Article
Engineering, Mechanical
Cheng Lu, Cheng-Wei Fei, Yun-Wen Feng, Yong-Jun Zhao, Xiao-Wei Dong, Yat-Sze Choy
Summary: The paper proposes a modified Kriging-based moving extremum framework (MKMEF) method for efficient probabilistic analysis of structural dynamic response, which utilizes extremum thought, MLS technique, and CEGA algorithm. A case study on aeroengine high-pressure turbine blisk validates the effectiveness of the method in considering fluid-thermal-solid interaction for radial running deformation.
ENGINEERING FAILURE ANALYSIS
(2021)
Article
Engineering, Mechanical
Jun-Yu Chen, Yun-Wen Feng, Da Teng, Wei-Huang Pan, Jia-Qi Liu
Summary: By combining dimensionality reduction and extremum response surface method, a dimensionality reduction-based extremum surrogate modeling strategy is developed to improve the transient reliability analysis of complex structures. The proposed method shows high modeling efficiency, low fitting error, excellent simulation efficiency, and simulation precision.
ENGINEERING FAILURE ANALYSIS
(2021)
Article
Mathematics
Hau T. Mai, Jaewook Lee, Joowon Kang, H. Nguyen-Xuan, Jaehong Lee
Summary: This paper presents an improved surrogate blind Kriging (IBK) and a combined infill strategy to solve constrained expensive black-box optimization problems. By enhancing the prediction accuracy of metamodels and updating them with an infill strategy, IBK can efficiently find the optimal solution and has been successfully applied to structural design optimization.
Article
Engineering, Civil
Shuangsheng Zhang, Jing Qiang, Hanhu Liu, Xiaonan Wang, Junjie Zhou, Dongliang Fan
Summary: This article proposes a new strategy for constructing an adaptive dynamic kriging surrogate model and applies it to optimize the remediation of contaminated groundwater. The model can effectively avoid the risk of losing the optimal solution and improve computational efficiency and accuracy.
WATER RESOURCES MANAGEMENT
(2022)
Article
Engineering, Marine
Yuliang Zhao, Sheng Dong
Summary: This study focuses on predicting fatigue damage of bimodal tension process using surrogate models like artificial neural network and kriging models, aiming to improve accuracy and efficiency. A parametric study, fatigue failure probability calculation, and long-term fatigue analysis under arbitrary wave conditions are conducted. The results show that the surrogate models-based approach provides a more accurate assessment of fatigue failure probability compared to spectral-based methods.
Article
Engineering, Civil
Abdul-Kader El Haj, Abdul-Hamid Soubra
Summary: This paper introduces a cost-effective probabilistic approach in engineering applications, consisting of an improved Kriging-based method to minimize the number of evaluations of the true performance function when computing a failure probability. The proposed approach, a variant of the classical Active learning method combining Kriging and Monte Carlo Simulation, has shown great efficiency compared to the classical AK-MCS approach.
Article
Engineering, Mechanical
Umberto Alibrandi, Lars V. Andersen, Enrico Zio
Summary: This paper applies information theory to probabilistic sensitivity analysis and surrogate modelling with active learning. It introduces a new measure of dependence between random variables using the informational coefficient of correlation. The paper also presents effective informational sensitivity indices based on mutual information and proposes two novel learning functions for adaptive sampling. Numerical examples demonstrate the features and potential applications of the proposed approach.
PROBABILISTIC ENGINEERING MECHANICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Behrooz Keshtegar, Mansour Bagheri, Cheng-Wei Fei, Cheng Lu, Osman Taylan, Duc-Kien Thai
Summary: Efficient modeling framework is necessary for nonlinear dynamic analyses of complex mechanical components. Accurate surrogate model for nonlinear responses of failures is important for robust and safe design conditions. The proposed Modified multi-extremum Response Surface basis Models (MRSM) use regression processes and sensitivity analysis to evaluate input variables and approximate dynamic structural analysis effectively.
