Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
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.
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.
Bayesian Inference for Modelling Uncertainty in Non-Standard Building Systems
Kannenberg, Fabian (Autor:in) / Gil Pérez, Marta (Autor:in) / Schneider, Tim (Autor:in) / Staab, Steffen (Autor:in) / Knippers, Jan (Autor:in) / Menges, Achim (Autor:in) / Eversmann, Philipp / Gengnagel, Christoph / Lienhard, Julian / Ramsgaard Thomsen, Mette
30.08.2024
Kannenberg , F , Gil Pérez , M , Schneider , T , Staab , S , Knippers , J & Menges , A 2024 , Bayesian Inference for Modelling Uncertainty in Non-Standard Building Systems . in P Eversmann , C Gengnagel , J Lienhard , M Ramsgaard Thomsen & J Wurm (eds) , Scalable Disruptors : Design Modelling Symposium Kassel 2024 . DMS: Design Modelling Symposium Berlin , Springer , Cham , pp. 69-80 , Design Modelling Symposium Kassel 2024 , Kassel , Germany , 16/09/24 . https://doi.org/10.1007/978-3-031-68275-9_6
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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