Intelligent Tire Prototype in Longitudinal Slip Operating Conditions.

With the recent advances in autonomous vehicles, there is an increasing need for sensors that can help monitor tire-road conditions and the forces that are applied to the tire. The footprint area of a tire that makes direct contact with the road surface, known as the contact patch, is a key parameter for determining a vehicle's effectiveness in accelerating, braking, and steering at various velocities. Road unevenness from features such as potholes and cracks results in large fluctuations in the contact patch surface area. Such conditions can eventually require the driver to perform driving maneuvers unorthodox to normal traffic patterns, such as excessive pedal depressions or large steering inputs, which can escalate to hazards such as the loss of control or impact. The integration of sensors into the inner liner of a tire has proven to be a promising method for extracting real-time tire-to-road contact patch interface data. In this research, a tire model is developed using Abaqus/CAE and analyzed using Abaqus/Explicit to study the nonlinear behavior of a rolling tire. Strain variations are investigated at the contact patch in three major longitudinal slip driving scenarios, including acceleration, braking, and free-rolling. Multiple vertical loading conditions on the tire are applied and studied. An intelligent tire prototype called KU-iTire is developed and tested to validate the strain results obtained from the simulations. Similar operating and loading conditions are applied to the physical prototype and the simulation model such that valid comparisons can be made. The experimental investigation focuses on the effectiveness of providing usable and reliable tire-to-road contact patch strain variation data under several longitudinal slip operating conditions. In this research, a correlation between FEA and experimental testing was observed between strain shape for free-rolling, acceleration, and braking conditions. A relationship between peak longitudinal strain and vertical load in free-rolling driving conditions was also observed and a correlation was observed between FEA and physical testing.

Noninvasive identification of directionally-dependent elastic properties of soft tissues using full-field optical data.

This paper introduces an innovative approach for elastic property characterization of soft tissues, having directional-dependent material behavior, via their vibration response measurement and interpretation. The full-field time-dependent surface displacements as a result of externally excited soft tissues are collected through digital image correlation (DIC). A developed analytical model, capturing the low-amplitude vibration behavior of anisotropic layered human skin with the incorporation of the influence of subcutaneous elasticity and inertia, is employed to accurately predict its resonant frequencies and pertaining displacement field images. An efficient solution approach for the model is implemented into an inverse algorithm to rapidly characterize the anisotropic elastic properties based on importing the vibration characteristics. To show the merit of the approach, a 3-D finite element (FE) simulation model was used to generate full-field data, detected and matched with a set of specific vibration modes via modal assurance criterion (MAC). The validity of the model implemented into the inverse characterization algorithm is demonstrated through a comparison of predicted vibration frequencies and mode-shapes simulated via the 3-D FE model for different cases with anisotropic elastic properties in different layers of the skin. It is shown that modes are influenced differently when anisotropic properties are introduced to the model. Thus, the established inverse characterization algorithm is capable of rapidly predicting the elastic material properties of anisotropic soft sheets with adequate accuracy.

Mechanical characterization of human skin-A non-invasive digital twin approach using vibration-response integrated with numerical methods.

This paper proposes an innovative approach to identify elastic material properties and mass density of soft tissues based on interpreting their mechanical vibration response, externally excited by a mechanical indenter or acoustic waves. A vibration test is performed on soft sheets to measure their response to a continuous range of excitation frequencies. The frequency responses are collected with a pair of high-speed cameras in conjunction with 3-D digital image correlation (DIC). Two cases are considered, including suspended/fully-free rectangular neoprene sheets as artificial tissue cutout samples and continuous layered human skin vibrations. An efficient theoretical model is developed to analytically simulate the free vibrations of the neoprene artificial sheet samples as well as the continuous layered human skins. The high accuracy and validity of the presented analytical simulations are demonstrated through comparison with the DIC measurements and the conducted frequency tests, as well as a number of finite element (FE) modeling. The developed analytical approach is implemented into a numerical algorithm to perform an inverse calculation of the soft sheets' elastic properties using the imported experimental vibration results and the predicted system's mass via the system equivalent reduction/expansion process (SEREP) method. It is shown that the proposed frequency-dependent inverse approach is capable of rapidly predicting the material properties of the tested samples with high accuracy.

Analysis of Shielding Effectiveness against Electromagnetic Interference (EMI) for Metal-Coated Polymeric Materials.

Lightweight materials, such as polymers and composites, are increasingly used in the automotive and aerospace industries. Recently, there has been an increase in the use of these materials, especially in electric vehicles. However, these materials cannot shield sensitive electronics from electromagnetic interference (EMI). The current work investigates the EMI performance of these lightweight materials using an experimental setup based on the ASTM D4935-99 standard and EMI simulation using the ANSYS HFSS. This work studies how metal coating from zinc and aluminum bronze can improve the shielding performance of polymer-based materials, such as polyphenylene sulfide (PPS), polyetheretherketone (PEEK), and polyphthalamide (PPA). Based on the findings of this study, a thin coating (50 µm) of Zn on the surface of PPS and a thin coating of 5 µm and 10 µm of Al-Bronze, respectively, on the surface of PEEK and PPA have indicated an increase in the shielding effectiveness (SE) when subjected to EMI. The shielding effectiveness significantly increased from 7 dB for the uncoated polymer to approximately 40 dB at low frequencies and up to approximately 60 dB at high frequencies for coated polymers. Finally, various approaches are recommended for improving the SE of polymeric materials under the influence of EMI.

Mechanical modeling and characterization of human skin: A review.

This paper reviews the advances made in recent years on modeling approaches and experimental techniques to characterize the mechanical properties of human skin. The skin is the largest organ of the human body that has a complex multi-layered structure with different mechanical behaviors. The mechanical properties of human skin play an important role in distinguishing between healthy and unhealthy skin. Furthermore, knowing these mechanical properties enables computer simulation, skin research, clinical studies, as well as diagnosis and treatment monitoring of skin diseases. This paper reviews the recent efforts on modeling skin using linear, nonlinear, viscoelastic, and anisotropic materials. The work also focuses on aging effects, microstructure analysis, and non-invasive methods for skin testing. A detailed explanation of the skin structure and numerical models, such as finite element models, are discussed in this work. This work also compares different experimental methods that measure the mechanical properties of human skin. The work reviews the experimental results in the literature and shows how the mechanical properties of human skin vary with the skin sites, the layers, and the structure of human skin. The paper also discusses how state-of-the-art technology can advance skin research.

Vibration analysis of healthy skin: toward a noninvasive skin diagnosis methodology.

Several noninvasive imaging techniques have been developed to monitor the health of skin and enhance the diagnosis of skin diseases. Among them, skin elastography is a popular technique used to measure the elasticity of the skin. A change in the elasticity of the skin can influence its natural frequencies and mode shapes. We propose a technique to use the resonant frequencies and mode shapes of the skin to monitor its health. Our study demonstrates how the resonant frequencies and mode shapes of skin can be obtained using numerical and experimental analysis. In our study, natural frequencies and mode shapes are obtained via two methods: (1) finite element analysis: an eigensolution is performed on a finite element model of normal skin, including stratum corneum, epidermis, dermis, and subcutaneous layers and (2) digital image correlation (DIC): several in-vivo measurements have been performed using DIC. The experimental results show a correlation between the DIC and FE results suggesting a noninvasive method to obtain vibration properties of the skin. This method can be further examined to be eventually used as a method to differentiate healthy skin from diseased skin. Prevention, early diagnosis, and treatment are critical in helping to reduce the incidence, morbidity, and mortality associated with skin cancer; thus, making the current study significant and important in the field of skin biomechanics.