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Analysis of pedestrian-to-vehicle collisions can be complex due to the nature of the interaction and the physics involved. The scarcity of evidence like video evidence (from CCTV or dashcams), data from the vehicle's ECU, witness accounts, and physical evidence such as tyre marks, complicates the analysis of these incidents. In cases with limited evidence, current forensic methods often rely on prolonged inquiry processes or computationally intensive simulations. Without adequate data, accurately estimating pedestrian kinematics and addressing hit-and-run scenarios becomes challenging. This research provides an alternative approach to enhancing pedestrian forensic analysis based on machine learning (ML) algorithms trained on over 3000 multi-body computer simulations with a diverse set of vehicle profiles and pedestrian anthropometries.

Nowadays, rolling resistance sits at the core of tyre development goals because of its considerable effect on the car’s fuel economy. In contrast to the experimental method, the finite element (FE) method offers an inexpensive and efficient estimation technique. However, the FE technique is yet to be a fully developed product particularly for rolling-resistance estimation. An assessment is conducted to study the role of material viscoelasticity representation in FE, in linear and non-linear forms, through the use of Prony series and parallel rheological framework (PRF) models, respectively, on the tyre’s rolling-resistance calculation and its accuracy. A unique approach was introduced to estimate the rolling resistance according to the tyre’s hysteresis energy coefficient.

Despite the increasing use of carbon fibre reinforced plastic (CFRP) composites, titanium and aluminium alloys still constitute a significant proportion of modern civil aircraft structures, which are primarily assembled via mechanical joining techniques. Drilling of fastening holes is therefore a critical operation, which has to meet stringent geometric tolerance and integrity criteria. The paper details the development of a three-dimensional (3D) finite element (FE) model for drilling aerospace grade aluminium (AA7010-T7451 and AA2024-T351) and titanium (Ti-6Al-4V) alloys. The FE simulation employed a Coupled Eulerian Lagrangian (CEL) technique. The cutting tool was modelled according to a Lagrangian formulation in which the mesh follows the material displacement while the workpiece was represented by a non-translating and material deformation independent Eulerian mesh.

This paper presents a statistical characterisation of the effects of variations in vehicle parameters on vehicle road load data using a quarter vehicle as a case study. A model of a quarter vehicle test rig constructed from a commercial SUV is created in a multi-body dynamics (MBD) simulation environment to reproduce the real-life behaviour of the SUV. The model is thereafter validated by correlating the response data collected from both the model and laboratory test rig to the same road input. In order to ensure that only the effects of the variation of the vehicle parameters are captured, a time domain drive signal for a kerb strike road event on the physical vehicle is generated from the proving ground data collected during durability testing of the vehicle.

The development of intelligent tire technology from concept to application covers multi-disciplinary fields. During the course of development, the computational method can play a significant role in understanding tire behavior, assisting in the design of the intelligent tire prototype system and in developing tire parameters estimation algorithm, etc. In this paper, a finite element tire model was adopted for developing a strain-based intelligent tire system. The finite element tire model was created considering the tire's composite structure and nonlinear properties of its constituent materials, and the FE model was also validated by physical tests. The FE model is used to study tire strain characteristics by steady state simulation for straight line rolling, traction and braking, as well as cornering. Tire loading conditions were estimated by feature extraction and data fitting.

There is an increasing recognition of injector deposit (ID) formation in fuel injection equipment as direct injection spark ignition (DISI) engine technologies advance to meet increasingly stringent emission legislation and fuel economy requirements. While it is known that the phenomena of ID in DISI engines can be influenced by changes in fuel composition, including increasing usage of aliphatic alcohols and additive chemistries to enhance fuel performance, there is however still a great deal of uncertainty regarding the physical and chemical structure of these deposits, and the mechanisms of deposit formation. In this study, a mechanical cracking sample preparation technique was developed to assess the deposits across DISI injectors fuelled with gasoline and blends of 85% ethanol (E85).

Recent developments in diesel engines lead to increased fuel efficiency and reduced exhaust gas temperature. Therefore more energy efficient aftertreatment systems are required to comply with tight emission regulations. In this study, a computational fluid dynamics package was used to investigate the thermal behaviour of a diesel aftertreatment system. A parametric study was carried out to identify the most influential pipework material and insulation characteristics in terms of thermal performance. In the case of the aftertreatment pipework and canning material effect, an array of different potential materials was selected and their effects on the emission conversion efficiency of a Diesel Oxidation Catalyst (DOC) were numerically investigated over a driving cycle. Results indicate that although the pipework material's volumetric heat capacity was decreased by a factor of four, the total emission reduction was only considerable during the cold start.

