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Thermomechanical Behavior of Brake Drums Under Extreme Braking Conditions

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Computers, Materials & Continua 2022年第8期72卷 2259-2273页

作者： T.khatir M.Bouchetara K.Derrar M.Djafri s.khatir M.Abdel Wahab Institute of science and Technology University Center Salhi Ahmed NaamaAlgeria Laboratory of Gas Combustion and Environment University of Sciences and Technology of OranL.P 1505 El-MenaouerOranUSTO 31000Algeria High school of Aeronautic Techniques Dar El Beida Algeria Ho Chi Minh City Open University Ho Chi Minh CityViet Nam Faculty of Engineering Van Lang UniversityHo Chi Minh CityVietnam soete Laboratory Faculty of Engineering and ArchitectureGhent UniversityTechnologieparkZwijnaarde 903B-9052 ZwijnaardeBelgium

Braking efficiency is characterized by reduced braking time and distance,and therefore passenger safety depends on the design of the braking *** the braking of a vehicle,the braking system must dissipate the kinetic energy by transforming it into heat energy.A too high temperature can lead to an almost total loss of braking *** excessive rise in brake temperature can also cause surface cracks extending to the outside edge of the drum friction *** transfer and temperature gradient,not to forget the vehicle’s travel environment(high speed,heavy load,and steeply sloping road conditions),must thus be the essential criteria for any brake system *** aim of the present investigation is to analyze the thermal behavior of different brake drum designs during the single emergency braking of a heavy-duty vehicle on a steeply sloping *** calculation of the temperature field is performed in transient mode using a three-dimensional finite element model assuming a constant coefficient of *** this study,the influence of geometrical brake drum configurations on the thermal behavior of brake drums with two different materials in grey cast iron FG200 and aluminum alloy 356.0 reinforced with silicon carbide(siC)particles is analyzed under extreme vehicle braking *** numerical simulation results obtained using FE software ANsYs are qualitatively compared with the results already published in the literature.

关键词： Drum brake finite element method braking energy distribution friction heat power friction heat flux transient temperature field

Vibration-based crack prediction on a beam model using hybrid butterfly optimization algorithm with artificial neural network

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Frontiers of structural and Civil Engineering 2022年第8期16卷 976-989页

作者： Abdelwahhab khatir Roberto CAPOZUCCA samir khatir Erica MAGAGNINI structural section DICEA Polytechnic University of MarcheAncona 60131Italy Faculty of Civil Engineering Ho Chi Minh City Open UniversityHo Chi Minh City 700000Vietnam

Vibration-based damage detection methods have become widely used because of their advantages over traditional *** paper presents a new approach to identify the crack depth in steel beam structures based on vibration analysis using the Finite Element Method(FEM)and Artificial Neural Network(ANN)combined with Butterfly Optimization Algorithm(BOA).ANN is quite successful in such identification issues,but it has some limitations,such as reduction of error after system training is complete,which means the output does not provide optimal *** paper improves ANN training after introducing BOA as a hybrid model(BOA-ANN).Natural frequencies are used as input parameters and crack depth as *** data are collected from improved FEM using simulation tools(ABAQUs)based on different crack depths and locations as the first ***,data are collected from experimental analysis of cracked beams based on different crack depths and locations to test the reliability of the presented *** proposed approach,compared to other methods,can predict crack depth with improved accuracy.

关键词： damage prediction ANN BOA FEM experimental modal analysis

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An efficient improved Gradient Boosting for strain prediction in Near-surface Mounted fiber-reinforced polymer strengthened reinforced concrete beam

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Frontiers of structural and Civil Engineering 2024年第8期18卷 1148-1168页

作者： Abdelwahhab khatir Roberto CAPOZUCCA samir khatir Erica MAGAGNINI Brahim BENAIssA Thanh CUONG-LE structural section DICEA Polytechnic University of MarcheAncona 60131Italy Centre for Engineering Application&Technology solutions Ho Chi Minh City Open UniversityHo Chi Minh City 70000Vietnam Design Engineering Laboratory Toyota Technological InstituteNagoya 468-8511Japan

