Of Deep Foundation Pit Supporting Structure The Research And Application Of Optimal Design Method

With the rapid development of urban construction, economy and technoloy, the increasing foundation pit engineering is confronted with higher requirement. Consequently, these projects should not only be safe and economical but also satisfy the control requirement of surrounding environment. Therefore, the structural optimization design of foundation pit engineering is paid great attention by engineers and technicians. Based on relevant literature, the structural optimization design of foundation pit engineering which divided into two levels, supporting scheme optimization and detailed structure design, is derived in this paper. Combined with the engineering example which is optimized by optimization theory and method, the basic theory and method of supporting scheme optimization and detailed structure design are emphatically investigated.At first, the methods for the earth pressure calculation and for the design of supporting structures in deep foundation pit are analyzed in detail, and the category, function and characteristics of the supporting structures are introduced. Secondly, giving the introduction of multi-target optimizing method for the supporting scheme of deep foundation pit engineering and suggesting firstly selected patterns which is relatively systematical, finding the result of multiplicity of weight of each affect factor by Analytical Hierarchy Process and optimizing the first-selected supporting scheme by fuzzy comprehensive evaluation. This paper uses MATLAB language to design programmer of optimizing method, and its application in the actual engineering has been proved to gain superior decision result. A new method-Genetic Algorithm is applied to optimization design on the best scheme and the theory and the implementation of the genetic algorithms are discussed in detail. An optimization mathematic model for cement-soil retaining wall has been set up. Genetic Algorithm tool of MATLAB is used to optimization design, and Geo-slope is used to analyse the result. It is proved that the Genetic Algorithm is good in the optimization design, and it brings better economic and social benefits.