Browse Topic: Military vehicles and equipment

Items (2,758)
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
Truck and Bus Tire Committee
TOC
Tobolski, Sue
Hybrid powertrain technology serves to improve performance, enable new functional capabilities, decrease fuel consumption, increase operational reach, and increase lethality by supporting advanced weapons systems. Several demonstrators have been developed for the Army, including those recently commissioned and tested by numerous programs over the last decade. This work examines the results of one of these demonstrators for a Light Tactical Vehicle (LTV) and analyzes tradeoffs in the components’ characteristics, including the battery size, energy, and power capabilities, specifically regarding the system’s ability to meet key performance and power generation requirements. This work was completed through test data analysis coupled with a vehicle 1D simulation. Results show design implementation impacts and tradeoffs between vehicle weight, performance, EV-only range, and fuel consumption that can be utilized for system-level optimization.
Worm, Zander ThomasGoodenough, BryantSchmidt, HenryPutrus, JohnathonNaber, Jeffrey
The automotive industry’s systems and over-the-air (OTA) updates have vulnerabilities in its software supply chain (SSC). Although frameworks like Uptane have improved OTA security, gaps remain in ensuring software integrity and provenance. In this paper, we examine challenges securing the automotive SSC and introduce a framework, GUIXCHAIN, that integrates version control, reproducible builds, blockchain technology, and software bills of materials (SBoMs) for transparency, auditability, and resilience. Reproducible builds guarantee identical resulting binaries when compiling the same source code in different environments, as any deviation in the final output indicates a potential compromise in the build process, such as malware injection. Our preliminary study shows Guixchain’s use of reproducible builds ensures consistent and integrity-secured software across various build environments. The blockchain provides forensic capabilities, offering a history of the what, who and where of
Aideyan, IwinosaPesé, Mert D.Brooks, Richard
In shoot-and-scoot tactics, a common rule is that artillery units should not reuse firing positions; a more cautious rule is that they should not even pass near an old firing position when relocating. We use the cautious rule to define a variant of the traveling salesman problem, where an artillery unit shall use as many firing positions as possible with minimal travel time and never reuse or pass near an old firing position. We develop greedy and randomized heuristic algorithms and test them on some examples, and an auxiliary algorithm that finds a lower bound of the travel time. We also use “independent sets” of graph theory to reduce a problem instance to one or several smaller instances. We find that one can get good solutions reasonably fast by running a randomized algorithm repeatedly and that problem reduction via independent sets can improve performance.
Damgaard, Thomas JonssonRittri, Mikael
Automated, telerobotic, and autonomous off road vehicles present unique safety concerns for their users, both military and civilian, due to their complexity and their extensive use of open source software. This is particularly true when personnel are intermingled with vehicles as is common during many operations. This paper presents a unique approach to providing true functional safety while permitting the developers of the automated/telerobotic/autonomous hardware and software to rapidly implement changes and improvements.
Underhill, MarkDelecki, RichSullivan, Denis O.
The emergence of SUAS as a threat vector introduces significant challenges in surveillance and defense due to their potential for low cross section and high speeds, defeating or evading many existing detection and tracking capabilities. This paper presents two algorithms—one for detection and one for tracking—developed for event cameras, which offer substantial improvements in temporal resolution, dynamic range, and low-light performance compared to traditional imaging systems, all of which are critical for effective UAS defense. These advancements address current limitations in using event cameras and pave the way for a new generation of robust robotic vision based on event cameras.
Anthony, DavidChambers, DavidTowler, Jerry
In the ever-evolving landscape of ground vehicle development, the integration of Artificial Intelligence (AI), Machine Learning (ML), and Software Production Factory (SPF) technologies offers unprecedented opportunities to accelerate rapid prototyping processes. This whitepaper explores the synergistic potential of these cutting-edge technologies, detailing their transformative impact on the design, development, and deployment of advanced ground vehicle systems. By leveraging AI and ML algorithms, engineers can automate complex design tasks, predict performance outcomes, and optimize configurations with unparalleled precision. Enhanced modeling and simulation capabilities driven by AI and ML, combined with Digital Engineering threads and twin, allow for more accurate virtual testing environments, reducing the need for physical prototypes and accelerating the iterative design process. This whitepaper serves as a crucial guide for stakeholders seeking to harness the full potential of
Griffin, KevinKanon, RobertRinaldo, AnthonyKouba, Russ
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.
Reardon, Jim
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.