ENGINEERING WITH COMPUTERS
(2022)
Article
Engineering, Aerospace
Gaiya Feng, Jiongran Wen, Chengwei Fei
Summary: A Marine Predators Algorithm (MPA)-based Kriging (MPA-Kriging) method is developed to predict the low-cycle fatigue (LCF) lifetime and estimate the reliability of turbine blisks. By introducing the MPA into the Kriging model, the MPA-Kriging method improves the modeling accuracy and simulation precision in reliability analysis. The proposed method demonstrates high precision and efficiency in LCF lifetime reliability prediction of turbine blisks, providing a promising approach for the evaluation of complicated structures.
Article
Mathematics
Yaohui Li, Junjun Shi, Zhifeng Yin, Jingfang Shen, Yizhong Wu, Shuting Wang
Summary: The proposed high-dimensional Kriging modeling method through principal component dimension reduction (HDKM-PCDR) can achieve faster modeling efficiency while reducing time consumption.
Article
Engineering, Mechanical
Bin Bai, Li Xiang, Xinye Li
Summary: This study proposes a methodology based on a reduced-order model to investigate the probabilistic distribution of intentionally mistuned blisk, and compares it with tuned and passive mistuned blisks. The results demonstrate that the proposed method effectively enhances stability and reduces output response, which is of great significance for probabilistic design of complex mechanical structures.
PROBABILISTIC ENGINEERING MECHANICS
(2022)
Article
Engineering, Multidisciplinary
Hui Liu, Ning-Cong Xiao
Summary: This study proposes an effective global non-probabilistic sensitivity analysis method based on adaptive Kriging model, which can analyze the key variables of product reliability in early design stage, with the advantages of reducing computational cost and ease of use.
EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY
(2022)
Article
Engineering, Industrial
R. Allahvirdizadeh, A. Andersson, R. Karoumi
Summary: This article focuses on the impact of high-speed trains on bridge safety due to excessive vibrations. It challenges the reliability and optimality of conventional design methods related to running safety and proposes a new approach called Reliability-Based Design Optimization. The new method uses minimum allowable mass and stiffness values to ensure the desired target reliability for running safety, without the need for dynamic analysis. Kriging meta-models and the Copula concept are used to improve the accuracy of the computational models and refine the RBDO problem, respectively.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Mechanical
Da Teng, Yun-Wen Feng, Jun-Yu Chen
Summary: In this study, an intelligent weighted Kriging-based moving extremum framework is developed by incorporating moving least squares thought, Gaussian weight, particle swarm optimization method and Kriging model into extremum response surface method. The effectiveness of the method is demonstrated through the verification of radial deformation of turbine blisk, showing high performance compared to direct simulation, ERSM and traditional Kriging model.
ENGINEERING FAILURE ANALYSIS
(2022)
Article
Computer Science, Artificial Intelligence
Shu-Chuan Chu, Zhi-Gang Du, Yan-Jun Peng, Jeng-Shyang Pan
Summary: A new algorithm combining fuzzy surrogate-assisted and probabilistic particle swarm optimization is proposed to solve high-dimensional expensive problems. By fitting fitness evaluation functions using various models and implementing particle swarm optimization, the algorithm aims to improve performance in solving high-dimensional problems.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Behrooz Keshtegar, Mansour Bagheri, Cheng-Wei Fei, Cheng Lu, Osman Taylan, Duc-Kien Thai
Summary: Efficient modeling framework is necessary for nonlinear dynamic analyses of complex mechanical components. Accurate surrogate model for nonlinear responses of failures is important for robust and safe design conditions. The proposed Modified multi-extremum Response Surface basis Models (MRSM) use regression processes and sensitivity analysis to evaluate input variables and approximate dynamic structural analysis effectively.
