Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/236144
Title: USING GENERATIVE DESIGN TOOL TO OPTIMISE ENERGY PERFORMANCE IN THE EARLY DESIGN STAGE
Authors: DOMINIC LEE WEN XIAN
Issue Date: 2022
Citation: DOMINIC LEE WEN XIAN (2022). USING GENERATIVE DESIGN TOOL TO OPTIMISE ENERGY PERFORMANCE IN THE EARLY DESIGN STAGE. ScholarBank@NUS Repository.
Abstract: The impact of adopting building performance simulations (BPS) to improve overall energy performance in the early design stage of building performance is considerable, but the application of BPS is often only done on one building design, usually after the major design decision have been made. For this reason, this dissertation aims to deliver and evaluate the performance-based generative design system. This generative design tool facilitates the decision-making process early in the design phase of building project life cycles, by generating design alternatives with energy optimisation in mind. An experimental approach will be adopted to apply the proposed generative design approach to recreate two existing high-rise Housing & Development Board (HDB) residential buildings in Singapore. Using shape-grammar and genetic algorithms, generated design alternatives will undergo EnergyPlus simulations to predict their annual Energy Used Intensities (EUI). The simulation results of the existing building and the generated solutions will be analysed and compared to determine the effectiveness of the proposed system. The findings of this study further highlight the potential of performance-based generative designs and its promise in an architectural context. The results of the simulation shows that the proposed systems are indeed able to generate unique solutions that show improvements in their annual EUI, in comparison to that of the existing buildings. In retrospect, generative tools, enhanced with optimization procedures, equip practitioners with a heightened ability in designing more energy-efficient buildings. Future research could be geared toward incorporating multi-objective optimisation into the generative designs systems to realistically reflect the actual design process.
URI: https://scholarbank.nus.edu.sg/handle/10635/236144
Appears in Collections:Bachelor's Theses

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Dominic Lee Wen Xian DBE_Dominic Wen Xian Le.pdf12.15 MBAdobe PDF

RESTRICTED

NoneLog In

Page view(s)

7
checked on Jan 26, 2023

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.