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Abstract Potassium titanate (KT) fibers/whiskers are used as a functional filler for partial replacement of asbestos in NAO friction materials (FMs). Based on little information reported in open literature; its exact role is not well defined since some papers claim it as the booster for resistance to fade (FR), or wear (WR) and sometimes as damper for friction fluctuations. Interestingly, KT fibers and whiskers (but not powder) are proved as carcinogens by the International Agency for Research on Cancer (IARC). However, hardly any efforts are reported on exploration of influence of KT powder and its optimum amount in NAO FMs (realistic composites) in the literature. Hence a series of five realistic multi-ingredient compositions in the form of brake-pads with similar parent composition but varying in the content of KT powder from 0 to 15 wt% (in the steps of 3) were developed. These composites were characterized for physical, mechanical, chemical and tribological performance.

Abstract Disc pad physical properties are believed to be important in controlling brake friction, wear and squeal. Thus these properties are carefully measured during and after manufacturing for quality assurance. For a given formulation, disc pad porosity is reported to affect friction, wear and squeal. This investigation was undertaken to find out how porosity changes affect pad natural frequencies, dynamic modulus, hardness and compressibility for a low-copper formulation and a copper-free formulation, both without underlayer, without scorching and without noise shims. Pad natural frequencies, modulus and hardness all continuously decrease with increasing porosity. When pad compressibility is measured by compressing several times as recommended and practiced, the pad surface hardness is found to increase while pad natural frequencies and modulus remain essentially unchanged.

Abstract An accurate and rapid thermal model of an axle-brake system is crucial to the design process of reliable braking systems. Proper thermal management is necessary to avoid damaging effects, such as brake fade, thermal cracking, and lubricating oil degradation. In order to understand the thermal effects inside of a lubricated braking system, it is common to use Computational Fluid Dynamics (CFD) to calculate the heat generation and rejection. However, this is a difficult and time-consuming process, especially when trying to optimize a braking system. This article uses the results from several CFD runs to train a Stacked Ensemble Model (SEM), which allows the use of machine learning (ML) to predict the systems’ temperature based on several input design parameters. The robustness of the SEM was evaluated using uncertainty quantification.

Abstract In this work, optimal modeling parameters for self-pierce riveting (SPR) were determined using a factorial design of experiments (DOE). In particular, we show statistically how each of the calibrating parameters used in modeling the SPR process through nonlinear finite element modeling can drastically change the geometry of the joint. The results of this study indicate that the degree of interlock, which is a key feature of a sound joint, is largely influenced by the friction between the die and bottom sheet as well as the friction between the rivet and top sheet. Furthermore, this numerical study also helped elucidate the role of friction in SPR and sheds light on how coatings with diverse friction coefficients can affect material deformation and ultimately structural integrity of the joint.

Abstract Due to the high deformability and energy dissipation capacity of polymer foams in compression, they are used in automotive applications to mitigate mechanical impacts. The mechanical response of the foams is strongly affected by their density. Phenomenological relations have been proposed to describe the effect of foam density on their stress-strain response in compression at a fixed loading rate and the effect of loading rate at a fixed foam density. In the present work, these empirical approaches are combined allowing for the dependence of loading rate effect in compression on foam density. The minimum experimental data set for calibration of the proposed model consists of compression test results at two different loading rates of foams with two different densities.

Abstract To gain a better understanding of the characteristics of corrugation, including the development and propagation of corrugation, and impact of vehicle and track dynamics, a computational model was established, taking into account the nonlinearity of vehicle-track coupling. The model assumes a fixed train speed of 300 km/h and accounts for vertical interaction force components and rail wear effect. Site measurements were used to validate the numerical model. Computational results show that (1) Wheel polygonalisation corresponding to excitation frequency of 545-572 Hz was mainly attributed to track irregularity and uneven stiffness of under-rail supports, which in turn leads to vibration modes of the bogie and axle system in the frequency range of 500-600 Hz, aggregating wheel wear. (2) The peak response frequency of rail of the non-ballasted track coincides with the excitation frequency of wheel-rail coupling; the resonance results in larger wear amplitude of the rail.

