A Search Of Slope Critical Sliding Surface Based On Bacterial Foraging Optimization Algorithm

In recent years,with the rapid development of the national economy and the continuous construction of infrastructure construction,many engineering safety problems have gradually emerged and attracted much attention.For a long time,the slope stability analysis has been an important research topic in the field of geotechnical engineering,and the slope critical sliding surface search is a key link in the slope stability analysis,which is an important basis for the slope structure design,safety assessment and the selection of reinforcement measures.However,the safety factor function is affected by soil parameters,load conditions,variable freedom and other factors,and often has many peaks,which tends to cause local convergence,so that the task of obtaining the most dangerous slip surface becomes very difficult.Thanks to the vigorous development of computer technology,a batch of group intelligent algorithms with higher optimization performance have emerged,which provides a new exploration idea for solving the optimization problems of nonlinear,high-dimensional and multi-peak.In order to deal with the above problems,the bacterial foraging optimization algorithm and the slip surface safety factor calculation and analysis model are combined through Matlab numerical analysis software to establish a new method of slope critical sliding surface search.The specific research method is as follows:(1)From the generation of geometric reasonable sliding surface and the execution efficiency,comprehensive elaboration and comparative analysis of advantages and disadvantages of three design variables,choose a more reasonable decision variable,expand the scope of the definition of “pohu”,design the reasonable judgment and eliminate the solution of “pohu”,successfully avoid more nonsense circular arc and non-circular arcs.(2)Based on the simplified Bishop method limit balance analysis theory or the simplified Janbu method limit balance analysis theory,designed a can solve homogeneous and heterogeneous slope any potential critical sliding surface of safety coefficient calculation method,the methed gives some solutions to the difficulties of program establishment,can through the Matlab numerical analysis software specific program code writing.(3)Improved bacterial foraging optimization algorithm: firstly,for the chemotactic operator,the teaching and learning optimization idea is introduced to improve the randomness of the algorithm search efficiency;design the adaptive swimming step size to replace the fixed step length to improve the search accuracy of the algorithm;add the good gene crossing strategy to improve the phenomenon of "two steps forward,one step back";secondly,for breeding operator,the distribution estimation algorithm based on Gaussian distribution to enhance the population diversity and avoid local convergence;finally,the adaptive migration probability is designed to solve the phenomenon of the optimal solution loss.After completing the improvement of the standard algorithm,the three common test functions are used to verify the effectiveness of the improvement strategy of the bacterial foraging optimization algorithm.(4)The bacterial foraging optimization algorithm before and after the improvement is applied to the solution of slope critical sliding surface in 3 to classical examples and the stability analysis of embankment slope engineering examples.The performance and optimization ability of the algorithm in dealing with such problems are explained in detail.The results show that: For the optimization problems with different structures and different dimensions,the optimization effect of the improved bacterial foraging optimization algorithm is far better than that of the standard bacterial foraging optimization method,indicating that the improved strategy for the standard algorithm is reliable and effective;In dealing with relatively simple homogeneous slope critical sliding surface search problem,the standard bacterial foraging optimization algorithm is feasible,but when the slope section complexity increases,the search difficulty will also increase,so that the algorithm needs to carry out several operations to determine the optimal solution,or it cannot get rid of local convergence,resulting in search failure;Compared with the standard bacterial foraging optimization algorithm,the improved algorithm has stronger global optimization performance,when dealing with complex slopes,it can not only effectively avoid the occurrence of "premature stagnation" phenomenon,but also has higher convergence speed and search accuracy.Exploring the application of bacteria foraging optimization algorithm in the search of slope critical sliding surface has opened up a new way to solve this kind of problem,so it has a certain theoretical significance.The preliminary verification shows that this optimization method is more robust and has a broad application prospect.Figure 49 table 13 reference 54...