ENGINEERING WITH COMPUTERS
(2022)
Article
Engineering, Aerospace
Chengwei Fei, Haotian Liu, Yatsze Choy, Lei Han, Rhea Patricia Liem
Summary: This article introduces a Hierarchical Model Updating Strategy (HMUS) for the dynamic model updating of complex assembled structures. The proposed strategy demonstrates high accuracy and efficiency in handling complex geometry, high nonlinearity, and numerous parameters.
CHINESE JOURNAL OF AERONAUTICS
(2022)
Article
Engineering, Mechanical
Lei Han, Peiyuan Li, Shengjie Yu, Cao Chen, Chengwei Fei, Cheng Lu
Summary: In this study, creep/fatigue accelerated failures of K403 superalloy turbine blades were examined in the laboratory, revealing damage behaviors and determining failure modes. The results conclude that significant discrepancies in fractographies and cross-sectional microstructures can be explained through qualitative and quantitative investigations. The observed morphologies are primarily attributed to dendrite separation and gamma' phase rafting behaviors, as well as the development of a "void migration mechanism" involving grain interior, grain boundary, and sub grain boundary. The failure of turbine blades shifts from a mixed mode to an intergranular mode, which is controlled by the contribution proportion of creep damage and fatigue damage.
INTERNATIONAL JOURNAL OF FATIGUE
(2022)
Article
Engineering, Electrical & Electronic
Mingpan Bi, Yinping Miao, Wenjie Li, Chengwei Fei, Kailiang Zhang
Summary: In this study, an ultrasensitive microfiber sensor integrated with Nb2CTX nanosheets was proposed and designed, which showed temperature compensation and potential applications in biosensing and environmental pollution monitoring.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2022)
Article
Chemistry, Multidisciplinary
Huan Li, Siqi Bu, Jiong-Ran Wen, Cheng-Wei Fei
Summary: Improving the stability of the power system by accurately identifying the modal parameters of DLFO and controlling the oscillation in time is crucial. A new method called SMPI, based on EMD, SSI, and Prony algorithms, efficiently matches the modal parameters of DLFO. The SMPI method demonstrates great accuracy in identifying full modal parameters and shows potential in troubleshooting various fields.
APPLIED SCIENCES-BASEL
(2022)
Article
Chemistry, Multidisciplinary
Yunwen Feng, Zhicen Song, Cheng Lu
Summary: This study proposes a mathematical product option selection optimization model combined with an Improved Non-dominated Sorting Genetic Algorithm for customized option selection in civil aircraft. The model aims to decrease aircraft fleet maintenance cost and improve availability. The effectiveness of the model is verified using the landing gear system. After optimization, the aircraft fleet maintenance cost is reduced by 20.71% and the availability is increased by 2.576%.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Industrial
Jun-Yu Chen, Yun-Wen Feng, Da Teng, Cheng Lu, Cheng-Wei Fei
Summary: This study develops a support vector machine-based similarity selection genetic algorithm for transient reliability analysis of structures and verifies its effectiveness through analyzing the stress of the nose landing gear shock strut outer fitting. The results show that the developed method has excellent modeling and simulation performance, and it outperforms other methods in terms of simulation characteristics and precision. This study provides a promising method for transient structural reliability analysis, which has the potential to improve the operational safety and reliability of the system.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Multidisciplinary
Cheng-Wei Fei, Huan Li, Cheng Lu, Lei Han, Behrooz Keshtegar, Osman Taylan
Summary: A synchronous modeling concept is proposed to improve the computational cost and accuracy for the multi-objective reliability design of complex structures. The Vectorial Surrogate Modeling (VSM) method is developed for synchronously establishing an overall model with multiple objectives. The VSM method shows superior performances in computational efficiency and accuracy for high-dimensional nonlinear problems.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Engineering, Aerospace
Cheng Lu, Huan Li, Lei Han, Behrooz Keshtegar, Cheng-Wei Fei
Summary: This paper develops a bi-iterative moving enhanced modeling (BIMEM) approach for probabilistic-based transient low cycle fatigue (LCF) prediction of aeroengine turbine blisk. The developed approach integrates extremum thought, Kriging model, moving least squares (MLS) technique, and modified particle swarm optimization (MPSO) algorithm. The results show that the reliability degree of the turbine blisk is 0.9986 when the allowable LCF life is 2968 cycles, and the primary factor affecting the LCF life is the strength coefficient, followed by gas temperature and fatigue strength exponent.
