Fail-safe topology optimization is valuable for ensuring that optimized structures remain operable even under damaged conditions.By selectively removing material stiffness in patches with a fixed shape,the complex phe...Fail-safe topology optimization is valuable for ensuring that optimized structures remain operable even under damaged conditions.By selectively removing material stiffness in patches with a fixed shape,the complex phenomenon of local failure is modeled in fail-safe topology optimization.In this work,we first conduct a comprehensive study to explore the impact of patch size,shape,and distribution on the robustness of fail-safe designs.The findings suggest that larger sizes and finer distribution of material patches can yield more robust fail-safe structures.However,a finer patch distribution can significantly increase computational costs,particularly for 3D structures.To keep computational efforts tractable,an efficient fail-safe topology optimization approach is established based on the framework of multi-resolution topology optimization(MTOP).Within the MTOP framework,the extended finite element method is introduced to establish a decoupling connection between the analysis mesh and the topology description model.Numerical examples demonstrate that the developed methodology is 2 times faster for 2D problems and over 25 times faster for 3D problems than traditional fail-safe topology optimization while maintaining similar levels of robustness.展开更多
Enabled by advancements in multi-material additive manufacturing,lightweight lattice structures consisting of networks of periodic unit cells have gained popularity due to their extraordinary performance and wide arra...Enabled by advancements in multi-material additive manufacturing,lightweight lattice structures consisting of networks of periodic unit cells have gained popularity due to their extraordinary performance and wide array of functions.This work proposes a density-based robust topology optimization method for meso-or macroscale multi-material lattice structures under any combination of material and load uncertainties.The method utilizes a new generalized material interpolation scheme for an arbitrary number of materials,and employs univariate dimension reduction and Gauss-type quadrature to quantify and propagate uncertainty.By formulating the objective function as a weighted sum of the mean and standard deviation of compliance,the tradeoff between optimality and robustness can be studied and controlled.Examples of a cantilever beam lattice structure under various material and load uncertainty cases exhibit the efficiency and flexibility of the approach.The accuracy of univariate dimension reduction is validated by comparing the results to the Monte Carlo approach.展开更多
This paper presents some recent developments in modelling and numerical analysis of piezoelectric systems and controlled smart structures based on a ?nite element formulation with embedded control. The control aims at...This paper presents some recent developments in modelling and numerical analysis of piezoelectric systems and controlled smart structures based on a ?nite element formulation with embedded control. The control aims at vibration suppression of the structure subjected to external disturbances, like wind and noise, under the presence of model inaccuracies, using the available measurements and controls. A smart structure under dynamic loads is analysed and comparison between results for beam with and without control is made. The numerical results show that the control strategy is very effective and suppresses the vibrations of the structure.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant Nos.12172095,11832009,and 12302008)the Natural Science Foundation of Guangdong Province(Grant No.2023A1515011770)Guangzhou Science and Technology Planning Project(Grant Nos.202201010570,202201020239,202201020193,and 202201010399)。
文摘Fail-safe topology optimization is valuable for ensuring that optimized structures remain operable even under damaged conditions.By selectively removing material stiffness in patches with a fixed shape,the complex phenomenon of local failure is modeled in fail-safe topology optimization.In this work,we first conduct a comprehensive study to explore the impact of patch size,shape,and distribution on the robustness of fail-safe designs.The findings suggest that larger sizes and finer distribution of material patches can yield more robust fail-safe structures.However,a finer patch distribution can significantly increase computational costs,particularly for 3D structures.To keep computational efforts tractable,an efficient fail-safe topology optimization approach is established based on the framework of multi-resolution topology optimization(MTOP).Within the MTOP framework,the extended finite element method is introduced to establish a decoupling connection between the analysis mesh and the topology description model.Numerical examples demonstrate that the developed methodology is 2 times faster for 2D problems and over 25 times faster for 3D problems than traditional fail-safe topology optimization while maintaining similar levels of robustness.
基金the Digital Manufacturing and Design Innovation Institute(DMDII)through award number 15-07-07the National Science Foundation Graduate Research Fellowship Program under Grant No.DGE-1842165.
文摘Enabled by advancements in multi-material additive manufacturing,lightweight lattice structures consisting of networks of periodic unit cells have gained popularity due to their extraordinary performance and wide array of functions.This work proposes a density-based robust topology optimization method for meso-or macroscale multi-material lattice structures under any combination of material and load uncertainties.The method utilizes a new generalized material interpolation scheme for an arbitrary number of materials,and employs univariate dimension reduction and Gauss-type quadrature to quantify and propagate uncertainty.By formulating the objective function as a weighted sum of the mean and standard deviation of compliance,the tradeoff between optimality and robustness can be studied and controlled.Examples of a cantilever beam lattice structure under various material and load uncertainty cases exhibit the efficiency and flexibility of the approach.The accuracy of univariate dimension reduction is validated by comparing the results to the Monte Carlo approach.
文摘This paper presents some recent developments in modelling and numerical analysis of piezoelectric systems and controlled smart structures based on a ?nite element formulation with embedded control. The control aims at vibration suppression of the structure subjected to external disturbances, like wind and noise, under the presence of model inaccuracies, using the available measurements and controls. A smart structure under dynamic loads is analysed and comparison between results for beam with and without control is made. The numerical results show that the control strategy is very effective and suppresses the vibrations of the structure.
