Stuttgart Center for Simulation Science (SC SimTech)

EXC 2075 Project Networks

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81 to 90 of 25,631 Results

README.md Sep 17, 2026 - Step 3b: Scaling Benchmarking Data Markdown Text - 12.0 KB - MD5: 835baa733f8e07953cd33d5c1f5866e9 overall readme file for the whole dataverse
Steps 1-3b: Raw Simulation Data Sep 17, 2026 - Stepwise Benchmarking: Data-Scarce Groundwater Heat Pumps' Modeling Pelzer, Julia; Böttcher, Fabian, 2026, "Steps 1-3b: Raw Simulation Data", https://doi.org/10.18419/DARUS-5920, DaRUS, V4 This dataset contains unprocessed simulation data of modeling heat flow from open-loop groundwater heat pumps. The dataset was simulated in 2D with Feflow using cut-outs from interpolated hydrogeological measurements of the Munich, Germany, region. Heat pump locations are chosen based on realistic positions, and extraction rates are adapted to fit...
README.md Sep 17, 2026 - Steps 1-3b: Raw Simulation Data Markdown Text - 12.0 KB - MD5: 835baa733f8e07953cd33d5c1f5866e9 overall readme file for the whole dataverse
All Steps: Pretrained Models Sep 14, 2026 - Stepwise Benchmarking: Data-Scarce Groundwater Heat Pumps' Modeling Pelzer, Julia; Kotchourko, Serge, 2026, "All Steps: Pretrained Models", https://doi.org/10.18419/DARUS-6436, DaRUS, V1 Pretrained models for "Stepwise Benchmarking: Data-Scarce Groundwater Heat Pumps' Modeling" This dataset contains the pretrained baseline models, namely CNO, ConvNeXt U-Net, DPOT, LGCNN, scOT, TFNO, and U-Net. A model is trained under a fixed budget on all three training steps in the benchmark and included if training is technically possible under...
examples_allMo_allD_norm2.pdf Sep 14, 2026 - All Steps: Pretrained Models Adobe PDF - 167.5 KB - MD5: 0223746cb1155548f3df14fdb514a9e6
model_comparison.ipynb Sep 14, 2026 - All Steps: Pretrained Models Jupyter Notebook - 396.7 KB - MD5: 1ca8f51a2f5e26531c287c8d15c99114
model_ranking_transpose.pdf Sep 14, 2026 - All Steps: Pretrained Models Adobe PDF - 27.8 KB - MD5: 282a7b348d753632d22a57300d9abddc
predictions_test.h5 Sep 14, 2026 - All Steps: Pretrained Models Hierarchical Data Format - 517.5 MB - MD5: 8bb1ba530ba8a89f25364919ea98ae5d
predictions_test.h5 Sep 14, 2026 - All Steps: Pretrained Models Hierarchical Data Format - 332.8 MB - MD5: ddacf3c87498541508527fbc2c667544
predictions_test.h5 Sep 14, 2026 - All Steps: Pretrained Models Hierarchical Data Format - 147.6 MB - MD5: 65e3986591da67b6f1ee6dd28eab0f74

README.md

Sep 17, 2026 - Step 3b: Scaling Benchmarking Data

Markdown Text - 12.0 KB -

overall readme file for the whole dataverse

Steps 1-3b: Raw Simulation Data

Sep 17, 2026 - Stepwise Benchmarking: Data-Scarce Groundwater Heat Pumps' Modeling

Pelzer, Julia; Böttcher, Fabian, 2026, "Steps 1-3b: Raw Simulation Data", https://doi.org/10.18419/DARUS-5920, DaRUS, V4

This dataset contains unprocessed simulation data of modeling heat flow from open-loop groundwater heat pumps. The dataset was simulated in 2D with Feflow using cut-outs from interpolated hydrogeological measurements of the Munich, Germany, region. Heat pump locations are chosen based on realistic positions, and extraction rates are adapted to fit...

README.md

Sep 17, 2026 - Steps 1-3b: Raw Simulation Data

Markdown Text - 12.0 KB -

overall readme file for the whole dataverse

All Steps: Pretrained Models

Sep 14, 2026 - Stepwise Benchmarking: Data-Scarce Groundwater Heat Pumps' Modeling

Pelzer, Julia; Kotchourko, Serge, 2026, "All Steps: Pretrained Models", https://doi.org/10.18419/DARUS-6436, DaRUS, V1

Pretrained models for "Stepwise Benchmarking: Data-Scarce Groundwater Heat Pumps' Modeling" This dataset contains the pretrained baseline models, namely CNO, ConvNeXt U-Net, DPOT, LGCNN, scOT, TFNO, and U-Net. A model is trained under a fixed budget on all three training steps in the benchmark and included if training is technically possible under...

examples_allMo_allD_norm2.pdf