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The most common and lethal weapons against military vehicles are the improvised explosive devices (IEDs). In an explosion, critical cabin’s penetrations and high accelerations can cause serious injuries and death of military personnel. This investigation uses single and multi-fidelity Bayesian optimization (BO) to design sandwich composite armors for blast mitigation. BO is an efficient methodology to solve optimization problems that involve black-box functions. The black-box function of this work is the finite element (FE) simulation of the armor subjected to blast. The main two components of BO are the surrogate model of the black-box function and the acquisition function that guides the optimization. In this investigation, the surrogate models are Gaussian Process (GP) regression models and the acquisition function is the multi-objective expected improvement (MEI) function. Information from low and high fidelity FE models is used to train the GP surrogates.

The transportation sector is facing three revolutions: shared mobility, electrification, and autonomous driving. To inform decision making and guide smart transportation system development at the city-level, it is critical to model and evaluate how travelers will behave in these systems. Two key components in such models are (1) individual travel demands with high spatial and temporal resolutions, and (2) travelers’ sociodemographic information and trip purposes. These components impact one’s acceptance of autonomous vehicles, adoption of electric vehicles, and participation in shared mobility. Existing methods of travel demand generation either lack travelers’ demographics and trip purposes, or only generate trips at a zonal level. Higher resolution demand and sociodemographic data can enable analysis of trips’ shareability for car sharing and ride pooling and evaluation of electric vehicles’ charging needs.

Notched spoilers may be used to suppress flow-induced cavity resonance in vehicles with open sunroofs or side windows. The notches are believed to generate streamwise vortices that break down the structure of the leading edge cross-stream vortices predominantly responsible for the cavity excitation. The objectives of the present study were to gain a better understanding of the buffeting suppression mechanisms associated with notched spoilers, and to gather data for computational model verification. To this end, experiments were performed to characterize the surface pressure field downstream of straight and notched spoilers mounted on a rigid wall to observe the effects of the notches on the static and dynamic wall pressure. Detailed flow velocity measurements were made using hot-wire anemometry. The results indicated that the presence of notches on the spoiler reduces drag, and thus tends to move the flow reattachment location closer to the spoiler.

This paper presents a method for indirect measurement of tire slip angles from chassis acceleration, yaw rate, and steer angle measurements. The chassis is assumed to be rigid so that acceleration data can be integrated to estimate velocities of the front and rear of the vehicle, from which slip angles can be predicted. The difference in front and rear slip angles is indicative of vehicle oversteer/understeer. Understeer data can then be correlated with position on the track to better understand vehicle handling behavior, aiding the tuning process. The technique is presented, and shown to work well with simulated data, even when the data is corrupted with up to 20% noise. Therefore, the inversion process presented here is theoretically sound. However, when the technique is applied to measured data from race cars, it is shown to be inaccurate. One suspected problem is the difficulty of getting accurate yaw rate data.

Operation & support costs for military weapon systems accounted for approximately 3/5th of the $500B Department of Defense budget in 2006. In an effort to ensure readiness and decrease these costs for ground vehicle fleets, health monitoring technologies are being developed for Condition-Based Maintenance of individual vehicles within a fleet. Dynamics-based health monitoring is used in this work because vibrations are a passive source of response data, which are global functions of the mechanical loading and properties of the vehicle. A common way of detecting faults in mechanical equipment, such as the suspension and chassis of a ground vehicle, is to compare measured operational vibrations to a reference (or healthy) signature to detect anomalies.

Swirl in Diesel engines is known to be an important parameter that affects the mixing of the fuel jets, heat release, emissions, and overall engine performance. The changes may be brought about through interactions of the swirling flow field with the spray and through modifications of the flow field. The purpose of this paper is to investigate the interaction of the swirl with sprays in a Diesel engine through a computational study. A multi-dimensional model for flows, sprays, and combustion in engines is employed. Results from computations are reported with varying levels of swirl and initial turbulence in two typical Diesel engine geometries. It is shown that there is an optimal level of swirl for each geometry that results from a balance between increased jet surface area and, hence, mixing rates and utilization of air in the chamber.

In Diesel engines, the vapor phase of the fuel jet is known to impinge on the walls. This impingement is likely to have an effect on mixing characteristics, the structure of the diffusion flame and on pollutant formation and oxidation. These effects have not been studied in detail in the literature. In this work, the structure of a laminar wall jet that is generated from the impingement of a free laminar jet on a wall is discussed. We study the laminar jet with the belief that the local structure of the reaction zone in the turbulent reacting jet is that of a laminar flame. Results from non-reacting and reacting jets will be presented. In the case of the non-reacting jets, the focus of the inquiry is on assessing the accuracy of the computed results by comparing them with analytical results. Velocity profiles in the wall jet, growth rates of the half-width of the jet and penetration rates are presented.