Brechtel, Charles E.Massey, Steven
A kinematic model of primary piston motion was developed along with a simplified combustion model for the purpose of evaluating various factors that could impact the piston skirt thrust loads of an Opposed Piston Two Stroke Diesel engine. The assessment considered connecting rod length, wrist pin mass, peak cylinder pressure, indicated torque, and wrist pin offset. The results show that small changes in connecting rod length could realize significant improvements in piston skirt friction as well as increased engine performance. The results indicate that small increases in overall engine width should be considered when optimizing for reduced oil consumption and enhanced piston skirt lubrication.
Srodawa, John
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
Tinker, NoahBoone, JuliaWang, Kuang-Ching
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.
Allen, Mark A.Jahnke, Justin P.Beyer, Frederick L.
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
Hoang, DannyGorsich, DavidCastanier, MatthewImani, Farhad
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
Connor, ZacharyScheithauer, SarahKoduru, RohithNardone, TannerLambert, Patrick
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
Brzozowski, AaronReimann, JethroLakshmanan, SridharMarrero, Pedro “Pete”Moyer, Benjamin D.
The U.S. Army and broader Department of Defense (DoD) require increasingly advanced energy storage solutions to power modern military vehicles and command systems. The adoption of electrified platforms, as well as the demand for silent watch, high-power surges, and wide-temperature operation, is pushing battery technology beyond the capabilities of conventional lead-acid and standard lithium-ion (Li-ion) chemistries. Tyfast has introduced a novel lithium vanadium oxide (LVO) anode that delivers high power, rapid charge capability, exceptional cycle life, and broad operating temperatures – all while using 100% domestically sourced vanadium oxide and lithium feedstock. This paper presents an overview of LVO-based battery technology, its performance characteristics, safety evaluations, and potential applications in military operations. We also highlight how this novel chemistry complements Army modernization goals and provides a path for future hybrid-electric combat and tactical vehicles
Liu, Haodongla O’, Gerardo JoseLiu, Ping
The publishing of MIL-STD-3072 is critical to the Army’s introduction of electrified vehicles. It is the first of three documents to replace MIL-PRF-GCS600A, a performance specification that is loosely referenced by engineers but lacks necessary details. MIL-STD-3072 defines the characteristics of 600 VDC electric power that will be supplied to utilization equipment. Following this release, MIL-HDBK-3072 will provide suggested test methods for compliance with the standard, and MIL-PRF-3072 will provide generic device specifications for interfaces, control, and safety. Together, these three documents define a set of requirements that vehicles and equipment with 600 VDC electrical systems must operate within.
Haynes, AricSpina, JasonBest, Melissa
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
McBain, Jordan
This study develops a biological-electrochemical process for ammonia fuel production from high-strength blackwater, integrating enhanced ammonification, anaerobic digestion (AD), and electrodialysis (ED). The system achieved 90% COD removal, with Bacillus subtilis increasing NH3-N concentrations by 113%, enhancing nitrogen recovery. AD reduced volatile solids by 60%, producing 200 mL/day of biogas with 70% methane content, and increased NH3-N from 215 to 308 mg/L in the effluent. ED concentrated ammonia to 3 g NH3-N/L with an energy consumption of 1.8 Wh/L, while diluted effluent contained <30 mg NH3-N/L. The system generated a net energy output of 20.48 kWh-e/day, transforming wastewater from an energy sink into an energy-positive process. This approach enables high-efficiency nitrogen recovery, converting waste into ammonia fuel for reformation efforts, while supporting decentralized sanitation solutions.
Thomas, BenjaminEmerson, EmiliaSmerigan, BlakeMonson, CarterLiu, YanBoltersdorf, JonathanHill, CarolineDillon, Robert J.Baker, David R.Dusenbury, JamesLiao, Wei
The early stages of product planning and concepting in advanced engineering domains are often hampered by high uncertainty, fragmented decision-making, and unstructured data. Traditional planning methodologies routinely lead to misalignment, inefficient risk assessments, and suboptimal product strategies. To address these challenges, we propose an AI-agentic decision intelligence (DI) framework that leverages Large Language Models (LLMs) to enhance decision-making in product planning and concept development. The proposed framework uses the transformative natural language processing capabilities and comprehensive knowledge of LLMs to capture and refine stakeholder intent, improve stakeholder engagement, and optimize workflow orchestration. Implementation of the framework is facilitated by state-of-the-art and rapidly evolving open-source tools, ensuring scalability and readiness for corporate environments. By enhancing decision confidence, adaptability, and automation, the framework
Murat, AlperChinnam, Ratna BabuRana, SatyendraRapp, Stephen H.Hansen, KurtRichman, Todd A.Bechtel, James E.
