基于无网格的模拟优化模型的比较分析与地下水修复的元启发算法进行比较分析
1Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai, 400076, India.
Scientific reports
|October 6, 2025
概括
一个新的模拟优化框架有效地设计了具有成本效益的地下水整治方案. 它集成了先进的算法,以最大限度地降低成本,并优化对受污染的含水层的井位置.
科学领域:
- 环境工程 环境工程
- 计算式水文地质学
- 优化技术 优化技术
背景情况:
- 地下水污染给环境和经济带来了重大挑战.
- 现有的整治策略往往缺乏成本效益和最佳设计.
- 模拟-优化 (SO) 框架为有效的整治规划提供了一个有希望的方法.
研究的目的:
- 为具有成本效益的地下水整治设计开发一个强大的SO框架.
- 整合无网状局部彼得罗夫·加勒金 (MLPG) 方法与用于增强模拟的元启发算法.
- 在和处理 (PAT) 计划中优化提取率和井位置.
主要方法:
- 结合地下水流量和运输模拟使用MLPG方法.
- 将MLPG与鱼优化算法 (WOA),鱼优化 (AO),金子优化 (GJO) 和差异进化 (DE) 的集成.
- 开发的SO模型 (MLPG-WOA,MLPG-AO,MLPG-GJO,MLPG-DE) 应用于假设和现场类型的含水层案例研究.
主要成果:
- 所有的SO模型都成功地在允许的污染限度内设计了修复策略.
- MLPG-WOA为假设的含水层确定了一种具有成本效益的单井解决方案 (INR 4,115,238).
- MLPG-DE确定了田式水库的最佳九井战略 (INR 145,072,081).
- 在这两项案例研究中都确定了最佳井位区域.
结论:
- 拟议的SO框架提供了高效可靠的地下水整治设计.
- 基于MLPG的SO模型提供优势,例如对初始估计的最小敏感性和快速收.
- 这些模型可以作为现有的PAT整治模型的有效替代品.
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