Multidisciplinary modeling for sustainable engineering design and assessment

Design and assessment activities have traditionally been performed with respect to a relatively narrow analysis boundary and without accounting for influences from or on the world outside the boundary. This “all other things being equal” mindset results in tractable, generally solvable problems, but it precludes the detection of externalities, consequences that manifest outside the analysis boundary. From a sustainability perspective, externalities whether they affect the environment, society, the economy, or other systems cannot be ignored. Moreover, many externalities lead in turn to feedback effects, often negative, on the system of interest. Failing to account for these effects can result in decisions that appear economically, environmentally, or otherwise optimal within a narrow analysis boundary but are sub-optimal or simply incorrect when a larger perspective is taken. To anticipate externalities and avoid the unpleasant surprises they lead to, it is critical to use a holistic perspective for sustainable design and assessment. While this is not a novel concept, to date most efforts towards sustainable design and assessment have been made within single fields of study, including engineering, economic analysis and life cycle assessment. The models used within each discipline are wellsuited to the traditional, narrow analysis boundary but frequently capture systems outside that boundary in a simplistic and even unrealistic fashion. This dissertation posits that for sustainability applications, a holistic perspective is best accomplished ii by combining modeling techniques and other methods from a variety of previously disparate disciplines. These various techniques each have shortcomings and advantages that are often complementary. Combining models from multiple disciplines thus offers an opportunity to create a widely applicable, integrated method with all of the advantages and relatively few of the shortcomings of each individual approach. This dissertation addresses the need for multidisciplinary modeling in sustainability applications. Two methods for sustainable assessment, both of which combine mathematical and statistical modeling with life cycle assessment, are developed. Regression streamlining applies linear regression and model cross-validation techniques to streamlined life cycle assessment, resulting in a simple and intuitive way to generate streamlined life cycle inventories as well as estimates of the error in the streamlined inventories relative to a full inventory. The Comprehensive Allocation Investigation Strategy (CAIS) is a calculation procedure for modeling life cycle inventories as functions of allocation decisions. The results can be used to detect situations in which one life cycle appears environmentally superior to another due to allocation decisions rather than differences in the inventories. The final contribution of this dissertation is the process-to-planet (P2P) modeling framework for sustainable engineering applications. Several applications of the P2P framework to engineering design are presented, with the conclusion that the P2P framework results in environmentally superior designs compared to conventional sustainable design methods. The P2P modeling approach also offers an opportunity to integrate fundamental engineering models with macro-economic equilibrium models, allowing engineering and economic policy design problems to be addressed within the same framework. As a first step towards this integration, a methodology and case