Dieseline combustion as a concept combines the advantages of gasoline and diesel by offline or online blending the two fuels. Dieseline has become an attractive new compression ignition combustion concept in recent years and furthermore an approach to a full-boiling-range fuel. High speed imaging with near-parallel backlit light was used to investigate the spray characteristics of dieseline and pure fuels with a common rail diesel injection system in a constant volume vessel. The results were acquired at different blend ratios, and at different temperatures and back pressures at an injection pressure of 100MPa. The penetrations and the evaporation states were compared with those of gasoline and diesel. The spray profile was analyzed in both area and shape with statistical methods. The effect of gasoline percentage on the evaporation in the fuel spray was evaluated.

Sloped medians provide a run-off area for errant vehicles so that they can be safely stopped off-road with or without barriers placed in the sloped median. However, in order to optimize the design of sloped medians and the containment barriers, it is essential to accurately model the behavior of vehicles on such sloped terrain surfaces. In this study, models of a vehicle fleet comprising a small sedan and a pickup truck and sloped terrain surface are developed in CarSim™ to simulate errant vehicle behavior on sloped median. Full-scale crash tests were conducted using the vehicle fleet driven across a 9.754 meters wide median with a 6:1 slope at speeds ranging from 30 to 70 km/h. Measured data such as the lateral accelerations of the vehicle as well as chassis rotations (roll and pitch) were synchronized with the vehicle motion obtained from the video data.

Aluminum metal matrix composites reinforced with particulates have attracted much attention in the automotive industry, due to their improved wear resistance in comparison to aluminum alloys, in recent years. The wear behavior is the critical factor influencing the product life and performance in engineering components. Carbon nanotubes (CNT) are one of the most promising candidates of reinforcements used to improve mechanical strength such as wear in metal matrix composites (MMCs). However, in industrial applications, wear tests are relatively expensive and prolonged. As a result, for several years, research has been increasingly concentrated on development of wear prediction models. In this study, prediction of wear behavior of aluminum (Al) matrix (MMCs) reinforced with different amounts (0, 0.5, 1 and 2 wt%) of CNTs was investigated. A nonlinear autoregressive exogenous (NARX) model structure was chosen for the modeling.

In the development of a more accurate laboratory scale method, the ability to replicate the thermal oxidative degradation mechanisms seen in gas turbine lubricants, is an essential requirement. This work describes an investigation into the influence of key reaction parameters and the equipment set up upon extent and mechanism of oil degradation. The air flow rate through the equipment was found to be critical to both degradation rate and extent of volatilization loss from the system. As these volatile species can participate in further reactions, it is important that the extent to which they are allowed to leave the test system is matched, where possible, to the conditions in the gas turbine. The presence of metal specimens was shown to have a small influence on the rate of degradation of the lubricant. Loss of metal from the copper and silver specimens due to the mild corrosive effect of the lubricant was seen.

Disc brake noise is recognized as a major problem of the automotive industry. Various experimental and numerical techniques have been developed to model the noisy brake and investigate possible solutions. Developing a virtual model of the disc brake which can accurately reproduce the behavior of the brake unit under different conditions is a considerable step forward towards reaching this goal. Among various aspects of the analytical model of a disc brake, application of the correct value of damping based on the material properties and functional frequency range of each component is a significant factor in ensuring correct prediction of the brake system behavior. Complex Eigenvalue Analysis is well established as a tool for predicting brake instabilities which can potentially lead to brake noise. However, it is known to over-predict instabilities i.e. predict instabilities which do not occur in the real brake system.

In the automotive industry, engine downsizing has been widely accepted as an enabler to improving the fuel economy and reducing the CO₂ emissions. The Atkinson cycle is one of the key technologies. In this paper, the Atkinson cycle with different expansion ratios are compared and analyzed. The investigation is compared with the benchmark whose expansion and compression ratio are identical. The aim is to understand the inherent characteristics of the over-expansion and its effect on the engine performance and emissions. The simulation results show that, the Atkinson cycle produces higher efficiency due to over-expansion. The Atkinson cycle has higher internal EGR compared with the benchmark at equivalent conditions, which contributes to lower the NOx and CO emissions.

