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Currently, when the Army studies ride quality and comfort, 6 Watts of absorbed power is commonly cited as a target. However, absorbed power is dependent upon vehicle speed and road roughness and does not fully describe the direct interaction between the occupant and the seat cushion. Recently, there has been a great deal of growth in Body Pressure Distribution (BPD) measurement technologies. This growth in technology allows for new perspectives in quantifying ride comfort. Up to this point, the Army has not capitalized on these new technologies and still heavily on absorbed power to quantify ride comfort. This paper explores how the Army has benefited from pressure mapping technologies to complement absorbed power in quantifying ride comfort of military vehicles.

This work is based on a current project funded by the United States Army Small Business Innovation Research (SBIR) Program and is being conducted with the Tank Automotive Research, Development and Engineering Center (TARDEC) Ground Systems Survivability (GSS) Team and Paradigm Research and Engineering. The focus of this project is to develop an advanced and novel sensing and activation strategy for Pyrotechnic Restraint Systems, Air Bags and other systems that may require activation. The overriding technical challenge is to activate these systems to effectively protect the Soldier during blast events in addition to Crash, Rollover and Other Injury Causing events. These activations of Pyrotechnic systems must occur in fractions of milliseconds as compared to typical automotive crashes.

In this paper, the capability of three methods of modelling detonation of high explosives (HE) buried in soil viz., (1) coupled discrete element & particle gas methods (DEM-PGM) (2) Structured - Arbitrary Lagrangian-Eulerian (S-ALE), and (3) Arbitrary Lagrangian-Eulerian (ALE), are investigated. The ALE method of modeling the effects of buried charges in soil is well known and widely used in blast simulations today [1]. Due to high computational costs, inconsistent robustness and long run times, alternate modeling methods such as Smoothed Particle Hydrodynamics (SPH) [2, 9] and DEM are gaining more traction. In all these methods, accuracy of the analysis relies not only on the fidelity of the soil and high explosive models but also on the robustness of fluid-structure interaction. These high-fidelity models are also useful in generating fast running models (FRM) useful for rapid generation of blast simulation results of acceptable accuracy.

Mobility assessment for combat vehicles is often a great challenge for the military due to various subjective attributes. The attributes' characteristics vary significantly depending on the vehicle type and its operating environments such as terrain, weather, and human factors. A clear definition and relationship between multiple attributes including human factors is necessary to assess mobility. To the best of authors' knowledge, many existing mobility assessment techniques use complex analytical methods and focus on individual attributes. In this paper, for the first time, the authors propose a novel approach to define vehicle mobility and its influencing attributes using qualitative linguistic fuzzy variables, which are defined as having values between 0 and 1. The authors also propose a fuzzy logic mobility (FLM) model and a simulation approach to assess a combat vehicle's mobility.

Fatigue damage sensing and monitoring of any structure is a prerequisite for reliable and effective structural health diagnosis. The designed sensor has alternate slots and strips with different strain magnification factor with respect to the nominal strain at its location. The strips experience the strains which closely resemble the actual strain distribution in the critical area of the component. One of the major advantages of this sensor is that it can be placed at any convenient location, still experiencing the same fatigue damage as a critical location. It can be used on various structures from ground civilian and military vehicles to steel bridges. This can predict the remaining useful life of a component or the number of miles (for any automobile) left for the component before it needed replacement. This paper mainly describes the design aspects of this sensor following analytical and finite element analysis (FEA) approaches.

The foundation of the nonlinear theory of asymmetric anisotropic sandwich plates with a first order compressible weak orthotropic core under a Friedlander-Type explosive blast is presented. The equations of motion are developed by means of Hamilton's Principle. Within the theory, the face sheets are asymmetric while adopting the Love-Kirchoff model. In addition, the core layer is assumed to be compressible (extensible) in the transverse direction thereby capturing any wrinkling or global instabilities. The theory is then simplified and applied for the case of sandwich plates with symmetric unidirectional fiber reinforced laminated composite facings with the axes of orthotropy not necessarily coincident with the geometrical axes. The governing solution is developed using the Extended-Galerkin method resulting in two coupled nonlinear second order ordinary differential equations which are then solved using the adaptive 4th-Order Runge-Kutta Method for a system of differential equations.

This paper discusses a new Department of Defense (DoD) initiative focused on the development of new generation of MBS computer software that have capabilities and features that are not provided by existing MBS software technology. This three-decade old technology fails to meet new challenges of developing more detailed models in which the effects of significant changes in geometry and large deformations cannot be ignored. New applications require accurate continuum mechanics based vehicle/soil interaction models, belt and chain drive models, efficient and accurate continuum based tire models, cable models used in rescue missions, models that accurately capture large deformations due to thermal and excessive loads, more accurate bio-mechanics models for ligaments, muscles, and soft tissues (LMST), etc.

