Structural model updating based on response surface and improved whale optimization algorithm

In engineering, structural model updating often faces challenges such as strong nonlinearity and high dimensionality of the updating parameters. Traditional optimization algorithms tend to get trapped in local optima and demonstrate low convergence efficiency when dealing with such problems. Although the Whale Optimization Algorithm (WOA) boasts stronger optimization capability than traditional algorithms, it struggles to balance exploration and exploitation. To address the above issues, this study proposes a model updating method based on the Response Surface Methodology (RSM) and the Improved Whale Optimization Algorithm (ImWOA). The ImWOA algorithm incorporates the improved Tent chaotic mapping to optimize the spatial distribution of the initial population, and adjusts the core parameter a for balancing the algorithm's exploration and exploitation capabilities via a nonlinear equation, thus achieving their collaborative optimization and further enhancing the global optimization performance and solution accuracy of the algorithm. To evaluate the performance of ImWOA, this study selected multiple benchmark test functions of varying dimensions and types, and compared it with the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and the standard WOA. The results show that ImWOA outperforms other algorithms in both exploration capability and optimization accuracy. To verify the effectiveness and applicability of the proposed method, multi-scenario case studies were conducted: it was first applied to the model updating of a cantilever beam, where the maximum error of natural frequencies was reduced from 9.9 % (pre-updating) to 1.6 % (post-updating), and the mode shapes were more consistent with the measured results. Furthermore, the method was applied to the model updating of a more complex jacket benchmark experimental model to simulate complex structural scenarios in practical engineering. The study confirms that the proposed RSM-ImWOA method can effectively solve the problems in high-dimensional and strongly nonlinear structural model updating, and possesses good engineering practical value.