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.
Salehi, EhsanThomas, JayDi Camillo, Stephen
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.
Towler, Meera DayGarza, Harold A.Chambers, David R.
Charcoal is a frequently used resource by the DoD with numerous applications. Military charcoal is produced through destructive distillation of a variety of wood types, resulting in a high degree of batch-to-batch variability. Depending on the application of the charcoal, this variability can result in undesirable characteristics in the end-product. To address this issue, DEVCOM AC is examining a charcoal bio-manufactured by DEVCOM CBC using bacteriophages. This highly controlled process results in the consistent production of charcoal with a variety of desirable characteristics, including a high surface area available for combustion due to its porosity as well as a high level of purity. In this effort, DEVCOM AC is investigating this bio-manufactured charcoal as a drop-in replacement in comparison to standard charcoal for applications of interest to boost ignition performance. This work will produce a drop-in-replacement for a DoD-critical resource with improved characteristics
Rozumov, EugeneBird, DavidCrumbley, AnnaMorris, LaurenGrau, HenryWilson, DanielStern, AaronDecker, Robert
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.
Johnston, StephenKondogiani, Chris
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.
Eddins, R.Lambert, C.Habic, D.Haynes, A.Spina, J.Schwartz, E.
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.
Ofer, DavidHui, SamTorname, NoahMcCoy, ChrisSiegal, EdNedder, DavidStringfellow, RichardRutberg, Michael
Architecting military ground vehicles is so complex that it requires a model of modular open-standard system architecture (OSSA) to enable rapid development, integration and fielding of capability components. Modular Open Systems Approach (MOSA) and Model-Based Systems Engineering (MBSE) help achieve modularity in OSSA models. However, enforcing and evaluating modularity in the OSSA models prior to production of software and hardware components is a significant challenge due to the lack of a domain-specific standard framework. This paper proposes a novel and comprehensive approach to ensure high modularity in military ground vehicle domain-specific OSSA models. The approach addresses the unique requirements and challenges in the creation of more modular and effective vehicle architecture.
Dattathreya, Macam
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.
Stanko, ThomasJoyce, JonathanBarry, JamesFlores, DavidHogan, JasonMiller, DavidBanoon, HawraaBostick, WilliamCampbell, CaleGangl, JoshuaHideg, ChristopherKlein, PhilipMacAfee, AndrewMalinowski, BenjaminMatthews, JeffreyMorton, StuartMontague, JoshuaThompson, ChristopherTily, ConorTrombley, AlexanderMikulski, Christopher
Time-Sensitive Networking (TSN) enhances Ethernet with features such as time synchronization, scheduled traffic, policing, and redundancy to enable highly deterministic and reliable communications in mission-critical systems. This paper presents a comprehensive approach to the configuration, analysis, and verification of TSN for critical systems, with a focus on time-sensitive applications such as tank barrel stabilization. The impact of different types of topologies, traffic types, and application requirements on the configuration complexity are presented along with various mathematical techniques to generate network solutions and verify against the system requirements. Detailed modeling, configuration, and analysis of TSN is demonstrated using a representative mixed criticality converged network. Lastly, configuration techniques to minimize the latency, jitter, and frame loss while maximizing the network utilization are presented.
Bush, Stephen F.Jabbar, Abdul
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
Lingg, MichaelPaul, HowardSullivan, KyleVanSolkema, William
This research evaluated the practicality of implementing Post-Quantum Cryptography (PQC) algorithms onboard resource-constrained computing devices, especially those found in automotive platforms. While computational efficiency within PQC is high, memory size and bandwidth constraints become relevant upon consideration of end-to-end implementation. The Controller Area Network (CAN) protocol utilizes only eight (8) bytes of data payload per message, requiring the large keys of PQC algorithms to be split into several messages. Power efficient 32-bit ARM microcontrollers were used for testing. Comparison was made between software implementations of both PQC and modern algorithms to evaluate relative computational cost. Ultimately, this research determined that the communication overhead required by PQC algorithms such as CRYSTALS-Kyber, CRYSTALS-Dilithium, and Falcon is not so egregious as to preclude them from implementation on board vehicular networks.
Smith, SethOwens, KyleKozan, Katherine
As part of technology maturation efforts, the COAT Lab evaluated the impact of external audio on driving performance in simulated under amor environments. To do so, we conducted an Engineering Evaluation Test (EET) wherein participants were asked to drive a simulated military vehicle through a Slalom course (primary task) while monitoring for aerial threats (secondary task). Using a combination of objective and subjective metrics, this evaluation quantified participants’ ability to maneuver and detect threats while using external audio as an enabling technology. Evaluation results indicated external audio positively benefited driving performance and situation awareness. However, evaluation results also indicated that external audio was not sufficient in and of itself for detecting time-sensitive aerial threats. Together, these results suggest a development path forward in which external audio is combined with visual information to enhance crew situation awareness under armor.
