Search Results

Conventional crank-based engines are limited by mechanical, thermal, and combustion inefficiencies. The free piston of a linear engine generator reduces frictional losses by avoiding the rotational motion and crankshaft linkages. Instead, electrical power is generated by the oscillation of a translator through a linear stator. Because the free piston is not geometrically constrained, dead center positions are not specifically known. This results in a struggle against adverse events like misfire, stall, over-fueling, or rapid load changes. It is the belief that incorporating springs will have the dual benefit of increasing frequency and providing a restoring force to aid in greater cycle to cycle stability. For dual free piston linear engines the addition of springs has not been fully explored, despite growing interest and literature.

A Hybrid Projectile (HP) is a round that transforms into a UAV after being launched. Some HP's are fired from a rifled barrel and must be de-spun and wings-level for lifting surfaces to be deployed. Control surfaces and controllers for de-spinning and wings-leveling were required for initial design of an HP 40 mm. Wings, used as lifting surfaces after transformation, need to be very close to level with the ground when deployed. First, the tail surface area needed to de-spin a 40 mm HP was examined analytically and simulated. Next, a controller was developed to maintain a steady de-spin rate and to roll-level the projectile in preparation of wing deployment. The controller was split into two pieces, one to control de-spin, and the other for roll-leveling the projectile. An adaptable transition point for switching controllers was identified analytically and then adjusted by using simulations.

This paper discusses the design and qualification of a High Temperature Sampling System (HTSS), capable of stripping the volatile fraction from a sample flow stream in order to provide for quantification of total, solid and volatile particulate matter (PM) on a near real-time basis. The sampling system, which incorporates a heated diesel oxidation catalyst, is designed for temperatures up to 450°C. The design accounts for molecular diffusion of volatile compounds, solid particles diffusion and reaction kinetics inside one channel of the oxidation catalyst. An overall solid particle loss study in the sampling was performed, and numerical results were compared with experimental data gathered at the West Virginia University Engine and Emissions Research Laboratory (EERL) and West Virginia University's Transportable Heavy-Duty Vehicle Emissions Testing Laboratory (THDVETL).

With the ever-increasing power of real time graphics and computational ability of desktop computers, the desire for a real-time simulation of the musculoskeletal system has become more pronounced. It is important that this simulation is realistic, interactive, runs in real time, and looks realistic, especially in our climate of Hollywood special-effects and stunning video games. An effective simulation of the musculoskeletal system hinges on three key features: accurate modeling of kinematic movement, realistic modeling of the muscle attachment points, and determining the direction of the forces applied at the points. By taking known information about the musculoskeletal system and applying it in a real time environment, we have created such a model of the human arm. This model includes realistic constraints on the joints and real-time wrapping algorithms for muscle action lines.

As predictive capabilities advance and human-model fidelity increases, so must validation of such predictions and models. However, subjective validation is sufficient only as an initial indicator; thorough, systematic studies must be conducted as well. Thus, the purpose of this paper is to validate postures that are determined using single-objective optimization (SOO) and multi-objective optimization (MOO), as applied to the virtual human Santos™. In addition, a general methodology and tools for posture-prediction validation are presented. We find that using MOO provides improvement over SOO, and the results are realistic from both a subjective and objective perspective.

As a part of the 1996 FutureCar Challenge competition, West Virginia University converted a 1996 Chevrolet Lumina to a series hybrid electric vehicle. This technical report summarizes the modifications made to the vehicle during 1997, the second year of the competition, and details the present state of development of this second-generation hybrid electric vehicle. In particular, the vehicle's powertrain configuration, component selection, control strategy for all modes of operation, emissions control strategies, vehicle structure and design modifications, and suspension design and modifications are all detailed. Also discussed, are the operational use of this vehicle and its intended market. The projected performance of the vehicle, obtained from computer simulations, is discussed in the light of results obtained from testing during 1996 and 1997.

The paper discusses the development of a model for the 2006 BMW 330i for the National Advanced Driving Simulator's (NADS) vehicle dynamics simulation, NADSdyna. The front and rear suspensions are independent strut and link type suspensions modeled using recursive rigid-body dynamics formulations. The suspension springs and shock absorbers are modeled as force elements. The paper includes parameters for front and rear semi-empirical tire models used with NADSdyna. Longitudinal and lateral tire force plots are also included. The NADSdyna model provides state-of-the-art high-fidelity handling dynamics for real-time hardware-in-the-loop simulation. The realism of a particular model depends heavily on how the parameters are obtained from the actual physical system. Complex models do not guarantee high fidelity if the parameters used were not properly measured. Methodologies for determining the parameters are detailed in this paper.

