Browse Topic: Military vehicles and equipment
This SAE Standard applies to all combinations of pneumatic tires, wheels, or runflat devices (only as defined in SAE J2013) for military tactical wheeled vehicles only as defined in SAE J2013. This applies to original equipment and new replacement tires, retread tires, wheels, or runflat devices. This document describes tests and test methodology, which will be used to evaluate and measure tire/wheel/runflat system and changes in vehicle performance. All of the tests included in this document are not required for each tire/wheel/runflat assembly. The Government Tire Engineering Office and Program Office for the vehicle system have the responsibility for the selection of a specific test(s) to be used. The selected test(s) should be limited to that required to evaluate the tire/wheel/runflat system and changes in vehicle performance. Selected requirements of this specification shall be used as the basis for procurement of a tire, wheel, and/or runflat device for military tactical wheeled
Modern-day sensors encounter performance bottlenecks due to latency in the data path to processing, analysis, and storage functions. This issue can be mitigated by introducing a direct PCI Express (PCIe) or PCIe-switched fabric connection to the sensor. PCIe significantly reduces latency, outperforming other standard connection forms like Ethernet. Let’s explore the efficiency and advantages of a PCIe connection and focus on the versatility of the PCIe-switched fabric.
The beta release of Systems Modeling Language (SysML) v2 provides a powerful, modular and interoperable modeling language that can serve as a practical and serviceable basis for the modeling of Modular Open Systems Approach (MOSA) compatible systems. This paper will explore some of the useful new features of this language and how these can be applied to the development of MOSA compatible systems. To demonstrate the capabilities of this modeling language, we will develop a “toy model” of a ground vehicle, complete with a MOSA compatible interface, in SysML v2 textual notation. Further discussion will demonstrate how this model can be distributed amongst other parties and organizations. This model will be developed fully in SysML v2 textual notation, demonstrating the power and ease of us of this new modeling notation.
As unmanned vehicular networks become more prevalent in civilian and defense applications, the need for robust security solutions grows in parallel. While ROS 2 offers a flexible platform for robotic operations, its security model lacks the adaptability required for dynamic trust management and proactive threat mitigation. To address these shortcomings, we propose a novel framework that integrates containerized ROS 2 nodes with Kubernetes-based orchestration, a dynamic trust management subsystem, and integrability with simulators for real-time and protocol-flexible network simulation. By embedding trust management directly within each ROS 2 container and leveraging Kubernetes, we overcome ROS 2’s security limitations by enabling real-time monitoring and machine learning-driven anomaly detection (via an autoencoder trained on custom data), facilitating the isolation or removal of suspicious nodes. Additionally, Kubernetes policies allow seamless scaling and enforcement of trust-based
Magnetotactic bacteria (MTB) are capable of biomineralizing crystalline single domain magnetic oxides and sulfides. MTB perform this synthesis inside of well-defined chambers attached to their cell wall called magnetosomes. Magnetosomes are phospholipid vesicles which assemble in chains inside MTB and allow the magnetic oxides to align into a self-assembled bar magnet inside the bacteria. These nano-scale bar magnets allow MTB to align with the earth’s magnetic field allowing the bacteria to thrive in natural aqueous environments as they live in a microaerophilic environment called the oxic/anoxic zone. This presentation will focus on progress regarding using these bio-synthesized magnetic particles for Department of Defense applications.
