<div>With the rapid development of clean energy technologies, various bottlenecks on supplies of related critical materials emerged. Since supply chains of critical materials often involved with multiple layers of markets with different characteristics, to better identify bottlenecks and increase critical material availability, it is vital to have better understanding and projection on these markets.</div><div>Agent-based modeling is a bottom-up approach that can imitate heterogenous objects in a changing environment. Therefore, it is an excellent tool to simulate markets with fierce competition and fast revolution. This work demonstrates the application of agent-based modeling by discussing three different topics related to critical material demand and supply induced by clean energy products.</div><div>The first application focused on LED residential lighting market. LED lighting market grew rapidly and introduced potential demand on several critical materials including indium. The work modeled consumers as heterogenous and irrational agents in network purchasing new bulbs based</div>

<p>The aging water infrastructure system in the United States has posed considerable hindrance to policy-makers as they seek to provide safe, reliable, and clean drinking water for communities. The deterioration of the physical water infrastructure negatively affects the economics of water utilities and can lead to increases in water rates for consumers, so that utilities can recover the financial losses. However, the dynamics emerging from the interactions among changes in water service reliability, water-rates, consumer behavior (with respect to water consumption and willingness to support water-rate changes in response to changes in water rates, and water utility economics, are still unknown factors in the management of water infrastructure systems. </p> <p>The overarching objective of this dissertation is the creation and demonstration of the dynamics of coupled human and water infrastructure systems under conditions of water main breaks and water-rate increases. First, using water-main break data for a 21-year period from two U.S. cities in the Great Lakes region, the dissertation demonstrates a methodology to estimate the system-wide monthly frequency of water main breaks as a function of a number of explanatory variables. Using a random-parameters negative-binomial approach, the statistical estimations show that pipe diameters, average pipe age, distribution of pipe age, pipe material, time of year, and mean monthly temperature all have a significant impact on monthly water main break frequencies. The results can assist asset managers in quantifying the effect of factors may have on the likelihood of water main breaks, as well as in making cost-effective decisions regarding pipe renewal.</p> <p>Next, by incorporating qualitative survey data and using quantitative econometric methods, consumer behaviors in responses to the water-rate increases, and based on perceptions of water service reliability and quality in a Midwestern U.S. city was evaluated. Using a multivariate binary probit approach, the results provide insights as to how individuals are likely to respond to water-rate increases based on the reliability of current water services and the quality of the supplied water. The outputs of the econometric enable utility managers to better understand the behavior of consumers under different rate conditions and help water utilities in their long-term and short-term financial analyses.</p> <p>Finally, the aforementioned two components are integrated into the interdependency analysis to evaluate the interactive effects of features of the physical water infrastructure (pipeline characteristics, water and associated energy losses, and the revenue loss for water utilities) and the behavior of stakeholders (water utilities and consumers). The developed hybrid system dynamics and agent-based model examines interdependencies between the physical water infrastructure, the water utility, and the water consumers to explore possible emergent behavior patterns of water users during water rate increases over time. The model is demonstrated over the 2001–2010 period on a case study city with a large water distribution system that includes 4,000 miles of pipeline and nine water treatment plants serving a population of 863,000. This model was then verified and validated throughout the development of simulation models and included the following steps: 1) data validity, 2) conceptual model validity, 3) computerized model validity, and 4) operational validity. The results suggest the simulated behavior of the model was reasonable and the output of the simulation model regrading water main break frequency, amount of water and associated energy losses, generated revenue, and payoff periods for implementing proactive maintenance strategies had the accuracy required for the model’s intended purpose. </p> <p>The framework developed in this doctoral study can be applied to different size classifications of cities, as well as different classifications of utility companies (such as electricity and gas) by updating the parameters in the model to reflect the characteristics of the infrastructure system components. The distinctive methodological approach in this doctoral work could capture the emergent behaviors of human-water infrastructure interactions such as the impact of increasing water-rates on residential consumers, the impact of water price elasticity cascading into the water utility revenue, and the impact of residential consumers’ water consumption on water utility revenues. In conclusion, the results of this doctoral research can assist asset managers in understanding their systems, identify pathways for growing revenue through reducing non-revenue water and increasing water-rates, and implementing a proactive pipeline asset management program towards the provision for safe, reliable, and clean drinking water.</p>