The Near-surface Mounted(NsM)strengthening technique has emerged as a promising alternative to traditional strengthening methods in recent *** the past two decades,researchers have extensively studied its potential,advantages,and applications,as well as related parameters,aiming at optimization of construction ***,there is still a need to explore further,both from a static perspective,which involves accounting for the nonconservation of the contact section resulting from the bond-slip effect between fiber-reinforced polymer(FRP)rods and resin and is typically neglected by existing analytical models,as well as from a dynamic standpoint,which involves studying the trends of vibration frequencies to understand the effects of various forms of damage and the efficiency of *** address this gap in knowledge,this research involves static and dynamic tests on simply supported reinforced concrete(RC)beams using rods of NsM carbon fiber reinforced polymer(CFRP)and glass fiber reinforced polymer(GFRP).The main objective is to examine the effects of various strengthening *** research conducts bending tests with loading cycles until failure,and it helps to define the behavior of beam specimens under various damage degrees,including concrete *** analysis by free vibration testing enables tracking of the effectiveness of the reinforcement at various damage levels at each stage of the loading *** addition,application of Particle swarm Optimization(PsO)and Genetic Algorithm(GA)is proposed to optimize Gradient Boosting(GB)training performance for concrete strain prediction in NsM-FRP *** GB using Particle swarm Optimization(GBPsO)and GB using Genetic Algorithm(GBGA)systems were trained using an experimental data set,where the input data was a static applied load and the output data was the consequent *** models of GBPsO and GBGA have been shown to provide highly accurate results for predicting *** model

关键词： NsM technique fiber-reinforced polymer rods static and dynamic analysis GB PsO GA finite element analysis

Fuzzy Adaptive Control of a Fractional Order Chaotic system With Unknown Control Gain sign Using a Fractional Order Nussbaum Gain

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IEEE/CAA Journal of Automatica sinica 2019年第3期6卷 816-823页

作者： khatir Khettab samir Ladaci Yassine Bensafia IEEE the Electrical Engineering Department University of Mohamed Boudiaf M’sila 28000 Algeria Electrical Engineering Department University of Skikda the EEA Department National Polytechnic School of Constantine B. P. 75 A Ali Mendjli 25000 Constantine Algeria sP-Lab Laboratory Department of Electronics Mentouri University Yassine Bensafia is with the Electrical Engineering Department University of Bouira

In this paper we propose an improved fuzzy adaptive control strategy, for a class of nonlinear chaotic fractional order(sIsO) systems with unknown control gain sign. The online control algorithm uses fuzzy logic sets for the identification of the fractional order chaotic system, whereas the lack of a priori knowledge on the control directions is solved by introducing a fractional order Nussbaum gain. Based on Lyapunov stability theorem, stability analysis is performed for the proposed control method for an acceptable synchronization error level. In this work, the Gr ¨unwald-Letnikov method is used for numerical approximation of the fractional order systems. A simulation example is given to illustrate the effectiveness of the proposed control scheme.

关键词： Adaptive fuzzy control chaos synchronization fractional order Nussbaum function Lyapunov stability nonlinear fractional order systems

Landau damping in a bounded magnetized plasma column

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Chinese Physics B 2015年第2期24卷 287-294页

作者： H.Zakeri-khatir F.M.Aghamir Department of Physics University of Tehran

The damping decrement of Landau damping and the effect of thermal velocity on the frequency spectrum of a propagating wave in a bounded plasma column are *** magnetized plasma column partially filling a cylindrical metallic tube is considered to be collisionless and *** Landau damping is due to the thermal motion of charge carriers and appears whenever the phase velocity of the plasma waves exceeds the thermal velocity of *** analysis is based on a self-consistent kinetic theory and the solutions of the wave equation in a cylindrical plasma waveguide are presented using Vlasov and Maxwell *** hybrid mode dispersion equation for the cylindrical plasma waveguide is obtained through the application of appropriate boundary conditions to the plasma-vacuum *** dependence of Landau damping on plasma parameters and the effects of the metallic tube boundary on the dispersion characteristics of plasma and waveguide modes are investigated in detail through numerical calculations.

