Article
Engineering, Industrial
Xiaoke Li, Heng Zhu, Zhenzhong Chen, Wuyi Ming, Yang Cao, Wenbin He, Jun Ma
Summary: This paper proposed an adaptive Kriging sampling strategy based on Classification Uncertainty Quantification (KCUQ) to address the low modeling efficiency and unsatisfied modeling accuracy issues in existing Kriging-assisted RBDO methods. The KCUQ method effectively considers the classification uncertainty of the Kriging model and updates the performance function with the largest classification error in each iteration for adaptive modeling based on unique features. Two numerical case studies were conducted to demonstrate the performance of the proposed KCUQ method in vehicle crashworthiness and axle bridge optimization applications.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Mechanical
Yongsu Jung, Kyeonghwan Kang, Hyunkyoo Cho, Ikjin Lee
Summary: The paper proposes a confidence-based design optimization (CBDO) to find a conservative optimum under surrogate model uncertainty, using Gaussian process modeling and metamodel-based optimization methods to reduce computational burden. The method introduces confidence to describe the uncertainty of reliability, and stochastic sensitivity analysis is developed to find a conservative optimum compared to RBDO at a specific confidence level.
JOURNAL OF MECHANICAL DESIGN
(2021)
Article
Computer Science, Hardware & Architecture
Chunyan Ling, Way Kuo, Min Xie
Summary: This study reviews the advantages and disadvantages of using surrogate models to streamline reliability-based design optimization (RBDO), as well as discussing the problems that need to be solved.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Mathematics
Shengwen Yin, Yuan Gao, Xiaohan Zhu, Zhonggang Wang
Summary: A novel anisotropy-based adaptive polynomial chaos (ABAPC) expansion method was developed to optimize structural-acoustic systems. The ABAPC method can efficiently reduce the computational cost and improve the computational efficiency of reliability-based design optimization.
Article
Engineering, Industrial
Sina Shirgir, Amir Shamsaddinlou, Reza Najafi Zare, Sorour Zehtabiyan, Masoud Hajialilue Bonab
Summary: This paper focuses on the optimization and reliability analysis of the optimum design of the nailing system for soil walls. The results demonstrate the significant influence of uncertainty in soil mechanical parameters on the reliability of the soil nail system. The reliability-based design optimization outcomes reveal that a nailing system can be designed to achieve the expected reliability and failure probability level.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Chemistry, Multidisciplinary
Shuang Zhou, Jianguo Zhang, Qingyuan Zhang, Ying Huang, Meilin Wen
Summary: This paper proposes an efficient uncertainty theory-based reliability analysis and design method to address the trade-offs between safety and cost in the early stage of structural design. It introduces the concept of uncertain measure and uses URI to estimate the reliable degree of structure. A URI-based design optimization model (URBDO) is constructed to tackle the problem of insufficient data in reliability analysis.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Electrical & Electronic
Niloofar Rashidi, Qiong Wang, Rolando Burgos, Chris Roy, Dushan Boroyevich
Summary: This article discusses how to incorporate parametric and model-form uncertainty quantification into multi-objective design and optimization. By estimating and validating model errors, the optimal solution for system design can be obtained, reducing sensitivity and loss.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2021)
Article
Engineering, Mechanical
Genshen Liu, Huaiju Liu, Caichao Zhu, Tianyu Mao, Gang Hu
Summary: The fatigue failure of gear transmission is a key factor that limits the performance and service life of wind turbines. The disregard of dynamic fatigue reliability in conventional design methods under random loading conditions leads to various issues, such as overweight structure or insufficient fatigue reliability. A novel gear transmission optimization model based on dynamic fatigue reliability sensitivity is developed to predict the optimal structural parameters, reducing volume by 3.58% while ensuring fatigue reliability.
FRONTIERS OF MECHANICAL ENGINEERING
(2021)
Article
Engineering, Aerospace
Clara Cid, Aitor Baldomir, Santiago Hernandez
Summary: An efficient approximate reliability-based design optimization method is proposed to handle both aleatory and epistemic uncertainty. By merging probability and evidence theory, the belief and plausibility of a specific performance function under mixed uncertainty can be quantified. The proposed method effectively addresses the issue of high computational cost by decoupling the optimization problem into separate deterministic optimization and reliability analysis phases.