Mechanical and thermal properties of the rubber compounds of a tire play an important role in the overall performance of the tire when it is in contact with the terrain. Although there are many studies conducted on the properties of the rubber compounds of the tire to improve some of the tire characteristics, such as the wear of the tread, there are a limited number of studies that focused on the performance of the tire when it is in contact with ice. This study is a part of a more comprehensive project looking into the tire-ice performance and modeling. In this study, to understand the effect of different rubber compounds on the tire performance, three identical tires from the same company have been chosen. The tires’ only difference is the material properties of the rubber. Two approaches have been implemented in this study.

Abstract Off-highway equipment are subjected to diverse environmental conditions, severe duty cycles, and multiple simultaneous operations. Due to its continuous, high-power adverse operating conditions, equipment are exposed to high thermal loads, which result in the deterioration of its performance and efficiency. This article describes a model-based system simulation approach for thermal performance evaluation of a self-propelled off-highway vehicle. The objective of developing the simulation model including thermal fidelity is to quantify the impact of thermal loads on vehicular system/subsystems performance. This article also describes the use of simulation models for driving architectural design decisions and virtual test replication in all stages of product development.

Abstract A new method that allows data-enabled (empirical) models, commonly used for automotive engine calibration, to extrapolate beyond the range of training data has been developed. This method used a physics-based system-level one-dimensional model to improve interpolation and allow extrapolation for three data-based algorithms, by modifying the model input (feature) space. Neural network, regression, and k-nearest neighbor predictions of engine emissions and volumetric efficiency were greatly improved by generating 736,281 artificial feature spaces and then performing feature selection to choose feature spaces (feature selection) so that extrapolations in the original feature space were interpolations in the new feature space. A novel feature selection method was developed that used a two-stage search process to uniquely select the best feature spaces for every prediction.

Abstract Addition of hydrogen to hydrocarbons in premixed turbulent combustion is of technological interest due to their increased reactivity, flame stability and extended lean extinction limits. However, such flames are a challenge to reaction modelling, especially as the strong preferential diffusion effects modify the physical processes, which are of importance even for highly turbulent high-pressure conditions. In the present work, Reynolds-averaged Navier-Stokes (RANS) modelling is carried out to investigate pressure and hydrogen content on methane/hydrogen/air flames.

Abstract This article investigates an adaptive test design approach for the purpose of a model-based engine calibration. Two different new algorithms are presented to take engine boundaries during test execution into account and selectively calculate new test points to increase engine model quality and its input domain. The algorithms are implemented into an adaptive test design framework and evaluated by an engine simulation with artificial Brownian noise added. The results highlight an increase in input space evaluation volume and a decrease in engine model error, while meeting calculation time constraints.

Abstract Cavitation erosion caused by high-frequency vibrating walls can appear in the cooling circuit of internal combustion engines along the liners. The vibrations caused by the mechanical forces acting on the crank drive can lead to temporary regions of low pressure in the coolant with local vapor formation, and vapor collapse close to the liner walls leads to erosion damage, which can strongly reduce the lifetime of the entire engine. The experimental investigation of this phenomenon is so time consuming and expensive, which it is usually not feasible during the design phase. Therefore, numerical tools for erosion damage prediction should be preferred. This study presents a numerical workflow for the prediction of cavitation erosion damages by coupling a three-dimensional (3D) Multi-Body-Dynamic (MBD) simulation tool with a 3D Computational Fluid Dynamics (CFD) solver.

Abstract An innovative analysis approach to evaluate heavy-duty vehicle downhill engine brake performance was developed. The vehicle model developed with GT-Drive simulates vehicle downhill control speeds with different engine brake retarding powers, transmission gears, and vehicle weights at sea level or high altitude. The outputs are then used to construct multi-factor parametric design charts. The charts can be used to analyze the vehicle-level engine brake capabilities or compare braking performance difference between different engine brake configurations to quantify the risk of engine retarding power deficiency at both sea level and high altitude downhill driving conditions.

Abstract Detailed and reduced kinetic mechanisms have been proposed for description of the complex chemistry of autoignition processes of n-heptane, as a representative diesel fuel. These kinetic models are attractive for a detailed 3-D CFD or multi-zone simulation, however the simulation time is normally not affordable for phenomenological engine process modeling. For phenomenological combustion models, typically single-to multiple-step Arrhenius equations are used to model the autoignition processes. Based on the number of Arrhenius equations and model structure the low-temperature, high-temperature and the negative temperature coefficient (NTC) behavior can be modeled. For diesel engine simulation modeling the ignition delay using Arrhenius equation(s) and a Livengood-Wu integration can deliver fairly good results, depending on the number of equations and calibration of constant parameters.

