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Abstract - The Warrior Injury Assessment Manikin (WIAMan) was developed to assess injury in Live Fire Test and Evaluation (LFTE) and laboratory development tests of vehicles and vehicle technologies subjected to underbody blast (UBB) loading. While UBB events impart primarily vertical loading, the occupant location in the vehicle relative to the blast can result in some inherent non-vertical, or off-axis loading. In this study, the WIAMan Technology Demonstrator (TD) was subjected to 18 tests with a 350g, 5-ms time duration drop tower pulse using an original equipment manufacturer (OEM) energy attenuating seat in four conditions: purely vertical, 15° forward tilt, 15° rearward tilt, and 15° lateral tilt to simulate the partly off-axis loading of an UBB event. The WIAMan TD showed no signs of damage upon inspection. Time history data indicates the magnitude, curve shape, and timing of the response data were sensitive to the off-axis loading in the lower extremity, pelvis, and spine.

Vehicle navigation in off-road environments is challenging due to terrain uncertainty. Various approaches that account for factors such as terrain trafficability, vehicle dynamics, and energy utilization have been investigated. However, these are not sufficient to ensure safe navigation of optionally manned ground vehicles that are prone to detection using thermal infrared (IR) seekers in combat missions. This work is directed towards the development of a vehicle IR signature aware navigation stack comprised of global and local planner modules to realize safe navigation for optionally manned ground vehicles. The global planner used A* search heuristics designed to find the optimal path that minimizes the vehicle thermal signature metric on the map of terrain’s apparent temperature. The local planner used a model-predictive control (MPC) algorithm to achieve integrated motion planning and control of the vehicle to follow the path waypoints provided by the global planner.

The “holy grail” for prognostics and health management (PHM) professionals in the aviation sector is to have integrated vehicle health management (IVHM) systems incorporated into standard aircraft maintenance policies. Such a change from current aerospace industry practices would lend credibility to this field by validating its claims of reducing repair and maintenance costs and, hence, the overall cost of ownership of the asset. Ultimately, more widespread use of advanced PHM techniques will have a positive impact on safety and, for some cases, might even allow aircraft designers to reduce the weight of components because the uncertainty associated with estimating their predicted useful life can be reduced. We will discuss how standard maintenance procedures are developed, who the various stakeholders are, and – based on this understanding - outline how new PHM systems can gain the required approval to be included in these standard practices.

Advancements in electric vertical takeoff and landing (eVTOL) aircraft have generated significant interest within and beyond the traditional aviation industry. One particularly promising application involves on-demand, rapid-response use cases to broaden first responders, police, and medical transport mission capabilities. With the dynamic and varying public service operations, eVTOL aircraft can offer potentially cost-effective aerial mobility components to the overall solution, including significant lifesaving benefits.

This paper describes an approach to integrating high-fidelity vehicle dynamics with a high-fidelity gaming engine, specifically with respect to terrain. The work is motivated by the experimental need to have both high-fidelity visual content with high-fidelity vehicle dynamics to drive a motion base simulator. To utilize a single source of terrain information, the problem requires the just-in-time sharing of terrain content between the gaming engine and the dynamics model. The solution is implemented as a client-server with the gaming engine acting as a stateless server and the dynamics acting as the client. The client is designed to actively maintain a locally cashed terrain grid around the vehicle and actively refresh it by polling the server in an on-demand mode of operation. The paper discusses the overall architecture, the protocol, the server, and the client designs. A practical implementation is described and shown to effectively function in real-time.

Frequently, a choice between system concepts must be made on the basis of something other than a detailed evaluation of the design effectiveness of these systems. This paper develops a rudimentary analysis process for use in addressing this problem.

The second-life use of batteries from electric vehicles (EV) represents an excellent and cost-effective option for energy storage applications, including the control of fluctuations in energy supply and demand or in combination with solar photovoltaic and wind turbine. Indeed, these batteries are normally replaced from EV use before the end of their service life, when they still have 70-80% of the original capacity. Depending on the cell chemistry and the specific design, such batteries can still be employed in less stressful applications than the automotive one, including commercial, residential, and industrial applications. With the aim to promote the transition to a circular closed-loop economy for spent traction batteries, this study consists in a systematic literature review of available options for reusing EV batteries as a storage system in a factory environment, highlighting benefits and critical aspects.

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.

In alignment with the U.S. Army's Climate Strategy and the broader trend in automotive technology, there is a strategic shift towards electrification and hybridization of the vehicle fleet. While a major goal of this effort is to mitigate the carbon footprint of the U.S. Army's vehicle operations, this transition also presents an opportunity to harness advancements in automotive electrification. Among the key vehicles in focus are tactical wheeled vehicles, which provide military forces with versatile and rugged transportation solutions for various combat scenarios, ensuring mobility, protection, and adaptability on the battlefield. This study investigates the potential of electrified tactical wheeled vehicles by conducting a survey involving a diverse group of vehicle operators across various ranks within the U.S. Army.