In modern defense manufacturing, achieving technological superiority hinges on both rapid decision-making and unparalleled precision engineering. Advanced machining systems, such as 5-axis CNC machines, play a pivotal role by enabling the production of intricate, free-form geometries with micron-level accuracy. However, these advances often necessitate deep domain expertise for optimal tool selection and machining parameter configuration. This paper introduces GraphLLM, a model-agnostic approach that integrates structured knowledge graphs with large language models (LLMs) to enhance the accuracy and reliability of technical responses. By automatically extracting domain-specific entities and relationships from documents, GraphLLM mitigates LLM hallucinations and improves performance, especially in technically challenging or out-of-distribution queries. Experimental evaluations across various LLaMA models demonstrate significant uplifts of 25%, highlighting the framework’s potential to
While the Department of Defense’s transition to model-based deliverables promises numerous benefits, it presents a formidable challenge for acquisition program offices struggling to acquire the requisite skill sets. A critical deficiency in experience with Systems Modeling Languages (e.g., SysML) and essential modeling tools (e.g., Cameo Systems Modeler) has resulted in a preference for traditional document-based deliverables. This paper explores how Model-Based Systems Engineers can address this gap by leveraging data-driven insights to support design reviews and enhance stakeholder communication. To overcome the challenge of limited Model-Based Systems Engineering expertise, we introduce a model-based design review tool that simplifies complex vendor system architecture models, making the information readily usable for Subject Matter Experts. The tool’s ”indirect commenting method” and heuristics facilitate effective model evaluation and increase confidence in vendor designs beyond
Data security remains an issue of the utmost concern in contested environments. Mechanisms such as data encryption, beam-forming antennas, and frequency-hopping radio have emerged to mitigate some of the concerns in radio-frequency (RF) communications, but they do not remove all risk. Consequently, there is still a consistent appetite for alternative solutions. This paper presents a case for the use of the free-space optical (FSO) communications technology ImpLi-Fi as one such alternative. FSO communication is promising because of the ease with which the signal beam may be steered and limited, making detection and interception more difficult than with RF, and ImpLi-Fi in particular is desirable for its exceptional outdoor performance and ease of integration into existing light sources. The paper briefly illustrates the origins of the contested logistics (CL) problem and CL use cases for secure communication channels, before describing the ImpLi-Fi technology in some detail; exploring
The development of cyber-physical systems necessarily involves the expertise of an interdisciplinary team – not all of whom have deep embedded software knowledge. Graphical software development environments alleviate many of these challenges but in turn create concerns for their appropriateness in a rigorous software initiative. Their tool suites further enable the creation of physics models which can be coupled in the loop with the corresponding software component’s control law in an integrated test environment. Such a methodology addresses many of the challenges that arise in trying to create suitable test cases for physics-based problems. If the test developer ensures that test development in such a methodology observes software engineering’s design-for-change paradigm, the test harness can be reused from a virtualized environment to one using a hardware-in-the-loop simulator and/or production machinery. Concerns over the lack of model-based software engineering’s rigor can be
Considering the rapid pace of technological innovation, and understanding that most of this innovation is realized through software, it’s imperative that MOSA aligned standards for software development and verification also support compliance with safety and security best practices. The Future Airborne Capability Environment® (FACE) Technical Standard is one of the foremost MOSA aligned standards designed to promote portability and create software product lines across the military aviation domain. This paper will present several ways the FACE Technical Standard and Approach, together with complementary software safety/software security standards and best practices, support the development of reusable safe and secure software.
The Vision for Off-road Autonomy (VORA) project used passive, vision-only sensors to generate a dense, robust world model for use in off-road navigation. The research resulted in vision-based algorithms applicable to defense and surveillance autonomy, intelligent agricultural applications, and planetary exploration. Passive perception for world modeling enables stealth operation (since lidars can alert observers) and does not require more expensive or specialized sensors (e.g., radar or lidar). Over the course of this three-phase program, SwRI built components of a vision-only navigation pipeline and tested the result on a vehicle platform in an off-road environment.
Advances in conformable tank technology have resulted in opportunities to harness and deploy hydrogen energy in a variety of operational environments. Various use cases are described, and the benefits of these unique storage systems in vehicular, stationary, and bulk storage applications are illustrated. The impressive scalability of conformable hydrogen tank production is also explained, as it relates to the cost effective and broad application of these storage systems.
Increasing the mission capability of ground combat and tactical vehicles can lead to new concepts of operation that enhance safety and effectiveness of warfighters. High-temperature power electronics enabled by wide-bandgap semiconductors such as silicon carbide can provide the required power density to package new capabilities into space-constrained vehicles and provide features including silent mobility, boost acceleration, regenerative braking, adaptive cooling, and power for future protection systems and command and control (C2) on the move. An architecture using high voltage [1] would best satisfy the ever-increasing power demands to enable defense against unmanned aerial systems (UAS) and offensive directed energy (DE) systems for advanced survivability and lethality capabilities.
CAMX Power is developing enhanced safety, high-power, OV-tolerant Li-ion 6T batteries implementing our CELX-RC® chemistry which incorporates our proprietary GEMX® cathode opposite lithium titanate (LTO) anode. The advantages of the CAMX Power 6T battery include high tolerance of severe mechanical, thermal and electrical abuse, exceptional fast charge capability, and extreme low-temperature performance capabilities (e.g., -60 °C). This 6T battery can also be repeatedly discharged to 0V and stored in that condition without maintenance, greatly enhancing logistical management, handling and safety. The CAMX Power 6T battery will provide enhanced performance and safety in extreme environments and operational conditions which cannot be met by 6T batteries made with conventional Li-ion chemistry.
The use of modeling and simulation (M&S) to enable aggressive training, testing, analysis, and experimentation of capabilities has risen in recent years. An increase in M&S demand to enable Force Readiness necessitates the use of modular and reusable simulation software. To meet this need, the U.S. Army Combat Capabilities Development Command Ground Vehicle Systems Center (DEVCOM GVSC) has developed a modular simulation software framework called Project Great Lakes (ProjectGL). The software supports complex simulation requirements for multiple vehicles, terrains, sensors and other technologies, while using a common, internal framework to support extensive configuration. The paper presents the framework’s core design philosophy, architecture and common use cases. The paper concludes with a discussion on possible areas of framework expansion and development guidelines for partners interested in extending the framework.
