Bayesian inference for modelling uncertainty in non-standard building systems
Bayesian inference for modelling uncertainty in non-standard building systems
This paper introduces a Bayesian inference approach tailored for modelling uncertainty in non-standard building systems. The proposed framework is exemplified through a case study on coreless filament winding, offering insights into the interplay between probabilistic modelling and structural design. By integrating heterogeneous data sources encompassing fabrication parameters, geometry, material properties, and structural response metrics, the proposed methodology offers a comprehensive solution for quantifying uncertainty in novel construction processes. Through probabilistic graphical models and Bayesian inference techniques, this research contributes to advancing the understanding and management of uncertainty in the co-design of non-standard building systems, facilitating informed decision-making for architects and engineers.
69-80
Kannenberg, Fabian
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Gil Perez, Marta
44224912-0ada-4455-95d8-ccf1464d01c3
Schneider, Tim
6814e544-caa8-4cd6-856b-92c2c99c15dc
Staab, Steffen
bf48d51b-bd11-4d58-8e1c-4e6e03b30c49
Knippers, Jan
e94ff797-23c0-46e9-85e3-ac28cabfb166
Menges, Achim
032209c4-fbf5-4359-a89b-70434daf9376
30 August 2024
Kannenberg, Fabian
2d5dff24-5c31-4756-ac37-ddefc1a3d880
Gil Perez, Marta
44224912-0ada-4455-95d8-ccf1464d01c3
Schneider, Tim
6814e544-caa8-4cd6-856b-92c2c99c15dc
Staab, Steffen
bf48d51b-bd11-4d58-8e1c-4e6e03b30c49
Knippers, Jan
e94ff797-23c0-46e9-85e3-ac28cabfb166
Menges, Achim
032209c4-fbf5-4359-a89b-70434daf9376
Kannenberg, Fabian, Gil Perez, Marta, Schneider, Tim, Staab, Steffen, Knippers, Jan and Menges, Achim
(2024)
Bayesian inference for modelling uncertainty in non-standard building systems.
Eversmann, Philipp, Gengnagel, Christoph, Lienhard, Julian, Ramsgaard Thomsen, Mette and Wurm, Jan
(eds.)
In Scalable Disruptors. DMS 2024.
Springer Cham.
.
(doi:10.1007/978-3-031-68275-9_6).
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper introduces a Bayesian inference approach tailored for modelling uncertainty in non-standard building systems. The proposed framework is exemplified through a case study on coreless filament winding, offering insights into the interplay between probabilistic modelling and structural design. By integrating heterogeneous data sources encompassing fabrication parameters, geometry, material properties, and structural response metrics, the proposed methodology offers a comprehensive solution for quantifying uncertainty in novel construction processes. Through probabilistic graphical models and Bayesian inference techniques, this research contributes to advancing the understanding and management of uncertainty in the co-design of non-standard building systems, facilitating informed decision-making for architects and engineers.
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Accepted/In Press date: 2 May 2024
Published date: 30 August 2024
Venue - Dates:
Design Modeling Symposium, , Kassel, Germany, 2024-09-16 - 2024-09-18
Identifiers
Local EPrints ID: 493509
URI: http://eprints.soton.ac.uk/id/eprint/493509
PURE UUID: 00bde8cb-fee9-46d3-a4bb-cf3c73fac160
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Date deposited: 04 Sep 2024 16:42
Last modified: 05 Sep 2024 01:46
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Contributors
Author:
Fabian Kannenberg
Author:
Marta Gil Perez
Author:
Tim Schneider
Author:
Steffen Staab
Author:
Jan Knippers
Author:
Achim Menges
Editor:
Philipp Eversmann
Editor:
Christoph Gengnagel
Editor:
Julian Lienhard
Editor:
Mette Ramsgaard Thomsen
Editor:
Jan Wurm
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