An experimental investigation was conducted on a small-bore, high-speed diesel engine to study the effect of different operating parameters on combustion and engine-out emissions in the conventional and low temperature regimes. For the conventional diesel combustion, the spray behavior is analyzed and a differentiation is made between the conditions in the small-bore and the larger bore quiescent chamber engines. The effects of the injection pressure, exhaust gas recirculation (EGR), injection timing and swirl ratio (SR) on combustion and engine-out emission are investigated. The trade-off between NOx and smoke, measured in Bosch smoke unit, (BSU), is investigated with a special attention to the low temperature combustion regime, (LTC). The results showed that the LTC regime could be reached at fairly high EGR rates under all the injection pressures investigated in this work. The margin for the variation in EGR was limited just before the misfiring EGR.

An experimental study was carried out to visualize the spray and combustion inside an AVL single-cylinder research diesel engine converted for optical access. The injection system was a hydraulically-amplified electronically-controlled unit injector capable of high injection pressure up to 180 MPa and injection rate shaping. The injection characteristics were carefully characterized with injection rate meter and with spray visualization in high-pressure chamber. The intake air was supplied by a compressor and heated with a 40kW electrical heater to simulate turbocharged intake condition. In addition to injection and cylinder pressure measurements, the experiment used 16-mm high-speed movie photography to directly visualize the global structures of the sprays and ignition process. The results showed that optically accessible engines provide very useful information for studying the diesel combustion conditions, which also provided a very critical test for diesel combustion models.

A simulation approach is defined that integrates a military mission assessment tool (One Semi-Automated Forces) with a commercial automotive control/energy consumption development tool (Autonomie). The objective is to enable vehicle energy utilization and fuel consumption impact assessments relative to US Army mission effectiveness and commercial drive cycles. The approach to this integration will be described, along with its potential to meet its objectives.

The Powertrain Analysis and Computational Environment (PACE) is a forward-looking powertrain simulation tool that is ready for a High-Performance Computing (HPC) environment. The code, written in C++, is one actor in a comprehensive ground vehicle co-simulation architecture being developed by the CREATE-GV program. PACE provides an advanced behavioral modeling capability for the powertrain subsystem of a conventional or hybrid-electric vehicle that exploits the idea of reusable vehicle modeling that underpins the Autonomie modeling environment developed by the Argonne National Laboratory. PACE permits the user to define a powertrain in Autonomie, which requires a single desktop license for MATLAB/Simulink, and port it to a cluster computer where PACE runs with an open-source BSD-3 license so that it can be distributed to as many nodes as needed.

The United States Army Tank Automotive Research, Development and Engineering Center (TARDEC) built systems to measure the suspension parameters, center of gravity, and moments of inertia of wheeled vehicles. This is part of an ongoing effort to model and predict vehicle dynamic behavior. The new machines, the Suspension Parameter Identification and Evaluation Rig (SPIdER) and the Vehicle Inertia Parameter Evaluation Rig (VIPER), have sufficient capacity to cover most heavy, wheeled vehicles. The SPIdER operates by holding the vehicle sprung mass nominally fixed while hydraulic cylinders move an “axle frame” in bounce or roll under each axle being tested. Up to two axles may be tested at once. Vertical forces at the tires, displacements of the wheel centers in three dimensions, and steer and camber angles are measured.

Fatigue life estimation, reliability and durability are important in acquisition, maintenance and operation of vehicle systems. Fatigue life is random because of the stochastic load, the inherent variability of material properties, and the uncertainty in the definition of the S-N curve. The commonly used fatigue life estimation methods calculate the mean (not the distribution) of fatigue life under Gaussian loads using the potentially restrictive narrow-band assumption. In this paper, a general methodology is presented to calculate the statistics of fatigue life for a linear vibratory system under stationary, non-Gaussian loads considering the effects of skewness and kurtosis. The input loads are first characterized using their first four moments (mean, standard deviation, skewness and kurtosis) and a correlation structure equivalent to a given Power Spectral Density (PSD).

Designing an efficient cooling system with low power consumption is of high interest in the automotive engineering community. Heat generated due to the propulsion system and the on-board electronics in ground vehicles must be dissipated to avoid exceeding component temperature limits. In addition, proper thermal management will offer improved system durability and efficiency while providing a flexible, modular, and reduced weight structure. Traditional cooling systems are effective but they typically require high energy consumption which provides motivation for a paradigm shift. This study will examine the integration of passive heat rejection pathways in ground vehicle cooling systems using a “thermal bus”. Potential solutions include heat pipes and composite fibers with high thermal properties and light weight properties to move heat from the source to ambient surroundings.