Multi-objective optimization of prefabricated slabs - A case study in parametric design
| dc.contributor.author | Zayton, Gabriella | |
| dc.contributor.author | Karlsson, William | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för arkitektur och samhällsbyggnadsteknik (ACE) | sv |
| dc.contributor.examiner | Rempling, Rasmus | |
| dc.date.accessioned | 2021-06-17T07:31:48Z | |
| dc.date.available | 2021-06-17T07:31:48Z | |
| dc.date.issued | 2021 | sv |
| dc.date.submitted | 2020 | |
| dc.description.abstract | Starting in 2022, the Swedish government will introduce a new law, demanding cli mate declarations from developers of new buildings. Structural engineers have an important role when it comes to deciding on a suitable design that satisfies demands on climate impact, cost and efficacy. One may call this a multi-objective optimiza tion problem. The purpose is to contribute to the reduction of the climate impact in the design process. The aim is to present a method that can be used by structural engineers to choose the optimal prefabricated element with respect to climate impact and el ement costs. The objective is to create an algorithm able to vary parameters and produce a database with all possible solutions as output. The investigation of this master thesis was divided into three different parts. The first part included a literature study on material, slab elements, climate analysis and optimization. After the literature study, the second part continued with generation of database including FE analysis, LCA calculation and cost estimation. The third part of this study consists of post-processing and presenting extracted results from the database through creation of scatter plots, linear regression and Decision Tree Models. The study presents a workflow possible of measuring optimality according to the established definition. The inclusion of more design and behavioural constraints will further improve the detail level of the study. The use of Decision Tree Models was found advantageous and further testing could lead to trained algorithm capable of predicting optimality of elements not originally part of the database. | sv |
| dc.identifier.coursecode | ACEX30 | sv |
| dc.identifier.uri | https://hdl.handle.net/20.500.12380/302583 | |
| dc.language.iso | eng | sv |
| dc.setspec.uppsok | Technology | |
| dc.subject | Climate impact, Life Cycle Analysis, Slab design, Finite Element, | sv |
| dc.subject | Full Factorial Design, Decision Tree Model. | sv |
| dc.title | Multi-objective optimization of prefabricated slabs - A case study in parametric design | sv |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.uppsok | H |