Article
Computer Science, Interdisciplinary Applications
Haijun Xia, Zhiping Qiu, Lei Wang
Summary: This study explores a novel reliability-based topology optimization framework for determining optimal material configurations for freely vibrating continuum structures with unknown-but-bounded uncertainties. By introducing the concept of non-probabilistic reliability and utilizing the performance measure approach, the study overcomes convergence difficulties and demonstrates its validity through numerical examples.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Automation & Control Systems
Junbo Tan, Sorin Olaru, Maria M. Seron, Feng Xu
Summary: This paper focuses on designing an input sequence via the minimization of a suitable cost function to ensure active fault diagnosis of discrete-time linear parameter-varying systems regardless of changes in scheduling variables. It uses convex polyhedrons to characterize system uncertainties and proposes an efficient optimization method by analyzing the geometric properties of the objective function to obtain the optimal input sequence.
Article
Automation & Control Systems
Hao Liu, Yuzhe Li, Qing-Long Han, Tarek Raissi
Summary: In this article, a novel proactive attack defense strategy is proposed for dealing with the secure remote estimation issue in cyber-physical systems with unknown-but-bounded noises in the presence of man-in-the-middle attacks. The proposed strategy includes time-varying and secret data processes and watermark to guarantee the detection rate, and it can be applied to detect replay attacks. Four different attack scenarios are discussed in the analysis of the detection ability of the defense approach. The effectiveness of the proposed proactive defense strategy is illustrated through the example of an unmanned aircraft system subject to malicious attacks.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(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
Automation & Control Systems
Hao Liu, Shaodong Wang, Ben Niu, Yuzhe Li
Summary: This article proposes a novel attack detection approach based on zonotopes for linear parameter-varying systems with unknown-but-bounded noises. It considers DoS, RAs, and FDI attacks, introduces a free-weighting matrix to reduce conservativeness, and guarantees the radius of the intersection zonotope to be limited. Additionally, the method does not require prior knowledge of the specific type of attack.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Hao Yang, Yilian Zhang, Wei Gu, Fuwen Yang, Zhiquan Liu
Summary: This paper introduces a set-membership filtering scheme for state estimation of an automatic guided vehicle (AGV), which can effectively handle unknown-but-bounded noises and reduce sensor precision requirement. By designing a set-membership estimation algorithm, the state estimation ellipsoids containing the true states can be obtained.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2022)
Article
Computer Science, Interdisciplinary Applications
Dongliang Liu, Zhiping Qiu
Summary: This study focuses on the robust topology optimization of structures with truss-like lattice materials under unknown but bounded uncertainties. A formulation for robust topology optimization is developed to account for uncertainties in load magnitude and direction, as well as truss-like lattice material diameter. Absolute and relative robustness indices are established to measure structure robustness, and a subinterval dimension-wise method is proposed to address difficulties in determining response intervals caused by large uncertainties. Two examples are provided to demonstrate the effectiveness of the method in complex structures with significant uncertainty.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Engineering, Civil
Lei Wang, Yingge Liu, Zeshang Li, Juxi Hu, Bing Han
Summary: This paper conducts a study on non-probabilistic reliability-based topology optimization (NRBTO) scheme for continuum structures based on the parameterized level set method (PLSM). The stress constraint is transformed into the non-probabilistic reliability-based scheme using the interval-set model, and the reliability is evaluated by the optimization feature distance (OFD). The NRBTO scheme considers the unknown-but-bounded (UBB) uncertainties of the material and external load of the optimized structure.
