INDOOR OVERHEATING RISK: A FRAMEWORK FOR TEMPORAL BUILDING ADAPTATION DECISION-MAKING
type: CreativeWork
description: Overheating in buildings is predicted to increase as a result of a warming climate and urbanisation in most cities. With regards to responding to this challenge, decision makers ranging from_ design teams, local authorities, building users, national programs and market innovators; and during the different stages of a building’s service life, want to know a few pertinent matters: What space characteristics and buildings are at a higher risk and by how much?; What are the tradeoffs between alternative design and/or user-based actions?; What are the likely or possible consequences of their decisions?; What is the impact of climate change to indoor overheating?; among other decision support questions. However, such decision appraisal information still remains buried and dispersed in existing simulation models, and empirical studies, and not yet been clearly articulated in any existing study or model. Especially decision support information articulated in a way that gives each decision maker maximum capacity to anticipate and respond to thermal discomfort in different spaces and through the lifetime of a building. There is a need for an integrated and systematic means of building adaptation decision-support, which provides analytical leverage to these listed decision makers. A means that: 1) assimilates a range of indoor thermal comfort's causal and solution space processes; 2) reveals and enhances the exploration of the space and time-dependent patterns created by the dynamics of the indoor overheating phenomenon through time; and one that 3) imparts insight into decision strategy and its synthesis across multiple decision makers. This study recognises the lack of an overarching framework attending to the listed concerns. Therefore, the key aim of this thesis is to develop and test a building adaptation decision-support framework, which extends the scope of existing frameworks and indoor overheating risk models to facilitate trans-sectional evaluations that reveal tempo…
abstract: Overheating in buildings is predicted to increase as a result of a warming climate and urbanisation in most cities. With regards to responding to this challenge, decision makers ranging from_ design teams, local authorities, building users, national programs and market innovators; and during the different stages of a building’s service life, want to know a few pertinent matters: What space characteristics and buildings are at a higher risk and by how much?; What are the tradeoffs between alternative design and/or user-based actions?; What are the likely or possible consequences of their decisions?; What is the impact of climate change to indoor overheating?; among other decision support questions. However, such decision appraisal information still remains buried and dispersed in existing simulation models, and empirical studies, and not yet been clearly articulated in any existing study or model. Especially decision support information articulated in a way that gives each decision maker maximum capacity to anticipate and respond to thermal discomfort in different spaces and through the lifetime of a building. There is a need for an integrated and systematic means of building adaptation decision-support, which provides analytical leverage to these listed decision makers. A means that: 1) assimilates a range of indoor thermal comfort's causal and solution space processes; 2) reveals and enhances the exploration of the space and time-dependent patterns created by the dynamics of the indoor overheating phenomenon through time; and one that 3) imparts insight into decision strategy and its synthesis across multiple decision makers. This study recognises the lack of an overarching framework attending to the listed concerns. Therefore, the key aim of this thesis is to develop and test a building adaptation decision-support framework, which extends the scope of existing frameworks and indoor overheating risk models to facilitate trans-sectional evaluations that reveal tempo…
author: Gichuyia, Linda Nkatha
language: en
keywords: Indoor overheating risk, Thermal comfort, Climate change adaptation, decision analytics, uncertainty analysis, sensitivity analysis, System Dynamics modelling
license: https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/88f68509-dd2e-43d5-948d-4e6db542090a/download
license: https://www.rioxx.net/licenses/all-rights-reserved/
date published: 2017-06-29
date modified: 2026-07-22T22:24:11Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.17146