相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。
Article
Engineering, Industrial
Jiaxiang Liu et al.
Summary: This paper proposes a two-stage framework based on non-probabilistic time-dependent reliability and artificial neutral network for the design of uncertain vibration active control systems. By decoupling the design of ASPD and PID gains into two stages, the influence of uncertain parameters is reduced, and the efficiency and practicality of optimization are improved.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Multidisciplinary
Zeshang Li et al.
Summary: This paper focuses on the higher requirements for lightweight design of structures and the development of advanced design technology. It proposes a concurrent reliability-based topology optimization design method considering multi-source hybrid uncertainties and defect damage.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2023)
Article
Engineering, Mechanical
Zeshang Li et al.
Summary: This paper proposes a concurrent robust topology optimization method considering manufacturing factors and hybrid uncertainties. The minimum size is controlled based on the boundary gradient under the level set frame. The influence of random defects on the mechanical property is analyzed via the homogenization method. The Taylor expansion method and collocation method are used to calculate the influence of hybrid uncertainties on structural response. The parameter update strategy of the optimization algorithm is improved, which extends the constraints of the optimization model and can solve the optimization model under severe constraints. Three examples show efficiency, results, and applicability.
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
(2023)
Article
Computer Science, Interdisciplinary Applications
Lei Wang et al.
Summary: This paper proposes a cross-scale robust topology optimization method for fixed boundary structures, considering the uncertainties of force magnitude and direction. The method aims to constrain the robustness of structural response and unit-cell configuration. It introduces an adaptive subinterval dimension-wise method for strongly nonlinear propagation analysis problems and utilizes the filter-projection technique to enhance the manufacturability of the unit cell and suppress the influence of manufacturing defects. Two examples are presented to demonstrate the applicability and effectiveness of the method.
ENGINEERING WITH COMPUTERS
(2022)
Article
Mathematics, Applied
Gourav Agrawal et al.
Summary: The study examines a SIMP-based robust topology optimization design for NPR metamaterials under material uncertainty, showing that RTO produces more stable designs with variations ranging from 1.72% to 2.54%, significantly lower than deterministic topology optimization.
FINITE ELEMENTS IN ANALYSIS AND DESIGN
(2022)
Article
Computer Science, Interdisciplinary Applications
Jing Zheng et al.
Summary: This paper develops a new robust topology optimization method for structures under thermo-mechanical loadings considering hybrid uncertainties. It introduces an efficient dimension reduction-based orthogonal polynomial expansion method for hybrid uncertainty analysis. The method takes into account both random and interval uncertainties related to material properties and loadings.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Engineering, Civil
Wei Shen et al.
Summary: In this study, a reliability-based shape and topology optimization method for plane frames is proposed, with the quantile estimated using the maximum entropy method and an iterative scheme employed to solve deterministic optimization problems. The force density method is applied for simultaneous shape and topology optimization. The results demonstrate the effectiveness and feasibility of the proposed method.
Article
Mechanics
Xuechen Gu et al.
Summary: This paper presents a novel multiscale concurrent topology optimization method for optimizing structures filled with multiple microstructures and connected by solid interfaces. The method proposes optimization techniques at both the macro and micro scales, achieving improved structural performance through solid interface layers and optimizing the distribution of microstructures.
COMPOSITE STRUCTURES
(2022)
Article
Mechanics
Maximilian Eckrich et al.
Summary: This paper presents a workflow that combines topology optimization and fiber placement technologies for lightweight applications. It addresses the specific material characteristics of fiber reinforced polymers (FRP) and the limitations of fiber placement processes, and utilizes various methods to optimize part shape, fiber orientation, and fiber placement paths.
COMPOSITE STRUCTURES
(2022)
Article
Engineering, Multidisciplinary
Liangbing Guo et al.
Summary: This paper presents a reliability-based topology optimization (RBTO) model considering buckling and compliance constraints. The Kreisselmeier-Steinhauser aggregation function and a modified chaos control strategy are utilized to improve computational efficiency and robustness. Sensitivities of the probabilistic constraint with respect to design and random variables are derived and verified through finite difference method.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2022)
Article
Mechanics
Kyeong-Soo Yun et al.
Summary: This paper presents a topology optimization method for microstructures of viscoelastic composites, utilizing numerical methods and adjoint sensitivity analysis to find the optimal microstructures and minimize the difference between prescribed and effective relaxation moduli. Several numerical examples demonstrate the effectiveness of the proposed approach in optimizing viscoelastic composites based on volume fraction, relaxation time, and stiffness.
INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES
(2022)
Article
Engineering, Mechanical
Yaru Liu et al.
Summary: This paper explores an effective method for identifying the distributed dynamic load (DDL) that varies in both time and space dimensions using limited acceleration responses. The spatial distribution of the DDL is approximated using a radial basis function (RBF) interpolation strategy, and the temporal distribution is obtained through an inverse Newmark iteration. A multi-dimensional interval model is developed to quantify uncertainties, and a Chebyshev-interval surrogate model is constructed to obtain the fuzzy-interval boundaries of the DDL. The feasibility of this approach is demonstrated through three examples, showing promising applications in different structures and loading conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Industrial
Lei Wang et al.
Summary: This study investigates a novel convexity-oriented time-dependent reliability-based topology optimization (CTRBTO) framework that comprehensively considers universal uncertainties and time-varying natures in configuration design. Uncertain factors are quantified using the convex set model, and dynamic responses are expressed using the convex process model. The boundary rules and time-dependency properties are revealed using the full-dimensional convex-set collocation theorem. A new convex time-dependent reliability (CTR) index is defined to determine failure judgment of local dynamic stiffness, and the CTRBTO strategy is driven by this index. The computational robustness is ensured using a gradient-based iterative algorithm, and the design sensitivities are analyzed using the Lagrange multiplier method. Numerical examples demonstrate the effectiveness of the proposed method.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Computer Science, Interdisciplinary Applications
Zongliang Du et al.
Summary: This study proposes an efficient and easy-to-extend three-dimensional topology optimization method, which improves the efficiency and performance of the optimization process by introducing new numerical techniques and optimizing the load transmission path.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Lei Wang et al.
Summary: This paper proposes an efficient dynamic robust topology optimization method that optimizes the overall dynamic response of a structure at full time. By adopting the equivalent static load method and the parametric Level-Set method, the dynamic response is efficiently obtained and the stability and efficiency of topology optimization are balanced. Additionally, uncertainty characterization methods based on interval model are used to account for the impact of uncertainties, effectively quantifying them in the optimization process. The proposed method is applied to important structures in aeronautical engineering, with three examples demonstrating its effectiveness in different aspects.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Engineering, Civil
Kang Gao et al.
Summary: This study presents a novel computational framework for Robust Topology Optimization (RTO) considering imprecise random field parameters. The proposed method provides upper and lower bounds for mean and standard deviation of compliance, and obtains optimized topological layouts for different scenarios. The validity and accuracy of the method are rigorously examined by comparing with other optimization methods.
THIN-WALLED STRUCTURES
(2022)
Article
Engineering, Aerospace
Achyut Paudel et al.
Summary: This paper presents an efficient numerical approach for uncertainty quantification using a higher-order Taylor series expansion. The approach evaluates local sensitivities in the Taylor series using a modified forward finite difference (ModFFD) method that is both highly accurate and computationally efficient. The method is applicable for any input distributions and can handle both correlated and uncorrelated random input variables. Tests on various analytical and engineering problems demonstrate the high accuracy and computational efficiency of the approach, especially for random inputs with non-standard distributions and varying correlation.
AEROSPACE SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Multidisciplinary
Lei Wang et al.
Summary: This paper proposes a robust topology optimization method considering bounded field parameters with uncertainties based on the variable time step parametric level-set method. The method develops a variable time step strategy for level set function evolution by utilizing the gradient of the level set function and radial basis function interpolation to separate time and space, achieving better design results. Furthermore, dimension reduction methods and dimension wise methods based on polynomials are employed to characterize and quantify the uncertainties of bounded field parameters. Finally, the sensitivity of the robust optimization model is derived based on the shape derivative principle, serving as the basis for gradient-based optimization algorithms. Three examples are provided to illustrate the effectiveness, necessity, and influence of important parameters in the proposed method.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Engineering, Multidisciplinary
Zeshang Li et al.
Summary: With the increasing diversification of engineering structure performance requirements and the continuous refinement of processing and manufacturing, structural design faces more factors to be considered. This study proposes a feature-driven robust topology optimization strategy considering movable non-design domain and complex uncertainty. It quantifies the influence of non-design domain and uncertainty on structural topology, analyzes the mathematical properties of structural response, and derives the sensitivity of the optimization model, providing a basis for gradient-based optimization algorithms.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
Lei Wang et al.
