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The recently published Lightweight Combat Vehicle Science and Technology Campaign [1] recommended the Army develop a quantitative understanding of the operational impact that weight reduction has to the Army and create appropriate metrics that would better reflect the performance trade with regards to weight. That paper raised the question of what a ton of weight is worth in operational effectiveness and cost. This paper is an attempt to clarify this complex topic. The impact of select programmatic considerations, operational considerations, and financial considerations are discussed. Throughout, the paper provides example analyses based on vehicle weight, performance, and cost data. The paper closes with a discussion of the issues presented, research recommendations, and closing comments.

Warranty forecasting of repairable systems is very important for manufacturers of mass produced systems. It is desired to predict the Expected Number of Failures (ENF) after a censoring time using collected failure data before the censoring time. Moreover, systems may be produced with a defective component resulting in extensive warranty costs even after the defective component is detected and replaced with a new design. In this paper, we present a forecasting method to predict the ENF of a repairable system using observed data which is used to calibrate a Generalized Renewal Processes (GRP) model. Manufacturing of products may exhibit different production patterns with different failure statistics through time. For example, vehicles produced in different months may have different failure intensities because of supply chain differences or different skills of production workers, for example.

We have recently obtained experimental data and used them to develop computational models to quantify occupant impact responses and injury risks for military vehicles during frontal crashes. The number of experimental tests and model runs are however, relatively small due to their high cost. While this is true across the auto industry, it is particularly critical for the Army and other government agencies operating under tight budget constraints. In this study we investigate through statistical simulations how the injury risk varies if a large number of experimental tests were conducted. We show that the injury risk distribution is skewed to the right implying that, although most physical tests result in a small injury risk, there are occasional physical tests for which the injury risk is extremely large. We compute the probabilities of such events and use them to identify optimum design conditions to minimize such probabilities.

The U.S. Army currently uses JP-8 for global operations according to the "one fuel forward policy" that was enacted almost twenty years ago in order to help reduce the logistics burden of supplying a variety of fuels for given Department of Defense vehicle and base applications. One particular challenge with using global JP-8 is the lack of or too broad a range of specified combustion and fuel system affecting properties including ignition quality, high temperature viscosity, and lubricity. In addition to these challenges, the JP-8 fuel specification currently allows the use of blending with certain types of synthetic jet fuels up to 50% by volume. This blended fuel also doesn't include an ignition quality or high temperature viscosity specification, but does include a lubricity specification that is much less restrictive than DF-2.

Vehicle surface contamination can degrade not only soldier vision but also the effectiveness of camera and sensor systems mounted externally on the vehicle for autonomy and situational awareness. In order to control vehicle surface contamination, a better understanding of dust particle generation, transport and accumulation is necessary. The focus of the present work is simulation of vehicle surface contamination on the rear part of the vehicle due to the interaction of the combat vehicle track with the ground and dust in the surrounding ambient atmosphere. A notional tracked military vehicle is used for the Computational fluid dynamics (CFD) simulation. A CFD methodology with one-way-coupled Lagrangian particle modeling is used. The simulation is initially run with only air flow to solve the air pressure, velocity, and turbulence quantities in a steady state condition.

Diesel engine cold-start problems include long cranking periods, hesitation and white smoke emissions. A better understanding of these problems is essential to improve diesel engine cold-start. In this study computer simulation model is developed for the steady state and transient cold starting processes in a single-cylinder naturally aspirated direct injection diesel engine. The model is verified experimentally and utilized to determine the key parameters that affect the cranking period and combustion instability after the engine starts. The behavior of the fuel spray before and after it impinges on the combustion chamber walls was analyzed in each cycle during the cold-start operation. The analysis indicated that the accumulated fuel in combustion chamber has a major impact on engine cold starting through increasing engine compression pressure and temperature and increasing fuel vapor concentration in the combustion chamber during the ignition delay period.

