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
Automation & Control Systems
Qie Liu, Biao Huang, Yi Chai, Wenbo Li
Summary: The identification of topology in sparse networks is crucial for network modeling in various fields. An efficient algorithm based on stochastic optimization is proposed to decrease computational complexity and is suitable for network identification with large data sets.
Article
Computer Science, Interdisciplinary Applications
Micah Kranz, Julian Kajo Luedeker, Benedikt Kriegesmann
Summary: The paper introduces a rigorous formulation of adjoint systems for robust design optimization. The presented approach allows for the optimization of any objective function by considering deformation and maximum stress as objectives subjected to random material stiffness and geometry. The method requires solving at most three additional adjoint systems per uncertain system response, regardless of the number of random variables. Despite the assumption of linearity with respect to random parameters, the approach is able to find robust designs according to the validation with Monte Carlo simulations.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Engineering, Multidisciplinary
Shun-Peng Zhu, Behrooz Keshtegar, Mohamed El Amine Ben Seghier, Enrico Zio, Osman Taylan
Summary: This study proposes two improved particle swarm optimization algorithms to enhance the convergence rate and global convergence of structural reliability analysis. The experimental results show that the proposed methods using improved PSO algorithms are more robust and efficient than the traditional FORM methods for solving high-dimensional engineering problems.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Civil
Siyu Zhu, Tianyu Xiang
Summary: The stochastic pseudo excitation method (SPEM), based on the PEM principle, is introduced to represent the randomness of dynamic input by using the amplitude of excitation as a random variable. It offers an effective way to solve dynamic reliability problems. By integrating the new algorithm into the FORM, the dynamic reliability of uncertain structures subjected to random excitation can be studied.
INTERNATIONAL JOURNAL OF STRUCTURAL STABILITY AND DYNAMICS
(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
Engineering, Multidisciplinary
Jan Christoph Krueger, Micah Kranz, Timo Schmidt, Robert Seifried, Benedikt Kriegesmann
Summary: A modified robust design optimization approach is presented in this paper, which computes the mean value and standard deviation for arbitrary objective functions using the first-order second-moment method. Existing approaches for computing the variance gradient are either reliant on the finite element code or computationally expensive. The novel approach provided in this paper can be easily implemented as a non-intrusive method, with a cost equivalent to finite differences and independent of the number of variables. It also offers an analytic alternative with wider applicability.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2023)
Article
Mathematics, Applied
Qian Yu, Kunyang Wang, Binhu Xia, Yibao Li
Summary: This paper utilizes the phase field method to address the compliance minimization problem in topology optimization, proposing equations and evolution schemes while demonstrating efficiency and accuracy through experiments.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Computer Science, Software Engineering
Zherong Pan, Xifeng Gao, Kui Wu
Summary: Topology Optimization (TO) is crucial for optimizing load-bearing mechanical parts. We propose a new TO solver using the Projected Gradient Descent algorithm and inexact Finite Element Analysis. We prove its convergence to a first-order critical point.
COMPUTER-AIDED DESIGN
(2023)
Article
Computer Science, Interdisciplinary Applications
Wellison Jose de Santana Gomes, Alexandre Galiani Garmbis, Andre Teofilo Beck
Summary: This paper proposes a hybrid approach to solve highly nonlinear time-variant reliability problems through the combination of Monte Carlo Simulation (MCS), First-Order Reliability Method (FORM) and a root-finding method. The approach achieves efficiency by classifying initial crack size samples and computing non-zero probabilities, and solves the optimization problem based on information acquired from a single Monte Carlo run. The proposed approach demonstrates efficiency and convergence to reference solutions.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Engineering, Civil
Marcos A. Valdebenito, Xiukai Yuan, Matthias G. R. Faes
Summary: This paper presents an approach for estimating the fuzzy failure probability associated with reliability problems. The main contribution of this work is addressing the problem with the First-Order Reliability Method, with some minor modifications. The proposed approach can provide an estimate of the membership function associated with the failure probability with reduced numerical costs.
Article
Computer Science, Artificial Intelligence
Pan Zhou, Xiao-Tong Yuan, Shuicheng Yan, Jiashi Feng
Summary: The paper introduces an efficient Riemannian Stochastic Path Integrated Differential Estimator algorithm for solving finite and online Riemannian non-convex minimization problems with lower computational cost compared to prior algorithms. The algorithm's recursive gradient estimation mechanism allows it to achieve epsilon-approximate stationary points within a certain number of stochastic gradient evaluations, outperforming other Riemannian optimization methods.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2021)
Article
Computer Science, Interdisciplinary Applications
Xuchun Ren, Xiaodong Zhang
Summary: This study introduces a novel method for topology optimization by integrating polynomial dimensional decomposition, topology derivative, and level-set method to effectively deal with a large number of random inputs. The approach allows for the analysis of stochastic moments and sensitivities through analytical expressions, while utilizing the level-set function and reaction-diffusion equation for topology evolution.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Mathematics, Applied
Spyridon Pougkakiotis, Dionysis Kalogerias
Summary: In this paper, we analyze a zeroth-order proximal stochastic gradient method for weakly convex stochastic optimization problems. The proposed algorithm utilizes Gaussian smoothing technique to estimate the zeroth-order gradient of a related partially smooth surrogate problem. This method does not require first-order information and provides state-of-the-art convergence rates.
SIAM JOURNAL ON SCIENTIFIC COMPUTING
(2023)
Article
Multidisciplinary Sciences
Sanmun Kim, Chanhyung Park, Shinho Kim, Haejun Chung, Min Seok Jang
Summary: This work reports on the influence of design parameters on the optical efficiency of metasurface-based color splitters, as well as the possibility of fabricating them in legacy fabrication facilities with low structure resolutions.
