Article
Engineering, Multidisciplinary
Bobin Guan, Min Wan, Xiangdong Wu, Xuexi Cui, Yisheng Zhang
Summary: This study proposes a novel lightweight design process that incorporates the influence of assembly connection and non-probabilistic uncertainty in material properties. The proposed method is applied to the structural design of a forming machine, and the results demonstrate the importance of considering these factors in ensuring safe and lightweight structures.
ENGINEERING OPTIMIZATION
(2023)
Article
Engineering, Mechanical
Zeng Meng, Gang Yang, Qiangbo Wu, Shan Xiao, Quhao Li
Summary: Resonance can be avoided by preventing structural natural frequencies from falling within the operating frequency range. However, these frequencies are influenced by uncertain parameters. Therefore, a reliability-based eigenvalue topology optimization model is established to consider these uncertainties. To reduce computational burden, a frequency-band constraint shifting method (FBCSM) is proposed. Sensitivities of eigenfrequencies with respect to design and random variables are derived. Examples demonstrate the effectiveness and efficiency of the proposed model and FBCSM.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Computer Science, Interdisciplinary Applications
Yanben Han, Meng Li, Yufei Liu, Xinyu Geng, Peiyuan He, Chengbo Cui
Summary: Spaceborne large aperture membrane microstrip reflectarray antenna has the advantages of high gain, lightweight and small storage volume, but its application is restricted due to difficulty in effectively influencing the distribution of prestress in the membrane reflector and its sensitivity to uncertainties. This paper proposes a method of affecting prestress distribution by attaching an irregular shaped additional layer and a non-probabilistic uncertain topology optimization method to design the shape of the additional layer. The effectiveness of these methods is verified through numerical examples.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Engineering, Multidisciplinary
Lixiong Cao, Jie Liu, Ling Xie, Chao Jiang, Rengui Bi
Summary: This paper proposes a new polygonal convex set model for quantifying non-probabilistic uncertainties, combining principal component analysis and cluster analysis to construct models at different levels, and solving uncertainty propagation problems using the simplex optimization method.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Computer Science, Interdisciplinary Applications
Xiang Li, Xibing Li, Zilong Zhou, Yonghua Su, Wengui Cao
Summary: This paper introduces a non-probabilistic information-gap approach (IGA) for assessing rock tunnel reliability in the face of severely deficient information on rock properties. The IGA is applied in a typical rock tunnel example to quantify uncertainties and assess reliability through an information-gap model and robustness function constructed to address severe lack of information.
COMPUTERS AND GEOTECHNICS
(2021)
Article
Computer Science, Interdisciplinary Applications
Subhayan De, Kurt Maute, Alireza Doostan
Summary: This paper presents a stochastic gradient-based approach to address the computational challenges in reliability-based topology optimization of structures. By using Bayes' rule and a parametric exponential model, the gradients of the failure probability can be efficiently estimated, requiring only a small number of random samples per iteration.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Computer Science, Interdisciplinary Applications
Junjie Zhan, Zhonghang Bai
Summary: This paper presents a non-probabilistic reliability-based topology optimization method under distributed loading uncertainty, evaluating the structural reliability and determining the optimum topology to minimize structural volume. The nested optimization problem is solved using a gradient-based algorithm, and the computational cost is reduced using the concerned performance approach. Numerical examples demonstrate the effectiveness of the proposed method.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Automation & Control Systems
Martina Mammarella, Victor Mirasierra, Matthias Lorenzen, Teodoro Alamo, Fabrizio Dabbene
Summary: This paper proposes a sample-based procedure to obtain simple and computable approximations of chance-constrained sets. The procedure allows for controlling the complexity of the approximating set and obtaining the desired probabilistic guarantees through a probabilistic scaling procedure. The proposed approach has applications in various problems related to systems and control.
Article
Engineering, Multidisciplinary
Hao Yang, Haojun Tian, Yue Zhang, Peng Hao, Bo Wang, Qiang Gao
Summary: Performing reliability-based design optimization with insufficient data is challenging. Existing nonprobabilistic models only account for available or known samples, which may lead to hazardous results when data is insufficient. A novel bootstrap-based ellipsoidal convex model (BECM) is proposed to account for both known and unknown data and achieve conservative results in a rational manner.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Lei Wang, Zeshang Li, BoWen Ni, Kaixuan Gu
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
Computer Science, Interdisciplinary Applications
Piotr Tauzowski, Bartlomiej Blachowski, Janos Logo
Summary: The study aims to propose a simple and efficient method for reliability based topology optimization for structures made of elasto-plastic material, tracking the probability of structural failure and ensuring safety levels specified by the designer. It combines yield-limited topology optimization with reliability analysis using a first order approach, demonstrating effectiveness on benchmark problems and the elasto-plastic topology design of L-shape structures frequently used in stress constrained topology optimization approaches.
