Highly thermal integrated heat pipe-solid oxide fuel cell

Zeng, Hongyu; Wang, Yuqing; Shi, Yixiang; Cai, Ningsheng; Yuan, Dazhong

doi:10.1016/j.apenergy.2018.02.040

Cited by 42 publications

(14 citation statements)

References 42 publications

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“…Regarding tubular SOFCs, an annular heat pipe design decreased the temperature gradient by 10 • C/cm [93]. It further demonstrated that the reduction could significantly increase the power density.…”

Section: Cryogenic Pumpsmentioning

confidence: 91%

Thermal Management System Architecture for Hydrogen-Powered Propulsion Technologies: Practices, Thematic Clusters, System Architectures, Future Challenges, and Opportunities

et al. 2022

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The thermal management system architectures proposed for hydrogen-powered propulsion technologies are critically reviewed and assessed. The objectives of this paper are to determine the system-level shortcomings and to recognise the remaining challenges and research questions that need to be sorted out in order to enable this disruptive technology to be utilised by propulsion system manufacturers. Initially, a scientometrics based co-word analysis is conducted to identify the milestones for the literature review as well as to illustrate the connections between relevant ideas by considering the patterns of co-occurrence of words. Then, a historical review of the proposed embodiments and concepts dating back to 1995 is followed. Next, feasible thermal management system architectures are classified into three distinct classes and its components are discussed. These architectures are further extended and adapted for the application of hydrogen-powered fuel cells in aviation. This climaxes with the assessment of the available evidence to verify the reasons why no hydrogen-powered propulsion thermal management system architecture has yet been approved for commercial production. Finally, the remaining research challenges are identified through a systematic examination of the critical areas in thermal management systems for application to hydrogen-powered air vehicles’ engine cooling. The proposed solutions are discussed from weight, cost, complexity, and impact points of view by a system-level assessment of the critical areas in the field.

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Section: Cryogenic Pumpsmentioning

confidence: 91%

Thermal Management System Architecture for Hydrogen-Powered Propulsion Technologies: Practices, Thematic Clusters, System Architectures, Future Challenges, and Opportunities

et al. 2022

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“…For the two-phase frictional pressure drop, the homogeneous model is used. Therefore, the calculation process is similar Equation (11) and Equation (12), in which the two-phase Reynold number should be used.…”

Section: Flow and Momentum Conservationmentioning

confidence: 99%

“…With heat pipes, the ceramic plant can save about 110 600 Sm 3 of natural gas per year. Zeng et al 11 integrated heat pipes in solid oxide fuel cells. The temperature gradient in fuels decreases from 31 to 13 K/cm and the power output is improved by 65%.…”

Section: Introductionmentioning

confidence: 99%

Modeling and numerical investigation on the effects of filling ratio in a large separate heat pipe loop

Kuang

Wang

2021

Intl J of Energy Research

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Large separate heat pipe is a potential selection to establish the passive cooling system to remove decay heat from the Spent Fuel Pool. In this system, heat pipes are expected to work properly and effectively for a long time without human intervention. Due to the physical dimensions and structures, flow patterns, and fluid distribution in large-scale heat pipes differ from those in conventional ones. Based on the condensation flow patterns, a flow condensation model is presented. Then, a separate heat pipe model considering filling ratio effects is developed. Using the new model, the mean absolute errors of simulation are 5.5% (water), 5.1% (ammonia), and 4.3% (R134a). While in the conventional condensation model, these errors are 29.4%, 9.7%, and 10%. It is found

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“…[1][2][3] Therefore, 310s stainless steel can be used in various industrial fields as a supercritical water reactor (SWR), molten carbonate fuel cell (MCFC), polymer electrolyte membrane fuel cell (PEMFC), solid oxide fuel cell (SOFC), solar power, and hydrogen energy services. [1][2][3][4][5][6][7] 310s stainless steel is often applied in high temperature environments. For instance, the standard operating temperature for a molten carbonate fuel cell (MCFC) is 650℃.…”

Section: Introductionmentioning

confidence: 99%

“…[3] A working temperature of 600℃-1000℃ is considered to be appropriate for the solid oxide fuel cell. [6] Therefore, it is crucial to study the deformation behavior and flow stress variation during the deformation of 310s stainless steel. However, the existing literature lacks experimental research into deformation and modeling of the flow stress of 310s stainless steel under the aforementioned temperature range.…”

Section: Introductionmentioning

confidence: 99%

Regime-Switched Neural Networks: Flow Stress Modeling Strategy of 310s Stainless Steel During Hot Deformation

Cho

Song

2021

IEEE Access

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This study examines the high temperature deformation and constitutive modeling of flow stress for 310s stainless steel. To this end, hot tensile experiments were conducted under the temperatures of 700℃ and 800℃ at the strain rates of 0.0002/s, 0.002/s, and 0.02/s. Flow stress was modeled using the Arrhenius type constitutive equation and neural network approach. Specifically, Regime-Switched Neural Networks (RSNN), a set of neural networks with switching, has been newly proposed as a better predictive model for flow stress. The modeling performance of the RSNN model was evaluated through a comparison with traditional Arrhenius-type constitutive equations and the single neural network model. The results showed that the accuracy of the proposed RSNN was substantially higher than those of the existing Arrhenius-type equations, and the prediction performance was therefore significantly improved. In addition, the accuracy of the proposed RSNN was improved by approximately more than 24% in comparison with the existing global model-a single neural network-thus confirming the superiority of the proposed switching model. INDEX TERMS 310s stainless steel, Artificial neural network, Constitutive modelingThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.

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Highly thermal integrated heat pipe-solid oxide fuel cell

Cited by 42 publications

References 42 publications

Thermal Management System Architecture for Hydrogen-Powered Propulsion Technologies: Practices, Thematic Clusters, System Architectures, Future Challenges, and Opportunities

Thermal Management System Architecture for Hydrogen-Powered Propulsion Technologies: Practices, Thematic Clusters, System Architectures, Future Challenges, and Opportunities

Modeling and numerical investigation on the effects of filling ratio in a large separate heat pipe loop

Regime-Switched Neural Networks: Flow Stress Modeling Strategy of 310s Stainless Steel During Hot Deformation

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