One dominant “wind noise” generating mechanism in road vehicles is the interaction between turbulent flows and flexible structures which include side glass windows. In this study, the effects of seal mechanical properties on the sound generated from flow-induced vibration of side glass windows were investigated. The primary goal was to assess the influence of seal support properties on the noise generated from a plate. Two different models to calculate the optimal support stiffness of the seal that minimizes the velocity response are presented. The results show that both the velocity response and the sound radiation are strongly influenced by dissipation of vibration energy at the edges. It is demonstrate that support tuning can yield significant noise and vibration reduction.

Sound transmission through door and window sealing systems is one important contributor to vehicle interior noise. The noise generation mechanism involves the vibration of the seal due to the unsteady wall pressures associated with the turbulent flow over the vehicle. For bulb seals, sound transmission through the seal is governed by the resonance of the seal membranes and the air cavity within the bulb (the so-called mass-air-mass resonance). The objective of this study was to develop a finite element (FE) model to predict the sound transmission loss of elastomeric bulb seals. The model was then exercized to perform a parametric study of the influence of seveal seal design parameters. The results suggest that the sound transmission loss increases as the membrane thicknesses and/or the separation distance between the two seal walls are increased. The addition of additional internal “webs” was found to have adverse effects on the sound barrier performance.

An increase in the number of vehicles per capita coupled with stricter emission regulations have made the development of newer and better hybrid vehicle architectures indispensable. Although electric hybrids have more visibility and are now commercially available, hydraulic hybrids, with their higher power densities and cheaper components, have been rigorously explored as the alternative. Several architectures have been proposed and implemented for both on and off highway applications. The most commonly used architecture is the series hybrid, which requires an energy conversion from the primary source (engine) to the secondary domain. From he re, the power flows either into the secondary source (high-pressure accumulator) or to the wheels depending upon the state of charge of the accumulator. A mode-switching hydraulic hybrid, which is a combination of a hydrostatic transmission and a series hybrid, was recently developed in the author’s research group.

Rolling element bearings provide near frictionless relative motion between two rotating parts. Automotive transmissions use various ball and rolling element bearings to accommodate the relative motion between rotating elements. In order to understand changes in bearing performance due to the loads imposed through the transmission, advanced modeling of the bearing is required. This paper focuses on the effects of cage flexibility on bearing performance. A flexible cage model was developed and incorporated into a six degree-of-freedom dynamic, deep groove ball bearing model. A lumped mass approach was used to represent the cage flexibility and was validated through an ANSYS forced response analyses of the cage. Results from the newly developed Flexible Cage Model (FCM) and an identical numerical model employing a rigid bearing cage were compared to determine the effects of varying ball-to-cage pocket clearance and cage stiffness on cage motion and ball-to-cage pocket contact forces.

Conventional suspension analysis of three-dimensional suspensions typically use two-dimensional analyses. This is done by projecting suspension components onto two-dimensional planes and then performing a two-dimensional analysis in each of these orthogonal planes or neglecting motions in one of the planes entirely. This requires multiple iterations because changes in one plane require a checking of their effects on motion in the other orthogonal planes. In doing so, much of the insight and accuracy gained from a three-dimensional analysis can be lost. A three-dimensional kinematic analysis approach is presented and applied to a dual A-Arm suspension system. All motions are considered instantaneously about a screw axis instead of a point as used by the usual two-dimensional modeling approach. The model predicts deflections of suspension components in response to the three-dimensional forces present at the contact patch.

Typical vehicle dynamics simulations demand a trade-off between short computation times and accuracy. Many of the more simple models are based on the kinematic roll center and the more accurate models tend to be multi-body dynamics simulation programs. There is a need for a model that improves the accuracy of the kinematic roll center models while still maintaining short computation times. Such a model could be used track-side during races to guide race teams toward improved handling. The model presented in this paper removes many of the assumptions and limitations of the kinematic roll center model. The model accounts for three-dimensional forces present at the contact patch and predicts deflections of suspension components. The modeling approach is applied to a NASCAR Craftsman Truck to predict the effects of suspension design and tuning on steady-state understeer characteristics of the vehicle. Braking and acceleration forces can also be applied to the vehicle.