To impact the decision making for military ground vehicles, we are using High Performance Computing (HPC) to speed up the time for analyzing the reliability of a design in modeling and simulation. We use parallelization to get accurate results in days rather than months. We can obtain accurate reliability prediction with modeling and simulation, using uncertainties and multiple physics-of-failure, but by utilizing parallel computing we get results in much less time than conventional analysis techniques.

This paper investigates a hierarchical optimization procedure for the optimum synthesis of a double-axle steering mechanism by considering the dynamic load of a vehicle which is seldom discussed in the previous literature. Firstly, a multi-body model of double-axle steering is presented by characterizing the detailed leaf spring effect. Accordingly, the influences of dynamic load including the motion interference of steering linkage resulted from the elastic deformation of leaf spring, and the effects of wheel slip angle and the position discrepancy of wheel speed rotation centers are explored systematically. And then, a hierarchical optimization method based on target cascading methodology is proposed to classify the design variables of double-axle steering mechanism into four levels. At last, a double-axle steering mechanism of a heavy-duty truck is utilized to demonstrate the validity of this method.

Inverse Kinematics on a human model combined with optimization provides a powerful tool to predict realistic human postures. A human posture prediction tool brings up the need for greater flexibility for the user, as well as efficient computation performance. This paper demonstrates new methods that were developed for the application of digital human simulation as a software package by allowing for any number of user specified end-effectors and increasing communication efficiency for posture prediction. The posture prediction package for the digital human, Santos™, uses optimization constrained by end-effectors on the body with targets in the environment, along with variable cost functions that are minimized, to solve for all joint angles in a human body. This results in realistic human postures which can be used to create optimal designs for things that humans can physically interact with.

The Army continues to improve its Reliability-based Design Optimization (RBDO) process, expanding from component optimization to system optimization. We are using the massively parallel computing power of the Department of Defense (DoD) High Performance Computing (HPC) systems to simultaneously optimize multiple components which interact with each other in a mechanical system. Specifically, we have a subsystem of a military ground vehicle, consisting of more than four components and are simultaneously optimizing five components of that subsystem using RBDO methods. We do not simply optimize one component at a time, sequentially, and iterate until convergence. We actually simultaneously optimize all components together. This can be done efficiently using the parallel computing environment. We will discuss the results of this optimization, and the advantages and disadvantages of using HPC systems for this work.

Collision avoidance in digital human modeling is critical for design and analysis, especially when there is interaction between the avatar and his/her environment. This paper describes a new algorithm for obstacle avoidance with optimization-based posture prediction. This new approach is motivated by a need for decreased computational time and increased fidelity for modeling and analysis of collision avoidance tasks. Posture prediction is run in an iterative loop while conducting collision detection to dynamically update collision avoidance constraints. It is shown that this approach is substantially faster than the basic method involving a fixed number of sphere-based avoidance constraints with a single optimization/posture-prediction run. The method is demonstrated using an upper-body virtual human model in a cab setting.

Dual primary full-flow dilution tunnels represent an integral part of a heavy-duty transportable emissions measurement laboratory designed and constructed to comply with US Code of Federal Regulations (CFR) 40 Part 1065 requirements. Few data exist to characterize the evolution of particulate matter (PM) in full scale dilution tunnels, particularly at very low PM mass levels. Size distributions of ultra-fine particles in diesel exhaust from a naturally aspirated, 2.4 liter, 40 kW ISUZU C240 diesel engine equipped with a diesel particulate filter (DPF) were studied in one set of standard primary and secondary dilution tunnels with varied dilution ratios. Particle size distribution data, during steady-state engine operation, were collected using a Cambustion DMS500 Fast Particulate Spectrometer. Measurements were made at four positions that spanned the tunnel cross section after the mixing orifice plate for the primary dilution tunnel and at the outlet of the secondary dilution tunnel.

Two and three-dimensional test cases were simulated using a detailed kinetic mechanism for di-methyl ether to represent methane combustion. A piston-bowl assembly for the compression and expansion strokes with combustion has been simulated at 1500 RPM. A fine grid was used for the 2-D simulations and a rather coarse grid was used for the 3-D calculations together with a k-ε subgrid-scale turbulence model and a partially stirred reactor model with three time scales. Ignition was simulated artificially by increasing the temperature at one point inside the cylinder. The results of these simulations were compared with experimental results. The simulation involved an engine with a homogeneous charge of methane as fuel. Results indicate that pressure fluctuations were captured some time after the ignition started, which indicates knock conditions.

