The vision of the Cluster of Excellence Integrative Computational Design and Construction for Transformative Architecture (EXC IntCDC) is to harness the full potential of digital technologies in order to rethink design, fabrication and construction based on integration and interdisciplinarity, with the goal of enabling game-changing innovation in the building sector as it can only occur through highly integrative fundamental research in an interdisciplinary, large-scale research undertaking.

The Cluster aims to lay the methodological foundations for a profound rethinking of the design and building process and related building systems by adopting an integrative computational approach based on interdisciplinary research encompassing architecture, structural engineering, building physics, engineering geodesy, manufacturing and system engineering, computer science and robotics, social sciences and humanities. We aim to bundle the internationally recognised competencies in these fields of the University of Stuttgart and the Max Planck Institute for Intelligent Systems to accomplish our research mission.

The Cluster’s Industry Consortium will ensure direct knowledge exchange, transfer and rapid impact. Taking into account the significant difference between the building industry and other industries, we will tackle the related key challenges of achieving a higher level of integration, performance and adaptability, and we will address the most important building typologies of multi-storey buildings, long-span buildings, and the densification of urban areas.

The Cluster’s broad methodological insights and interdisciplinary findings are expected to result in comprehensive approaches to harnessing digital technologies, which will help to address the ecological, economic and social challenges that current incremental approaches cannot solve.

