在催化系统中非线性反应-扩散动力学的启发式计算方法
Saad Jamshed1, Muhammad Shoaib1, Hijaz Ahmad2,3,4
1Department of Physics, AIR University, PAF Complex, E-9, Islamabad, 44000, Pakistan.
Scientific reports
|October 29, 2025
概括
本研究介绍了一种混合遗传算法 (GA) 和调配方法,用于解决化学工程扩散反应系统中的Lane-Emden方程. 该方法有效地模拟了各种几何形状和参数的度概况.
科学领域:
- 化学工程是化学工程的重要组成部分.
- 数学建模的数学建模
- 反应动力学反应动力学
背景情况:
- 莱恩-埃姆登方程对于模拟热量和质量转移以及化学反应等现象至关重要.
- 在化学工程中,了解催化剂和生物催化剂系统中的度概况至关重要.
研究的目的:
- 在扩散反应系统中使用一种新的混合方法解决莱恩-埃姆登方程.
- 研究关键参数对圆柱形和球形几何形状中的度概况的影响.
主要方法:
- 开发了一种混合方法,结合了配合技术和遗传算法 (GA) 的混合方法.
- 该方法用于分析利用催化剂和生物催化剂模型的扩散反应系统.
- 系统评估了蒂尔模量 (ρ),无维激活能量 (μ) 和无维反应热量 (α) 的影响.
主要成果:
- 基于混合GA的方法成功地解决了扩散反应系统的Lane-Emden方程.
- 对于催化剂和生物催化剂系统,有效地建模了度概况.
- 该方法在广泛的参数值 (低和高 ρ,μ,α) 中显示出有效性.
结论:
- 拟议的混合遗传算法方法为化学工程中的Lane-Emden方程提供了一个强大的解决方案.
- 这种方法解决了以前技术的局限性,并突出了GA在复杂的扩散反应建模中的力量.
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