A decision-support framework for design of non-residential net-zero energy buildings

Designing Net-Zero Energy Buildings (NZEB) is a complex and collaborative team process involving knowledge sharing of experts leading to the common goal of meeting the Net-Zero Energy (NZE) project objectives. The decisions made in the early stages of design drastically affect the final outcome of design and energy goals. The Architecture, Engineering and Construction (AEC) industry is pursuing ways to improve the current building design process and project delivery methods for NZEBs. To enable the building industry to improve the building design process, it is important to identify the gaps, ways of improvement and potential opportunities to structure the decision-making process for the purpose of NZE performance outcome. It is essential to identify the iterative phases of design decisions between the integrated team of experts for the design processes conducted in these early stages to facilitate the decision-making of NZEB design. The lack of a structured approach to help the AEC industry in making informed decisions for the NZEB context establishes the need to evaluate the argumentation of the NZEB design decision process. The first step in understanding the NZEB design decision process is to map the current processes in practice that have been successful in achieving the NZE goal. Since the energy use performance goal drives the design process, this research emphasizes first the need to document, in detail, and investigate the current NZEB design process with knowledge mapping techniques to develop an improved process specific to NZEB context. In order to meet this first objective, this research qualitatively analyzed four NZEB case studies that informed decision-making in the early design phases. The four components that were studied in the early design phases included (1) key stakeholders involved (roles played), (2) phases of assessments (design approach), (3) processes (key processes, sub-processes and design activities affecting performance) and (4) technology (knowledge type and flow). A series of semi-structured, open ended interviews were conducted with the key decision-makers and decision facilitators to identify their roles in the early design process, the design approach adopted, rationale for decision-making, types of evaluations performed, and tools used for analysis. The qualitative data analysis was performed through content analysis and cognitive mapping techniques. Through this process, the key phases of decision-making were identified that resulted in understanding of the path to achieving NZE design goal and performance outcome. The second objective of this research was to identify the NZE decision nodes through a comparative investigation of the case studies. This research also explored the key issues specific to each stakeholder group. The interrelationships between the project objectives, decision context, occupants usage patterns, strategies and integrated systems, building operation and renewable energy production was identified through a series of knowledge maps and visual process models leading to the identification of the key performance indicators. This research reviewed the similarities and differences in the processes to identify significant opportunities that can improve the early building design process for NZEBs. This research identifies the key decision phases used by the integrated teams and describes the underlying structure that can change the order of key phases. A process mapping technique was adapted to capture the practice-based complex NZEB design approach and draw insights of the teamwork and interdisciplinary communication to enable more comprehensive understanding of linkages between processes, sub-processes and design activities, knowledge exchange, and decision rationale. Key performance indicators identified for early design of NZEBs resulted in developing a decision support process model that can help AEC industry in making informed decisions. This dissertation helps improve understanding of linkages between processes; decision nodes and decision rationale to enable industry-wide NZEB design process assessment and improvement. The dissertation discusses the benefits the proposed NZEB design process model brings to the AEC industry and explores future development efforts.