All previous correlations of the ignition delay (ID) period in diesel combustion show a positive activation energy, which means that shorter ID periods are achieved at higher charge temperatures. This is not the case in the autoignition of most homogeneous hydrocarbons-air mixtures where they experience the NTC (Negative Temperature Coefficient ) regime in the intermediate temperature range, from about 800 K to 1000 K). Here, the autoignition reactions slow down and longer ID periods are experienced at higher temperatures. Accordingly the global activation energy for the autoignition reactions of homogeneous mixtures should vary from positive to negative values.

Mercury is a high-fidelity, physics-based object-oriented software for conducting simulations of vehicle performance evaluations for requirements and engineering metrics. Integrating cutting-edge, massively parallel modeling techniques for soft, cohesive and dry granular soil that will integrate state-of-the-art soil simulation with high-fidelity multi-body dynamics and powertrain modeling to provide a comprehensive mobility simulator for ground vehicles. The Mercury implements the Chrono::Vehicle dynamics library for vehicle dynamics, which provides multi-body dynamic simulation of wheeled and tracked vehicles. The powertrain is modeled using the Powertrain Analysis Computational Environment (PACE), a behavior-based powertrain analysis based on the U.S. Department of Energy’s Autonomie software. Vehicle -terrain interaction (VTI) is simulated with the Ground Contact Element (GCE), which provides forces to the Chrono-vehicle solver.

Systems engineering is a key discipline to develop, deploy, and sustain military systems. The wide variety of product types and the tendency to leverage emerging technologies require that disciplined technical planning and management processes be used by both engineers and program managers in all phases of a product's life cycle. This paper describes requirements development, management, and architecture in military systems engineering and acquisition be it software or hardware.

Reliability and resiliency (R&R) definitions differ depending on the system under consideration. Generally, each engineering sector defines relevant R&R metrics pertinent to their system. While this can impede cross-disciplinary engineering projects as well as research, it is a necessary strategy to capture all the relevant system characteristics. This paper highlights the difficulties associated with defining performance of such systems while using smart microgrids as an example. Further, it develops metrics and definitions that are useful in assessing their performance, based on utility theory. A microgrid must not only anticipate load conditions but also tolerate partial failures and remain optimally operating. Many of these failures happen infrequently but unexpectedly and therefore are hard to plan for. We discuss real life failure scenarios and show how the proposed definitions and metrics are beneficial.

Optimizing the trade-off between reliability and cost of operating a microgrid, including vehicles as both loads and sources, can be a challenge. Optimal energy management is crucial to develop strategies to improve the efficiency and reliability of microgrids, as well as new communication networks to support optimal and reliable operation. Prior approaches modeled the grid using MATLAB, but did not include the detailed physics of loads and sources, and therefore missed the transient effects that are present in real-time operation of a microgrid. This article discusses the implementation of a physics-based detailed microgrid model including a diesel generator, wind turbine, photovoltaic array, and utility. All elements are modeled as sources in Simulink. Various loads are also implemented including an asynchronous motor. We show how a central control algorithm optimizes the microgrid by trying to maximize reliability while reducing operational cost.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Real-time driving simulations are an important tool for verifying vehicle and vehicle component designs with a driver in the loop. They not only provide a cost effective solution but also an ability to verify designs in a safe and controlled operating environment. A real-time driving experiment has been developed for Stryker to compare the ride and handling performance of a baseline passive suspension to that of a Magneto-Rheological (MR) semi-active damper suspension. The Tank Automotive Research Development and Engineering Center (TARDEC) has integrated this new suspension into a real time vehicle dynamics model of the Stryker using the MR suspension model developed by the Original Equipment Manufacturer (OEM). Using this real-time model and the TARDEC Ride Motion Simulator (RMS), TARDEC associates, along with associates from the Stryker Program Management office and the suspension OEM were able to drive and compare the passive and MR Stryker in a virtual environment.

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.