Article
Engineering, Aerospace
Xia Jiang, Zhenzhou Lu
Summary: This paper proposes a double-loop method, DL-AK-FS, for efficiently solving the design optimization problem with time-dependent failure possibility. The method combines the adaptive kriging model and fuzzy simulation, improving accuracy and efficiency when dealing with complex performance functions and multiple minimum performance target points.
Article
Engineering, Aerospace
Ming Huang, Zuohong Zhou, Kaiyuan Zhang, Zhigang Li, Jun Li
Summary: This investigation introduces an efficient parallel framework for uncertainty quantification, significantly reducing sample requirements while maintaining computational precision. The research findings reveal the significant factors contributing to the variability in leakage flow rate and cooling performance, emphasizing potential issues in operational conditions. Additionally, the study identifies the point at which the probability of blade failure sharply increases, indicating the need for mandatory overhaul.
AEROSPACE SCIENCE AND TECHNOLOGY
(2023)
Review
Mathematical & Computational Biology
Xiaoke Li, Qingyu Yang, Yang Wang, Xinyu Han, Yang Cao, Lei Fan, Jun Ma
Summary: Reliability-based design optimization (RBDO) involves handling uncertainties in engineering through surrogate models to reduce computational burden. This paper reviews commonly used surrogate modeling methods and discusses surrogate-assisted RBDO methods, including a comparison of existing methods, sample selection, and accuracy evaluation. Furthermore, global and local modeling methods are classified and compared using a two-dimensional RBDO numerical example, highlighting the advantages and disadvantages of each approach. Lastly, the paper provides a summary and future outlook on surrogate-assisted RBDO methods.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2021)
Article
Engineering, Mechanical
Sifeng Bi, Kui He, Yanlin Zhao, David Moens, Michael Beer, Jingrui Zhang
Summary: This paper investigates the NASA Langley Challenge on Optimization under Uncertainty by proposing approaches for both forward and inverse treatment of uncertainty propagation and quantification. The categorization of subproblems into forward or inverse procedures allows for dedicated techniques to be proposed for each direction. The focus is on balancing theoretical development and practical methods for uncertainty propagation and quantification.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Computer Science, Interdisciplinary Applications
Shuang Zhou, Jianguo Zhang, Qingyuan Zhang, Meilin Wen
Summary: This paper proposes a methodology of hybrid reliability analysis and optimization based on chance theory to control aleatory and epistemic uncertainties in the preliminary design phase of engineering structures. It uses random variables to describe aleatory uncertainty and uncertain variables to quantify epistemic uncertainty. The chance measure and chance reliability indicator (CRI) are introduced to model structural reliability in the presence of hybrid uncertainty. Two CRI estimation methods and two solving strategies are developed for mixed reliability assessment and design optimization. The performance and feasibility of the proposed analysis model and solution technique are verified through four engineering applications.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Zhou Yang, Unsong Pak, Yu Yan, Cholu Kwon
Summary: RBROD was conducted on a drum brake to reduce the influence of random parameters uncertainty on safety performance of vehicles, with a mathematical model established and results showing that the drum brake met reliability, robustness, and optimization design requirements. The adaptive Kriging method demonstrated the highest calculation accuracy and efficiency among the four meta-model methods used.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Mechanics
K. T. Hughes, S. Balachandar, A. Diggs, R. Haftka, N. H. Kim, D. Littrell
Article
Materials Science, Composites
Yiming Zhang, Nam H. Kim, Upul R. Palliyaguru, Jaco F. Schutte, Raphael T. Haftka
JOURNAL OF COMPOSITE MATERIALS
(2020)
Article
Engineering, Mechanical
Seokgoo Kim, Nam Ho Kim, Joo-Ho Choi
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2020)
Article
Chemistry, Analytical
Seokgoo Kim, Nam Ho Kim, Joo-Ho Choi
Article
Energy & Fuels
Woosung Choi, Kanmaniraja Radhakrishnan, Nam-Ho Kim, Jun Su Park
Summary: This study proposes a multi-fidelity surrogate (MFS) model for predicting the heat transfer coefficient (HTC) on turbine blades. By comparing the prediction results of LF and HF surrogates, as well as the MFS model with the HF data, it is shown that the MFS model has advantages in accuracy and efficiency.
