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Structural and Multidisciplinary Optimization最新文献

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Topology optimization of multi-material active structures to reduce energy consumption and carbon footprint 拓扑优化多材料活性结构,降低能耗和碳足迹
IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-01-01 DOI: 10.1007/s00158-023-03698-3
Yafeng Wang, Ole Sigmund
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引用次数: 0
Active learning for adaptive surrogate model improvement in high-dimensional problems. 在高维问题中改进自适应代用模型的主动学习。
IF 3.6 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2024-01-01 Epub Date: 2024-07-10 DOI: 10.1007/s00158-024-03816-9
Yulin Guo, Paromita Nath, Sankaran Mahadevan, Paul Witherell

This paper investigates a novel approach to efficiently construct and improve surrogate models in problems with high-dimensional input and output. In this approach, the principal components and corresponding features of the high-dimensional output are first identified. For each feature, the active subspace technique is used to identify a corresponding low-dimensional subspace of the input domain; then a surrogate model is built for each feature in its corresponding active subspace. A low-dimensional adaptive learning strategy is proposed to identify training samples to improve the surrogate model. In contrast to existing adaptive learning methods that focus on a scalar output or a small number of outputs, this paper addresses adaptive learning with high-dimensional input and output, with a novel learning function that balances exploration and exploitation, i.e., considering unexplored regions and high-error regions, respectively. The adaptive learning is in terms of the active variables in the low-dimensional space, and the newly added training samples can be easily mapped back to the original space for running the expensive physics model. The proposed method is demonstrated for the numerical simulation of an additive manufacturing part, with a high-dimensional field output quantity of interest (residual stress) in the component that has spatial variability due to the stochastic nature of multiple input variables (including process variables and material properties). Various factors in the adaptive learning process are investigated, including the number of training samples, range and distribution of the adaptive training samples, contributions of various errors, and the importance of exploration versus exploitation in the learning function.

本文研究了一种新方法,用于在具有高维输入和输出的问题中高效构建和改进代理模型。在这种方法中,首先要确定高维输出的主成分和相应特征。对于每个特征,使用主动子空间技术识别输入域的相应低维子空间;然后在相应的主动子空间中为每个特征建立代用模型。我们提出了一种低维自适应学习策略,用于识别训练样本以改进代理模型。与关注标量输出或少量输出的现有自适应学习方法相比,本文针对高维输入和输出的自适应学习,采用了一种新的学习函数,在探索和利用之间取得了平衡,即分别考虑了未探索区域和高误差区域。自适应学习以低维空间中的活动变量为单位,新添加的训练样本可以很容易地映射回原始空间,以运行昂贵的物理模型。所提出的方法在增材制造部件的数值模拟中得到了验证,该部件的高维场输出量(残余应力)由于多个输入变量(包括过程变量和材料属性)的随机性而具有空间可变性。研究了自适应学习过程中的各种因素,包括训练样本的数量、自适应训练样本的范围和分布、各种误差的贡献以及学习函数中探索与利用的重要性。
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引用次数: 0
Concurrent optimization of actuator/sensor layout and control parameter on piezoelectric curved shells with active vibration control for minimizing transient noise 同时优化具有主动振动控制功能的压电曲面壳上的致动器/传感器布局和控制参数,以最大限度地降低瞬态噪声
IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-12-21 DOI: 10.1007/s00158-023-03707-5
Hao Zheng, Guozhong Zhao, Wen-Xi Han, Yang Yu, Weizhen Chen
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引用次数: 0
Aerodynamic shape optimization of gas turbines: a deep learning surrogate model approach 燃气轮机气动外形优化:深度学习代用模型方法
IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-12-21 DOI: 10.1007/s00158-023-03703-9
Vahid Esfahanian, Mohammad Javad Izadi, Hosein Bashi, Mehran Ansari, Alireza Tavakoli, Mohammad Kordi
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引用次数: 0
Stability constraints for geometrically nonlinear topology optimization 几何非线性拓扑优化的稳定性约束
IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-12-01 DOI: 10.1007/s00158-023-03712-8
Peter D. Dunning
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引用次数: 0
Multi-material and thickness optimization of laminated composite structures subject to high-cycle fatigue 承受高循环疲劳的层压复合材料结构的多材料和厚度优化
IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-12-01 DOI: 10.1007/s00158-023-03708-4
S. Hermansen, Erik Lund
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引用次数: 0
Two-stage optimization method for design of reinforced concrete frames using optimal pre-determined section database and non-revisiting genetic algorithm 利用最优预设截面数据库和非重访遗传算法设计钢筋混凝土框架的两阶段优化方法
IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-12-01 DOI: 10.1007/s00158-023-03709-3
A. Tanhadoust, M. Madhkhan, M. Daei
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引用次数: 0
An efficient 2D/3D NURBS-based topology optimization implementation using page-wise matrix operation in MATLAB 在 MATLAB 中使用分页矩阵运算实现基于 NURBS 的高效二维/三维拓扑优化
IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-12-01 DOI: 10.1007/s00158-023-03701-x
Chungang Zhuang, Z. Xiong, Han Ding
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引用次数: 0
An efficient uncertainty propagation analysis method of non-parameterized P-boxes based on dimension-reduction integral and maximum entropy estimation 基于降维积分和最大熵估计的非参数化 P-box 的高效不确定性传播分析方法
IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-12-01 DOI: 10.1007/s00158-023-03705-7
Huichao Xie, Jinwen Li, Haibo Liu, Hao Hu, Daihui Liao
{"title":"An efficient uncertainty propagation analysis method of non-parameterized P-boxes based on dimension-reduction integral and maximum entropy estimation","authors":"Huichao Xie, Jinwen Li, Haibo Liu, Hao Hu, Daihui Liao","doi":"10.1007/s00158-023-03705-7","DOIUrl":"https://doi.org/10.1007/s00158-023-03705-7","url":null,"abstract":"","PeriodicalId":21994,"journal":{"name":"Structural and Multidisciplinary Optimization","volume":"267 ","pages":""},"PeriodicalIF":3.9,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138991854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A co-optimization method of thermal-stress coupling 3D integrated system with through silicon via 带硅通孔的热应力耦合三维集成系统的共同优化方法
IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2023-11-29 DOI: 10.1007/s00158-023-03706-6
Xianglong Wang, Dongdong Chen, Di Li, Yintang Yang
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引用次数: 0
期刊
Structural and Multidisciplinary Optimization
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