Ground vehicle software continues to increase in cost and complexity, in part driven by tightly integrated systems and vendor lock-in. One method of reducing costs is reuse and portability, encouraged by the Modular Open Systems Approach and the Future Airborne Capability Environment (FACE) architecture. While FACE provides a Conformance Testing Suite to ensure portability between compliant systems, it does not verify that components correctly implement standard interfaces and desired functionality. This paper presents a layered test methodology designed to ensure that a FACE component correctly implements working communication interfaces, correctly handles the full range of data the component is expected to manage, and correctly performs all of the functionality the component is required to perform. This testing methodology includes unit testing of individual components, integration testing across multiple units, and full hardware in the loop system integration testing, offering a
Object detection has many different uses in Command and Control (C2) systems such as autonomous control, target tracking, threat detection, and general surveillance. Graphics Processing Units (GPUs) are the de-facto standard hardware for these types of workloads in datacenter environments. Still, when deploying to an edge environment many considerations are required to ensure an optimized deployment. This paper provides a general overview of how to utilize GPUs for AI inference for object detection at the edge using NVIDIA® HoloScan as well as an overview of the many considerations to account for when selecting the most optimal GPU for any specific ground vehicle solution.
Thermal or infrared signature management simulations of hybrid electric ground vehicles require modeling complex heat sources not present in traditional vehicles. Fast-running multi-physics simulations are necessary for efficiently and accurately capturing the contribution of these electrical drivetrain components to vehicle thermal signature. The infrared signature and heat transfer simulation tool, “Multi-Service Electro-optic Signature” (MuSES), is being updated to address these challenges by expanding its thermal-electrical simulation capabilities, provide a coupling interface to system zero- and one-dimensional modeling tools, and model three-dimensional air flow and its convection effects. These simulation capabilities are used to compare the infrared signatures of a tactical ground vehicle with a traditional powertrain to a hybrid electric version of the same vehicle and demonstrate a reduction in contrast while operating under electrically powered conditions of silent watch and
The Ground Vehicle Systems Center (GVSC) has an ongoing effort to use Industrial Design to explore the toughest problems faced by the Army modernization community. That effort takes several steps from the Design thinking discipline and seeks to understand Soldier perspectives, define problems and propose conceptual solutions. This paper summarizes the employment of Industrial Design at GVSC as well as outputs from two key Design projects. It concludes by presenting the combined learned outcomes from several Design efforts at GVSC and proposes ways in which Industrial Design and Design Thinking can better drive Army modernization, by understanding user’s needs, and committing to Innovation.
The integration of digital twins within a digital thread framework offers significant benefits for managing Army ground and surface water vehicles. This paper examines how digital twins can enhance lifecycle management, operational efficiency, and maintenance for mature and new military vehicle programs. Scalable and cost-effective implementation with layered capabilities allows organizations to start with a cost-effective foundational model and phase in additional layers of capability over time. This phased approach allows you to expand your digital twin capabilities as program budgets permit, ensuring that you can adapt to evolving requirements without overwhelming upfront investment. For established programs, digital twins enable real-time monitoring, predictive analytics, and data-driven decisions, improving resource allocation and cutting costs. For new programs, they speed up prototyping, integrate modern technologies, and enhance training capabilities. Case studies demonstrate
Employment of Robotic and Autonomous Systems requires a different paradigm of mission planning, one which considers not only the tasks to be performed by the RAS themselves but regards the flow of information to support the observability of the RAS by the operator. GTRI has developed an initial capability for mission planning of mixed motive, heterogeneous, autonomous systems for management of macro level metrics that support the decision making of the operator or user during employment. The work is ongoing, extensible to additional capability sets, and modular to support integration of other autonomous capabilities.
The success of off-road missions for ground vehicles depends heavily on terrain traversability, which in turn requires a thorough understanding of soil characteristics a key component being soil moisture content. When large areas need to be analyzed, satellite imagery is often used, although this approach typically reduces the spatial resolution. This decrease of spatial resolution creates what are known as mixed pixels, when two or more classes or features are in a single pixel’s area, which can lead to noisier data and lower accuracy models. This paper investigates using linear spectral unmixing as a way to help clean / mitigate noisy data to yield better predictive models. Hyperspectral remote sensing from the Hyperion satellite platform and ground truth from the International Soil Moisture Network (ISMN) are used for the dataset. This study found that soil moisture content prediction, comparing the mixed multilayer perceptron (MLP) model with an unmixing approach revealed a 10–30
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