale Modelling Technology

Coupling Methods

Coupling implies to combining results of different part models into a single, comprehensive solution.

Manual Coupling

• Inputs to a code at one scale are influenced by study of the outputs of a previously run code at another scale.

• Ex- Coupling timescale: Hours to weeks

Loose Coupling b/w codes

• Typically performed using workflow tools

• Often in different memory spaces

• Ex- Coupling timescale: minutes

Tight Coupling b/w codes

• Typically performed using coupling methods (e.g. CCA)

• Maybe in same memory spaces

• Hard to develop changes

• Ex- Coupling timescale: Seconds

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Multiscale Modelling Fundamentals

Multiscale Modelling Strategies and Methodologies

Methods

Analytical

Numerical

1. Matched Asymptotics

2. Averaging Methods

3. The WKB Method

4. The Mori-Zwanzig

Formalism

1. Linear Scaling Algorithms

2. Sublinear Scaling Algorithms

3. Type A & B problems

4. Concurrent and Sequential

coupling

Multiscale Modelling Strategies and Methodologies

Sequential Multiscale Modelling

• Establish the macroscale model with some details

of the constitutive relations that are

precomputed from micro or nanoscale models.

• Macroscopic model is determined first.

• Only suitable when the number of parameters

passed between the models are few.

• Very effective when simulation of specific

materials and application is involved in multiscale.

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Multiscale Modelling Strategies and Methodologies

Concurrent Multiscale Modelling

• In this, a series of processes which combine

information available from distinct length and

time scales into a single coherent, coupled

simulation.

• The quantities needed in macroscopic model are

computed on-the-fly from microscopic model as

the computation proceeds.

• Different scales of material behaviour are

considered concurrently.

• Different scaled algorithm are combined together

with matching procedures invoked in some

overlapping domain to resolve Multiphysics.Micromanufacturing Lab, I.I.T. Kanpur

Modelling and Simulation Approaches for Machining Processes

• In the manufacturing field, metal material machining processes are essential to produce designed products that

are worth many billions of dollars.

• For manufacturing of advanced materials and products, the underlying phenomenon in processes span a wide and

hierarchically organised sequence of time and length scales.

• Multiscale modelling is effectively used to predict and test the capability of the designed product so as to optimise

the production process.

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Multiscale Modelling of Laser-Assisted Hybrid Machining Process

• Hybrid machining is based on the

simultaneous and controlled

interaction of process mechanism

and/or energy sources having a

significant effect on performance

parameters.

• Ex- Laser-assisted milling, vibration-

assisted grinding.

• For the assisted hybrid machining, the

main mechanical cutting is coupled

with one or several other types of

energy inputs such as ultrasonic

vibration, thermal, fluid, magnetic field

etc.

Laser-assisted Milling

Laser-assisted turning

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Process work Principles and Features

• The laser beam is focused directly in front of the cutting tool,

softens the material so machining becomes easier.

• An increase in the temperature offers an increase in the surface

roughness.

• In comparison to conventional cutting, the plastically deformed

layer within the workpiece’s subsurface is deeper and more

uniform which indicates the existence of favourable compressive

residual stress.

• Due to heat the deformation shifts from brittle to ductile. Hence,

difficult-to-machine materials can be easily machined using

Laser-Assisted-Machining (LAM).

• Only a narrow location is heated so as to have minimum Heat-

affected Zone (HAZ).

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Multiscale Modelling Considerations for Laser -Assisted Hybrid Machining

• Laser beam energy is absorbed by the w/p surface and converted to thermal energy causing the temperature to rise.

For thermal response, in a cylindrical coordinate system is expressed as,

Schematic Diagram for turning

The Heat generated due to the plastic deformation could be calculated as:

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Pre- and Postprocessing

Material Parameters

• Tensile Strength• Yield Strength• Reduction of Area• Elongation• Modulus of Elasticity• Density• Specific Heat

Cutting Parameters

• Cutting Speed• Feed Rate• Depth of Cut• Cutting Width• Workpiece Speed

Tool Related Parameters

• Rake Angle• Relief Angle• Radius of Tip• Sand wheel Diameter• Hardness

Laser-Related Parameters

• Laser Power• Laser Beam Diameter• Laser Head Velocity• Pyrometer Laser Head

Output

• Component Geometry• Surface Residual Stress• Overall Temp. Distribution• Cutting force• Stress Variation

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Case Study: Laser-Assisted Machining of Mold Steel

• A 2D numerical Model of the laser assisted cutting of

NAK80 is done.

• Combination of two process:

• Simulation of moving laser heat source applied on

the local surface of workpiece which causes the

corresponding temperature field to rise and

material to soften.

• Simulation of cutting process with stress leading to

plastic deformation and finally shear.

• Chemical composition of NAK80 is:

C, 0.15%; Si, 0.3%; Mn, 1.5%; Ni, 3.0%; Al, 1.0%; Cu,

1.0%; Fe, 93.05%

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Case Study: Laser-Assisted Machining of Mold Steel

Boundary Conditions and Assumptions

• Tool is rigid.

• Workpiece is assumed to be isotropic and follows

Johnson-Cook Plastic criterion.

• No material phase transformation is assumed

under machined surface is considered.

• Rake angle = 10

• Clearance angle = 6

• Tool nose angle = 0.02 mm

• Cutting Speed = 25 mm/s

• Depth of Cut = 0.1 mm

• Laser power = 2000 W

• Laser Head Velocity = 25 mm/s

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Case Study: Laser-Assisted Machining of Mold Steel

Results and Conclusion

• The temperature distribution as a result of laser radiation was simulated. The corresponding laser heat

flux follows Gaussian distribution.

• The final temperature is 1270 C at the local position near the laser spot; the maximum thickness of HAZ is

around 7.5 mm.

• The max. cutting forces and stresses caused by LAM are 1290 MPa and 2290 MPa which are obviously

lower than their conventional contemporaries.Micromanufacturing Lab, I.I.T. Kanpur

Thank You

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