Summary: This paper presents a study on non-probabilistic reliability-based topology optimization (NRBTO) scheme for continuum structures, incorporating unknown-but-bounded uncertainties of material and external loads. The transformation of partial differential equations to ordinary differential equations using compactly supported radial basis functions, and the evaluation of reliability using the optimization feature distance are key components of the approach. Additionally, sensitivity analysis is conducted using interval parametric vertex approach, shape derivative concept and adjoint vector method to optimize the evolution of level-set functions, while numerical results demonstrate the significant impact of considering UBB uncertainties during topology optimization.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Sheng Chu et al.
Summary: This paper focuses on robust topology optimization for fiber-reinforced composite structures under loading uncertainty, presenting an effective method for simultaneous optimization of fiber angles and structural topology. The study uses a new parameterization scheme and Monte Carlo simulation method to handle the optimization problem, sensitivity analysis, and Kriging metamodel for reducing computational cost.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Mathematics, Applied
Aditya Vishwanathan et al.
Summary: The paper investigates the impact of uncertain boundary conditions on topology optimization, demonstrating how to consider uncertainty in BCs in design, and proposes a robust objective using a weighted sum of mean and standard deviation to effectively reduce the variance and worst-case performance of the objective function.
FINITE ELEMENTS IN ANALYSIS AND DESIGN
(2021)
Article
Mathematics, Applied
Youngsuk Jung et al.
Summary: This paper proposes a new method for multi-material topology optimization that can concurrently determine the structural layout and joint interface. By using a modified discrete material optimization approach, the method allows for independent control of different materials and expands the applicability of the method to cases with more than two design materials.
FINITE ELEMENTS IN ANALYSIS AND DESIGN
(2021)
Article
Mathematics, Applied
Yuki Noguchi et al.
Summary: This paper presents a level set-based topology optimization method for acoustic metasurfaces to achieve negative refraction. By using design variables and sensitivity analysis, an effective optimization solution for two-layered metasurfaces is proposed.
FINITE ELEMENTS IN ANALYSIS AND DESIGN
(2021)
Article
Engineering, Mechanical
Jong Kyeom Lee et al.
Summary: A reliability-based topology optimization method is proposed for designing mufflers under noise frequency and temperature uncertainties. The method uses partition volume as the objective function and acoustical reliability and transmission loss as constraints to design a simple yet highly reliable muffler.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Engineering, Multidisciplinary
Xiaopeng Li et al.
Summary: The proposed hybrid level set method simultaneously optimizes supporting structure and embedded component positions and orientations. It represents components and supporting structure using explicit and implicit level sets, allowing for smooth geometries and clear interfaces. By using two sets of design variables in a unified optimization loop, the overall design variables are greatly reduced.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Song Bai et al.
Summary: The paper presents a robust topology optimization method for structures with bounded loads and spatially correlated material uncertainties. The method combines random structural loads with bounded nature and random field discretization to model uncertainties, with a focus on minimizing mean value and standard deviation of structural compliance. Numerical examples show that the proposed method results in structurally robust designs against uncertainties.
COMPUTERS & STRUCTURES
(2021)
Article
Engineering, Multidisciplinary
Steven Dixler et al.
Summary: The optimal spline dimensional decomposition (SDD) method proposed in this study provides a more accurate way to calculate the second-moment statistics and the cumulative distribution function of output random variables in high-dimensional uncertainty quantification analysis of complex systems. This method reduces computational complexity compared to traditional methods such as polynomial chaos expansion and sparse-grid quadrature.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Pengya Fang et al.
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
(2020)
Article
Engineering, Aerospace
Xiuqiang Jiang et al.
AEROSPACE SCIENCE AND TECHNOLOGY
(2020)
Article
Engineering, Mechanical
Jing Zheng et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2019)
Article
Computer Science, Interdisciplinary Applications
Hui Liu et al.
COMPUTERS & STRUCTURES
(2019)
Article
Computer Science, Interdisciplinary Applications
Peng Wei et al.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2018)
Article
Engineering, Multidisciplinary
Lei Wang et al.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2017)
Article
Engineering, Multidisciplinary
G Allaire et al.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2005)
Article
Computer Science, Interdisciplinary Applications
YL Mei et al.
ADVANCES IN ENGINEERING SOFTWARE
(2004)