The aim of this paper is to present a numerical analysis of high-speed flows over a missile geometry. The N1G missile has been selected for our study, which is subjected to a high-speed flow at Mach 4 over a range of Angle of attack (AoA) from 0° to 6°. The analysis has been conducted for a 3-dimensional missile model using ANSYS environment. The study contemplates to provide new insights into the missile aerodynamic performance which includes the coefficient of lift (CL) , coefficient of drag (CD) and coefficient of moment (CM) using computational fluid dynamics (CFD). As there is a lack of availability of data for missile geometry, such as free stream conditions and/or the experimental data for a given Mach number, this paper intends to provide a detailed analysis at Mach 4. As the technology is advancing, there is a need for high-speed weapons (missiles) with a good aerodynamic performance, which intern will benefit in reduction of fuel consumption.

Materials play a key role in our day to day life and have shaped the industrial revolution to a great extent. Right selection of material for meeting a particular objective is the key to success in today’s world where the cost as well as sustainability of any equipment or a system have assumed greater significance than ever before. In automotive industry, materials have a definitive role as far as the mobility and safety is concerned. Materials that can absorb the required energy or impact can be manufactured through different manufacturing as well as metallurgical processes which involves appropriate heat treatment and bringing correct chemical compositions etc. However, they can also be formed by simpler methods such as combining certain materials together in the form of layered combinations to form light weight composites.

A common scenario in engineering design is the availability of several black-box functions that describe an event with different levels of accuracy and evaluation cost. Solely employing the highest fidelity, often the most expensive, black-box function leads to lengthy and costly design cycles. Multi-fidelity modeling improves the efficiency of the design cycle by combining information from a small set of observations of the high-fidelity function and large sets of observations of the low-fidelity, fast-to-evaluate functions. In the context of Bayesian optimization, the most popular multi-fidelity model is the auto-regressive (AR) model, also known as the co-kriging surrogate. The main building block of the AR model is a weighted sum of two Gaussian processes (GPs). Therefore, the AR model is well suited to exploit information generated by sources that present strong linear correlations.

The advancement of both sensory and unmanned technology, combined with increased utilization of autonomous platforms in complex teaming scenarios, has created a need for practical design space exploration tools to aid in the synthesis of effective System-of-Systems (SoS). The presented work describes a modular, flexible, and extensible framework, referred to herein as the Technologies and Teaming Evaluation (TATE) framework, for straightforward identification of high-quality SoS, which may include both manned and autonomous elements, through quantitative evaluation of system-level and SoS-level attributes against a set of user-defined reference tasks.

Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.

In the early days, there were significant limitations to the build size of laser powder bed fusion (L-PBF) additive manufacturing (AM) machines. However, machine builders have addressed that drawback by introducing larger L-PBF machines with expansive build volumes. As these machines grow, their size capability approaches that of directed energy deposition (DED) machines. Concurrently, DED machines have gained additional axes of motion which enable increasingly complex part geometries—resulting in near-overlap in capabilities at the large end of the L-PBF build size. Additionally, competing technologies, such as binder jet AM and metal material extrusion, have also increased in capability, albeit with different starting points. As a result, the lines of demarcation between different processes are becoming blurred.

While traveling on any type of ground, the damper of a vehicle has the critical task of attenuating the vibrations generated by its irregularities, to promote safety, stability, and comfort to the occupants. To reach that goal, several passive dampers projects are optimized to embrace a bigger frequency range, but, by its limitations, many studies in semiactive and active dampers stands out by promoting better control of the vehicle dynamics behavior. In the case of military vehicles, which usually have more significant dimensions than the common ones and can run on rough or unpaved lands, the use of semi-active or active dampers reveals itself as a promising alternative. Motivated by that, the present study performs an analysis of the vertical dynamics of a wheeled military vehicle with four axles, using magnetorheological dampers. This study is made using a configuration of the distances between the axles of the vehicle, which is chosen from five available options.

Mobile heavy article tilter and positioner (HATP) is special purpose vehicle designed to level, articulate and positioning of very heavy load within the accuracy of arc minutes and in a stipulated time in fully auto mode. HATP system uses sophisticated electronic controller system to carry out required task in auto mode. This electronic controller system comprises of various types of electronic hardware, software, sensors and actuators. As this system is dealing with heavy load, any failure in any of subsystem of HATP can result into catastrophe. Therefore active and passive safety measure at various levels must be incorporated into system which firstly prevents the failure and reduce the effect of failure. The safety system for HATP system has been divided in three major levels: 1. Access level safety 2. Operational safety 3. Preventive safety. All three levels of safety is incorporated at appropriate subsystem based on Risk Priority Number (RPN) and failure mode effect analysis.