THIN-WALLED STRUCTURES
(2023)
Article
Automation & Control Systems
Van-Truong Nguyen, Chyi-Yeu Lin, Shun-Feng Su, Wei Sun, Meng Joo Er
Summary: This article presents a global finite-time active disturbance rejection control (ADRC) scheme for tracking control of redundant parallel manipulators with unknown bounded uncertainties, which combines ADRC and global finite-time control for high accuracy trajectory tracking control. The proposed approach removes the condition in the original ADRC that the derivative of the uncertainties is required to be bounded, and utilizes an extended state observer for real-time estimation of total uncertainty. The scheme shows fast convergence to a semi-global finite-time stable equilibrium and superior tracking control performance, with advantages including uncertainty rejection, ease of implementation, robustness, chattering-free operation, high precision, and no need for prior knowledge of bounded uncertainties. Simulation results validate the effectiveness of the proposed method.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Song Bai, Zhan Kang
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
Automation & Control Systems
Xiaoyi Zhang, Jie Wu, Xisheng Zhan, Tao Han, Huaicheng Yan
Summary: This article investigates the time-varying formation (TVF)-containment tracking problem for linear multiagent systems (MASs) with unknown and bounded input of the tracking leader. A novel adaptive discontinuous TVF-containment tracking protocol is proposed for linear MAS. Theoretical analysis shows that the leaders can achieve the expected TVF and track the trajectory of the tracking leader, while the follower agents can move into the convex hull formed by the leader agents.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Lei Wang, Zeshang Li, BoWen Ni, Xiaojun Wang, Wenpin Chen
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
Automation & Control Systems
Oleg Granichin, Victoria Erofeeva, Yury Ivanskiy, Yuming Jiang
Summary: This article discusses estimation and tracking problems in a distributed sensor network, focusing on SPSA-based consensus algorithms. Sufficient conditions are introduced to guarantee stability of estimates without relying on stringent statistical assumptions about observation noise.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(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
Engineering, Multidisciplinary
Lei Wang, Bowen Ni, Xiaojun Wang, Zeshang Li
Summary: With the rapid development of intelligent manufacturing and smart design, the optimal design conception for composite laminates is attracting more attention in both academic and engineering fields. Most current research focuses on deterministic laminate design, while uncertainty-oriented topological designs for heterogeneous composites are rarely considered. This study presents a new layout optimization process combining hybrid uncertainty quantification analysis and non-probabilistic reliability-based topology optimization. Several typical optimization cases are presented to demonstrate the validity and effectiveness of the developed methodology.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Engineering, Multidisciplinary
Akshay J. Thomas, Mateusz Jaszczuk, Eduardo Barocio, Gourab Ghosh, Ilias Bilionis, R. Byron Pipes
Summary: We propose a physics-guided transfer learning approach to predict the thermal conductivity of additively manufactured short-fiber reinforced polymers using micro-structural characteristics obtained from tensile tests. A Bayesian framework is developed to transfer the thermal conductivity properties across different extrusion deposition additive manufacturing systems. The experimental results demonstrate the effectiveness and reliability of our method in accounting for epistemic and aleatory uncertainties.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Zhen Zhang, Zongren Zou, Ellen Kuhl, George Em Karniadakis
Summary: In this study, deep learning and artificial intelligence were used to discover a mathematical model for the progression of Alzheimer's disease. By analyzing longitudinal tau positron emission tomography data, a reaction-diffusion type partial differential equation for tau protein misfolding and spreading was discovered. The results showed different misfolding models for Alzheimer's and healthy control groups, indicating faster misfolding in Alzheimer's group. The study provides a foundation for early diagnosis and treatment of Alzheimer's disease and other misfolding-protein based neurodegenerative disorders using image-based technologies.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Jonghyuk Baek, Jiun-Shyan Chen
Summary: This paper introduces an improved neural network-enhanced reproducing kernel particle method for modeling the localization of brittle fractures. By adding a neural network approximation to the background reproducing kernel approximation, the method allows for the automatic location and insertion of discontinuities in the function space, enhancing the modeling effectiveness. The proposed method uses an energy-based loss function for optimization and regularizes the approximation results through constraints on the spatial gradient of the parametric coordinates, ensuring convergence.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Bodhinanda Chandra, Ryota Hashimoto, Shinnosuke Matsumi, Ken Kamrin, Kenichi Soga
Summary: This paper proposes new and robust stabilization strategies for accurately modeling incompressible fluid flow problems in the material point method (MPM). The proposed approach adopts a monolithic displacement-pressure formulation and integrates two stabilization strategies to ensure stability. The effectiveness of the proposed method is validated through benchmark cases and real-world scenarios involving violent free-surface fluid motion.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Chao Peng, Alessandro Tasora, Dario Fusai, Dario Mangoni
