Flow boiling in microchannels has been extensively studied in the past decade. Instabilities, low critical heat flux (CHF) values, and low heat transfer coefficients have been identified as the major shortcomings preventing its implementation in practical high heat flux removal systems. A novel open microchannel design with uniform and tapered manifolds (OMM) is presented to provide stable and highly enhanced heat transfer performance. The effects of the gap height and flow rate on the heat transfer performance have been experimentally studied with water. The critical heat fluxes (CHFs) and heat transfer coefficients obtained with the OMM are significantly higher than the values reported by previous researchers for flow boiling with water in microchannels. A record heat flux of 506 Wlcrr? with a wall superheat of 26.2 °C was obtained for a gap size of 0.127 mm. The CHF was not reached due to heater power ¡imitation in the current design. A maximum effective heat transfer coefficient of 290,000Wlm^°C was obtained at an intermediate heat flux of 319Wlcm^ with a gap of 0.254 mm at 225mLlmin. The flow boiling heat transfer was found to be insensitive to flow rates between 40-333 mLlmin and gap sizes between 0.127-1.016mm, indicating the dominance of nucleate boiling. The OMM geometry is promising to provide exceptional performance that is particularly attractive in meeting the challenges of high heat flux removal in electronics cooling applications.
Temperature Cathode inlet RH Cell voltage Two-phase pressure drop Diagnostic tool a b s t r a c t Water management is a key area of interest in improving the performance of Proton Exchange Membrane fuel cells. Cell flooding and membrane dehydration are two extreme conditions arising from poor water management. Pressure drop has been recognized as a good diagnostic tool to determine the presence of liquid water in the reactant channels.Presence of liquid water in the channels increases the mass transport resistances and therefore reduces the cell performance, which is quantified by the cell voltage at a set current density. Since the two-phase pressure drop multiplier is uniquely related to the water content in the channel, it serves as a good diagnostic tool for directly predicting the cell performance. Experiments are carried out to establish the relationship between the pressure drop multiplier and cell voltage at different operating conditions. Cell temperature was varied from 30 C to 80 C and the inlet RH was varied from 0 to 95%. At the lower temperatures, a two-phase multiplier below 1.5 reduces flooding in the flow field. However, at the higher temperatures, a two-phase flow multiplier above 1.2 is preferred as it indicates the membrane remains hydrated for improved performance from the cell. The twophase pressure drop multiplier has been successfully demonstrated as a diagnostic tool to predict cell flooding and membrane dehydration.
As different research works report and daily life experiences confirm, learning models can result in biased outcomes. The biased learned models usually replicate historical discrimination in society and typically negatively affect the less represented identities. Robots are equipped with these models that allow them to operate, performing tasks more complex every day. The learning process consists of different stages depending on human judgments. Moreover, the resulting learned models for robot decisions rely on recorded labeled data or demonstrations. Therefore, the robot learning process is susceptible to bias linked to human behavior in society. This imposes a potential danger, especially when robots operate around humans and the learning process can reflect the social unfairness present today. Different feminist proposals study social inequality and provide essential perspectives towards removing bias in various fields. What is more, feminism allowed and still allows to reconfigure numerous social dynamics and stereotypes advocating for equality across people through their diversity. Consequently, we provide a feminist perspective on the robot learning process in this work. We base our discussion on intersectional feminism, community feminism, decolonial feminism, and pedagogy perspectives, and we frame our work in a feminist robotics approach. In this paper, we present an initial discussion to emphasize the relevance of feminist perspectives to explore, foresee, en eventually correct the biased robot decisions.
Increased utilization of Lithium-ion batteries for a variety of applications is driving the need for advanced simulation tools that can predict the combined structural, electrical, electrochemical, and thermal response to abuse conditions. If such simulation tools are integrated into the product development process, the resultant data has the potential to inform decisions during development and create highly optimized designs. Academic and national laboratory researchers have pioneered these models1-3, but there is currently no consensus on the required methods for multi-physics coupling or acceptable degree of homogenization. If coupling is present between the mechanical and electrical or thermal solvers, it is typically one-way and largely manually applied, which requires highly advanced users to implement due to mesh and element compatibility issues. In order to initiate a much larger investigation into the abuse response of Li-ion cells, modules, and packs, a coupled structural, electrical, and thermal simulation framework has been developed within the commercially available LS-DYNA software. The finite element model leverages a three-dimensional mesh structure that fully resolves the unit cell components. Depending on the time scale of the mechanical crush, coupling with the mechanical solver can be one-way for impact loading conditions that occur in the sub-second time scale, or two-way for continuous crush in the tens to hundreds of seconds time scale. Measurements of the resistance between unit cell layers as a function of applied pressure are reported and used to parameterize the coupling between the structural, electrical, and thermal solvers. A spatially distributed equivalent circuit model predicts the electrical response with minimal computational complexity. The thermal model provides information to schedule the electrical model parameters, while simultaneously accepting irreversible and reversible sources of heat generation. The spatially distributed models of the electrical and thermal dynamics allow for the localization of current density and corresponding temperature response to provide the necessary tool structure for predicting the onset of thermal runaway. Future work will focus on the structural material models and failure conditions required to quantitatively predict the battery crush response to a variety of loading conditions. Plans for additional multi-physics functionality within the simulation tool will also be highlighted. References: E. Sahraei, R. Hill, and T. Wierzbicki, J. Power Sources, 201, 307 – 321 (2012). E. Sahraei, M. Kahn, J. Meier, and T. Wierzbicki, RSC Adv., 5, 80369 – 80380 (2015). C. Zhang, S. Santhanagopalan, M. A. Sprague, and A. A. Pesaran, J. Power Sources, 290, 102 – 113 (2015).
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