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Title:Optimizing acoustic design and schematic architectural layouts of office buildings
Author(s):Alomani, Abdullah Abdulaziz Mohammed
Director of Research:El-Rayes, Khaled
Doctoral Committee Chair(s):El-Rayes, Khaled
Doctoral Committee Member(s):Liu, Liang; El-Gohary, Nora; Golparvar-Fard, Mani; Lilly, Brian
Department / Program:Civil & Environmental Eng
Discipline:Civil Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Acoustic quality, optimization, layout automation, image processing
Abstract:More than 33 million people work in office buildings in the USA that represent 18% of the total commercial buildings in the nation, and they spend half of their waking hours in these office buildings. To improve the comfort and productivity of these office building occupants, recent studies reported the need for (1) improving acoustic quality in office buildings as their unwanted noise adversely affect the productivity of their occupants and their job satisfaction; and (2) optimizing the schematic architectural layout designs to maximize their functional and operational performances. First, the acoustic quality in office buildings has been reported to suffer from noise level problems that adversely affect the productivity of building occupants and cause human stress, distraction, and low performance. To address and minimize these problems, office space designers need to utilize an optimal set of noise control materials to minimize these noise levels while keeping their cost to a minimum. Second, many of the developed architectural layout designs of iconic buildings around the world were inspired by nature. These nature-inspired thematic architectural layouts have been increasingly used in recent years by many architects. This architectural design task is often complex and challenging as it requires the creation of optimal architectural layouts that resemble the selected image from nature while complying with all owner specified space allocation requirements. The primary goal of this research study is to develop a novel model and methodology for optimizing the acoustic design of office buildings and automate the thematic architectural layout designs. To accomplish this goal, the research objectives of this study are to: (1) conduct a comprehensive literature review of the latest research studies on the impact of office building design, acoustic materials selection, image processing algorithms, optimizing the automation of generating the architectural layout designs, and optimization techniques; (2) develop a novel model for optimizing the design decisions of office buildings in order to minimize their cost of acoustic materials while complying with designer-specified requirements of acoustic quality; and (3) create a novel methodology that can automate the schematic design task of generating optimal thematic architectural layout that is inspired by an owner- or designer-specified image such as a local plant or a natural scene that provides a unique architectural theme for the project layout. The performance of the developed optimization model and methodology was analyzed using real-life case studies and application examples. The results of analysis demonstrated the novel, unique, and practical capabilities of the research outcomes in empowering decision makers, architects, designers, and engineers to (i) minimize the cost of acoustic materials; (ii) achieve designer-specified acoustic quality from the design phase; (iii) automate image processing; (iv) maximize compliance with designer-specified adjacency requirements; and (v) maximize functional and operational performances of the architectural layout. These capabilities will result in identifying optimal acoustic designs for office buildings and automating the generation of optimal thematic architectural layouts that preserve the image theme while complying with room adjacency and rooms area requirements.
Issue Date:2019-09-27
Type:Text
URI:http://hdl.handle.net/2142/106428
Rights Information:© 2019 Abdullah AlOmani
Date Available in IDEALS:2020-03-02
Date Deposited:2019-12


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