Article
Mechanics
K. T. Hughes, J. J. Charonko, K. P. Prestridge, N. H. Kim, R. T. Haftka, S. Balachandar
Summary: A series of experiments were conducted to study explosively driven multiphase flows at moderate-to-high volume fractions, with variations in particle beds and ambient fluids. Results showed that the primary impulse for particle bed motion in different volume fractions and ambient conditions arises from the contact interface between the ambient and detonation products.
Article
Engineering, Aerospace
Samaun Nili, Chanyoung Park, Nam H. Kim, Raphael T. Haftka, S. Balachandar
Summary: This study aims to quantify, rank, and isolate the contribution of error in each submodel to the error in the model prediction, using global sensitivity analysis as a tool.
Article
Chemistry, Multidisciplinary
Nam H. Kim, Ting Dong, David Weinberg, Jonas Dalidd
Summary: The study proposed a generalized optimality criteria method for topology optimization, capable of handling multiple inequality constraints with high computational efficiency.
APPLIED SCIENCES-BASEL
(2021)
Article
Materials Science, Multidisciplinary
James Nance, Ghatu Subhash, Bhavani Sankar, Rafael Haftka, Nam Ho Kim, Christian Deck, Sarah Oswald
Summary: Silicon carbide fiber-reinforced ceramic matrix composites are potential materials for nuclear fuel cladding, but residual stresses develop during fabrication. Micro-Raman spectroscopy was used to measure residual stress in SiC fibers at different stages of fabrication.
Review
Chemistry, Analytical
Seokgoo Kim, Joo-Ho Choi, Nam H. Kim
Summary: The paper reviews approaches for system-level prognostics, categorizing them into health index-based, component RUL-based, influenced component-based, and multiple failure mode-based prognostics. Two PHM datasets are used as examples to demonstrate system-level prognostics, while challenges for practical system-level prognostics are also discussed.
Article
Materials Science, Composites
Hemanth Thandaga Nagaraju, James Nance, Nam H. Kim, Bhavani Sankar, Ghatu Subhash
Summary: In this study, the variability in elastic constants of SiCf/SiCm composite was quantified using multiscale finite element simulations, variable screening, and high-fidelity surrogate modeling. The coefficient of variation was found to be less than 10%.
JOURNAL OF COMPOSITE MATERIALS
(2023)
Article
Chemistry, Analytical
Hyung Jun Park, Nam Ho Kim, Joo-Ho Choi
Summary: This paper explores the impact of sensor quality and data storage on the performance of predictive maintenance, and evaluates the accuracy and uncertainty of remaining useful life (RUL) prediction. By conducting numerical case studies and comparing real data sets, the cost-effectiveness of sensors for predictive maintenance is determined.
Article
Computer Science, Interdisciplinary Applications
Seokgoo Kim, Joo-Ho Choi, Nam Ho Kim
Summary: This paper introduces a physics-informed neural network (PINN) based prognostics method, which incorporates low-fidelity physics information as a constraint during the optimization process to reduce training uncertainty. Two case studies are conducted to demonstrate the effectiveness of reducing prediction uncertainty and the robustness to variability in test data.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Engineering, Manufacturing
Na Qiu, Depei Wang, Yajie Li, Mingwei Xiao, Qiang Gao, Nam H. H. Kim
Summary: Thin-walled structures are widely used in energy absorber design for their excellent crashworthiness. This paper proposes a new tapered structure called 'Conch tube' (CT) that imitates the shape of a conch shell, aiming to improve stability and energy absorption capacity. Numerical simulations show that by controlling the thread pitch and groove width, the deformation mode of the CT can be changed, resulting in a lower initial peak crushing force (IPCF). The effectiveness of the spiral groove structure in enhancing energy absorption and reducing IPCF is confirmed.
INTERNATIONAL JOURNAL OF CRASHWORTHINESS
(2023)
Article
Engineering, Aerospace
Ting Dong, Nam H. Kim
Summary: This paper discusses the challenges of identifying individual parameters when they are strongly correlated in physics-based prognostics. It introduces two methods to accurately determine the values of individual parameters in such cases. Experimental results show that the proposed methods are effective even in the presence of noise, reducing uncertainty in model parameters significantly.
