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Authors = Moustafa El-Gindy

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21 pages, 8433 KiB  
Article
Development of an Advanced Wear Simulation Model for a Racing Slick Tire Under Dynamic Acceleration Loading
by Alfonse Ly, Christopher Yoon, Joseph Caruana, Omar Ibrahim, Oliver Goy, Moustafa El-Gindy and Zeinab El-Sayegh
Machines 2025, 13(8), 635; https://doi.org/10.3390/machines13080635 - 22 Jul 2025
Viewed by 543
Abstract
This study investigates the development of a tire wear model using finite element techniques. Experimental testing was conducted using the Hoosier R25B slick tire mounted onto a Mustang Dynamometer (MD-AWD-500) in the Automotive Center of Excellence, Oshawa, Ontario, Canada. A general acceleration/deceleration procedure [...] Read more.
This study investigates the development of a tire wear model using finite element techniques. Experimental testing was conducted using the Hoosier R25B slick tire mounted onto a Mustang Dynamometer (MD-AWD-500) in the Automotive Center of Excellence, Oshawa, Ontario, Canada. A general acceleration/deceleration procedure was performed until the battery was completely exhausted. A high-fidelity finite element tire model using Virtual Performance Solution by ESI Group, a part of Keysight Technologies, was developed, incorporating highly detailed material testing and constitutive modeling to simulate the tire’s complex mechanical behavior. In conjunction with a finite element model, Archard’s wear theory is implemented algorithmically to determine the wear and volume loss rate of the tire during its acceleration and deceleration procedures. A novel application using a modified wear theory incorporates the temperature dependence of tread hardness to measure tire wear. Experimental tests show that the tire loses 3.10 g of mass within 45 min of testing. The results from the developed finite element model for tire wear suggest a high correlation to experimental values. This study demonstrates the simulated model’s capability to predict wear patterns, ability to quantify tire degradation under dynamic loading conditions and provides valuable insights for optimizing performance and wear estimation. Full article
(This article belongs to the Special Issue Advanced Technologies in Vehicle Interior Noise Control)
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34 pages, 3272 KiB  
Review
Analysis of Tire-Road Interaction: A Literature Review
by Haniyeh Fathi, Zeinab El-Sayegh, Jing Ren and Moustafa El-Gindy
Machines 2024, 12(11), 812; https://doi.org/10.3390/machines12110812 - 14 Nov 2024
Cited by 2 | Viewed by 4027
Abstract
This paper presents a comprehensive literature review of the most popular and recent work on passenger and truck tires. Previous papers discuss a huge amount of work on the modeling of passenger car tires using finite element analysis. In addition, recent works on [...] Read more.
This paper presents a comprehensive literature review of the most popular and recent work on passenger and truck tires. Previous papers discuss a huge amount of work on the modeling of passenger car tires using finite element analysis. In addition, recent works on tire–road interaction and the validation of tires using experimental measurements have been described. Moreover, the history of the tire-road contact algorithms is explained. In addition, friction modeling that is implemented in tire–road interaction applications are discussed. Also, a summary of current state-of-the-art research work definitions and requirements of the tread rubber compound are covered from previous studies using various literature reviews and hyper-viscoelastic material models that are implemented for the tread top and the tread base rubber compound. Furthermore, the effect of tire temperature from previous works is presented here. Finally, this literature review also highlights the shortcomings of recent research work and describes the areas lacking in the literature. Full article
(This article belongs to the Section Vehicle Engineering)
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13 pages, 2455 KiB  
Article
Modelling of Truck Tire–Rim Slip on Sandy Loam Using Advanced Computational Techniques
by William Collings, Zeinab El-Sayegh, Jing Ren and Moustafa El-Gindy
Geotechnics 2024, 4(1), 229-241; https://doi.org/10.3390/geotechnics4010012 - 25 Feb 2024
Viewed by 1402
Abstract
Vehicles often experience low tire pressures and high torques in off-road operations, making tire–rim slip likely. Tire–rim slip is undesirable relative rotation between the tire and rim, which, in this study, is measured by the relative tire–rim slip rate. There is little research [...] Read more.
