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EXC IntCDC Research Project 38 'Green Infrastructures for Building Stock Transformation'(University of Stuttgart, Max Planck Institute for Intelligent Systems)
EXC IntCDC Research Project 38 'Green Infrastructures for Building Stock Transformation' logo
Oct 8, 2026Cluster of Excellence Integrative Computational Design and Construction for Transformative Architecture (EXC IntCDC)
RP38-1: Regenerative Green Infrastructures for Existing Building Stock Densification, Conversion and Retrofitting
Oct 8, 2026 - KomS Dataverse
Stricker, Birthe; Kuch, Bertram; Schönung, Jürgen; Stumpf, Bernhard; Kohlgrueber, Vera; Braeutigam, Patrick, 2026, "CSO events - extended micropollutants", https://doi.org/10.18419/DARUS-6467, DaRUS, V1
Combined sewage overflow events were sampled in 2024 and 2025 by the Mannheim Municipal Drainage (Eigenbetrieb Stadtentwässerung Mannheim) at their ten most relevant (based on their yearly overflow volume) CSO retention basins as well as storage sewers within the catchment area of Mannheim (Germany). Samples were taken time-proportional as 20-min q...
Oct 8, 2026 - Institute of Applied Analysis and Numerical Simulation
Haasdonk, Bernard; Stamm, Benjamin; ZENG, Zhuoyao, 2026, "Replication Data for: Model Order Reduction for Parametric Dissipative Quantum Systems", https://doi.org/10.18419/DARUS-6519, DaRUS, V1, UNF:6:8h5IzpPtovnZ6Q3+22q5DA== [fileUNF]
Companion code and replication data for the paper "Model Order Reduction for Parametric Dissipative Quantum Systems" (Haasdonk, Stamm, Zeng). The Python package lindbladian_rbm builds reduced-basis (RB) surrogates of the steady state of parametrised Lindbladian master equations, in two reduced-space formulations: EigGreedy (a unit-norm constrained...
Knowledge Graphs(Universität Stuttgart)
Oct 8, 2026Analytic Computing
Oct 7, 2026 - Stochastic Simulation and Safety Research for Hydrosystems (LS3)
Scheurer, Stefania; Frenner, Riccardo; Bruennette, Tim; Oladyshkin, Sergey; Nowak, Wolfgang, 2026, "Replication Data for: Efficient Confidence Interval Computation for Physics-Aware Machine Learning of Diffusion-Sorption Models", https://doi.org/10.18419/DARUS-5967, DaRUS, V1, UNF:6:+gEES8LITw2YkntYAMuceg== [fileUNF]
Supplementary code to replicate key experiments from our paper. The code computes confidence intervals for the Finite Volume Neural Network (FINN), a physics-aware ML model that learns unknown parts of a PDE (here, the retardation function of a diffusion-sorption model). The workflow has four steps: 1. Train FINN on the observations. 2. Learn an em...
Oct 7, 2026 - Stochastic Simulation and Safety Research for Hydrosystems (LS3)
Scheurer, Stefania; Reiser, Philipp; Bruennette, Tim; Nowak, Wolfgang; Guthke (geb. Schöniger), Anneli; Bürkner, Paul-Christian, 2026, "Replication Data for: Uncertainty-Aware Surrogate-Based Amortized Bayesian Inference (UA-SABI)", https://doi.org/10.18419/DARUS-5670, DaRUS, V1
Supplementary code to replicate key experiments from our paper. The code trains Bayesian polynomial chaos surrogates (PCE/aPC, fitted in Stan via CmdStanPy) and uses them for amortized Bayesian inference with normalizing flows (BayesFlow, JAX backend). It covers standard surrogate-based ABI (SABI) and the uncertainty-aware variant (UA-SABI), which...
Oct 7, 2026 - Project: ChaNGe
Götz, Tobias, 2026, "Scalable Wireless EV Charging Infrastructure: $N$-Box Architecture Cost Analysis Dataset", https://doi.org/10.18419/DARUS-6323, DaRUS, V1, UNF:6:dj0Laa9lLdCUSF3SAAhcYw== [fileUNF]
This dataset contains the cost analysis results of a scaled wireless power transfer (WPT) infrastructure for EV charging with 22 kW per charging point. An infrastructure size ranging from 1 to 50 charging points a N-box architecture was evaluated for three power electronic topologies AC-AC, AC-DC, and AC-HF. All possible $m \times n = N$ combinatio...
Oct 7, 2026 - On-Site Robotic Adhesive Bonding
Opgenorth, Nils; Menges, Achim, 2026, "Adhesive Robot: Hardware Design Resources", https://doi.org/10.18419/DARUS-6448, DaRUS, V1
This dataset contains the mechanical hardware design resources for the adhesive robot, one of two robot classes used in a multi-robot construction system for the automated on-site assembly of prefabricated cross-laminated timber (CLT) floor panels. Working together with a digitally controlled tower crane and a fleet of assembly robots, the adhesive...
Oct 7, 2026 - On-Site Robotic Adhesive Bonding
Opgenorth, Nils; Menges, Achim, 2026, "Experimental Data on Robotic Adhesive Application and Joint Pressing", https://doi.org/10.18419/DARUS-6450, DaRUS, V1
This dataset contains the experimental and calibration data generated during the development and evaluation of the adhesive robot for the automated on-site bonding of prefabricated cross-laminated timber (CLT) floor panels. The adhesive robot is temporarily embedded at the interface between two panels, where it applies a two-component structural ad...
Oct 7, 2026 - On-Site Robotic Adhesive Bonding
Opgenorth, Nils; Menges, Achim, 2026, "Multi-Robot Control Software for Vision-Guided, Crane-Assisted On-Site Assembly and Adhesive Bonding", https://doi.org/10.18419/DARUS-6449, DaRUS, V1
This dataset contains the control and coordination software for a multi-robot construction system for the on-site assembly of prefabricated cross-laminated timber (CLT) floor panels. The system combines a digitally controlled tower crane with two classes of compact robots that are temporarily embedded within the panels during assembly: assembly rob...
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