Browse Topic: Military vehicles and equipment

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High-performance composite materials are widely used in the main structural components of satellites. Various cylindrical components will hit the satellite at the time. The cartridge is fixed and unchanging. Honeycomb structure and ceramic honeycomb structure are the same, the cylindrical component is lighter and can attack satellites at a greater speed under the same conditions as the propellant. In terms of mass quality, the speed can reach over 1.6 times, and ceramic honeycomb structure can have minimal kinetic energy loss and can face enemies in combat with thicker steel plates, allowing for continuous destruction. Cylindrical component remaining kinetic energy (∆E) is 3.2968e3 J, but ceramic cylindrical component ∆E is 2.082e3 J, and ceramic cylindrical component have more advantages, and there are fewer arbitrary steel balls flying.
Xu, JianYang, ZhenChang, XuefangLi, QiangZhang, KunQu, Dandan
This Aerospace Information Report (AIR) addresses the subject of aircraft inlet-swirl distortion. A structured methodology for characterizing steady-state swirl distortion in terms of swirl descriptors and for correlating the swirl descriptors with loss in stability pressure ratio is presented. The methodology is to be considered in conjunction with other SAE inlet distortion methodologies. In particular, the combined effects of swirl and total-pressure distortion on stability margin are considered. However, dynamic swirl, i.e., time-variant swirl, is not considered. The implementation of the swirl assessment methodology is shown through both computational and experimental examples. Different types of swirl distortion encountered in various engine installations and operations are described, and case studies which highlight the impact of swirl on engine stability are provided. Supplemental material is included in the appendices. This AIR is issued to bring together information and ideas required to address the inlet-swirl problem for which common industry practice has yet to be established. This document should foster the tests and analyses necessary to mature the ideas proposed by the committee to a recommended practice. These tests and analyses must include information that justifies three main features of the proposed swirl methodology: (1) swirl descriptors for correlating inlet swirl and stability pressure ratio loss, (2) computational techniques for analyzing compression systems (inlets, fans, compressors), and (3) test protocols (instrumentation and test techniques). The committee anticipates serving the industry by using such information to establish the consensus necessary for issuance of an SAE recommended practice.
S-16 Turbine Engine Inlet Flow Distortion Committee
As multi-vehicle cooperation becomes an increasingly important operational mode for armored vehicles, the performance of cooperative crews plays a crucial role in accomplishing coordinated missions and enhancing the functionality of the human–machine system. In this study, the influencing factors of crew performance in multi-vehicle cooperation of armored vehicles were initially extracted through a literature review. The Delphi method was then employed to collect expert opinions and perform a preliminary simplification of the indicator system, followed by an optimization of the system using exploratory factor analysis. The final indicator system consisted of 11 indicators, and the DEMATEL–TAISM method was further employed to analyze the interaction relationships among the identified key influencing factors. In terms of the interrelationships among influencing factors, the fundamental determinants of armored vehicle crew performance include individual capability and experience, operational characteristics, shared screen and auditory design, display–control interface and cabin layout, and intelligent and automated design. The findings suggest that improving crew capability and experience through training, optimizing the interface, cabin, and auditory design, and promoting intelligent and automated system design can significantly enhance armored vehicle crew performance.
Wang, RulanChen, XingjiangZhou, YueXie, FangWanyan, XiaoruLiu, Shuang
In order to ensure that the high-caliber artillery ammunition fuses can successfully complete their combat tasks with high quality, it is necessary to optimize the design of their structure and conduct simulation verification of their performance. Through optimization design, this paper determined that the distance between the antenna plate and the wind cap of the proximity detonation module of the high-caliber artillery ammunition fuse is 6.2mm, and the thickness of the wind cap top is 12.9mm; it also determined that in the coaxial line feeding mode, a circular patch is used as the antenna shape, with the lowest return loss (reaching -38.5244 dB), which is conducive to the emission of electromagnetic wave energy; by introducing the methods and processes of intensity simulation analysis and aerodynamic thermal simulation analysis, as well as the methods of performance verification, this paper provides reference and guidance for the simulation analysis of similar systems.
