The vision of the Cluster of Excellence Integrative Computational Design and Construction for 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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1,141 to 1,150 of 1,190 Results
Tabular Data - 407.8 KB - 73 Variables, 350 Observations - UNF:6:rGK52UVdhLeuLg5sCtbSBg==
This file contains the full list of buildings with general information, as well as analyzed and classified data on program (use of the building), structural system, materials used, massing and internal spatial organization.
MS Excel Spreadsheet - 254.2 KB - MD5: 8d17e388e6777bdd8bbe43661557c4db
This file contains both the full list of buildings with their general information (name, location, status and year of construction, number of stories, architect, links to sources), and analyzed and classified data on program (use of the buildings), structural system type, materials used, massing and internal spatial organization.
OpenOffice Spreadsheet - 83.8 KB - MD5: 7ee1c347c0261ba098e0a41fa2bc03f9
This file contains the full list of buildings and their general information (name, architect, height in number of stories, status and year of construction, location, sources).
Tabular Data - 117.4 KB - 12 Variables, 350 Observations - UNF:6:7rMyAmmwOg1K+roWfMCU2g==
This file contains the full list of buildings and their general information (name, architect, height in number of stories, status and year of construction, location, sources).
MS Excel Spreadsheet - 95.7 KB - MD5: cfa8064635d8984b7169f65aecd42bb4
This file contains the full list of buildings and their general information (name, architect, height in number of stories, status and year of construction, location, sources).
TAR Archive - 24.3 KB - MD5: 33db881cf3f39b29359cc578579ed327
Python scripts used to generate the tables and plots presented in the paper based on the experimental data. View README.md file for more detailed steps to reproduce the analysis.
Tabular Data - 1.3 KB - 3 Variables, 92 Observations - UNF:6:Cyou1bO+QPyzfhZGLR+QBA==
Data corresponding to the measured bond line thickness over the horizontal wide finger surface located at the compression side of the connection. Coordinates (x,y) and bond line thickness in [mm].
Tabular Data - 1.3 KB - 3 Variables, 92 Observations - UNF:6:DBoSP/EsBuxWL6yvBfhELg==
Data corresponding to the measured bond line thickness over the horizontal wide finger surface located at the tension side of the connection. Coordinates (x,y) and bond line thickness in [mm].
Tabular Data - 1.1 KB - 3 Variables, 79 Observations - UNF:6:e1lsDOV2X/SQrrgLNPvbFg==
Data corresponding to the measured bond line thickness over the inclined wide finger surface located at the compression side of the connection. Coordinates (x,y) and bond line thickness in [mm].
Tabular Data - 1.1 KB - 3 Variables, 79 Observations - UNF:6:7VjP97MXwJwPSfyLBYlIdQ==
Data corresponding to the measured bond line thickness over the inclined wide finger surface located at the tension side of the connection. Coordinates (x,y) and bond line thickness in [mm].
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