Vehicles often experience low tire pressures and high torques in off-road operations, making tire–rim slip likely. Tire–rim slip is undesirable relative rotation between the tire and rim, which, in this study, is measured by the relative tire–rim slip rate. There is little research on the effect of different terrains on tire–rim slip despite its significance for off-road driving; therefore, this topic was explored through Finite Element Analysis (FEA) simulations. An upland sandy loam soil was modelled and calibrated using Smoothed-Particle Hydrodynamics (SPH), and then a Regional Haul Drive (RHD) truck tire was simulated driving over this terrain, with a drawbar load added to increase drive torque. To examine their effects, five parameters were changed: tire–rim friction coefficient, longitudinal wheel speed, drawbar load, vertical load, and inflation pressure. The simulations showed that increasing the tire–rim friction coefficient and the inflation pressure decreased the tire–rim slip while increasing the vertical and drawbar loads increased the tire–rim slip. Varying the longitudinal wheel speed had no significant effect. Tire–rim slip was more likely to occur on the soil because it happened at lower drawbar loads on the soil than on the hard surface. These research results increased knowledge of tire–rim slip mechanics and provided a foundation for exploring tire–rim slip on other terrains, such as clays or sands. Full article
(This article belongs to the Special Issue Recent Advances in Geotechnical Engineering (2nd Edition))
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27 pages, 14638 KiB  
Article
Simulation and Validation of an 8 × 8 Scaled Electric Combat Vehicle
by Junwoo Kim, Moustafa El-Gindy and Zeinab El-Sayegh
Machines 2024, 12(2), 146; https://doi.org/10.3390/machines12020146 - 19 Feb 2024
Cited by 2 | Viewed by 2368
Abstract
In this research, an 8 × 8 scaled electric combat vehicle (SECV) is built. The scaled vehicle is evaluated in both experimental and simulated methods to analyze its performance. The scaled vehicle is developed to apply the Ackermann condition by implementing the individual [...] Read more.
In this research, an 8 × 8 scaled electric combat vehicle (SECV) is built. The scaled vehicle is evaluated in both experimental and simulated methods to analyze its performance. The scaled vehicle is developed to apply the Ackermann condition by implementing the individual steering and individual wheel speed control system at low speed. Individual eight-wheel rotational velocity control and individual eight-wheel steering angle control in real time are developed and installed on the remotely controlled scaled vehicle to meet a perfect Ackermann condition. Three different steering scenarios are developed and applied: a traditional steering scenario (first and second axle steering), fixed third axle steering scenario (first, second, and fourth axle steering), and all-wheel steering scenario. Stationary evaluation, turn radius evaluation, and double lane change evaluation are conducted to verify the application of the Ackermann condition. The differences between the experimental results and the simulated data are within an acceptable range. An important demonstration of this research is the novel validation of physical and simulated data in the application of the Ackermann condition for eight-wheel steering and velocity control for the three steering scenarios. Full article
(This article belongs to the Special Issue Intelligent Control and Active Safety Techniques for Road Vehicles)
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19 pages, 3523 KiB  
Article
Modeling and Validation of a Passenger Car Tire Using Finite Element Analysis
by Haniyeh Fathi, Zeinab El-Sayegh, Jing Ren and Moustafa El-Gindy
Vehicles 2024, 6(1), 384-402; https://doi.org/10.3390/vehicles6010016 - 9 Feb 2024
Cited by 15 | Viewed by 4736
Abstract
This paper focuses on the modeling and analysis of a four-groove passenger car tire, size 235/55R19, using finite element analysis. The Mooney–Rivlin material model is employed to define the hyperelastic behavior of the tire rubber compounds for all solid elements. The tire rim [...] Read more.