Several mechanisms are discussed to understand the particulate matter (PM) characterization in a high speed, direct injection, single cylinder diesel engine using low sulfur diesel fuel. This includes their formation, size distribution and number density. Experiments were conducted over a wide range of injection pressures, EGR rates, injection timings and swirl ratios, therefore covering both conventional and low temperature combustion regimes. A micro dilution tunnel was used to immediately dilute a small part of the exhaust gases by hot air. A Scanning Mobility Particle Sizer (SMPS) was used to measure the particulate size distribution and number density. Particulate mass was measured with a Tapered Element Oscillating Microbalance (TEOM). Analysis was made of the root cause of PM characterization and their relationship with the combustion process under different operating conditions.

The objective of this study was to optimize the occupant restraint systems for a light tactical vehicle in frontal crashes. A combination of sled testing and computational modeling were performed to find the optimal seatbelt and airbag designs for protecting occupants represented by three size of ATDs and two military gear configurations. This study started with 20 sled frontal crash tests to setup the baseline performance of existing seatbelts, which have been presented previously; followed by parametric computational simulations to find the best combinations of seatbelt and airbag designs for different sizes of ATDs and military gear configurations involving both driver and passengers. Then 12 sled tests were conducted with the simulation-recommended restraint designs. The test results were further used to validate the models. Another series of computational simulations and 4 sled tests were performed to fine-tune the optimal restraint design solutions.

Current U.S. Army ground vehicles predominately use commercial off-the-shelf or modified commercial diesel engines as the prime mover. Unique military engines are typically utilized when commercial products do not meet the mobility requirements of the particular ground vehicle in question. In either case, such engines traditionally have been calibrated using North American diesel fuel (DF-2) and Jet Propellant 8 (JP-8) compatibility wasn't given much consideration since any associated power loss due to the lower volumetric energy density was not an issue for most applications at then targeted climatic conditions. Furthermore, since the genesis of the ‘one fuel forward policy’ of using JP-8 as the single battlefield fuel there has been limited experience to truly assess fuel effects on diesel engine combustion systems until this decade.

U.S. Army ground vehicles predominately use JP-8 as the energy source for ground vehicles based on the ‘one fuel forward policy’. Though this policy was enacted almost twenty years ago, there exists little fundamental JP-8 combustion knowledge at diesel engine type boundary conditions. Nevertheless, current U.S. Army ground vehicles predominately use commercial off-the-shelf or modified commercial diesel engines as the prime mover. Unique military engines are typically utilized when commercial products do not meet the mobility and propulsion system packaging requirements of the particular ground vehicle in question.

This paper presents a computational framework for the physics-based simulation of light vehicles operating on discrete terrain. The focus is on characterizing through simulation the mobility of vehicles that weigh 1000 pounds or less, such as a reconnaissance robot. The terrain is considered to be deformable and is represented as a collection of bodies of spherical shape. The modeling stage relies on a novel formulation of the frictional contact problem that requires at each time step of the numerical simulation the solution of an optimization problem. The proposed computational framework, when run on ubiquitous Graphics Processing Unit (GPU) cards, allows the simulation of systems in which the terrain is represented by more than 0.5 million bodies leading to problems with more than one million degrees of freedom.

Non-conventional operating conditions and fuels in diesel engines can produce longer ignition delays compared to conventional diesel combustion. If those extended delays are longer than the injection duration, the ignition and combustion progress can be significantly influenced by the transient following the end of injection (EOI), and especially by the modification of the mixture field. The objective of this paper is to assess how those long ignition delays, obtained by injecting at low in-cylinder temperatures (e.g., 760-800K), are affected by EOI. Two multi-hole diesel fuel injectors with either six 0.20mm orifices or seven 0.14mm orifices have been used in a 2.34L single-cylinder optical diesel engine. We consider a range of ambient top dead center (TDC) temperatures at the start of injection from 760-1000K as well as a range of injection durations from 0.5ms to 3.1ms. Ignition delays are computed through the analysis of both cylinder pressure and chemiluminescence imaging.