1 to 10 of 131 Results
Aug 11, 2026 - EXC IntCDC Associated Project 58 'NeuralWood'
Akbar, Zuardin; Gambarelli, Serena; Wortmann, Thomas, 2026, "NeuralWood Spruce Boards: Raw Dataset", https://doi.org/10.18419/DARUS-5683, DaRUS, V1
Overview This dataset is part of the project Neuralwood: Neural Networks for the Prediction and Utilization of Natural Material Variations in Timber Construction by the Department for Computing in Architecture, Institute for Computational Design and Construction (ICD/CA) and Materials Testing Institute (MPA), University of Stuttgart. The dataset co... |
Jul 21, 2026 - EXC IntCDC Associated Project 47 'Optimisation and Machine Learning for Climate-Friendly Design'
Claus, Luisa; Joller, Simon; Yang, Xiliu; Zorn, Max Benjamin; Wortmann, Thomas, 2026, "Code for: Towards Flexible Building Energy Surrogate Models: A Novel Feature Representation Method", https://doi.org/10.18419/DARUS-6306, DaRUS, V1
This code provides the data preprocessing framework used in the publication "Towards Flexible Building Energy Surrogate Models: A Novel Feature Representation Method", designed to generate flexible, physically meaningful feature representations for surrogate modeling of building energy performance. The framework extracts fixed-length feature vector... |
Jun 25, 2026 - EXC IntCDC Research Project 36 'AI as Co-designer'
Elshani, Diellza; Marsillo, Laura; Wortmann, Thomas, 2026, "Semantic Timber Construction and Robotic Fabrication Knowledge Graph Dataset", https://doi.org/10.18419/DARUS-6131, DaRUS, V1, UNF:6:6EGQ+0zxmwTet5HhPVBWlA== [fileUNF]
This dataset accompanies the paper A Semantic Framework for Linking Building Design, Material Data, and Robotic Fabrication in Timber Construction. The dataset supports the reproducibility of a semantic framework that links building geometry, timber material properties, and robotic fabrication information through an ontology-driven knowledge graph.... |
Jun 19, 2026
RP36-1: AI as Co-Designer For Integrative Computational Design And Engineering Harnessing Biological Variability And Pre-Use Features Of Timber |
Jun 9, 2026 - Analytic Computing
Seifer, Philipp; Hernández, Daniel; Lämmel, Ralf; Staab, Steffen, 2024, "Code for From Shapes to Shapes", https://doi.org/10.18419/DARUS-3977, DaRUS, V2
From Shapes to Shapes (s2s): a tool and library for inferring shape constraints that validate the result graphs of graph-transformation queries. Version 1.0 accompanies "From Shapes to Shapes: Inferring SHACL Shapes for Results of SPARQL CONSTRUCT Queries" (WWW 2024, doi:10.1145/3589334.3645550); it archives the v1.0.0 source tree. Version 2.0 acco... |
May 26, 2026 - EXC IntCDC Research Project 12 'Computational Co-Design Framework for Fibre Composite Building Systems'
Grünvogel, Nicolai Hans Pascal; Mindermann, Pascal; Baruah, Angshuman C.; Sychterz, Ann; Bischoff, Manfred, 2026, "Replication Data for: Methodological Positioning of Fiberoptic Strain Sensors in Coreless Filament-Wound Lattice Composite Structures", https://doi.org/10.18419/DARUS-6107, DaRUS, V1, UNF:6:ma4kEP4vKnlM8QckneR4QQ== [fileUNF]
This data set contains: 7 input files to generate the mechanical model based on the direct stiffness method of the specific structures, described in detail in the related publication. 2 Excel files for the color-coding of the 4 sample structures for post-processing of the different schemes (qualitative/quantitative), described in detail in the rela... |
Apr 20, 2026 - EXC IntCDC Associated Project 47 'Optimisation and Machine Learning for Climate-Friendly Design'
Renner, Markus; Zorn, Max Benjamin; Dai, Anni; Wortmann, Thomas, 2026, "Supplemental Materials for: Evaluating Interactive Visualizations of Multi-Objective Optimization Results for Architectural Design Decision-Making", https://doi.org/10.18419/DARUS-5694, DaRUS, V1
This software provides an interactive visualization framework designed to support architects and engineers in exploring and making decisions from high-dimensional data generated by multi-objective optimization (MOO) in the Architecture, Engineering, and Construction (AEC) industry. The framework integrates multiple coordinated views (MCVs), includi... |
Apr 20, 2026 - EXC IntCDC Research Project 26 'AI-supported Collaborative Control and Trajectory Generation of Mobile Manipulators for Indoor Construction Tasks'
Hierholz, Alice; Röhm, Emil; Gienger, Andreas; Sawodny, Oliver, 2026, "Replication Data for: Distributed Trajectory Generation based on ADMM for Collaborative Workpiece Transport with Mobile Robots", https://doi.org/10.18419/DARUS-5722, DaRUS, V1
MATLAB code to replicate the results of the paper titled "Distributed Trajectory Generation based on ADMM for Collaborative Workpiece Transport with Mobile Robots". Tested with MATLAB23a. Requirements: CasADi Version 3.7.2 (Installation guide: https://web.casadi.org/get/) Inputs: Scenario description (number of cases, beam length, number of obstacl... |
Apr 15, 2026 - EXC IntCDC Research Project 14 'Extension of the Cyber-Physical Prefabrication Platform'
Hildebrandt, Harrison; Fischer, Oliver; Zechmeister, Christoph; Menges, Achim, 2026, "Replication Data for: Fibre Fabrication of Hybrid Flax Pavilion", https://doi.org/10.18419/DARUS-5841, DaRUS, V1
This dataset contains fabrication data for the production of fibre-composite building components for the Hybrid Flax Pavilion . It includes: LFW_Sim Workflow Description.docx: A description and the pseudocode of the tool (LFW_Sim), which was used to generate tool paths and data exchange files (DataFile) for use on a 4-axis lathe-type filament windi... |
Mar 20, 2026 - EXC IntCDC Associated Project 42 'Universal Timber Slab'
Zorn, Max Benjamin; Wortmann, Thomas, 2026, "Universal Timber Slab: Disciplinary Surrogate Models", https://doi.org/10.18419/DARUS-5801, DaRUS, V1
This dataset contains 9 trained surrogate models across all four disciplines predicting the performance of UTS bay elements and a demo Python script. Model Artifacts Each surrogate is saved as a .joblib file which stores: {
'model': <trained sklearn model>, # Trained model
'scaler': <StandardScaler or None>, # Feature scaler
'f... |
