91 to 100 of 295 Results
Sep 25, 2024 - Model Order Reduction & Numerics
Brodbeck, Maximilian; Bertrand, Fleurianne; Ricken, Tim, 2024, "dolfinx_eqlb v1.1.0", https://doi.org/10.18419/DARUS-4479, DaRUS, V1
dolfinx_eqlb is an open source library, extending FEniCSx by local flux equilibration strategies. The resulting H(div) conforming fluxes can be used for the construction of adaptive finite element solvers for the Poisson problem [1], elasticity [2][3][4] or poro-elasticity [5][6]. The flux equilibration relies on so called patches, groups of all ce... |
Sep 17, 2024 - Surrogate models for groundwater flow simulations
Pelzer, Julia, 2024, "Models and Prepared Datasets for LG-CNN", https://doi.org/10.18419/DARUS-4467, DaRUS, V2
Models trained with Heat Plume Prediction and datasets prepared with Heat Plume Prediction into reasonable format, reduced set of in/outputs, 2D, normalization used to train these models. Last relevant git commit: cae87d68faf96b2bd8dab935. Based on raw data from doi:darus-4156. |
Chiossi, Francesco; Haliburton, Luke; Ou, Changkun; Butz, Andreas; Schmidt, Albrecht, 2024, "Dataset for "Short-Form Videos Degrade Our Capacity to Retain Intentions: Effect of Context Switching On Prospective Memory"", https://doi.org/10.18419/DARUS-3327, DaRUS, V1, UNF:6:7FzpUkbNmyXLFXVYJ8abKQ== [fileUNF]
Social media platforms use short, highly engaging videos to catch users’ attention. While the short-form video feeds popularized by TikTok are rapidly spreading to other platforms, we do not yet understand their impact on cognitive functions. We conducted a between-subjects experiment (𝑁 = 60) investigating the impact of engaging with TikTok, Twit... |
Sep 16, 2024 - Model Order Reduction & Numerics
Brodbeck, Maximilian; Suditsch, Marlon; Seyedpour, Seyed Morteza; Ricken, Tim, 2024, "Data for: Phase transition in porous materials - Effects of material parameters and deformation regime on mass conservativity", https://doi.org/10.18419/DARUS-4460, DaRUS, V1, UNF:6:liYTqWrj3J/cX+8NzdBIAA== [fileUNF]
This dataset contains the original results published in "Phase transition in porous materials: effects of material parameters and deformation regime on mass conservativity" (doi: 10.1007/s00466-024-02557-2). Abstract: Phase transition in porous materials is relevant within different engineering applications, such as freezing in saturated soil or pa... |
Sep 16, 2024 - Model Order Reduction & Numerics
Brodbeck, Maximilian; Bertrand, Fleurianne; Ricken, Tim, 2024, "dolfinx_eqlb v1.0.0", https://doi.org/10.18419/DARUS-4459, DaRUS, V1
dolfinx_eqlb is an open source library, extending FEniCSx by local flux equilibration strategies. The resulting H(div) conforming fluxes can be used for the construction of adaptive finite element solvers for the Poisson problem [1], elasticity [2][3][4] or poro-elasticity [5][6]. The flux equilibration relies on so called patches, groups of all ce... |
Sep 16, 2024 - SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing"
Evers, Marina; Weiskopf, Daniel, 2024, "Supplementary Material for Uncertainty-aware Spectral Visualization", https://doi.org/10.18419/DARUS-4447, DaRUS, V1
In this supplemental material, we provide supplemental information (PDF document with derivations of the results presented in the paper and two additional use cases) and the supplementary video for uncertainty-aware spectral analysis. We model an uncertain time series as a multivariate Gaussian process. We propagate the uncertainty and explicitly c... |
Sep 13, 2024 - Institute of Aerodynamics and Gas Dynamics
Appelbaum, Jason; Kloker, Markus J.; Wenzel, Christoph, 2024, "Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers", https://doi.org/10.18419/DARUS-4345, DaRUS, V3
Spanwise [z] and temporal [t] averaged turbulent fields of four direct numerical simulations (DNS) of a turbulent boundary layer (TBL) calculated using the code NS3D. Datasets ZPG-C & ZPG-F both have approximately zero pressure gradient along the wall boundary, whereas PG-C & PG-F have a nearly identical non-zero pressure gradient. Both ZPG-C and P... |
Sep 13, 2024 - Surrogate models for groundwater flow simulations
Pelzer, Julia, 2024, "Datasets: 6 Heat Pumps, Simulation - Raw + Prepared", https://doi.org/10.18419/DARUS-4473, DaRUS, V1
This dataset serves as training data for modeling the temperature field emanating from several open loop groundwater heat pumps (six heat pumps, randomly placed). It is simulated with Pflotran and stored in h5 format. The two datasets contain 1000 and additional 4000 data points. Each data point consists of one simulation run until a near steady st... |
Sep 13, 2024 - Projects without PN Affiliation
Hermann, Sibylle, 2024, "Database for: Documenting Research in Simulation Science to Enhance Understanding for Reusability", https://doi.org/10.18419/DARUS-4142, DaRUS, V1, UNF:6:mhHYSODfUq/dE3D6o/V/ww== [fileUNF]
Replication Data for an analysis of research articles from computational mechanics, all using the software Pasimodo https://www.itm.uni-stuttgart.de/en/software/pasimodo/ Categories for analysing the articles: To understand the context of the citation, we classified the citations into referring and reuse. Where referring is meant to be, when a cita... |
Sep 10, 2024 - Surrogate models for groundwater flow simulations
Pelzer, Julia, 2024, "Raw Simulation Datasets for Extending Heat Plumes", https://doi.org/10.18419/DARUS-4133, DaRUS, V2
These data sets serve as training and testing data for modelling the extension of temperature field emanating from one groundwater heat pump. There are simulated with Pflotran and saved in h5 format. The data set for training is called "dataset_medium_k_3e-10_1000dp". It contains 999 simulation runs, each simulated until a near steady state is reac... |