AEROSPACE SCIENCE AND TECHNOLOGY
(2023)
Article
Engineering, Mechanical
Cheng Lu, Da Teng, Behrooz Keshtegar, Abdulaziz S. Alkabaa, Osman Taylan, Cheng-Wei Fei
Summary: In complex aeroengine structures, it is important to consider multi-physical loads for safe design. This study proposes hybrid artificial neural network (ANN) models to simulate the failure modes of turbine blisk, using machine learning approaches. The accuracy of ANN-based models is discussed using six music-inspired optimization algorithms. The Gaussian GHS algorithm shows superior performance with the highest accuracy and tendency among the other optimization algorithms.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Industrial
Cheng Lu, Da Teng, Jun -Yu Chen, Cheng-Wei Fei, Behrooz Keshtegar
Summary: In this paper, the concept of vectorial modeling is proposed by introducing matrix theory into the point modeling concept. An adaptive vectorial surrogate modeling framework (AVSMF) is developed based on this concept and adaptive modeling strategy. The effectiveness of AVSMF is demonstrated through three examples and comparison with other methods, showing its advantages in computational efficiency and precision.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Aerospace
Gaiya Feng, Jiongran Wen, Chengwei Fei
Summary: A Marine Predators Algorithm (MPA)-based Kriging (MPA-Kriging) method is developed to predict the low-cycle fatigue (LCF) lifetime and estimate the reliability of turbine blisks. By introducing the MPA into the Kriging model, the MPA-Kriging method improves the modeling accuracy and simulation precision in reliability analysis. The proposed method demonstrates high precision and efficiency in LCF lifetime reliability prediction of turbine blisks, providing a promising approach for the evaluation of complicated structures.
Article
Engineering, Aerospace
Chunyi Zhang, Zheshan Yuan, Huan Li, Jiongran Wen, Shengkai Zheng, Chengwei Fei
Summary: A multi-extremum adaptive fuzzy network method is proposed to enhance the accuracy and efficiency of reliability analysis for an aero-engine vectoring exhaust nozzle. The method combines the multi-extremum surrogate model technique with an adaptive neuro-fuzzy inference system to improve the modeling precision and approximation capability of the neural network model.
Article
Computer Science, Hardware & Architecture
Chao Huang, Siqi Bu, Cheng-Wei Fei, Namkyoung Lee, Shu Wa Kong
Summary: This article presents a unified reliability assessment method for aeroengine blisks considering multiple uncertainties. By utilizing the ensemble generalized constraint neural network, the time-consuming issue of probabilistic finite-element model simulation is overcome.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Engineering, Aerospace
Chengwei Fei, Jiongran Wen, Lei Han, Bo Huang, Cheng Yan
Summary: An optimizable image segmentation method (OISM) based on SLIC, feature migration model, and RF classifier is proposed for solving the small sample image segmentation problem. It is demonstrated that the proposed method has acceptable accuracy and retains better target boundary.
Article
Engineering, Aerospace
Andre F. P. Ribeiro, Carlos Ferreira, Damiano Casalino
Summary: This study compares a filament-based free wake panel method to experimental and validated numerical data in order to simulate propeller slipstreams and their interaction with aircraft components. The results show that the free wake panel method is able to successfully capture the slipstream deformation and shearing, making it a useful tool for propeller-wing interaction in preliminary aircraft design.
AEROSPACE SCIENCE AND TECHNOLOGY
(2024)