Grant, LaurenShrestha, SumitHoffing, Russell Cohen
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.
Whitlock, Nick
Ground vehicles in operation produce a unique vibration signature. This signature is a key indicator of vehicle system, sub-system, and component health but is often not visible to the naked eye or detectable without specialized equipment. Vibration analysis tools can capture these signatures and unlock their value by establishing a signature baseline and detecting changes to that baseline. Changes are strong and consistent indicators of incipient failure and failure progression, and therefore useful as diagnostic reports and prognostic markers. Existing vibration analysis tools and techniques make these signatures quantifiable, but these tools require on-equipment sensors and lengthy data collection processes. Motion Amplification (MA), however is a powerful new vibration analysis technology that overcomes sensor limitations and speeds data collection and analysis by replacing sensor-based vibration analysis tools with video recordings. The recordings use each individual picture
Aebischer, David
Model-Based Systems Engineering (MBSE) is a growing field in engineering design, enabling rapid prototyping and deployment of concepts. However, the quality of engineering simulations depends heavily on the quality of the models used. As a result, quantifying and reducing model error is critical in MBSE. To do this effectively, examining how model error is measured is crucial. Error metrics reduce the complex relationship between predicted and measured behavior to a single scalar value. This compression can introduce bias, but it is necessary for error quantification and surrogate generation. This paper examines the impact of this compression on model behavior and offers a decision framework for choosing error metrics. While not all uncertainty is reducible, modelers should decide which uncertainties are acceptable and how they are measured.
Taylor, EvanMocko, GregoryLouis, Ed
Time-Sensitive Networking (TSN) is a modern networking technology that promises to combine the speed, performance, and scalability of traditional best-effort Ethernet with the resilience and assurance of a safety-critical communications bus, all in a single physical network infrastructure. Although TSN is over a decade old, the collection of standards and profiles of which it consists are still evolving at a fast pace. Significant work remains to converge on a set of standardization and implementation details that will lead to meaningful interoperability in military ground vehicle applications. This paper explores the current state of TSN and how DEVCOM-GVSC’s partnership with industry, through collaborative refinement of ground combat vehicle requirements, is accelerating the adoption of this foundational MOSA-enabling technology.
Sopel, ShaneElliott, LeonardKinstler, ErikSalama, Christina
Navigation in off-road terrains is a well-studied problem for self-driving and autonomous vehicles. Frequently cited concerns include features like soft soil, rough terrain, and steep slopes. In this paper, we present the important but less studied aspect of negotiating vegetation in off-road terrain. Using recent field measurements, we develop a fast running model for the resistance on a ground vehicle overriding both small vegetation like grass and larger vegetation like bamboo and trees. We implement of our override model into a 3D simulation environment, the MSU Autonomous Vehicle Simulator (MAVS), and demonstrate how this model can be incorporated into real-time simulation of autonomous ground vehicles (AGV) operating in off-road terrain. Finally, we show how this model can be used to simulate autonomous navigation through a variety of vegetation with a PID speed controller and measuring the effect of navigation through vegetation on the vehicle speed.
Goodin, ChristopherMoore, Marc N.Hudson, Christopher R.Carruth, Daniel W.Salmon, EthanCole, Michael P.Jayakumar, ParamsothyEnglish, Brittney
Drones, or Unmanned Aerial Vehicles (UAVs) pose an increasing threat to military ground vehicles due to their precision strike capabilities, surveillance functions, and ability to engage in electronic warfare. Their agility, speed, and low visibility allow them to evade traditional defense systems, creating an urgent need for advanced AI-driven detection models that quickly and accurately identify UAV threats while minimizing false positives and negatives. Training effective deep-learning models typically requires extensive, diverse datasets, yet acquiring and annotating real-world UAV imagery is expensive, time-consuming, and often non-feasible, especially for imagery featuring relevant UAV models in appropriate military contexts. Synthetic data, generated via digital twin simulation, offers a viable approach to overcoming these limitations. This paper presents some of the work Duality AI is doing in conjunction with the Army’s Program Executive Office Ground Combat Systems (PEO GCS
Mejia, FelipeShah, SunilYoung, Preston C.Brunk, Andrew T.