A analytical technique for predicting the aerodynamic performance of propellers with tip devices (proplets) using vortex lattice method shows that the ideal efficiency of a fixed diameter propeller can be improved by 1-5%. By suitable orientation and sweep of the proplet, the noise analysis method presented predicts that propellers with tip devices will have approximately the same noise as propellers without tip devices. Therefore proplets can be added to a fixed diameter propeller to improve the efficiency with no increase in noise or the noise may be reduced by decreasing the diameter with no loss in aerodynamic efficiency.

“Truck Ride” in this study refers to some vehicle ride parameters involved in tractor-trailer combinations. For the study, a mathematical model of a tractor-trailer vehicle as a vibrating system was developed. Principles of vibration theory were applied to the model while a digital computer was employed to investigate the complex system. To parallel the analytical investigation of the tractor-trailer vehicle, vehicle studies were conducted using a magnetic tape recorder and associated instrumentation installed in the tractor. Parameters studied included coupler position on the tractor, laden weight of trailer, spring rates of the different axles of the combination, damping capacity associated with each spring rate, vehicle speed, and “tar strip” spacing of the highway and cab mountings. The mathematical results were used as a basis for empirical study. A comparison of calculated and empirical data are reported.

This paper discusses the necessity for designing farm tractors which have logical, rather than arbitrary, safety features. The paper is directed primarily to those who buy and use industrial equipment and urges this group to exercise their influence on tractor design by purchasing only those vehicles which meet recommended standards for safety and construction.

In the last years, lithium-ion batteries (LIBs) have become the most important energy storage system for consumer electronics, electric vehicles, and smart grids. A LIB is composed of several unit cells. Therefore, one of the most important factors that determine the performance of a LIB are the characteristics of the unit cell. The design of LIB cells is a challenging problem since it involves the evaluation of expensive black-box functions. These functions lack a closed-form expression and require long-running time simulations or expensive physical experiments for their evaluation. Recently, Bayesian optimization has emerged as a powerful gradient-free optimization methodology to solve optimization problems that involve the evaluation of expensive black-box functions. Bayesian optimization has two main components: a probabilistic surrogate model of the black-box function and an acquisition function that guides the optimization.

This paper presents experimental results that validate eco-driving and eco-heating strategies developed for connected and automated vehicles (CAVs). By exploiting vehicle-to-infrastructure (V2I) communications, traffic signal timing, and queue length estimations, optimized and smoothed speed profiles for the ego-vehicle are generated to reduce energy consumption. Next, the planned eco-trajectories are incorporated into a real-time predictive optimization framework that coordinates the cabin thermal load (in cold weather) with the speed preview, i.e., eco-heating. To enable eco-heating, the engine coolant (as the only heat source for cabin heating) and the cabin air are leveraged as two thermal energy storages. Our eco-heating strategy stores thermal energy in the engine coolant and cabin air while the vehicle is driving at high speeds, and releases the stored energy slowly during the vehicle stops for cabin heating without forcing the engine to idle to provide the heating source.

Accurate modeling of the transient structure of reacting diesel jets is important as transient features like autoignition, flame propagation, and flame stabilization have been shown to correlate with combustion efficiency and pollutant formation. In this work, results from Reynolds-averaged Navier-Stokes (RANS) simulations of flame lift-off in diesel jets are examined to provide insight into the lift-off physics. The large eddy simulation (LES) technique is also used to computationally model a lifted jet flame at conditions representative of those encountered in diesel engines. An unsteady flamelet progress variable (UFPV) model is used as the turbulent combustion model in both RANS simulations and LES. In the model, a look-up table of reaction source terms is generated as a function of mixture fraction Z, stoichiometric scalar dissipation rate Xst, and progress variable Cst by solving the unsteady flamelet equations.

The design of better active materials for lithium-ion batteries (LIBs) is crucial to satisfy the increasing demand of high performance batteries for portable electronics and electric vehicles. Currently, the development of new active materials is driven by physical experimentation and the designer’s intuition and expertise. During the development process, the designer interprets the experimental data to decide the next composition of the active material to be tested. After several trial-and-error iterations of data analysis and testing, promising active materials are discovered but after long development times (months or even years) and the evaluation of a large number of experiments. Bayesian global optimization (BGO) is an appealing alternative for the design of active materials for LIBs. BGO is a gradient-free optimization methodology to solve design problems that involve expensive black-box functions. An example of a black-box function is the prediction of the cycle life of LIBs.