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相关概念视频

Turnover Number and Catalytic Efficiency01:19

Turnover Number and Catalytic Efficiency

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The turnover number of an enzyme is the maximum number of substrate molecules it can transform per unit time. Turnover numbers for most enzymes range from 1 to 1000 molecules per second. Catalase has the known highest turnover number, capable of converting up to 2.8×106 molecules of hydrogen peroxide into water and oxygen per second. Lysozyme has the lowest known turnover number of half a molecule per second.
Chymotrypsin is a pancreatic enzyme that breaks down proteins during digestion....
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相关实验视频

Updated: May 5, 2026

Combustion Characterization and Model Fuel Development for Micro-tubular Flame-assisted Fuel Cells
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使用修改的火算法确定固体氧化物燃料电池的最佳参数.

Rahul Khajuria1, Mahipal Bukya2, Ravita Lamba3

  • 1Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur, India.

Scientific reports
|September 28, 2024
PubMed
概括
此摘要是机器生成的。

一个修改的消防算法 (MFHA) 准确地识别了固体氧化物燃料电池 (SOFC) 模型参数. 这种方法通过提供精确的参数估计来提高SOFC能源系统设计的性能.

关键词:
修改过的火算法 修改过的火算法参数识别 参数识别极化曲线的两极化曲线固体氧化物燃料电池的燃料电池是什么统计分析 统计分析

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科学领域:

  • 能源系统工程 能源系统工程
  • 计算科学 计算科学
  • 电化学 电化学 电化学

背景情况:

  • 准确的数学模型对于设计结合固体氧化物燃料电池 (SOFC) 的强大的能源系统至关重要.
  • 在SOFC模型中识别未知参数对于可靠的性能预测和系统优化至关重要.
  • 现有的方法可能缺乏复杂的SOFC参数估计所需的效率或准确性.

研究的目的:

  • 提出和评估一个修改的消防算法 (MFHA) 准确确定SOFC数学模型的未知参数.
  • 评估MFHA在商用圆柱形SOFC和5kW动态堆估计参数方面的性能.
  • 为了比较MFHA的有效性与原来的消防算法 (FHA) 和其他已建立的算法.

主要方法:

  • 针对SOFC参数识别而定制的修改过的消防算法 (MFHA) 的开发.
  • 在四个不同的温度 (1073 K到1273 K) 上,将MFHA应用于西门子的圆柱形SOFC模型.
  • 在各种压力和温度下,在96个细胞,5千瓦的动态SOFC堆中实施MFHA进行参数估计.

主要成果:

  • 对于圆柱状细胞,MFHA 实现了非常低的平方误差 (SSE) 总和,最小的 SSE 值低至 1.03E-05.
  • 对于5千瓦的堆,MFHA在不同的温度和压力下给出了1.18E-03到6.00E-02之间的SSE值.
  • 在这两个案例研究中,MFHA在现有算法中表现出优越或可比的性能.

结论:

  • 修改后的火算法 (MFHA) 是一种高精度和高效的方法,用于识别固体氧化物燃料电池数学模型中的未知参数.
  • MFHA在各种SOFC配置中的成功应用凸显了其强度和改善SOFC能源系统设计的潜力.
  • 拟议的MFHA为研究人员和工程师提供了一个有价值的工具,他们致力于SOFC建模和优化.