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Grain Temperature-Dependent Thermal Properties Estimation Using FI-QPSO Algorithm

机译:使用FI-QPSO算法谷物温度依赖性热性能估计

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摘要

A hybrid fuzzy inference-quantum particle swarm optimization (FI-QPSO) algorithm is developed to estimate the temperature-dependent thermal properties of the grain. The fuzzy inference scheme is established to determine the contraction-expansion coefficient according to the aggregation degree of particles. The heat transfer process in the grain bulk is solved using the finite element method, and the estimation task is formulated as an inverse problem. Numerical experiments are performed to study the effects of the surface heat flux, measurement errors, and the individual space on the estimation results. Comparison with the quantum particle swarm optimization (QPSO) algorithm and conjugate gradient method (CGM) is also conducted, and it shows the validity of the estimation method established in this paper.
机译:开发了一种混合模糊推理 - 量子粒子群综合优化(FI-QPSO)算法以估计谷物的温度依赖性热性能。 建立模糊推理方案以根据颗粒的聚集度确定收缩膨胀系数。 使用有限元方法解决晶粒体中的传热过程,并且将估计任务制定为逆问题。 进行数值实验以研究表面热通量,测量误差和各个空间对估计结果的影响。 还进行了与量子粒子群优化(QPSO)算法和共轭梯度法(CGM)的比较,并显示了本文建立的估计方法的有效性。

著录项

  • 来源
    《Journal of Heat Transfer》 |2021年第9期|093501.1-093501.7|共7页
  • 作者单位

    Institute of Higher Education Chongqing Medical and Pharmaceutical College Chongqing 4001331 China;

    School of Mechanical and Power Engineering Chongqing University of Science and Technology Chongqing 401331 China;

    School of Mechanical and Power Engineering Chongqing University of Science and Technology Chongqing 401331 China;

    School of Mechanical and Power Engineering Chongqing University of Science and Technology Chongqing 401331 China;

    School of Mechanical and Power Engineering Chongqing University of Science and Technology Chongqing 401331 China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    grain; thermal properties; estimation; fuzzy inference; QPSO;

    机译:粮食;热性能;估计;模糊推理;QPSO;

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