Launch vehicle development programs have experienced significant difficulties in achieving first flight. Optimism during the initiation of these complex programs, coupled with the innovative nature of the technologies they employ, has resulted in a long list of programs unable to remain within the national means. A recent example of this challenge is the Constellation program which was canceled in 2011 due to excessive cost overruns and schedule slippage. The budgetary constraints currently placed on NASA's Space Launch System (SLS) highlights the need for a greater emphasis on affordability. Where affordability is defined in this research as the ability to remain under the mandated funding curve for all points in a system's life cycle while simultaneously meeting schedule goals given that performance requirements are met. The proposed research aims to address the gap between current practices and an affordability-centric design approach by capturing manufacturing technology effects on the affordability of the baseline vehicle concept. Historically, cost overruns and schedule slippages escalate once production begins and are only truly realized at the first launch of a system. These trends, based upon systems which leveraged traditional materials and processes, suggest a shortcoming in the ability of current practices to assess manufacturing implications during the early design phases. The advent of advanced materials and the new process required to fabricate parts from them, further challenges these practices, and threaten to exacerbate the already excessive overruns experience once production begins. Manufacturing technologies, such as composite materials, automated fabrication processes, and the use of stiffener concepts, can no longer be considered independently. This observation leads to the conclusion that improvements in vehicle affordability can only be realized by bringing manufacturing information forward into the Conceptual Design phase. The goal of this research is to support the development of affordable launch vehicles by quantitatively capturing the effects of manufacturing technology selection during Conceptual Design. A manufacturing influenced design methodology is combined with established techniques of time-phasing and risk propagation to evaluate the expected affordability of a launch vehicle baseline concept. The method is benchmarked against expected performance and affordability trends established in literature. The experiments used to build this methodology provide interesting insight into the excess risk typically carried into Preliminary Design due to a lack of the temporal nature of cost. Fundamental implications include the notion that the most expensive candidate (i.e. the highest total cost) does not correspond to the candidate with the highest annual cost insurance. Furthermore, the assessment of risk — within the traditional total cost domain — by overlaying vertical constraints onto uncertainty distributions results in the inclusion of many unaffordable candidates. The final chapter of this thesis applies the method to a relevant launch vehicle, the Exploration Upper Stage (EUS) of the SLS Block IB, which is currently in its Conceptual Design phase. This chapter compares two viable candidate manufacturing technologies based on affordability criteria established herein. The application of this methodology provides the decision maker with a significant amount of information previously unavailable and affords her additional degrees of freedom regarding appropriate Design, Development, Testing, Evaluation, and Production (DDTE&P) planning. This will ultimately enable the selection of an affordable vehicle baseline which will be robust to uncertainty in congress-appropriated funding and thus circumvent risks associated with government program cancellation.

Civil infrastructure facilities play a central role in the economic, social and political health of modern society and their safety, integrity and functionality must be maintained at manageable cost over their service lives through design and periodic maintenance. Hurricanes and tropical cyclones, tornadoes, earthquakes and floods are paramount among the potentially devastating and costly natural disasters impacting civil infrastructure. Even larger losses may occur in the future, given the population growth and economic development accompanying urbanization in potentially hazardous areas of the world. Moreover, in recent years, the effects that global climate change might have on both the frequency and severity of extreme events from natural hazards and their effect on civil infrastructure facilities have become a major concern for decision makers. Potential influences of climate change on civil infrastructure are even greater for certain facilities with service periods of 100 years or more, which are substantially longer than those previously considered in life-cycle engineering and may extend across multiple generations. Customary risk-informed decision frameworks may not be applicable to such long-term event horizons, because they tend to devalue the importance of current decisions for future generations, causing an ethical and moral dilemma for current decision-makers. Thus, intergenerational risk-informed decision frameworks that consider facility performance over service periods well in excess of 100 years and extend across multiple generations must be developed. This dissertation addresses risk-informed decision-making for civil infrastructure exposed to natural hazards, with a particular focus on the equitable transfer of risk across multiple generations. Risk-informed decision tools applied to extended service periods require careful modifications to current life-cycle engineering analysis methods to account for values and decision preferences of both current and future generations and to achieve decisions that will be sustainable in the long term. The methodology for supporting equitable and socio-economical sustainable decisions regarding long-term public safety incorporates two essential ingredients of such decisions: global climate change effect on stochastic models of extreme events from natural hazards and intergenerational discounting methods for equitable risk-sharing. Several specific civil infrastructure applications are investigated: a levee situated in a flood-prone city; an existing dam built in a strong earthquake-prone area; and a special moment resisting steel frame building designed to withstand hurricanes in Miami, FL. These investigations have led to the conclusion that risks can and should be shared across multiple generations; that the proposed intergenerational decision methods can achieve goals of intergenerational equity and sustainability in engineering decision-making that are reflective of the welfare and aspirations of both current and future generations; and that intergenerational equity can be achieved at reasonable cost.

