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Development and application of a microstructure dependent thermal resistor model for UO2 reactor fuel with high thermal conductivity additives

机译:高热导率添加剂的UO2反应器燃料微结构依赖热电阻模型的开发与应用

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High thermal conductivity additives are being explored to make next generation accident tolerant fuels for light water reactors (LWRs). The goal is to create composite fuels that will more effectively dissipate heat, thus lowering the high centerline temperatures that develop in current LWR fuel. These fuels can employ various additives and the fuel microstructures vary depending on the manufacturing process. In this work, a thermal resistor model is developed to quickly estimate the effective thermal conductivity of a composite with a high thermal conductivity additive. This model is unique in that it employs a parameter, the continuousness of the secondary constituent, to consider the composite microstructure in its predictions. A genetic algorithm was developed to measure a composite's continuousness. The model and algorithm are validated using data from literature from four experimental composites composed of UO2 with beryllium oxide and silicon carbide additives. The model predictions have an absolute mean error across a wide temperature range of less than 0.50 W/mK in most cases. These tools are then used to create a set of guidelines for microstructure design. (C) 2020 Elsevier B.V. All rights reserved.
机译:正在探索高热导率添加剂以使轻型水反应器(LWRS)制造下一代事故耐燃料。目标是创造将更有效地散热的复合燃料,从而降低当前LWR燃料中发展的高中心线温度。这些燃料可以采用各种添加剂,并且燃料微结构根据制造方法而变化。在这项工作中,开发了热电阻模型以快速估计具有高导热性添加剂的复合材料的有效导热率。该模型的独特之处在于它采用参数,二次成分的连续性,以考虑其预测中的复合微结构。开发了一种遗传算法来测量复合材料的连续性。使用由氧化铍和碳化硅添加剂组成的四种实验复合材料的文献中的来自文献的数据验证了模型和算法。在大多数情况下,模型预测在宽温度范围内具有小于0.50W / MK的宽温度范围的绝对误差。然后,这些工具用于创建一组微观结构设计的指导。 (c)2020 Elsevier B.v.保留所有权利。

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