Abstract This work presents a numerical study of the performance and nitrogen oxides (NOx) emissions of a conventional ethanol engine converted to work as a flex-fuel nonconventional architecture: the Split-Cycle Engine (SCE). For this study, the conventional engine fueled with hydrous ethanol was modeled and validated with data from experimental tests. Then the model was converted to operate as an SCE with two compressors and two expanders and simulated with a progressive downsizing of the compressors of the SCE. When the swept volume of the compressors was reduced to 87% of that of the expanders, the thermal conversion efficiency increased by 3.3%. Because of this, the downsized SCE was submitted to simulation runs using two different fuels: hydrous ethanol (H100) and an indolene-ethanol blend (H85). The results of the simulations were compared to the experimental results of the conventional engine.

Abstract The article presents the development of a lean approach for virtual electronic control unit (ECU) calibration. In this calibration method, virtual models are used to improve the calibration quality or reduce the calibration effort. Unlike state-of-the-art approaches, no dedicated engine simulation models for hardware-in-the-loop (HiL) operation are utilized. The developed engine simulation consists of physical ECU real-time capable 0D models. Major benefit of this approach is the multiple use of the developed models for virtual calibration of customer ECUs and vehicle operation using rapid-control-prototyping-ECUs (RCP-ECUs). The engine model consists of a physical air path, an air charge model, a gas exchange and a torque model as well as a novel mathematical combustion and exhaust gas temperature model. The configuration of the engine model was done for a turbocharged four-cylinder gasoline reference engine.

Abstract Objectified analysis and evaluation tools offer cost- as well as time-saving potentials regarding the calibration process of vehicle control units. To reduce the time required for the calibration effort, standardized processes including the frontloading of development tasks enable swift calibration procedures and can be used to develop a basis for the comparison of different vehicles and also the calibration quality. In this environment, objectified evaluation methods are also being developed for the investigation of the drivability of electric vehicles. This article presents a methodology for assessing the longitudinal drive behavior of battery electric vehicles during deceleration maneuvers. The aim is to objectively evaluate the vehicle deceleration by means of reproducible driving maneuvers. In addition to further measurement signals, the longitudinal acceleration signal serves as the main evaluation basis.

Abstract The efficiency of the traditional machining process becomes limited because of the mechanical properties and complexity of the geometric shape of the processed materials. This difficulty is resolved through the nonconventional machining process. Electric Discharge Machining (EDM) process is one of the popular nonconventional machining processes among all nonconventional machining processes for processing such materials. The main objective of the present research work is to evaluate the effect of percentage weight fraction of reinforcement and process parameters on machining responses during EDM of aluminum (Al) 7075-reinforced boron carbide (B4C) and graphite metal matrix composite (MMC) and optimization of the result.

Abstract Fretting failure mode is commonly observed at the contact interface of mating parts, held together under normal load and subjected to vibratory and/or imbalanced system forces. This article presents the fretting fatigue life estimation of a complete flat-flat contact pair using a relatively new approach, i.e., deviatoric strain amplitude-based (SI) parameter, further combined with Ding’s empirical parameter D fret2, which considers the effect of resultant frictional work on fretting fatigue life. The results are compared with traditional critical plane-based methods like Smith-Watson-Topper (SWT) and Fatemi-Socie (FS). Observing high load-factor values corresponding to material yielding, non-linear material models are considered to account for possible plastic shakedown/ratcheting phenomenon. Overall good experimental correlation is observed for all three fatigue initiation methods, within a ±3N scatter band.

Abstract Although tread block deformation analysis is important, the deformation measurement is difficult because fast-rotating tires maintain a continuous contact with the road surface. Furthermore, capturing small displacements near the edge of tread blocks using a high-speed camera is difficult because of the particularly limited resolution. Additionally, the tread blocks being significantly deformed at the edge and susceptible to wear powder, the state change of the feature points, is highly probable. To overcome these problems, a system that obtains high-resolution images and measures the deformation of a fast-rotating body (tire) is proposed herein. The developed system captures the deformation behavior through intermittent imaging. To further measure the strain distribution, fine tracking markers are drawn on the tread block using a laser processing machine. The displacement of the marker is calculated using the particle mask correlation method.