基于启发式算法的悬臂式挡土墙尺寸优化及参数分析

发布时间：2018-04-18 23:13

本文选题：悬臂式挡土墙 + 尺寸优化　；参考：《湖北工业大学》2017年硕士论文

【摘要】：悬臂式挡土墙结构在工程中被普遍使用,但传统的trial-and-error设计方法非常依赖设计师的经验,且远称不上优化。随着国家正在逐步建设遍布全国的交通网,在“十三五计划”中提出推进“一带一路”建设,交通基础建设被摆在了很重要的位置,悬臂式挡土墙最优化设计不仅能保证挡土墙建设的安全性,而且具有较强经济性。首先,在现有的悬臂式挡土墙研究、土压力理论计算和群智能优化算法发展的基础上,通过选取9个尺寸设计变量来描述悬臂式挡土墙不同构造,以墙体每米的结构造价作为为目标函数,以结构尺寸限制和挡墙稳定性条件为约束条件,利用内点罚函数处理约束条件,建立了悬臂式挡土墙结构的尺寸约束最优化模型,编制了python优化程序。然后,结合一个工程实际问题,分别采用常规的悬臂式挡土墙设计方法与采用启发式算法—遗传算法(GA)、粒子群算法(PSO)、模拟退火(SA)—智能设计方法对悬臂式挡土墙最优化模型进行了求解,通过计算该模型所花费的时间和最终结果的优劣,得出常规设计中的用钢量是启发式算法设计用钢量的2~3倍,常规设计中单位长度最低造价是启发式算法设计单位长度最低造价的两倍,启发式算法可有效的应用于悬臂式挡土墙的尺寸最优化智能设计中,同时对比了各个算法的可行性和效率性。最后,利用可行且高效的求解了悬臂式挡土墙最优化模型的计算程序,通过只单独选取一个参数进行分析,其他参数保持不变,对比分析了悬臂式挡土墙优化设计结果对有效内摩擦角、地表载荷、填土重度和基底摩擦系数变化的灵敏度,得出悬臂式挡土墙造价对地表载荷的变化最敏感,对内摩擦角与填土重度较为敏感,对基底摩擦系数最不敏感。
[Abstract]:Cantilever retaining wall structure is widely used in engineering, but the traditional trial-and-error design method is very dependent on the designer's experience, and is far from optimal. As the country is gradually building throughout the transportation network, in the "13th Five-Year plan" put forward "The Belt and Road construction, traffic infrastructure construction is placed in a very the important position of the cantilever retaining wall optimization design can not only ensure the safety of the retaining wall construction, but also has a strong economy. Firstly, the research on the existing cantilever retaining wall, foundation soil pressure calculation and swarm intelligent optimization algorithms on the development, through the selection of 9 design variables to describe the different structure of cantilever retaining wall and as the objective function is the cost per meter of wall structure, the structure size limit and the stability of retaining wall as the constraint condition, the internal penalty function and constraints , built the cantilever retaining wall structure size optimization model, a python optimization program. Then, combined with a practical engineering problem, respectively with conventional cantilever retaining wall design method and a heuristic algorithm - genetic algorithm (GA), particle swarm algorithm (PSO), simulated annealing (SA) - intelligent the design method for solving optimization model of cantilever retaining wall, through the model time and the final result, the conventional design of steel consumption is 2~3 times the amount of steel the heuristic algorithm design, the conventional design of unit length of the minimum cost is two times the minimum cost per unit length heuristic algorithm design. The design of Intelligent Heuristic Algorithm for size optimization applied to the cantilever retaining wall, and compared the feasibility and efficiency of the proposed algorithm. Finally, the use of feasible and efficient To solve the calculation procedure of cantilever retaining wall optimization model, through the analysis of only one parameter is selected, the other parameters remain unchanged, comparative analysis of the cantilever retaining wall optimization design results of the effective internal friction angle, surface load, friction coefficient and sensitivity of severe basal change fill, obtained the most sensitive cantilever retaining wall to change cost the surface load, angle and filling are sensitive to severe internal friction, the friction coefficient is not sensitive to the substrate.

【学位授予单位】：湖北工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU476.4

【相似文献】