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A novel stress influence function (SIF) methodology for stress-constrained continuum topology optimization

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Abstract

This study presents a new stress influence function (SIF) methodology for continuum topology optimization under consideration of local strength failure. Firstly, the qp-relaxation criterion is involved to circumvent the stress singularity. To deal with the large-scale stress constraints in topology optimization, the local stress constraint is reflected in the objective along with the material volume by multiplication, and the weight of stress is characterized by stress influence function. Meanwhile, three types of stress influence functions are proposed for comparison. By means of the study on the characteristic of high-stress elements, the rationality of the SIF methodology is illustrated, in which the proposed method may achieve the full-stress state of high-stress element. Numerical examples are given to demonstrate the applicability and validity of the proposed methodology. It is shown that the proposed methodology can obtain reasonable results. Consequently, the proposed SIF methodology provides a novel strategy with high computational efficiency for topology optimization considering local strength failure.

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Acknowledgments

The project is supported by the National Key Research and Development Program (No. 2016YFB0200700), the National Nature Science Foundation of the People’s Republic of China (No. 11432002 and No. 11602012), and the Defense Industrial Technology Development Program (Nos. JCKY2016204B101 and JCKY2017601B001). Besides, the authors wish to express their many thanks to the reviewers for their useful and constructive comments.

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Correspondence to Zhiping Qiu.

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The replication of results part is available in the supplementary material, in which the whole source code for Fig. 3 and the part source code for Fig. 9 are given.

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Responsible Editor: Xu Guo

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Xia, H., Qiu, Z. A novel stress influence function (SIF) methodology for stress-constrained continuum topology optimization. Struct Multidisc Optim 62, 2441–2453 (2020). https://doi.org/10.1007/s00158-020-02615-2

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