Computational Fluid Dynamics (CFD) is used to simulate chemical reactions and transport phenomena occurring in a single channel of a honeycomb-type automotive catalytic converter under lean burn combustion. Microkinetic analysis is adopted to develop a detailed elementary reaction mechanism for propane oxidation on a silver catalyst. Activation energies are calculated based on the theory of the Unity Bond Index-Quadratic Exponential Potential (UBI-QEP) method. The order-of-magnitude of the pre-exponential factors is obtained from Transition State Theory (TST). Sensitivity analysis is applied to identify the important elementary steps and refine the pre-exponential factors of these reactions. These pre-exponential factors depend on inlet temperatures and propane concentration; therefore optimised pre-exponential factors are written in polynomial forms. The results of numerical simulations are validated by comparison with experimental data.

The use of accurate tire material properties is a major requirement for conducting a successful tire analysis using finite element method (FEM). Obtaining these material properties however poses a major challenge for tire modelers and researchers due to the complex nature of tire material and associated proprietary protections of constituent material properties by tire manufactures. In view of this limitation, a simple and effective procedure for generating tire materials data used in tire finite element analysis (FEA) is presented in this paper. All the tire test specimens were extracted from a tire product based on special considerations such as specimen dimension and shape, test standard, precondition of specimen and test condition for cords. The required material properties of tire rubber component, including hyperelasticity and viscoelasticity were obtained using simple uni-axial tension test.

The objective of the current research was to predict and analyze the flow through the grill of air intake system which is positioned behind the front wheel arch of vehicle. Most of the vehicle used today locates the grill of air intake at the front side so to acquire benefit of ram effect. In some cases, however, the grill is located behind the vehicle to improve wading performance. The geometry of air intake system of Land Rover Freelander was used in the modelling approach. The study was focused on different flow speeds on the grill at high load operation where the air speed at the grill side is high and creates negative pressure. The CFD results are validated against experimental data of steady flow test bench.

The traditional system design methodology (which follows a preliminary design, analysis, appraisal and redesign pattern) for automotive systems makes balancing contradicting design constraints such as cost, reliability and performance very difficult. Often all of the constraints are not met, and, even if they are, the resultant design may be sub-optimal. This paper outlines a new design approach using constraint satisfaction methods to create an optimal design, where all of the constraints are satisfied. Once the constraints are identified and represented in a suitable format, the design task can be semi-automated using a suitable algorithm. This paper explains how to identify and represent constraints in an automotive problem, the algorithms that can be used to solve the design problem, and how the outcome can be used as an extension to the existing design methodology.

Millimetre wave radar sensors are being actively developed for automotive applications including Intelligent Cruise Control (ICC), Collision Warning (CW), and Collision Avoidance (CA). Knowledge of the road geometry is of fundamental importance to these future intelligent automotive systems. The interest in such systems is evidenced by manufacturers now starting to incorporate radars in production luxury vehicles. Determination of the road geometry, day and night, under all weather conditions, is a challenging problem requiring both fundamental research and systems studies. Current automotive radar systems rely heavily on the use of extrapolating yaw rate data generated within the vehicle to produce a prediction of the path of the road ahead. This use of historical data is only satisfactory if the road trajectory is uniform. Sudden discontinuities in the path, such as bends, cause this method of path prediction to produce significant errors.

This paper presents the findings of theoretical and practical studies of an exhaust-gas reforming process, as applied to hydrocarbon fuels. It is shown that hydrogen-containing gaseous reformed fuels can be produced by the interaction of hot combustion products and an n-heptane feedstock in a small-scale catalytic reforming reactor. Predicted and observed reformed fuel chemical compositions were found to correlate well at the lower reactor space velocities tested, where chemical equilibrium conditions can be closely approached. Under these conditions, respective hydrogen and carbon monoxide yields of around 32 and 20 volume per cent were obtained. Under certain conditions, it was found that carbon solids were deposited on the reforming catalyst. Measures taken to avoid this problem included changes in the reforming oxidant to fuel ratio, and the addition of excess steam to the oxidant composition.