A subinterval decomposition analysis method for uncertain structures with large uncertainty parameters. (15th February 2018) - Fu, C.M.
Highlights: A novel subinterval decomposition analysis method for uncertain structure is proposed. It is suitable to address uncertain structures with strong nonlinearity and large interval parameters. Sensitivities of responses with respect to interval parameters are not required. The efficiency and accuracy of proposed method compared with three other algorithms. Abstract: A simple and efficient subinterval decomposition analysis method is proposed to evaluate the lower and upper bounds of structural responses with large uncertain parameters. The proposed method decomposes the original structural system with multi-dimensional interval parameters into multiple one-dimensional subsystems. Every subsystem has only one interval parameter and the other interval parameters are substituted by their midpoint values. By dividing the interval parameter of each subsystem into several subintervals with small uncertainty, the lower and upper bounds of the system are approximately calculated by only a few subinterval combinational analyses instead of all possible combinations of subintervals. Finally, the accuracy and efficiency of the proposed method compared with the first-order Taylor method, Chebyshev interval method and traditional subinterval method are verified by several numerical examples and applications.