|dc.description.abstract||The architecture, engineering, and construction community is taking action to reduce energy consumption. Fulfilling energy performance requirements entails complex decision-making at the architectural design stage, when a large number of parameters are undecided and the level of uncertainty is high. The early stage of design, in particular, is characterized by its iterative nature of divergent phases in which design alternatives are generated and convergent phases in which alternatives are assessed and selected. It is during or at the end of these phases that decision-making occurs under considerable uncertainty. Therefore, the methods and tools applied during these phases should account for the iterative, complex, and uncertain characteristics of the design process. At present, the building industry lacks a consistent approach to decision making during the phrases of the early stage of design: The divergent phase, when concepts are generated, consists of no practical framework within which designers generate more promising alternatives regarding energy performance, and the convergent phase, when concepts are evaluated and selected, includes no algorithm within it that designers can use to validate their decisions and provide confidence in their decisions. These deficiencies necessitate a clear step-wise approach that supports the proper design exploration by generation and evaluation of design alternatives, highlights significant parameters regarding energy performance for a variety of design scenarios, allows for coupled decisions under uncertainty, and align with the iterative nature of design process.
This research hypothesizes that (1) a new systematic method based on linear inverse modeling (LIM) can generate plausible ranges for design parameters given a preferred thermal energy performance at the early stage of architectural design; and (2) the application of the proposed approach can lead to a higher probability of achieving energy efficient buildings (increase the chances of developing promising concepts), which is the main objective of performance-based design; and finally (3) in comparison to the current prescriptive approach, the proposed performance-based method help designers with the design process by providing more design freedom and guidance. Such an approach also accounts for the iterative nature of an architectural design and promotes a step-by-step procedure for making a decision and updating information as each new decision is made. In contrast to the conventional “forward modeling” in building performance analysis in which the design parameters are considered input and the energy performance are output, the “inverse modeling” deals with the performance objective as input and the design parameters are inferred as the output of the analysis.
The study practices the proposed inverse modeling approach for making decisions regarding energy performance at the early design stages in four case studies, representing two different types of buildings in four climate zones. Such practices show the capability of the proposed inverse modeling to help designers in design space exploration, sequential decision-making, and trade-off study at the early stage of design. This method is proven to be a validate candidate for fulfilling desired energy performance and provide guidance and freedom in building design process. This thesis research contributes to the body of knowledge pertaining to building energy modeling and decision making at the early design stage, and its framework can be used by all groups of designers, the energy analysis experts as well as non-energy-expert architects, for a more informed decision-making regarding energy.||