COMPUTERS & STRUCTURES
(2021)
Article
Computer Science, Interdisciplinary Applications
Bowen Ni, Xiaojun Wang, Tangqi Lv, Lei Wang, Zeshang Li
Summary: This study proposes a non-probabilistic thermo-elastic reliability-based topology optimization scheme for lightweight design of composite laminates under thermo-elastic loads. The study introduces the equivalent constitutive relation and derives the deterministic topology optimization formulation. It also utilizes interval modeling and optimization feature distance to handle uncertainties and ensure structural safety.
ENGINEERING WITH COMPUTERS
(2022)
Article
Computer Science, Interdisciplinary Applications
Jonghyun Kim, Ikjin Lee
Summary: This paper presents a reliability-based topology optimization framework using nodal design variables for dealing with geometric uncertainties. The structural layout is represented by a density field constructed using nodal densities, and the geometric variation is modeled through nodal shifts and density field perturbations. The optimization problem is decoupled using sequential optimization and reliability assessment method, and the sensitivities are derived analytically. Numerical examples demonstrate the effectiveness of the proposed framework for handling geometric uncertainties.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Mathematics, Interdisciplinary Applications
Junjie Zhan, Zhenguo Wang, Jian Xing
Summary: This study focuses on addressing the uncertainties inherent in the manufacturing and application of multi-material structures. A novel topology optimization method based on non-probabilistic reliability is developed, which characterizes uncertainties using a convex set and a non-probability bounded field model. The proposed method is validated through numerical examples considering uncertainties in parameters and field loading.
COMPUTATIONAL MECHANICS
(2023)
Article
Thermodynamics
Zilong Zhao, Yanwen Xu, Yu-Feng Lin, Xinlei Wang, Pingfeng Wang
Summary: The study analyzed the impact of probabilistic uncertainties in design variables of a ground source heat pump system using reliability-based design optimization method, determining optimal design solutions to improve performance and economic competitiveness.
APPLIED THERMAL ENGINEERING
(2021)
Article
Acoustics
Xianfeng Man, Baizhan Xia, Zhen Luo, Jian Liu, Kun Li, Yonghong Nie
Summary: Acoustic metamaterials with fractal structures, such as LFAMs, are engineered to regulate sound propagation behavior on subwavelength scales, showcasing multi-band blocking and absorption capabilities. The dispersion relations, effective properties, and sound suppression abilities of LFAMs are systematically analyzed to explore their potential applications for low-frequency sound control.
JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA
(2021)
Article
Engineering, Multidisciplinary
Shuhao Wu, Zhen Luo, Zuyu Li, Shutian Liu, Lai-Chang Zhang
Summary: PMMs are a new class of three-dimensional mechanical metamaterials with vanishing shear modulus, designed based on structural architecture rather than composition, achieved through topology optimization for pentamode properties.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Materials Science, Multidisciplinary
Zuyu Li, Zhen Luo, Lai-Chang Zhang, Chun-Hui Wang
Summary: This paper presents an efficient topology optimization method for discovering novel pentamode lattice microarchitectures with certain elastic symmetries, and demonstrates the effectiveness of the proposed method by using a genetic algorithm to solve the topology optimization problem.
MATERIALS & DESIGN
(2021)
Article
Biophysics
Ramtin Gharleghi, Heidi Wright, Vanessa Luvio, Nigel Jepson, Zhen Luo, Anushan Senthurnathan, Behzad Babaei, B. Gangadhara Prusty, Tapabrata Ray, Susann Beier
Summary: The study focused on optimizing stent designs for hemodynamic performance by identifying ideal combinations of design variables. The usage of multi-objective optimization algorithms helped predict ideal designs that could reduce adverse events risk and enhance mechanical performance of the stents. Three best designs for each objective and two overall best designs were identified out of 50 designs.
JOURNAL OF BIOMECHANICS
(2021)
Article
Instruments & Instrumentation
Di Guo, Zhan Kang, Yiqiang Wang, Ming Li
Summary: This study creates multi-material soft modules using topology optimization method to design two types of modules, enabling target bending curvatures and maximal twisting capability. By assembling these modules, various actuation modes can be achieved, including a soft gripper for complex grasping tasks. Both numerical and experimental results verify the performance of the multi-material soft modules and modularized SPAs.
