Physically Motivated Water Modeling in Control-Oriented Polymer Electrolyte Membrane Fuel Cell Stack Models

Polymer electrolyte membrane fuel cells (PEMFCs) are prone to membrane dehydration and liquid water flooding, negatively impacting their performance and lifetime. Therefore, PEMFCs require appropriate water management, which makes accurate water modeling indispensable. Unfortunately, available control-oriented models only replicate individual water-related aspects or use oversimplistic approximations. This paper resolves this challenge by proposing, for the first time, a control-oriented PEMFC stack model focusing on physically motivated water modeling, which covers phase change, liquid water removal, membrane water uptake, and water flooding effects on the electrochemical reaction. Parametrizing the resulting model with measurement data yielded the fitted model. The parameterized model delivers valuable insight into the water mechanisms, which were thoroughly analyzed. In summary, the proposed model enables the derivation of advanced control strategies for efficient water management and mitigation of the degradation phenomena of PEMFCs. Additionally, the model provides the required accuracy for control applications while maintaining the necessary computational efficiency.

Effect of SEN immersion depth on mold flow profile and slag entrapment during continuous casting of steel

Mold flux entrapment during continuous casting of steel contributes to both surface and sub-surface defects in the final product. Continuous casting operating parameters such as casting speed, SEN immersion depth, SEN port geometry, argon flow, and mold EMS significantly affect the mold flow conditions and flow profile. During continuous casting operation, SEN immersion depth is continuously varied to avoid localized erosion of SEN, and it impacts the flow dynamics in the mold. In the present work, water modeling studies were carried out for a wide range of mold widths (1200-1800 mm) and casting speeds (0.8-1.4 m/min) on a 0.5 scaled down water model to optimize casting speed for different combinations of SEN immersion depth and mold width. Results from water modeling were further validated using nail board studies in the actual plant. A safe operating matrix was identified from these experiments to avoid mold slag entrapment during continuous casting.

Model Informed Data Collection in Coupled Human-Water Systems: An Exploratory Application of a Hydrological and Agent-Based Model

<p>Hydrological systems in the Anthropocene have shown substantial shifts from their natural processes due to human modifications. Consequently, deploying coupled human-water modeling is a critical tool to analyze observed changes. However, the development of socio-hydrological models often requires extensive qualitative data collection in the field and analysis. Despite the advances in developing inter-disciplinary methodologies in utilizing qualitative data for coupled human-water modeling, there is a need to identify influential parameters in these systems to inform data collection. Here, we present an exploratory socio-hydrological model to systemically investigate the feedback system of public infrastructure providers, resource users, and the dynamics of water scarcity at the catchment scale to inform data collection and analysis in the field. Specifically, we propose a novel socio-hydrological model by employing and integrating a top-down hydrological model and an extension of Aqua.MORE Model (an Agent-Based Model designed to simulate dynamics of water supply and demand). Specifically, we model alternate behavioral theories of human decision-making to represent the agents’ behavior. Then, we perform sensitivity analysis techniques to identify key socio-economic and behavioral parameters affecting emergence patterns in a stylized human-dominated catchment. We apply the proposed methodology to the Lake Mendocino Watershed in Northern California, US. The results will potentially point which parameters are influential and how they could be mapped to a particular interview or survey question. This study will help us to identify features of decision-making behavior for inclusion in fieldwork, that be might be overlooked in the absence of the proposed modeling. We anticipate that the proposed approach also contributes to the current Panta Rhei Research Initiative of the International Association of Hydrological Sciences (IAHS) which aims at improving the interpretation of the hydrological processes governing the socio-hydrological systems by focusing on their changing dynamics in connection with rapidly changing human systems.</p>