关键词： Landau damping cylindrical plasma waveguide Vlasov equation dispersion characteristic

Analysis of Landau damping in radially inhomogeneous plasma column

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Chinese Physics B 2018年第5期27卷 365-373页

作者： H Rajabalinia-Jelodar M K salem F M Aghamir H Zakeri-khatir Plasma Physics Research Center Science and Research BranchIslamic Azad University Department of Physics University of Tehran

The Landau damping behavior in a cylindrical inhomogeneous warm magnetized plasma waveguide has been *** radial inhomogeneity for different characteristic lengths（L0） with strong spatial dispersion has been taken into *** analyses have been considered for two limits ωce 〈 ωpe and ωce 〉 ωpe. Due to the radial inhomogeneity of the plasma, all essential equations for studying the Landau damping are calculated in the Bessel–Furrier and differential Bessel–Furrier expansions. The dependence of Landau damping on the inhomogeneity, temperature and external magnetic field for electrostatic modes is scrutinized and described in detail through numerical calculations. The associated numerical results are presented and discussed.

关键词： inhomogeneous warm plasma cylindrical plasma waveguide Landau damping electrostatic modes

Data-driven approach to solve vertical drain under time-dependent loading

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Frontiers of structural and Civil Engineering 2021年第3期15卷 696-711页

作者： Trong NGHIA-NGUYEN Mamoru KIKUMOTO samir khatir salisa CHAIYAPUT HNGUYEN-XUAN Thanh CUONG-LE Department of Civil Engineering Yokohama National UniversityYokohama 240-8501Japan Faculty of Civil Engineering Ho Chi Minh City Open UniversityHo Chi Minh City 70000Vietnam Department of Electrical Energy MetalsMechanical Constructions and SystemsFaculty of Engineering and ArchitectureGhent UniversityGhent 9000Belgium Department of Civil Engineering School of EngineeringKing Mongkut’s Institute of Technology LadkrabangBangkok 10520Thailand CIRTECH Institute Ho Chi Minh City University of Technology(HUTECH)Ho Chi Minh City 708300Vietnam

Currently,the vertical drain consolidation problem is solved by numerous analytical solutions,such as time-dependent solutions and linear or parabolic radial drainage in the smear zone,and no artificial intelligence(AI)approach has been ***,in this study,a new hybrid model based on deep neural networks(DNNs),particle swarm optimization(PsO),and genetic algorithms(GAs)is proposed to solve this *** DNN can effectively simulate any sophisticated equation,and the PsO and GA can optimize the selected DNN and improve the performance of the prediction *** the present study,analytical solutions to vertical drains in the literature are incorporated into the DNN–PsO and DNN–GA prediction models with three different radial drainage patterns in the smear zone under timedependent *** verification performed with analytical solutions and measurements from three full-scale embankment tests revealed promising applications of the proposed approach.

关键词： vertical drain artificial neural network time-dependent loading deep learning network genetic algorithm particle swarm optimization

Machine learning based models for predicting compressive strength of geopolymer concrete

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Frontiers of structural and Civil Engineering 2024年第7期18卷 1028-1049页

作者： Quang-Huy LE Duy-Hung NGUYEN Thanh sANG-TO samir khatir Hoang LE-MINH Amir H.GANDOMI Thanh CUONG-LE Center for Engineering Application and Technology solutions Ho Chi Minh City Open UniversityHo Chi Minh 700000Vietnam Institute of Civil Engineering Ho Chi Minh City University of TransportHo Chi Minh 700000Vietnam Faculty of Engineering&Information Technology University of Technology SydneyUltimoNSW 2007Australia

