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Overview and comparison of different time-efficient computational strategies and methods (HPC vs Upscaling vs Surrogates)
Start with DEM glass beads
Comparison with real world ground truth
Hackathon plan
Presenting the WG1 Update
https://docs.google.com/presentation/d/1A-1bW1kANEfAay8pCeZmq3zH3Qhoo1HOjlxsja4-f0U/edit?usp=sharing
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Experimental
Ben Jenkins Is the data open-access?
DEM
Datasets
There is data corresponding to linear spring model. Correct Timo Plath? If yes, how can we download it?
- Timo Plath is on it
Codebases to generate datasets from scratch
Open-source
(semi/fully) Closed-source
https://gitlab.com/gdigitaltwins
nicolin did the implementation in Blaze and provides Blaze binary
Ben Jenkins LIGGGHTS
Rocky
Different calibration techniques
Yannick Descantes has a test case that we will use to check numerical stability in heap formation.
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Execution
Split into two groups HPC and Alternative Methods (AI/ML, Surrogate models)
G1 - HPC by nicolin
Assign tasks to complete the benchmark case of the rotating drum
G2 - Alternative methods by Deepak Tunuguntla Hongyang Cheng
Talk by Timo Plath on Reduced Order DPMTo be filled very soon.
Setup a central github repo for all the relevant ML-based algorithms for granular materials
To be cont.
Additional references
Different calibration techniques
Yannick Descantes has a test case that we will use to check numerical stability in heap formation.
Timo Plath has a script in MercuryDPM for Rotating drum and Surrogate model calibration