| | ---
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| | license: mit
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| | viewer: false
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| | ---
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| |
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| | # Description
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| |
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| | This dataset contains a set of example simulations using [diffSPH](https://github.com/tum-pbs/diffSPH). A dataloader and further information is available as part of _diffSPH_.
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| |
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| |
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| | # Simulation Setup
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| |
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| | The general simulation setup:
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| | - Domain Size: $1[m]\times 1[m]$ ($[-0.5, 0.5]^2$)
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| | - Particle Count: $128 \times 128 = 16384$
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| | - Particle size: $1/ (128\times 128) = 0.000061035[m^2]$
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| | - Neighborhood Size: $45.228$ neighbors per particle
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| | - Rest Density: $1 [kg/m^2]$
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| | - Timestepping: Fixed $\Delta t = 1 [ms]$
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| | - Integration Scheme: Symplectic Euler for WCSPH, RK2 for compressible SPH
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| | - SPH Formulation: $\delta^+$-SPH for WCSPH, CRKSPH for compressible SPH
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| | - Shifting Scheme: $\delta^+$-SPH for WCSPH only
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| | - Boundary Handling Scheme: MDBC
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| | - Viscosity: $\delta^+$-SPH, $\operatorname{Re}=2000$
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| |
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| |
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| | # Data Layout:
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| |
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| | Each simulation is stored as a single hdf5 file with meta information available about the simulation configuration and parameters. Each timestep is a seperate group under the simulationData group. For more information on how to process the data, see _diffSPH_. To load the data using diffSPH you can simply:
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| |
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| | ```py
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| | import torch
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| | import matplotlib.pyplot as plt
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| | import warnings
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| | from tqdm import TqdmExperimentalWarning
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| | warnings.filterwarnings("ignore", category=TqdmExperimentalWarning)
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| | from tqdm.autonotebook import tqdm
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| | from diffSPH.plotting import visualizeParticles, updatePlot
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| | from diffSPH.operations import sph_op
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| | from diffSPH.kernels import getSPHKernelv2
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| |
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| | from diffSPH.dataLoader import *
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| | from BasisConvolution.convLayerv3 import BasisConvLayer
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| |
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| | configuration = DataConfiguration(
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| | frameDistance=1,
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| | frameSpacing=1,
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| | maxRollout=1,
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| | historyLength=1,
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| | skipInitialFrames=0,
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| | cutoff=0
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| | )
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| | folder = './data/compressible/circleCase'
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| |
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| |
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| | processed = processFolder(folder, configuration)
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| |
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| | for file in processed:
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| | print(f'File: {file["fileName"]}, FrameCount: {len(file["frames"])}, Samples: {len(file["samples"])}, Style: {file["style"]}, Number of samples: {len(processed[0]["samples"])}, first sample: {processed[0]["samples"][0]}, last sample: {processed[0]["samples"][-1]}')
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| |
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| | dataset, datasetLoader = getDataLoader(processed, 4, shuffle = True)
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| | datasetIter = iter(datasetLoader)
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| | nextData = next(datasetIter)
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| |
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| | priorStates, currentState, trajectoryStates, domains, rotMats, configs, neighborhoods = loadAugmentedBatch(
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| | dataset, nextData, configuration, device = 'cuda', dtype = torch.float32,
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| | augmentAngle = False,
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| | )
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| |
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| | fig, axis = plt.subplots(1, len(nextData), figsize=(len(nextData) * 4, 5), squeeze = False)
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| | plots = []
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| | axes = axis.flatten()
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| | for b in range(len(domains)):
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| | plot = visualizeParticles(fig, axes[b],
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| | particles = currentState,
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| | domain = domains[b],
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| | quantity = currentState.densities,
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| | which = 'both',
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| | mapping = 'L2',
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| | cmap = 'viridis',
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| | visualizeBoth=True,
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| | kernel = kernelNameToKernel(configs[b]['kernel']),
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| | plotDomain = True,
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| | gridVisualization=False, markerSize=2,
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| | batch = b, streamLines = False)
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| | axes[b].set_title(f'Batch {b} {nextData[b]} - t={currentState.time[b]:.2f}s,')
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| | plots.append(plot)
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| |
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| | fig.tight_layout()
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| | ```
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| |
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| | _diffSPH_ contains more examples on how to then use this data for training with both CConv networks and GNNs.
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| |
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| | # Dataset Overview
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| |
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| | ## Compressible SPH
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| |
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| | All simulations have 12 initial conditions available to them. For region cases the density and pressure are randomized per region, for the other cases there is a uniform octave noise across the domain to sample the density and pressure field, and the velocity field as divergence free
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| |
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| | ## Circular Regions
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| |
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| | Initial | Final
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| | ---|---
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| | |
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| | |
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| |
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| |
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| | ## Dual Regions
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| |
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| | Initial | Final
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| | ---|---
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| | |
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| | |
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| |
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| | ## Quad Regions
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| |
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| | Initial | Final
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| | ---|---
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| | |
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| | |
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| |
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| | ## Density Pressure Noise
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| |
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| | Initial | Final
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| | ---|---
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| | |
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| | |
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| |
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| | ## Random Velocity Field
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| |
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| | Initial | Final
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| | ---|---
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| | |
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| | |
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| |
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| | ## Weakly Compressible SPH
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| |
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| | Each simulaiton has 16 initial conditions available, except for the Taylor Green Vortex like initial conditions which are initialized for 2 and 4 vortices only.
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| | ### Periodic Domains
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| | BC | Initial | Final
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| | ---|---|---
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| | NoSlip |  | 
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| | FreeSlip |  | 
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| |
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| | ### With an Obstacle
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| |
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| | BC | Initial | Final
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| | ---|---|---
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| | NoSlip |  | 
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| | FreeSlip |  | 
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| |
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| | ### Bounded Domain
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| | BC | Initial | Final
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| | ---|---|---
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| | NoSlip |  | 
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| | FreeSlip |  | 
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| | ### Both
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| | BC | Initial | Final
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| | ---|---|---
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| | NoSlip |  | 
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| | FreeSlip |  | 
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| |
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| | ### Taylor Green Vortex
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| | x | Obstacle ? | Domain ?
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| | ---|---|---
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| | -| | 
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| | -||
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|
