基于遗传算法的隧道光面爆破参数优化模型研究
Research on Optimization Model of Tunnel Smooth Blasting Parameters Based on Genetic Algorithm
张慰龙 1罗西森1
作者信息
- 1. 中铁建大桥工程局集团第五工程有限公司,四川 成都 610500
- 折叠
摘要
隧道光面爆破是一种控制爆破技术,能够保持新壁面平整而不受明显破坏.提出了一种基于遗传算法的隧道光面爆破参数优化模型,该模型以隧道光面爆破效果的综合评价函数为目标函数,以隧道开挖断面尺寸、岩性等级、地质条件等为约束条件,以周边孔间距、光爆层厚度、装药量等为决策变量,通过选择、交叉、变异等操作,不断产生新的个体,并根据适应度函数评价个体的优劣,最终得到最优或近似最优的隧道光面爆破参数.通过算例分析,验证了该模型的有效性和可行性,为隧道工程提供了合理且优化的光面爆破参数,提高了隧道质量和安全性.
Abstract
Tunnel smooth blasting is a controlled blasting technique that can keep the new wall surface smooth and free from obvious damage.A tunnel smooth blasting parameter optimization model based on genetic algorithm is proposed,which takes the comprehensive evaluation function of tunnel blasting effectiveness as the objective func-tion,with constraints such as tunnel excavation section dimensions,rock mass classification,and geological condi-tions.The decision variables include the spacing between peripheral blastholes,blast layer thickness,and explosive charge quantity.Through operations such as selection,crossover,and mutation,new individuals are continuously gen-erated.Individuals are evaluated based on their fitness function,ultimately obtaining the optimal or near-optimal tunnel blasting parameters.Through the example analysis,the validity and feasibility of the model are verified,which provides reasonable and optimized smooth blasting parameters for tunnel engineering,and improves the quality and safety of tunnel.
关键词
隧道光面爆破/遗传算法/参数优化/适应度函数Key words
tunnel smooth blasting/genetic algorithm/parameter optimization/fitness function引用本文复制引用
出版年
2024
NETL
NSTL
万方数据