Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Reviving and adapting a vernacular architectural element to promote low carbon homes using genetic algorithms: the case of Rawshan

Alelwani, Raed 2021. Reviving and adapting a vernacular architectural element to promote low carbon homes using genetic algorithms: the case of Rawshan. PhD Thesis, Cardiff University.
Item availability restricted.

[thumbnail of PhD Thesis]
Preview
PDF (PhD Thesis) - Accepted Post-Print Version
Download (9MB) | Preview
[thumbnail of Cardiff University Electronic Thesis and Dissertation Publication Form] PDF (Cardiff University Electronic Thesis and Dissertation Publication Form) - Supplemental Material
Restricted to Repository staff only

Download (133kB)

Abstract

When reviving vernacular architectural elements in developed countries, evaluations using computational intelligence techniques, as well as the corresponding cultural and environmental aspects, are important areas of consideration. A Rawshan is one such vernacular architectural element that embodies Arab-Islamic values and was a prominent feature in Saudi Arabia’s architectural history. This study aims to facilitate the revival of the Rawshan vernacular architectural element, utilizing Genetic Algorithms and establishing an optimized Rawshan design framework that takes into account the local climatic conditions, context, and socio-cultural challenges. As the biggest country in the Middle East, Saudi Arabia is characterized by a variety of climates and topographies, making it an ideal case study for this research. To address the study objectives, a comprehensive, five stage study is conducted. This investigation attempts to: (a) identify factors resulting in a revival of vernacular architecture in general, and for the Rawshans in Saudi Arabia in particular; (b) determine the values (criteria) of the Rawshan that constitute its identity; (c) evaluate the Rawshan's ability to reduce energy consumption; (d) establish and develop an energy-efficient Rawshan framework that supports architects, designers, and building professionals to reviving Rawshan in the Saudi Arabian climate, context and, cultural requirements; and (e) propose six different optimized Rawshans for six different climates. Living room prototypes that face different directions are input into the established framework, thereby validating it through the identification of various energy consumption levels. Each stage of this research utilizes a specific methodology: secondary data; public survey analysis, using the SPSS software; site visits and a modelling analysis, using Rhinoceros 3D and its plug-in, Grasshopper; decision-maker expert interviews, using NVivo analysis software; computational intelligent techniques, using Grasshopper and its components for simulations and optimizations; and a validation analysis. This study contributes to the body of knowledge within this field by offering a framework for reviving the Rawshan vernacular architectural element to reduce energy consumption,while also providing adequate daylight for Saudi Arabian homes. Consequently, two methods of optimization algorithms were used: (a) a single-objective optimization method (SOO) that used energy and UDLI as its objectives; and (b) a multi-objective optimization method (MOO). These findings are broadly applicable to other regions with similar climatic conditions and cultural requirements, such as those in the Middle East and GCC countries. The findings of the SOO revealed that the Rawshan reduced energy consumption by 1–3% in the east, west, and south directions of a virtual living room located in Jeddah. Moreover, by comparing the methods that were utilized with the simulation of the living room without a Rawshan, it was found that there was less energy efficiency for cities located at the sea level, for example, Jeddah, Dammam, and Jizan. However, for all the cities analyzed, the MOO methods effectively decreased energy consumption in living rooms with a Rawshan.

Item Type: Thesis (PhD)
Date Type: Completion
Status: Unpublished
Schools: Engineering
Uncontrolled Keywords: Genetic Algorithm, Optimisation, Vernacular Architecture, Rawshan Vernacular Architectural Element, Energy Consumption, Daylight
Date of First Compliant Deposit: 13 December 2021
Last Modified: 05 Aug 2022 01:36
URI: https://orca.cardiff.ac.uk/id/eprint/145934

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics