exploring the properties of free standing column …€¦ · exploring the properties of free...
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EXPLORING THE PROPERTIES OF FREE STANDING COLUMN
BUILT OUT OF DESIGNED GRANULAR PARTICLES
USING LEVEL SET-DISCRETE ELEMENT METHOD
OMKAR KADAM Junior Undergraduate, IIT Gandhinagar
Department of Mechanical Engineering
Mentor: Prof. Jose Andrade, Siavash, Raj, Robert
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ROADMAP
- Introduction, Motivation and possible future applications.
- Choosing initial shape of particles for experiments and simulations.
- LS-DEM(Level Set-Discrete Element Method).
- Experiments and simulation results.
- Optimizing shape of particles for maximizing both compressive and tensile strength.
- Ongoing and future work.
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Introduction & Motivation
- Aggregate architectures are full-scale
spatial formations made from loose
granular matter
- The idea is to design a grain shape that
governs the behaviour of the structure
- Reduce the material cost
- Easy to dismantle and reuse
Dierichs, K. and Menges, A., 2016
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Additional Possible Applications
Range of Cooling Effect: Optical Properties:
- Green Construction
- Variable structures because of voids
https://www.holidify.com/places/jaipur/hawa-mahal-sightseeing-2131.html Dierichs, K. and Menges, A., 2016. Towards an aggregate architecture: designed granular systems as programmable matter in architecture. Granular Matter, 18(2), p.25.fig.9
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Choosing the initial shape
Dierichs, K. and Menges, A., 2016
To begin with the simulations, we chose S-shaped particles
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Why “S” shaped particles?
- These particles are capable of entangling among themselves
- This shape (due to entanglement) will help the column to resist tension
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Choosing the shape of “S”
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Choosing the shape of “S”
Straight portions of “S”
Curvy “S”
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Choosing the shape of “S”
- If S shaped particle falls with straight portion then it won’t be able to interlock.
- Increasing the curvature of “S” shaped particle increases the probability of interlocking
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LS-DEM (Level Set-Discrete Element Method)
- LSDEM is used to represent the shape of the constituent
particles
- A level set function is an implicit function whose value, at
a given point, is the signed distance from that point to the
surface of the particle
- The values of a level set function are stored at discrete
points on a grid, and interpolation is used to compute
values between grid points.
- Normal force-linear contact or Hertzian contact model
- Tangential force- Coulomb friction modelhttps://www.semanticscholar.org/paper/Level-set-discrete-element-method-for-computations-Kawamoto-And%C3%B2/4165b5d76d1de3a5151938bacd12335a10e4d022
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Input file for 2D S-shaped particles
Shape Parameters
- Two cases - symmetric and
unsymmetric
- Currently - Symmetric case
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Input file for 2D S-shaped particles
- Referred concept of 3D objects.
- Total 6 equations.
- Position of each grid point with respect to
particle.
- Surface is divided uniformly
Nodes outside the particle Nodes inside the particle
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Pluviation of 2D S-shaped particles
Kinetic Energy
Time Step
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Stress-Controlled Compression
- Uniformly distributed compressive force is
applied on the top wall.
- Stress Tensor =
Force
=
- The top wall moves down and compresses the
particles until the stress produced by the
particles is equal to the stress on the top wall.
- The strain produced in the system is
calculated from the displacement of the top
wall.
- Strain=
- Compressive strength.
xy
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Net Force on Top Wall
- Verified the code for
different forces
applied on the top
wall.
- Finally, the net force
on the wall always
converged to 0.
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Stress-Controlled Compression on 10 Particles
Initial Position
Final Position
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Stress-Controlled Compression on 200 Particles
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Extra Interlocking Due to compression
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Stress-Controlled Compression on 200 Particles
Initial Position Final Position
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Experiments
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Stress-Controlled Compression on 200 Particles
- Compression increased interlocking.
- Chain of particles.
- Increase in tensile strength.
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Stress-Strain Plot for 200 Particles
Compressive strength=104.30 N/m
- Compressive strength is small because of voids and particles are capable of displacing themselves into these voids.
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Comparing Results of Simulation and Experiment
Strain-Controlled Stress-Controlled
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Optimization of Computation- Wrote a robust code for 2D case to get Level-set.
- Shape and size will vary in the search of optimization - The grid dimensions are set according to the particle shape and size to optimize
the computation
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Optimizing shape for compressive strength
Framework
- Constraints
- The framework is ready and can be used for both 3D and unsymmetric case
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Tensile Force on Particles
- Expecting the chains of particles
- This will increase tensile strength
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Ongoing and future work
- Understanding how to analyse the 2D structure under tensile force using LS-DEM
- Optimizing 2D shape in both compression and tension
- Repeating the same with 3D particle
- Validating the results obtained by simulations through experiments
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Thank you!