A two-level multipoint approximation concept is proposed. Based upon the values and the first-order derivatives of the critical constraint functions at the points obtained in the procedure of optimization, explicit functions approximating the primal constraint functions have been created. The nonlinearities of the approximate functions are controlled to be near those of the constraint functions in their expansion domains. Based on the principle above, the first-levd sequence of explicitly approximate problems used to solve the primarily structural optimization problem are constructed. Each of them is approximated again by the second-level sequence of approximate problems, which are formed by using the linear Taylor series expansion and then solved efficiently with dual theory. Typical numerical examples including optimum design for trusses and frames are solved to illustrate the power of the present method. The computational results show that the method is very efficient and no intermediate/generalized design variable is required to be selected. It testifies to the adaptability and generality of the method for complex problems.

A new concept for complex structural optimization problems is presented. Based on investigation of the mechanical nature of the studied problem, a set of basic mechanical characteristics can be introduced as the generalized variables. A high-quality explicit first-level approximate problem FA is formed by first-order Taylor series expansion of the behaviour constraints in terms of the generalized variables. The FA is explicit but highly non-linear with respect to design variables. Therefore, a second-level approximation is introduced to solve the F A by considering a sequence of second-level approximate problems SA in the design variable space. This approach is a Two-Level Approximation Concept. Its application to space frame synthesis shows its good grasp of the mechanical nature of the problem. The computational results for several examples show that the method presented in this paper is very efficient.

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This paper presents the multidisciplinary design optimization (MDO) for an earth observation satellite. The aim of the paper is to use various multidisciplinary optimization methods to optimize the numerical models of an earth observation satellite under iSIGHTTM software environment. Based on the best earth observation criteria, a mathematical model of the earth observation satellite is proposed, which considers the design variables, the state variables and constraints of the payload system, the attitude system, the control system, the power system, the structure system, and the propulsion system. This paper conducts the optimization by using the above three methods, and compare the efficiency and applicability among the methods.

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