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This paper proposes a novel method to design the internal stiffeners layout of the supporting parts of a machine tool. This method skillfully adopts the natural growth law of leaf veins. Firstly, the similarity between the growth law of leaf veins and the layout of stiffeners in the supporting parts is dealt with in detail. The mechanical properties of different growth types of leaf veins are compared and analyzed by the finite element simulation. In addition, the optimality of the adaptive growth law of leaf veins is also analyzed. Then, a parameter optimization method of stiffeners layout based on a variable cross-section structure is proposed. Distinct from the traditional design of stiffeners layout, the method proposed in this paper not only adopts the idea of a variable cross-section structure, but also simulates the adaptive growth law of leaf veins through a parametric method. In the process of establishing a meta model, three modeling methods are compared, and the excellent performance of the genetic algorithm and BP neural network (GABPNN) method in meta model accuracy is determined. And a marine predator algorithm is implemented to optimize the meta model. Finally, the method proposed in this paper is applied to the design of the column part of a machine tool, and the effectiveness of the proposed method is verified by simulation and experiments, which provides a good idea for the design of stiffeners layout of the supporting parts of a machine tool. [ABSTRACT FROM AUTHOR]

To improve the dynamic performance and reduce the weight of the planet carrier in wind turbine gearbox, a multi-objective optimization method, which is driven by the maximum deformation, the maximum stress and the minimum mass of the studied part, is proposed by combining the response surface method and genetic algorithms in this paper. Firstly, the design points' distribution for the design variables of the planet carrier is established with the central composite design (CCD) method. Then, based on the computing results of finite element analysis (FEA), the response surface analysis is conducted to find out the proper sets of design variable values. And a multi-objective genetic algorithm (MOGA) is applied to determine the direction of optimization. As well, this method is applied to design and optimize the planet carrier in a 1.5MW wind turbine gearbox, the results of which are validated by an experimental modal test. Compared with the original design, the mass and the stress of the optimized planet carrier are respectively reduced by 9.3% and 40%. Consequently, the cost of planet carrier is greatly reduced and its stability is also improved. [ABSTRACT FROM AUTHOR]

In this paper, the simple genetic algorithm (SGA) is improved by combining with the simulated annealing algorithm (SAA) for the parameter identification of a reinforced concrete (RC) frame on elastic foundation. SGA adopts parallel search strategy, which is based on the concept of "survival of the fittest" in optimization while SAA adopts a serial form and the process is endowed with time-variety probable jumping property so that local optimization could be prevented. The global searching ability is developed by combining the two methods and the new algorithm is named genetic annealing hybrid algorithm (GAHA). Modal experiments were carried out on a four-storey RC frame structural model with isolated embedded footings in laboratory. The measured natural frequencies and mode shapes have been utilized to identify the physical parameters of the frame by the proposed method. Four cases of concrete elastic modulus and foundation dynamic shear modulus are identified, and the results are compared with the usual sensitivity methods (SM). By model updating, the results show that the elastic modulus of concrete increases with respect to the storey. The identified elastic modulus of the concrete is generally larger than that found by compressive testing because the dynamic modulus of concrete is larger than the static modulus of concrete. The identified soil dynamic shear modulus also increases with the storey since the soil property depends on the pressure exerted on the soil. It is also shown that the identified results by GAHA are better than that of SM. [ABSTRACT FROM AUTHOR]