# Optimization of Pile Driver Frame Based on Sensitivity Analysis
## 4 Optimized Design of Structures  
### Sensitivity Analysis  
The mass of the large body skeleton of a pile driver is related to the mass of each of the thin plates that make up its structure. For thin slabs, the dimensional properties that affect their mass are dominated by the thickness of the slabs. Therefore, the sensitivity analysis of the bulk skeleton structure to the thickness of each slab is the main consideration. The results of the sensitivity calculation are typically derived from the design of experiment analysis [19]. The experimental factors that have a big effect on the performance of the skeleton structure can be obtained by screening from several design variables. The sensitivity calculation method can be used to achieve a reasonable allocation of materials, so as to improve the light weight of the large body structure. The influence of the change of the design parameters of the large body skeleton structure on the performance and extent of the large body structure are quantitatively studied. Then, the parameters that are most sensitive to the response of the large body structure performance in the optimization design process will be screened out. In turn, the optimal range of variables for optimal design is obtained, and the optimal design variables are further extracted. The sensitivity analysis of the large body structure of the pile driver in the most dangerous working conditions involves the large body strength, stiffness and total mass of the large body structure of the pile driver. Considering that the large body structural members are all thin steel plates, the thickness of large body plates is selected as the structural design variable. Sensitivity analysis is performed for the maximum stress at the nodes of the large body structure, the maximum displacement, and the mass of the large body skeleton of the pile driver. Design of experiment is computed analytically using an iterative approach, and for experiments, the maximum and minimum values of the design variables, that is, the upper and lower limits, must be determined. After consulting with relevant technical experts, R\({}_{1}\) is taken as between 0.03 m and 0.05 m, R\({}_{2}\) is taken as between 0.02 m and 0.04 m, R\({}_{3}\) is taken as between 0.025 m and 0.045 m, R\({}_{4}\) is taken as between 0.025 m and 0.045 m, R\({}_{5}\) is taken as between 0.04 m and 0.06 m, and R\({}_{6}\) is taken as between 0.05 m and 0.07 m. There are numerous commonly used experimental design methods, such as Central Composite [20; 21; 22], Fractional Factorial, Full Factorial, Latin Hypercube, Orthogonal Array, Sobol Sequence, etc. The Latin square experimental method is a sampling method based on the principle of equal probability or equal distance for multidimensional stratified sampling by constraining the locations of sample points. It allows the sample points to be distributed more evenly throughout the design space. Compared with other experimental methods, the advantage of this sampling method is that it has a sampling memory function, which can avoid repeated sampling. The Latin square experimental method can cover the whole design space with a smaller number of sample points, so as to efficiently obtain more comprehensive spatial information. Moreover, this sampling method does not require too much for the number of sample dimensions and sample points. Therefore, in order to obtain sample points for experimental design more efficiently and comprehensively, this paper adopts the Latin square experimental method to obtain data on the variation of each performance value of the large body structure with independent variables [23]. The sensitivity analysis results of the thickness of the large body structure's steel plate to the mass, displacement and structural stress were obtained after the arithmetic analysis, as shown in Tables 2-4.