SMART MATERIALS AND STRUCTURES
(2021)
Article
Computer Science, Interdisciplinary Applications
Jie Gao, Lin Wang, Zhen Luo, Liang Gao
Summary: This paper presents a compact and efficient MATLAB code for isogeometric topology optimization (ITO), showcasing the development and functions of various components, and demonstrating the effectiveness of the code through numerical examples.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Engineering, Multidisciplinary
Mahmoud Alfouneh, Van-Nam Hoang, Zhen Luo, Quantian Luo
Summary: This article investigates the topology optimization of multi-layer multi-material composite structures under static loading. The moving iso-surface threshold optimization method, previously defined for single or cellular materials, is extended to multi-layer multi-material structures using a physical response function discrepancy scheme. It is also integrated with an alternating active-phase algorithm as an alternative procedure. The proposed methods are applied to three types of objective functions, namely, minimizing compliance, maximizing mutual strain energy, and minimizing full-stress designs. Examples are presented and compared with existing literature to verify the derived formulations for topology optimization of multi-layer multi-material structures.
ENGINEERING OPTIMIZATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Yixiao Zhu, Yaguang Wang, Xiaopeng Zhang, Zhan Kang
Summary: This paper proposes a new constraint form to prevent natural frequencies from falling within a given frequency band. The effectiveness of this constraint is demonstrated in topology optimization, where topological evolutions of the structural configuration are involved during the optimization process.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Engineering, Multidisciplinary
Wenjun Wu, Huikai Zhang, Yiqiang Wang, Pai Liu, Zhan Kang
Summary: In this paper, a numerical method of concurrent topology optimization is proposed for maximizing the natural frequencies of structures consisting of layer-wise graded microstructures. The method allows for simultaneous optimization of the configuration and spatial distribution of graded microstructures in the macrostructural design domain, with the use of microscale design constraints to retain the desired design space.
INTERNATIONAL JOURNAL OF COMPUTATIONAL METHODS
(2023)
Article
Mechanics
Ya-Fei Zhao, Shun-Qi Zhang, Xiang Wang, Song-Yun Ma, Guo-Zhong Zhao, Zhan Kang
Summary: This article develops a geometrically nonlinear finite element formulation based on the first-order shear deformation hypothesis for static and dynamic analysis of carbon nanotube reinforced magneto-electro-elastic plates. It verifies the proposed model and studies the impact of different functionally graded patterns on reinforcement efficiency.
COMPOSITE STRUCTURES
(2022)
Article
Materials Science, Multidisciplinary
Zuyu Li, Wei Gao, Michael Yu Wang, Zhen Luo
Summary: Auxetic metamaterials are mechanically unique materials with negative Poisson's ratios and counter-intuitive deformation behavior. This paper presents a systematic method for designing novel three-dimensional auxetic microlattices. The optimized microlattices exhibit desired properties such as elastic isotropy, negative Poisson's ratio, and zero thermal expansion. The study demonstrates the potential of these materials for various applications.
MATERIALS & DESIGN
(2022)
Article
Nanoscience & Nanotechnology
Chen Du, Yiqiang Wang, Zhan Kang
Summary: This paper proposes a novel family of metamaterials that can achieve and maintain negative Poisson's ratios up to 0.50 applied strains by fully utilizing out-of-plane buckling. These materials possess unique properties, including a wide range of negative Poisson's ratios, sheet thickness-insensitive auxeticity, and excellent shape recoverability. They have potential applications in areas such as compliant robotics, bio-medical devices, and flexible electronics.
ACS APPLIED MATERIALS & INTERFACES
(2023)
Article
Materials Science, Multidisciplinary
Wenjun Wu, Pai Liu, Yiqiang Wang, Zhan Kang
Summary: This paper introduces a new design of bistable structures that achieve torsional bistability under uniaxial compression. The proposed structure is composed of two co-axis polygonal prisms connected by struts, and torsional bistability is achieved by opposite rotations of the prisms. An analytical model and numerical simulations demonstrate the need for a dual-material design for the inclined and connecting struts to induce bistability.
MATERIALS & DESIGN
(2023)
Article
Mechanics
Yixiao Zhu, Zhan Kang
Summary: This paper presents a more efficient topology optimization method for three-dimensional Phononic Crystals (PnCs) by avoiding the expensive eigenvalue problem and improving the design iteration efficiency through successive iteration of analysis and design. The effectiveness of the proposed method is demonstrated by numerical examples with over one million degrees of freedom.
COMPOSITE STRUCTURES
(2023)
Article
Multidisciplinary Sciences
Sheikh Hossain, Zhen Luo, Evelyne Deplazes, Suvash C. Saha
Summary: This study investigates the effects of different shaped AuNPs on model LSM through molecular dynamics simulations, finding that AuNPs have a greater impact on the compressed state of the monolayer, preventing it from reaching the surface tension required for normal exhalation and thinning the monolayer. Insights from this study may aid future research on how AuNP shapes affect the LSM during inhalation or exhalation.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2021)