As fuel economy and emissions regulations increase in stringence, automakers face ever increasing difficulty in meeting government imposed standards. In this paper a study of fuel economy improving techniques used to meet these regulations, notably Corporate Average Fuel Economy (CAFE), and the upper limit on the effectiveness of these techniques is presented. The effects of external vehicle improvements, such as lightweighting, rolling resistance and aerodynamic improvements were investigated to illustrate the limitations of these methods to dramatically improve overall vehicle efficiency. Engine efficiency improvements, including the effects of compression ignition (unthrottled) versus spark ignition (throttled) engine types were examined. Other engine efficiency areas that were investigated were the implementation of cylinder deactivation and gasoline direct injection engines.

Computational fluid dynamics (CFD) model has been widely applied in internal combustion (IC) engine research. The integration of chemical kinetic model with CFD provides an opportunity for researchers to investigate the detailed chemical reactions for better understanding the combustion process of IC engines. However, the simulation using CFD has generally focused on the examination of primary parameters, such as temperature and species distributions. The detailed investigation on chemical reactions is limited. This paper presents the development of a post-processing tool capable of calculating the rate of production (ROP) of interested species with the known temperature, pressure, and concentration of each species in each cell simulated using CONVERGE-SAGE CFD model.

In this research, the magnetoplasmadynamic (MPD) effects of applying a toroidal magnetic field around an ionized exhaust plume were investigated to manipulate the exhaust profile of the plasma jet under near vacuum conditions. Tests for this experiment were conducted using the West Virginia University (WVU) Hypersonic Arc Jet Wind Tunnel. A series of twelve N52 grade neodymium magnets were placed in different orientations around a steel toroid mounted around the arc jet’s exhaust plume. Four different magnet orientations were tested in this experiment. Two additional configurations were run as control tests without any imposed magnetic fields surrounding the plume. Each test was documented using a set of 12 photographs taken from a fixed position with respect to the flow. The photographic data was analyzed by comparing images of the exhaust plume taken 10, 20, and 30 seconds after the plasma jet was activated.

The range-extended electric vehicle (REEV) is a complex nonlinear system powered by internal combustion engine and electricity stored in battery. This research proposed a Multiple Operation Points (MOP) control strategy of REVV based on operation features of REEV and the universal characteristic curve of the engine. The switching logic rules of MOP strategy are designed for the desired transition of the operation mode, which makes the engine running at high efficiency region. A Genetic algorithm (GA) is adapted to search the optimal solution. The fuel consumption is defined as the target cost function. The demand power of engine is defined as optimal variable. The state of charge (SOC) and vehicle speed are selected as the state variables. The dynamic performance of vehicle and cycling life of battery is set as the constraints. The optimal switching parameters are obtained based on this control strategy. Finally, a dynamic simulation model of REEV is developed in Matlab/Simulink.

Gasoline-powered vehicles compose the vast majority of all light-duty vehicles in the United States. Improving fuel economy is currently a topic of great interest due to the rapid rise in gasoline costs as well as new fuel-economy and greenhouse-gas emissions standards. The Chevrolet Silverado is currently one of the top selling trucks in the U.S. and has been previously modeled using the commercial finite element code LS-DYNA by the National Crash Analysis Center (NCAC). This state-of the art model was employed to examine alternative weight saving configurations using material alternatives and replacement of traditional steel with composite panels. Detailed mass distribution analysis demonstrated the chassis assembly to be an ideal candidate for weight reduction and was redesigned using Aluminum 7075-T6 Alloy and Magnesium Alloy HM41A-F.

3D CFD spark-ignition IC engine simulations are extremely complex for the regular user. Truly-predictive CFD simulations for the turbulent flame combustion that solve fully coupled transport/chemistry equations may require large computational capabilities unavailable to regular CFD users. A solution is to use a simpler phenomenological model such as the G-equation that decouples transport/chemistry result. Such simulation can still provide acceptable and faster results at the expense of predictive capabilities. While the G-equation is well understood within the experienced modeling community, the goal of this paper is to document some of them for a novice or less experienced CFD user who may not be aware that phenomenological models of turbulent flame combustion usually require heavy tuning and calibration from the user to mimic experimental observations.