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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.

We describe how we apply the SAE AS 5506 Architecture and Analysis Design Language (AADL) [4] to reason about contextual and architectural concerns for cyber security. A system’s cyber security certification requires verification that the system’s cyber security mechanisms are correct, non-bypassable, and tamper-resistant. We can verify correctness by examining the mechanism itself, but verifying the other qualities requires us to examine the context in which that mechanism resides. Understanding that context and validating the system’s evolving design against that context is an objective for the Architecture Centric Virtual Integration Process (ACVIP), an AADL-based approach to model and detect system design defects before they become too costly to fix. We describe our work to apply AADL to assess non-bypassability and tamper-resistance. The results of our research - tool plugins for cyber security architectural validation - support system developers today in their ACVIP activities.

Game-changing opportunities abound for the application of vehicle health management (VHM) across multiple transportation-related sectors, but key unresolved issues continue to impede progress. VHM technology is based upon the broader field of advanced analytics. Much of traditional analytics efforts to date have been largely descriptive in nature and offer somewhat limited value for large-scale enterprises. Analytics technology becomes increasingly valuable when it offers predictive results or, even better, prescriptive results, which can be used to identify specific courses of action. It is this focus on action which takes analytics to a higher level of impact, and which imbues it with the potential to materially impact the success of the enterprise. Artificial intelligence (AI), specifically machine learning technology, shows future promise in the VHM space, but it is not currently adequate by itself for high-accuracy analytics.

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.

In recent years, the increasing complexity of modern aerospace systems has driven the rapid adoption of robust Model-Based Systems Engineering (MBSE). MBSE is a development methodology centered around computational models, which are instrumental in supporting the design and analysis of intricate systems. In this context, the Architecture Analysis and Design Language (AADL) and Systems Modeling Language (SysML) are two prominent modeling languages for specifying and analyzing the structure and behavior of a cyber-physical system. Both languages have their own specific use cases and tool environments and are typically employed to model different aspects of system design. Although multiple software tools are available for transforming models from one language to another, their effectiveness is limited by fundamental differences in the semantics of each language.

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.

This paper investigates the fuel saving potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the Lithium-ion battery pack in the hybridized configuration. On the other hand, the powertrain supervisory control optimization finds the most efficient way to split power demands between the battery pack and the engine. Most of the previous literatures implement them separately. In contrast, combining the sizing and energy management problem into a single optimization problem produces the global optimal solution. This study proposes a novel unified framework to couple Genetic Algorithm (GA) with Pontryagin’s Minimum Principle (PMP) to determine the battery pack sizing and the power split control sequence simultaneously.

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.

Success in metal additive manufacturing (AM) relies on the optimization of a large set of process parameters to achieve materials whose properties and performance meet design and safety requirements. Despite continuous improvements in the process over the years, the quality of AM parts remains a major concern for manufacturers. Today, researchers are starting to move from discrete geometry-dependent build parameters to continuously variable or dynamically changing parameters that are geometry- and scan-path aware. This approach has become known as “feedforward control.” Process Control for Defect Mitigation in Laser Powder Bed Fusion Additive Manufacturing discusses the origins of feedforward control, its early implementations in AM, the current state of the art, and a path forward to its broader adoption. Click here to access the full SAE EDGETM Research Report portfolio.

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.

We present an approach in which we use simulation to capture the two-way coupling between the dynamics of a vehicle and that of a fluid that sloshes in a tank attached to the vehicle. The simulation is carried out in and builds on support provided by two modules: Chrono::FSI (Fluid-Solid Interaction) and Chrono::Vehicle. The dynamics of the fluid phase is governed by the mass and momentum (Navier-Stokes) equations, which are discretized in space via a Lagrangian approach called Smoothed Particle Hydrodynamics. The vehicle dynamics is the solution of a set of differential algebraic equations of motion. All equations are discretized in time via a half-implicit symplectic Euler method. This solution approach is general - it allows for fully three dimensional (3D) motion and nonlinear transients. We demonstrate the solution in conjunction with the simulation of a vehicle model that performs a constant radius turn and double lane change maneuver.

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.

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.