Stormwater sewer infrastructure is at risk due to ageing, structural deterioration, population growth, and climate change. Since the consequences of the sewer system failure can adversely impact the community safety, environment and economy, a resilient infrastructure system is of essential importance. However, limited reinvestment budget and insufficient asset management practices impact the rehabilitation of urban sewerage systems. Therefore, an effective and efficient rehabilitation plan is needed to help proper investment decisions. An effective rehabilitation plan will maximize hydraulic performance while minimizing the overall failure risk within a limited budget. The current study aims to address this issue through designing a risk-informed methodology in three steps. First, the hydraulic risk index (obtained using the SWMM model) was combined with the ageing pipe index. The framework uses multi-objective optimization technique to generate solutions under specific sewerage conditions. We named this new framework as Hydraulics and Risk Combined Model (HRCM). Several scenarios including high hydraulic risk, high ageing risk, hydraulic risk and ageing risk (combined problems), and limited budget problems, are used to test the performance of the proposed methodology. The results show that the proposed model could provide a satisfactory solution. Then, in order to increase the calculation speed and improve the accuracy, sensitivity and cost-effectiveness analyses were also conducted for the proposed methodology with different algorithms. The results show that different algorithms offer various benefits. A new calculation method was offered by combining the advantages of the previous methods. Finally, a new optimization method named Phenotype Searching Method, which was enlightened by sexual selection processes, was offered. This method can enhance the selection processes to specific phenotypes (pipes) so that it can increase the convergence speed and increase the performance of the HRCM model.

Asset management within the nuclear industry has become an increasingly relevant topic as safety requirements have tightened and energy security has become more important. Asset management ensures performance and reliability in a nuclear facility by balancing costs, opportunities, and risks to get the most out of assets. Asset management processes can often be modeled as capital budgeting problems, where investments are evaluated based on costs and benefits, which establishes a link to mathematical optimization. This study addresses asset management at the Swedish nuclear power plant, Forsmark, and aims to implement an optimization model to improve the project selection related to maintenance and replacement of assets at the plant. First, the most relevant areas of nuclear asset management are identified through a comprehensive literature review. The most relevant method, identified as a mix between risk-informed asset management and capital budgeting, is then implemented to fit the prerequisites at Forsmark. Several models of different complexity are developed and the resulting stochastic model incorporates uncertainty of input variables by assuming underlying distributions. Finally, a methodology to incorporate a quantitative risk measure in the optimization is suggested through the use of conditional value at risk. Results are generated based on simulated data and illustrate the potential of implementing the method at Forsmark. / Tillgångsförvaltning inom kärnkraftsindustrin har blivit alltmer aktuellt i takt med att säkerhetskraven har skärpts och tillförlitlighet i energiproduktionen blivit viktigare. Effektiv tillgångshantering säkerställer prestanda och reliabilitet i ett kärnkraftverk genom att hitta en balans mellan kostnader, möjligheter och risker för att maximera nyttan av tillgångar. Projekturval i tillgångsförvaltningen kan ofta modelleras som ett kapitalbudgeteringsproblem, där investeringar utvärderas utifrån kostnader och uppsida, vilket påvisar en koppling till matematisk optimering. Denna studie behandlar tillgångshantering vid det svenska kärnkraftverket Forsmark och syftar till att implementera en optimeringsmodell för att förbättra projekturvalet relaterat till underhåll av tillgångar vid anläggningen. Det första steget i studien bearbetar den befintliga litteraturen inom området för att få en uppfattning av relevanta metoder. Den mest relevanta metoden identifierades som en mix mellan riskinformerad tillgångsförvaltning och kapitalbudgetering. En metod baserad på de generella principerna för dessa områden utvecklades och anpassades för de specifika förutsättningarna på Forsmark. Flera modeller av olika komplexitet utvecklades och den slutgiltiga stokastiska modellen inkorporerar osäkerhet i de mest relevanta ingångsvariablerna genom att anta sannolikhetsfördelningar. Slutligen föreslås en metod för att implementera ett kvantitativt riskmått i optimeringen genom att använda CVaR. Resultaten genereras utifrån simulerade data och illustrerar potentialen i att implementera metoden på Forsmark.

A gap exists in the methods used in industry and available in academia that prevents customers and engineers from having a voice when considering engineering risk appetite in the dynamic shaping of early-phase conceptual design trade study outcomes. Current methods used in Collaborative Design Centers either collect risk information after a conceptual design has been created, treat risk as an afterthought during the trade study process, or do not consider risk at all during the creation of conceptual designs. This dissertation proposes a risk-informed decision making framework that offers a new way to account for risk and make decisions based upon risk information within conceptual complex system design trade studies. A meaningful integration of the consideration of risk in trade studies is achieved in this framework thus elevating risk to the same level as other important system-level design parameters. Trade-offs based upon risk appetites of individuals are explicitly allowed under the framework, enabled by an engineering-specific psychometric risk survey that provides aspirational information to use in utility functions. This dissertation provides a novel framework and supporting methodologies for risk-informed design decisions and trades to be made that are based upon engineering risk appetites in conceptual design trade studies. / Graduation date: 2012