Mustafa Sami Abdullatef^*, Faten N. Alzubaidi, Anees Al-Tamimi, Yasser Ahmed Mahmood

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.8, pp. 2083-2107, 2023, DOI:10.32604/fdmp.2023.027266

Abstract The ongoing effort to create methods for detecting and quantifying fatigue damage is motivated by the high levels of uncertainty in present fatigue-life prediction approaches and the frequently catastrophic nature of fatigue failure. The fatigue life of high strength aluminum alloy 2090-T83 is predicted in this study using a variety of artificial intelligence and machine learning techniques for constant amplitude and negative stress ratios (). Artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), support-vector machines (SVM), a random forest model (RF), and an extreme-gradient tree-boosting model (XGB) are trained using numerical and experimental input data obtained from fatigue tests… More > Graphic Abstract

Yanju Wang¹, Zhenyu Zhu², Aixue Sha¹, Wenfeng Hao^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2655-2676, 2023, DOI:10.32604/cmes.2023.025749

Abstract Many titanium alloy subcomponents are subjected to fatigue loading in aerospace engineering, resulting in fatigue failure. The fatigue behavior of Ti₂AlNb alloy subcomponents was investigated based on the Seeger fatigue life theory and the improved Lemaitre damage evolution theory. Firstly, the finite element models of the standard openhole specimen and Y-section subcomponents have been established by ABAQUS. The damage model parameters were determined by fatigue tests, and the reliability of fatigue life simulation results of the Ti₂AlNb alloy standard open-hole specimen was verified. Meanwhile, the fatigue life of Ti₂AlNb alloy Y-section subcomponents was predicted. Under the same initial conditions, the… More >

Ying Wang^*, Zheng Yan, Yangyang Wu

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1339-1370, 2023, DOI:10.32604/cmes.2023.025830

Abstract In this paper, a numerical model of fretting fatigue analysis of cable wire and the fretting fatigue damage constitutive model considering the multi-axis effect were established, and the user material subroutine UMAT was written. Then, the constitutive model of wear morphology evolution of cable wire and the constitutive model of pitting evolution considering the mechanical-electrochemical effect were established, respectively. The corresponding subroutines UMESHMOTION_Wear and UMESHMOTION_Wear_Corrosion were written, and the fretting fatigue life was further predicted. The results show that the numerical simulation life obtained by the program in this paper has the same trend as the tested one; the error… More > Graphic Abstract

Donghai Li^1,2, Jiawei Tian¹, Shengwen Shi², Shanchao Wang², Jucai Deng², Shuilong He^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 421-445, 2023, DOI:10.32604/cmes.2023.024133

Abstract To better improve the lightweight and fatigue durability performance of the tractor cab, a multi-objective lightweight design of the cab was carried out in this study. First, the finite element model of the cab with counterweight loading was established and then confirmed by the physical testing, and use the inertial relief method to obtain stress distribution under unit load. The cab-frame rigid-flexible coupling multi-body dynamics model was built by Adams/car software. Taking the cab airbag mount displacement and acceleration signals acquired on the proving ground as the desired signals and obtaining the fatigue analysis load spectrum through Femfat-Lab virtual iteration.… More > Graphic Abstract

Jun Zhang¹, Xiaobin Li¹, Long Zhao^2,*, Zixin Li¹, Shuo Wang¹, Pan Yao¹, Pengfei Dai²

Energy Engineering, Vol.120, No.3, pp. 617-631, 2023, DOI:10.32604/ee.2022.024855

Abstract In this paper, the research on ACSR temperature of broken strand and fatigue damage after broken strand is carried out. Conduct modeling and Analysis on the conductor through Ansoft Maxwell software. The distribution of magnetic force lines in the cross section of the conductor after strand breaking and the temperature change law of the conductor with the number of broken strands are analyzed. A model based on electromagnetic theory is established to analyze the distribution of magnetic lines of force in the cross section of the conductor after strand breaking and the temperature variation law of the conductor with the… More >

Rong Yuan¹, Ruitao Chen², Haiqing Li^3,*, Wenke Yang¹, Xiaoxiao Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2331-2347, 2023, DOI:10.32604/cmes.2023.023788

Abstract Wind power is a kind of important green energy. Thus, wind turbines have been widely utilized around the world. Wind turbines are composed of many important components. Among these components, the failure rate of the transmission system is relatively high in wind turbines. It is because the components are subjected to aerodynamic loads for a long time. In addition, its inertial load will result in fatigue fracture, wear and other problems. In this situation, wind turbines have to be repaired at a higher cost. Moreover, the traditional reliability methods are difficult to deal with the above challenges when performing the… More >

Mingyong Li¹, Lirong Tang¹, Longfei Ma¹, Honggang Zhao¹, Jinyu Hu¹, Yan Wei^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2349-2371, 2023, DOI:10.32604/cmes.2023.022604

Abstract The learning status of learners directly affects the quality of learning. Compared with offline teachers, it is difficult for online teachers to capture the learning status of students in the whole class, and it is even more difficult to continue to pay attention to students while teaching. Therefore, this paper proposes an online learning state analysis model based on a convolutional neural network and multi-dimensional information fusion. Specifically, a facial expression recognition model and an eye state recognition model are constructed to detect students’ emotions and fatigue, respectively. By integrating the detected data with the homework test score data after… More >

Junya Tanehashi¹, Szuchi Chang², Takahiro Hirosei³, Masaki Izawa², Aman Goyal², Ayumi Takahashi⁴, Kazuhito Misaji^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2287-2306, 2023, DOI:10.32604/cmes.2023.022432

Abstract This research aims to quantify driver ride comfort due to changes in damper characteristics between comfort mode and sport mode, considering the vehicle’s inertial behavior. The comfort of riding in an automobile has been evaluated in recent years on the basis of a subjective sensory evaluation given by the driver. However, reflecting driving sensations in design work to improve ride comfort is abstract in nature and difficult to express theoretically. Therefore, we evaluated the human body’s effects while driving scientifically by quantifying the driver’s behavior while operating the steering wheel and the behavior of the automobile while in motion using… More > Graphic Abstract

Xiaoli Wei¹, D. A. Makhloof^1,2, Xiaodan Ren^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 9-34, 2023, DOI:10.32604/cmes.2022.020160

Abstract Fatigue failure phenomena of the concrete structures under long-term low amplitude loading have attracted more attention. Some structures, such as wind power towers, offshore platforms, and high-speed railways, may resist millions of cycles loading during their intended lives. Over the past century, analytical methods for concrete fatigue are emerging. It is concluded that models for the concrete fatigue calculation can fall into four categories: the empirical model relying on fatigue tests, fatigue crack growth model in fracture mechanics, fatigue damage evolution model based on damage mechanics and advanced machine learning model. In this paper, a detailed review of fatigue computing… More >

Fei Wang^1,2, Yinxing Wan¹, Man Li^1,2, Haiyun Huang^1,2, Li Li¹, Xueying Hou¹, Jiahui Pan^1,2, Zhenfu Wen³, Jingcong Li^1,2,*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3573-3586, 2023, DOI:10.32604/iasc.2023.029698

Abstract Fatigue is a state commonly caused by overworked, which seriously affects daily work and life. How to detect mental fatigue has always been a hot spot for researchers to explore. Electroencephalogram (EEG) is considered one of the most accurate and objective indicators. This article investigated the development of classification algorithms applied in EEG-based fatigue detection in recent years. According to the different source of the data, we can divide these classification algorithms into two categories, intra-subject (within the same subject) and cross-subject (across different subjects). In most studies, traditional machine learning algorithms with artificial feature extraction methods were commonly used… More >