PSI - Issue 52

Dong Xiao et al. / Procedia Structural Integrity 52 (2024) 667–678 Dong Xiao et al. / Structural Integrity Procedia 00 (2023) 000–000

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5. Conclusion

This study presents a surrogate-assisted e ffi cient global optimisation method for impact identification in conjunc tion with the FEM model. The proposed model-based approach utilizes a Kriging surrogate to establish a relationship between impact location, impact force (design variables) and response di ff erences (objective function) that need to be minimized. The optimisation process is facilitated by the e ffi cient global optimisation algorithm, with the generalized expected improvement criterion employed for infill sampling. These infilled samples represent new combinations of design variables, and the FEM model is used to simulate the impacts corresponding to these infilled samples. To expedite the optimisation, local surrogates for impact location and peak force are constructed, enabling adaptive bounding of these variables. The proposed method is validated on the composite plate FEM model using experimental impact force history as inputs. The results demonstrate that the impact identification process converges at approxi mately 60 impact simulations. At this point, the errors in impact location and peak force are below 3 mm and 10% respectively. The subsequent optimisation focus shifts towards fine-tuning the design variables. In conclusion, the proposed surrogate-assisted e ffi cient global optimisation method achieves accurate impact iden tification with fewer than 100 impact simulations, showcasing its e ffi ciency and e ff ectiveness. By leveraging surrogate models and e ffi cient search strategies, the algorithm significantly reduces the computational burden while ensuring precise and reliable impact identification.

Acknowledgements

We would like to express gratitude to the China Scholarship Council (CSC) for funding Dong Xiao’s PhD studies.

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