Novel solution framework for inverse problem considering interval uncertainty

This article proposes a novel solution framework for the inverse problem considering interval uncertainty in structural or systemic responses, which provides an efficient tool for the uncertain inverse problems of nonlinear structures or systems. Interval is used to model and characterize the uncertainty, and the bounds of uncertain structural responses are only required. In each iterative step, the approximate deterministic inverse problem is constructed according to the interval analysis results, and then the identified intervals of inputs are updated by solving the approximate deterministic inverse problem. Therefore, the interval inverse problem is decoupled into a series of interval analyses and deterministic inverse problems that are alternately solved, which dramatically promotes the computational efficiency of the interval inverse problem. Besides, an iterative mechanism is proposed to ensure the convergence of the whole procedure. Finally, two numerical examples and an engineering application are investigated to demonstrate the accuracy and efficiency of the proposed method.

Automated summary

This article proposed a novel solution framework for the inverse problem considering interval uncertainty, effectively promoting computational efficiency. The method decouples the interval inverse problem into a series of interval analyses and deterministic inverse problems that are alternately solved, with an iterative mechanism to ensure convergence throughout the process.