Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744389
Title: Indoor overheating risk : a framework for temporal building adaptation decision-making
Author: Gichuyia, Linda Nkatha
ISNI:       0000 0004 7225 6398
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2017
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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 temporal decision strategies. The generic framework frames a multi-method analysis aiming to underpin decision appraisal for different spaces over a 50 to 100-year time horizon. It constitutes an underlying architecture that engages the dimensions of decision support information generation, information structuring, its exploration and dissemination, to ease in drawing decision strategy flexibly and transparently. The multi-method framework brings together: 1) Systems thinking methods to a) facilitate the systematic exposure of the elements that shape indoor overheating risk, and b) reveal the processes that shape multi-stakeholder decision-making response over time; 2) The use of normative, predictive and exploratory building scenarios to a) examine the overheating phenomenon over time, and b) as a lens through which to explore the micro-dynamics brought about by aspects of heterogeneity and uncertainty; and 3) The application of both computational and optimization techniques to appraise potential routes towards indoor thermal comfort over an extended time scale by a) tracking shifts in frequency, intensity and distribution of indoor overheating vulnerability by causal elements over time and space; and b) tracking shifting optima of the heat mitigation solution space, with respect to time, climate futures, heterogeneity of spaces, and due to thermal comfort assumptions. The framework’s potential has been demonstrated through its application to office buildings in Nairobi.
Supervisor: Steemers, Koen Sponsor: Gates Cambridge Scholarship
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.744389  DOI:
Keywords: Indoor overheating risk ; Thermal comfort ; Climate change adaptation ; decision analytics ; uncertainty analysis ; sensitivity analysis ; System Dynamics modelling
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