This paper focuses on the modeling and analysis of a four-groove passenger car tire, size 235/55R19, using finite element analysis. The Mooney–Rivlin material model is employed to define the hyperelastic behavior of the tire rubber compounds for all solid elements. The tire rim is modeled as a rigid body using aluminum alloy material, and the beads are modeled as beam elements using steel material. The tire model is validated in both static and dynamic domains through several simulations and is compared to published measured data. The tire is validated using footprint and vertical stiffness tests in the static domain. In the static footprint test, a steady-state vertical load is applied, and the tire–road contact area is computed. In the vertical stiffness test, a ramp vertical load is applied, and the tire’s vertical displacement is measured to calculate the tire’s vertical stiffness. In the dynamic domain, the tire is validated using drum-cleat and cornering tests. In the drum-cleat test, a drum with a 2.5 m diameter and a cleat with a 15 mm radius is used to excite the tire structure and obtain the frequency of the vertical and longitudinal first modes of vibration, that is, by applying the fast Fourier transformation (FFT) of the vertical and longitudinal reaction forces at the tire center. In addition to this test, the tire model is pre-steered on a flat surface with a two-degree slip angle and subjected to a steady state linear speed of 10 km/h to predict the cornering force and compute the cornering stiffness. In addition, the effect of tire longitudinal speed on the rolling resistance coefficient is then predicted at zero slip angle using the ISO 28580 rolling resistance test. The findings of this research work provide insights into passenger car tire–road interaction analysis and will be further used to perform tire rubber compound material model sensitivity analysis. Full article
(This article belongs to the Topic Vehicle Dynamics and Control)
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17 pages, 6012 KiB  
Article
An Advancement in Truck-Tire–Road Interaction Using the Finite Element Analysis
by Haniyeh Fathi, Mehran Khosravi, Zeinab El-Sayegh and Moustafa El-Gindy
Mathematics 2023, 11(11), 2462; https://doi.org/10.3390/math11112462 - 26 May 2023
Cited by 11 | Viewed by 3035
Abstract
This paper aimed to investigate the cornering characteristics of a Regional Haul Steer II, RHS 315/80 R22.5 truck tire traveling on a dry, hard surface using the Finite element analysis (FEA). This research was carried out using commercial Finite Element software and Pam-Crash [...] Read more.
This paper aimed to investigate the cornering characteristics of a Regional Haul Steer II, RHS 315/80 R22.5 truck tire traveling on a dry, hard surface using the Finite element analysis (FEA). This research was carried out using commercial Finite Element software and Pam-Crash in an Explicit Environment. A finite element truck tire model was developed to apply the tire terrain cornering condition. The concentrated loads and boundary conditions for the rim and wheel were applied to the model. The rubber material was defined using the Mooney–Rivlin model. The truck tire cornering operating conditions, including three different speeds with respect to various positive slip angles, were investigated. Several simulations were repeated at various operating conditions, including three different inflation pressures and three different vertical loads. Subsequently, the tire lateral force was computed using the local and global frame coordinates. Additionally, the self-aligning moment was extracted from the tire cross-section at each operating condition. Finally, a comparison between the simulation results showed that the tire lateral force was highly sensitive to the variation of the slip angles at the higher domain, and also that the tire inflation pressure, regardless of the speed, was considered to be one of the main parameters directly affecting the tire-cornering properties. Full article
(This article belongs to the Special Issue Nonlinear Vibration Theory and Mechanical Dynamics)
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30 pages, 3724 KiB  
Review
Defect Detection Methods for Industrial Products Using Deep Learning Techniques: A Review
by Alireza Saberironaghi, Jing Ren and Moustafa El-Gindy
Algorithms 2023, 16(2), 95; https://doi.org/10.3390/a16020095 - 8 Feb 2023
Cited by 142 | Viewed by 35156
Abstract
Over the last few decades, detecting surface defects has attracted significant attention as a challenging task. There are specific classes of problems that can be solved using traditional image processing techniques. However, these techniques struggle with complex textures in backgrounds, noise, and differences [...] Read more.
Over the last few decades, detecting surface defects has attracted significant attention as a challenging task. There are specific classes of problems that can be solved using traditional image processing techniques. However, these techniques struggle with complex textures in backgrounds, noise, and differences in lighting conditions. As a solution to this problem, deep learning has recently emerged, motivated by two main factors: accessibility to computing power and the rapid digitization of society, which enables the creation of large databases of labeled samples. This review paper aims to briefly summarize and analyze the current state of research on detecting defects using machine learning methods. First, deep learning-based detection of surface defects on industrial products is discussed from three perspectives: supervised, semi-supervised, and unsupervised. Secondly, the current research status of deep learning defect detection methods for X-ray images is discussed. Finally, we summarize the most common challenges and their potential solutions in surface defect detection, such as unbalanced sample identification, limited sample size, and real-time processing. Full article
(This article belongs to the Special Issue Deep Learning Architecture and Applications)
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