Summary: This article discusses the importance of the tangent stiffness matrix of constraints in multibody systems and provides a general formulation based on quaternion parametrization. The article also presents the analytical expression of the tangent stiffness matrix derived through linearization. Examples demonstrate the positive effect of this additional stiffness term on static and eigenvalue analyses.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Thibaut Vadcard, Fabrice Thouverez, Alain Batailly
Summary: This contribution presents a methodology for detecting isolated branches of periodic solutions to nonlinear mechanical equations. The method combines harmonic balance method-based solving procedure with the Melnikov energy principle. It is able to predict the location of isolated branches of solutions near families of autonomous periodic solutions. The relevance and accuracy of this methodology are demonstrated through academic and industrial applications.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Weisheng Zhang, Yue Wang, Sung-Kie Youn, Xu Guo
Summary: This study proposes a sketch-guided topology optimization approach based on machine learning, which incorporates computer sketches as constraint functions to improve the efficiency of computer-aided structural design models and meet the design intention and requirements of designers.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Leilei Chen, Zhongwang Wang, Haojie Lian, Yujing Ma, Zhuxuan Meng, Pei Li, Chensen Ding, Stephane P. A. Bordas
Summary: This paper presents a model order reduction method for electromagnetic boundary element analysis and extends it to computer-aided design integrated shape optimization of multi-frequency electromagnetic scattering problems. The proposed method utilizes a series expansion technique and the second-order Arnoldi procedure to reduce the order of original systems. It also employs the isogeometric boundary element method to ensure geometric exactness and avoid re-meshing during shape optimization. The Grey Wolf Optimization-Artificial Neural Network is used as a surrogate model for shape optimization, with radar cross section as the objective function.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
C. Pilloton, P. N. Sun, X. Zhang, A. Colagrossi
Summary: This paper investigates the smoothed particle hydrodynamics (SPH) simulations of violent sloshing flows and discusses the impact of volume conservation errors on the simulation results. Different techniques are used to directly measure the particles' volumes and stabilization terms are introduced to control the errors. Experimental comparisons demonstrate the effectiveness of the numerical techniques.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Ye Lu, Weidong Zhu
Summary: This work presents a novel global digital image correlation (DIC) method based on a convolution finite element (C-FE) approximation. The C-FE based DIC provides highly smooth and accurate displacement and strain results with the same element size as the usual finite element (FE) based DIC. The proposed method's formulation and implementation, as well as the controlling parameters, have been discussed in detail. The C-FE method outperformed the FE method in all tested examples, demonstrating its potential for highly smooth, accurate, and robust DIC analysis.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Mojtaba Ghasemi, Mohsen Zare, Amir Zahedi, Pavel Trojovsky, Laith Abualigah, Eva Trojovska
Summary: This paper introduces Lung performance-based optimization (LPO), a novel algorithm that draws inspiration from the efficient oxygen exchange in the lungs. Through experiments and comparisons with contemporary algorithms, LPO demonstrates its effectiveness in solving complex optimization problems and shows potential for a wide range of applications.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Jingyu Hu, Yang Liu, Huixin Huang, Shutian Liu
Summary: In this study, a new topology optimization method is proposed for structures with embedded components, considering the tension/compression asymmetric interface stress constraint. The method optimizes the topology of the host structure and the layout of embedded components simultaneously, and a new interpolation model is developed to determine interface layers between the host structure and embedded components.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Qiang Liu, Wei Zhu, Xiyu Jia, Feng Ma, Jun Wen, Yixiong Wu, Kuangqi Chen, Zhenhai Zhang, Shuang Wang
Summary: In this study, a multiscale and nonlinear turbulence characteristic extraction model using a graph neural network was designed. This model can directly compute turbulence data without resorting to simplified formulas. Experimental results demonstrate that the model has high computational performance in turbulence calculation.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Jacinto Ulloa, Geert Degrande, Jose E. Andrade, Stijn Francois
Summary: This paper presents a multi-temporal formulation for simulating elastoplastic solids under cyclic loading. The proper generalized decomposition (PGD) is leveraged to decompose the displacements into multiple time scales, separating the spatial and intra-cyclic dependence from the inter-cyclic variation, thereby reducing computational burden.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Multidisciplinary
Utkarsh Utkarsh, Valentin Churavy, Yingbo Ma, Tim Besard, Prakitr Srisuma, Tim Gymnich, Adam R. Gerlach, Alan Edelman, George Barbastathis, Richard D. Braatz, Christopher Rackauckas
Summary: This article presents a high-performance vendor-agnostic method for massively parallel solving of ordinary and stochastic differential equations on GPUs. The method integrates with a popular differential equation solver library and achieves state-of-the-art performance compared to hand-optimized kernels.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)