Huang, Y (2010) Sustainable infrastructure system modeling under uncertainties and dynamics. PhD thesis, University of California, Davis, USA.
Abstract
Infrastructure systems support human activities in transportation, communication, water use, and energy supply. The dissertation research focuses on critical transportation infrastructure and renewable energy infrastructure systems. The goal of the research efforts is to improve the sustainability of the infrastructure systems, with an emphasis on economic viability, system reliability and robustness, and environmental impacts. The research efforts in critical transportation infrastructure concern the development of strategic robust resource allocation strategies in an uncertain decision-making environment, considering both uncertain service availability and accessibility. The study explores the performances of different modeling approaches (i.e., deterministic, stochastic programming, and robust optimization) to reflect various risk preferences. The models are evaluated in a case study of Singapore and results demonstrate that stochastic modeling methods in general offers more robust allocation strategies compared to deterministic approaches in achieving high coverage to critical infrastructures under risks. This general modeling framework can be applied to other emergency service applications, such as, locating medical emergency services. The development of renewable energy infrastructure system development aims to answer the following key research questions: (1) is the renewable energy an economically viable solution? (2) what are the energy distribution and infrastructure system requirements to support such energy supply systems in hedging against potential risks? (3) how does the energy system adapt the dynamics from evolving technology and societal needs in the transition into a renewable energy based society? The study of Renewable Energy System Planning with Risk Management incorporates risk management into its strategic planning of the supply chains. The physical design and operational management are integrated as a whole in seeking mitigations against the potential risks caused by feedstock seasonality and demand uncertainty. Facility spatiality, time variation of feedstock yields, and demand uncertainty are integrated into a two-stage stochastic programming (SP) framework. In the study of Transitional Energy System Modeling under Uncertainty, a multistage stochastic dynamic programming is established to optimize the process of building and operating fuel production facilities during the transition. Dynamics due to the evolving technologies and societal changes and uncertainty due to demand fluctuations are the major issues to be addressed.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Fan, Y |
| Uncontrolled Keywords: | accessibility; optimization; reliability; renewable energy; sustainability; uncertainty; communication; decision making; programming; resource allocation; risk management; strategic planning; Singapore; case study; environmental impact |
| Index terms: | strategy, renewable energy infrastructure, society, renewable energy, preference, environmental impact, programming, mitigation, decision-making, variation, case study, renewable energy system, Singapore, accessibility, resource allocation, human activity, energy distribution, dissertation, critical infrastructure, modelling, risk management, strategic planning, dynamics, transportation infrastructure, energy system, dynamic programming |
| Subjects: | research dissemination and communication, data collection methods, risk assessment, environmental impact, programming, analytical methods, resource management, energy systems, decision-making and reasoning, algorithms, inclusive design, management, financial risk, Geography, contractual condition, sociology, decision analysis, systems engineering, communities and social development, infrastructure and transport systems |
| Topics: | Engineering Principles, Geographical Context, Risk Management, Sustainability, Digital Applications, Design Practice, Contract Administration, Site Management, Business Strategy, Cost Management, Research Practice, Stakeholder Management |
| Descriptive scope: | 3 PCE |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here