Recently,great attention has been paid to geopolymer concrete due to its advantageous mechanical and environmentally friendly *** effort has been made in experimental studies to advance the understanding of geopolymer concrete,in which compressive strength is one of the most important *** facilitate engineering work on the material,an efficient predicting model is *** this study,three machine learning(ML)-based models,namely deep neural network(DNN),K-nearest neighbors(KNN),and support vector machines(sVM),are developed for forecasting the compressive strength of the geopolymer concrete.A total of 375 experimental samples are collected from the literature to build a database for the development of the predicting models.A careful procedure for data preprocessing is implemented,by which outliers are examined and removed from the database and input variables are standardized before feeding to the fitting *** standard K-fold cross-validation approach is applied for evaluating the performance of the models so that overfitting status is well managed,thus the generalizability of the models is *** effectiveness of the models is assessed via statistical metrics including root mean squared error(RMsE),mean absolute error(MAE),correlation coefficient(R),and the recently proposed performance index(PI).The basic mean square error(MsE)is used as the loss function to be minimized during the model fitting *** three ML-based models are successfully developed for estimating the compressive strength,for which good correlations between the predicted and the true values are obtained for DNN,KNN,and *** numerical results suggest that the DNN model generally outperforms the other two models.

关键词： geopolymer concrete compressive strength prediction machine-learning based model deep neural network K-nearest neighbor support vector machines

Overall Assessment of Heat Transfer for a Rarefied Flow in a Microchannel with Obstacles Using Lattice Boltzmann Method

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Computer Modeling in Engineering & sciences 2024年第1期138卷 273-299页

作者： siham Hammid khatir Naima Omolayo M.Ikumapayi Cheikh Kezrane Abdelkrim Liazid Jihad Asad Mokdad Hayawi Rahman Farhan Lafta Rashid Naseer Ali Hussien Younes Menni Laboratory of Development in Mechanics and Materials(LDMM) Zian Achour UniversityDjelfaPB 3117Algeria Department of Technology University Center Salhi Ahmed Naama(Ctr.Univ.Naama)P.O.Box 66Naama45000Algeria Department of Mechanical and Mechatronics Engineering Afe Babalola University Ado Ekiti360101Nigeria Departement of Physics Faculty of ScienceAbou Bekr Belkaid UniversityTlemcen13000Algeria Department of Physics Faculty of Applied SciencesPalestine Technical University-KadoorieTulkarmPalestine Aeronautical Technical Engineering Al-Farahidi UniversityBaghdad10011Iraq Mechanical Engineering Department University of KerbalaKarbala56001Iraq Information and Communication Technology Research Group Scientific Research CenterAl-Ayen UniversityThi-QarIraq National University of science and Technology Dhi QarIraq

The objective of this investigation is to assess the effect of obstacles on numerical heat transfer and fluid flow momentum in a rectangular microchannel(MC).Two distinct configurations were studied:one without obstacles and the other with alternating obstacles placed on the upper and lower *** research utilized the thermal lattice Boltzmann method(LBM),which solves the energy and momentum equations of fluids with the BGK approximation,implemented in a Python coding *** jump and slip velocity conditions were utilized in the simulation for the MC and extended to all obstacle *** study aims to analyze the rarefaction effect,with Knudsen numbers(Kn)of 0.012,0.02,and *** outcomes indicate that rarefaction has a significant impact on the velocity and temperature *** presence of nine obstacles led to slower fluid movement inside the microchannel MC,resulting in faster cooling at the *** MCs with obstacles,the rarefaction effect plays a crucial role in decreasing the Nusselt number(Nu)and skin friction coefficient(Cf).Furthermore,the study demonstrated that the obstacles played a crucial role in boosting fluid flow and heat transfer in the *** findings suggest that the examined configurations could have potential applications as cooling technologies in micro-electro-mechanical systems and microdevice applications.

关键词： Microfluid rarefied flow LBM microchannel Knudsen number numerical simulation