Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
A Pedagogical Benchmark Experiment for the Application of Multidisciplinary Design Optimization in Early Stage Building Design
This research is built upon a previously established, early stage, multidisciplinary design optimization (MDO) framework, entitled Evolutionary Energy Performance Feedback for Design (EEPFD), and proceeds with observing the impact of EEPFD on the early stages of design by conducting a pedagogical benchmark experiment. This experiment has two main observational interests. The first objective is to observe discrepancies between the human versus automated decision-making processes and the resulting performance of the solution space from each process. The second objective is to understand students' ability to translate their design intent into a parametric model, as this is a crucial component in the implementation of EEPFD. By comparing EEPFD and the benchmark pedagogical process, this paper provides an initial assessment of the potential of EEPFD to reduce latency in decision-making and to find superior performing design solutions compared to the benchmark process. At the completion of this experiment, it was observed that EEPFD was able to deliver superior performing design solution spaces, but that students encountered difficulties in the translation of their design intent into a functioning parametric model.
A Pedagogical Benchmark Experiment for the Application of Multidisciplinary Design Optimization in Early Stage Building Design
This research is built upon a previously established, early stage, multidisciplinary design optimization (MDO) framework, entitled Evolutionary Energy Performance Feedback for Design (EEPFD), and proceeds with observing the impact of EEPFD on the early stages of design by conducting a pedagogical benchmark experiment. This experiment has two main observational interests. The first objective is to observe discrepancies between the human versus automated decision-making processes and the resulting performance of the solution space from each process. The second objective is to understand students' ability to translate their design intent into a parametric model, as this is a crucial component in the implementation of EEPFD. By comparing EEPFD and the benchmark pedagogical process, this paper provides an initial assessment of the potential of EEPFD to reduce latency in decision-making and to find superior performing design solutions compared to the benchmark process. At the completion of this experiment, it was observed that EEPFD was able to deliver superior performing design solution spaces, but that students encountered difficulties in the translation of their design intent into a functioning parametric model.
A Pedagogical Benchmark Experiment for the Application of Multidisciplinary Design Optimization in Early Stage Building Design
Lin, Shih-Hsin Eve (Autor:in) / Gerber, David Jason (Autor:in)
ASCE International Workshop on Computing in Civil Engineering ; 2013 ; Los Angeles, California
Computing in Civil Engineering (2013) ; 802-809
24.06.2013
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
| British Library Conference Proceedings | 2013
A scalable problem to benchmark robust multidisciplinary design optimization techniques
| Springer Verlag | 2024
A scalable problem to benchmark robust multidisciplinary design optimization techniques
| Springer Verlag | 2024