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
Patterson, StevenEdel, ZacharyCanull, LoganPryor, JoshuaRynes, PeteTison, NathanKorivi, Vamshi
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.
Nyanankpe, Guenter
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
Gonzalez, Troy A.
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.
Spratley, MichaelSchooley, AndrewDickerhoff, Trey
With ongoing microelectronic supply chain issues, the demand for genuine field-programmable gate arrays (FPGAs) is increasing – but so is the occurrence of counterfeit devices. Frequently, devices are used, salvaged from old systems, and repackaged as new. Recycled devices represent the largest class of counterfeit devices and are becoming more rampant with ongoing supply chain challenges. Therefore, it is often necessary to test whether a device is genuine before employing it in a new system. Current methods for evaluating devices are frequently destructive allowing for only small sample testing within lots. Other methods require complex external equipment and cannot be readily deployed throughout the supply chain. Graf Research Corporation has developed a methodology for using soft sensor telemetry bitstreams to characterize an FPGA device and subsequently classify whether a device is a repackaged counterfeit via statistical and machine learning models. The new method utilizes
Batchelor, WhitneyCrofford, CodyKoiner, JamesWinslow, MargaretTaylor, MiaPaar, KevinHarper, Scott
We introduce a LiDAR inertial odometry (LIO) framework, called LiPO, that enables direct comparisons of different iterative closest point (ICP) point cloud registration methods. The two common ICP methods we compare are point-to-point (P2P) and point-to-feature (P2F). In our experience, within the context of LIO, P2F-ICP results in less drift and improved mapping accuracy when robots move aggressively through challenging environments when compared to P2P-ICP. However, P2F-ICP methods require more hand-tuned hyper-parameters that make P2F-ICP less general across all environments and motions. In real-world field robotics applications where robots are used across different environments, more general P2P-ICP methods may be preferred despite increased drift. In this paper, we seek to better quantify the trade-off between P2P-ICP and P2F-ICP to help inform when each method should be used. To explore this trade-off, we use LiPO to directly compare ICP methods and test on relevant benchmark
Mick, DarwinPool, TaylorNagaraju, Madankumar SathenahallyKaess, MichaelChoset, HowieTravers, Matthew
We develop a set of communications-aware behaviors that enable formations of robotic agents to travel through communications-deprived environments while remaining in contact with a central base station. These behaviors enable the agents to operate in environments common in dismounted and search and rescue operations. By operating as a mobile ad-hoc network (MANET), robotic agents can respond to environmental changes and react to the loss of any agent. We demonstrate in simulation and on custom robotic hardware a methodology that constructs a communications network by “peeling-off” individual agents from a formation to act as communication relays. We then present a behavior that reconfigures the team’s network topology to reach different locations within an environment while maintaining communications. Finally, we introduce a recovery behavior that enables agents to reestablish communications if a link in the network is lost. Our hardware trials demonstrate the systems capability to
Noren, CharlesChaudhary, SahilShirose, BurhanuddinVundurthy, BhaskarTravers, Matthew
Computer vision is being revolutionized by the use of transformer-based machine learning architectures. However, these models need large datasets to enable pre-training through self-supervised learning. However, there is a lack of open-source datasets of the same magnitude as standard RGB color images. This work analyzes the effect of using randomly generated fractal-based hyperspectral images versus real data to understand the effect of pre-training dataset on a Swin image encoder model performance, during supervised-training of a semantic segmentation hyperspectral dataset. Two real data datasets are used for comparison to the synthetic dataset, one RGB-based and another hyperspectral-based to understand how variability in spectral resolution during pre-training effects model performance on semantic segmentation.
Medellin, AnthonyGrabowsky, DavidMikulski, DariuszLangari, Reza
This paper introduces a secure and cost-effective framework for integrating Commercial Off-the-Shelf (COTS) Generative Artificial Intelligence (GenAI) technology into government enterprise solutions. It explores key aspects of GenAI, emphasizing its transformative role in enhancing efficiency and decision-making within government operations. Central to the discussion is a GenAI Feasibility Study [1] conducted by Booz Allen for the Director, Operational Test & Evaluation (DOT&E), which outlines the development of the AI-Enabled Test & Evaluation Module (ATEM) GenAI Knowledge Assistant. The paper also examines critical factors for successful implementation, including use case definition, model selection, data quality, and prompt engineering.
Vandrovec, BryanKruger, JohnBirr, CalvinMazzara, MarkMossy, GlennHimmel, MaxBarnhart, JamesSenger, Jeff
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
Ewing, JordanJayakumar, ParamsothyKasaragod, AnushOommen, Thomas
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