We envision IntCDC to significantly shape the future of architecture and the building industry through a higher-level integration of computational design and engineering methods, effective cyber-physical (tightly interlinked computational and material) robotic construction processes and new forms of human-machine collaboration, efficient and sustainable next-generation building systems, and socio-cultural and ethical reflection. Thus, the Cluster will have significant impact on creating the conditions required for a liveable and sustainable future built environment, high-quality yet affordable architecture and a novel digital building culture.
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111 to 120 of 133 Results
Mar 15, 2023 - EXC IntCDC Research Project 12 'Computational Co-Design Framework for Fibre Composite Building Systems'
Gil Pérez, Marta; Zechmeister, Christoph; Kannenberg, Fabian; Mindermann, Pascal; Balangé, Laura; Guo, Yanan; Hügle, Sebastian; Gienger, Andreas; Forster, David; Bischoff, Manfred; Tarín, Cristina; Middendorf, Peter; Schwieger, Volker; Gresser, Götz Theodor; Menges, Achim; Knippers, Jan, 2023, "Object model data sets of the case study specimens for the computational co-design framework for coreless wound fibre-polymer composite structures", https://doi.org/10.18419/DARUS-3375, DaRUS, V1
This repository contains the object model data sets of the case study specimens from the related publication: Gil Pérez, M., Zechmeister, C., Kannenberg, F., Mindermann, P., Balangé, L., Guo, Y., Hügle, S., Gienger, A., Forster, D., Bischoff, M., Tarín, C., Middendorf, P., Schwieger, V., Gresser, G. T., Menges, A., Knippers, J.: 2022, Computational...
Mar 3, 2023 - EXC IntCDC Research Project 20 'Knowledge Representation for Multi-Disciplinary Co-Design'
Elshani, Diellza; Lombardi, Alessio; Hernández, Daniel; Staab, Steffen; Fisher, Al; Wortmann, Thomas, 2023, "BHoM to bhOWL converter", https://doi.org/10.18419/DARUS-3364, DaRUS, V1
The dataset is the release version v2.0.0 of the BHoM to bhOWL converter, which helps convert BHoM data to a knowledge graph in any software BHoM supports. BHoM (The Buildings and Habitats object Model) is collaborative framework that runs within several AEC design software, which helps to represent data in a object oriented database model. OWL (We...
EXC IntCDC Research Project 20 'Knowledge Representation for Multi-Disciplinary Co-Design'(University of Stuttgart, Max Planck Institute for Intelligent Systems)
EXC IntCDC Research Project 20 'Knowledge Representation for Multi-Disciplinary Co-Design' logo
Feb 23, 2023
RP20-1: Knowledge representation for multi-disciplinary co-design of buildings.
Jan 17, 2023 - EXC IntCDC Associated Project 11 'Imperfection Measurements on Timber Members'
Töpler, Janusch; Kuhlmann, Ulrike, 2023, "Measurement data: Laser scanning of timber buidlings", https://doi.org/10.18419/DARUS-3304, DaRUS, V1
The timber structures of 23 building projects were measured with a laser scanner Leica ScanStation P20 within the research project DIBt - ZP 52-5-13.194. Several buildings with concrete columns are also included in the data set. The measurements were carried out directly after assembly and alignment of the structures. The data sets of all measured...
EXC IntCDC Associated Project 11 'Imperfection Measurements on Timber Members'(University of Stuttgart, Max Planck Institute for Intelligent Systems)
EXC IntCDC Associated Project 11 'Imperfection Measurements on Timber Members' logo
Dec 13, 2022
AP11: Imperfection measurements on timber members at risk of buckling.
EXC IntCDC Research Project 7 'Integrated Testing and Numerical Verifications'(University of Stuttgart, Max Planck Institute for Intelligent Systems)
EXC IntCDC Research Project 7 'Integrated Testing and Numerical Verifications' logo
Dec 13, 2022
RP7-1: Development of an integrated approach of testing and numerical verifications.
Oct 12, 2022 - Institute for Structural Mechanics
Krake, Tim; von Scheven, Malte, 2022, "Matlab Implementation of Efficient Updates of Redundancy Matrices", https://doi.org/10.18419/DARUS-2870, DaRUS, V1
This is a Demo for the manuscript 'Efficient Update of Redundancy Matrices for Truss and Frame Structures' that demonstrates the speedup and accuracy of the proposed update formulas. The computation is done in single-precision. Please open and run the main file. Further information is contained in this file.
Sep 29, 2022 - SFB-TRR 161 INF "Collaboration Infrastructure"
Garkov, Dimitar; Müller, Christoph; Braun, Matthias; Weiskopf, Daniel; Schreiber, Falk, 2022, ""Research Data Curation in Visualization : Position Paper" (Data)", https://doi.org/10.18419/DARUS-3144, DaRUS, V1, UNF:6:yUhRXAoSoLD387EnHtthFg== [fileUNF]
Here, we make available the supplemental material regarding data collection from the publicaiton "Research Data Curation in Visualization : Position Paper". The dataset represents an aggregated collection of the data policies of selected publication venues in the areas of visualization, computer graphics, software, HCI, and Virtual Reality with inc...
Aug 29, 2022 - EXC IntCDC Research Project 5 'Reconfiguration of Training, Skills and Digital Literacy'
Wortmeier, Ann-Kathrin; Calepso, Aimée Sousa; Kropp, Cordula; Sedlmair, Michael; Weiskopf, Daniel, 2022, "Replication Data for BauHCI Video Analysis", https://doi.org/10.18419/DARUS-2117, DaRUS, V1, UNF:6:+IiMCK3MFfuUzdi5tz/L/g== [fileUNF]
The commercial videos are presenting visions of future Augmented reality applications. We analyzed 30 YouTube videos featuring AR devices in industrial manufacturing and construction. We offer the excel sheet including the list of the 30 commercial YouTube videos with information on year/title/duration/initiator/type of initiator/link/keywords in s...
Aug 9, 2022 - EXC IntCDC Research Project 12 'Computational Co-Design Framework for Fibre Composite Building Systems'
Abdelaal, Moataz; Schiele, Nathan Daniel; Angerbauer, Katrin; Kurzhals, Kuno; Sedlmair, Michael; Weiskopf, Daniel, 2022, "Supplemental Materials for: Comparative Evaluation of Bipartite, Node-Link, and Matrix-Based Network Representations", https://doi.org/10.18419/DARUS-3100, DaRUS, V1
The supplemental materials of the paper titled Comparative Evaluation of Bipartite, Node-Link, and Matrix-Based Network Representations, which was accepted for presentation at IEEE VIS 2022 conference. The structure of the folder is as follows: . └── code |── NetworkGeneration # the R code to generate the network data |── NetworkVis # the code that...
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