Liu, LiwenSun, ZhangyiNing, QuanliCai, Canwei
Accurate projectile dynamic modelling requires identifying aerodynamic parameters. The traditional methods for identifying aerodynamic parameters of missiles suffer from significant modeling errors. Therefore, this study proposes an improved butterfly-shaped optimization hybrid extreme learning machine algorithm. It combines the butterfly algorithm with a hybrid extreme learning machine, Cauchy mutation, and adaptive weight. The search ability of the Butterfly algorithm is enhanced by introducing the Cauchy distribution function and adaptive weighting factors. In addition, to balance the weights of searches and to optimize the regularization coefficients and kernel function parameters, the dynamic switching probability p is introduced. The identification accuracy of four different algorithms was compared under noise-free conditions. The feasibility of the improved butterfly-optimized hybrid extreme learning machine was verified. When there is noise, the strength of the algorithm is confirmed by comparing the effect of different noise levels on how well it can identify things. The simulation results show that the improved butterfly optimization hybrid extreme learning machine algorithm has higher accuracy and better robustness in identifying projectile aerodynamic parameters. The simulation results show that the improved butterfly optimization hybrid extreme learning machine algorithm has higher accuracy and better robustness in identifying projectile aerodynamic parameters.
Wang, QianqianWang, KangjianJiao, WenjieYi, WenjunChen, Jintong
The canard configuration has been widely adopted in short-range missiles. However, its main drawbacks include difficulties in roll control and a limited angle-of-attack (AoA) range. Compared to conventional canard missiles, the addition of a pair of control surfaces (referred to as “aileron”) behind the canard control surfaces achieves decoupling between the roll channel and pitch-yaw channel. To investigate the influence of ailerons on the aerodynamic characteristics of canard configuration missiles, numerical simulations were conducted for two typical flow conditions: subsonic (Mach 0.5) and supersonic (Mach2.0). The results show that the introduction of ailerons increases the normal force of missiles, causes the center of pressure to shift forward, and reduces the static stability of missiles, thus enhancing their maneuverability. When the ailerons control the roll channel, the effectiveness of the rolling moment remains consistent over the entire AoA range without adverse effects. However, when the canards control the pitch channel, the interference caused by the deflection of the canards on the ailerons leads to increased lift and generates additional nose-up pitching moments, which reduces the pitching moment effectiveness of the missile.
Zhang, ZilunXu, JiashengMei, Zhiwei
Rocket projectiles are a type of ammunition that get their power from rocket engines. Long-range guided rockets, in particular, hold great significance as they seem to mark the way forward in modern warfare. These guided projectiles take full advantage of the considerable range that long-range rockets offer and, at the same time, manage to achieve improved accuracy. This paper delves into a model that is used for predicting the impact point of rocket projectiles, with the application of the proportional navigation guidance law. It also undertakes an analysis of both the strengths and the weaknesses of this model. Through the formulation of equations related to the dynamics of the center of mass and some other supplementary equations, a rather comprehensive trajectory equation was worked out. When this trajectory was simulated, it brought about the creation of a firing table, which is of help in predicting the initial trajectory inclination angle.
Tao, WenwenWang, RuZhang, LiangPi, Runge
This study aims to solve the trajectory optimization problem of multi degree of freedom micro air vehicle (MAV) with the aim of improving its flight performance through technological innovation. A multi degree of freedom trajectory optimization (MDFTO) method with sideslip angle and angle of attack as the core control variables was proposed for multiple complex constraints in combat environment, such as terminal accuracy and overload limitation. This method can more accurately characterize and adapt the strong nonlinear, dynamic coupling and time varying characteristics of the MAV in high-speed maneuvering flight. In order to solve this MDFTO problem with multiple constraints and strong nonlinear characteristics efficiently, the hp adaptive pseudospectral method is used in this study, and is verified by simulations based on the GPOPS-II optimization platform. The algorithm has the advantages of highly accurate discrete state and control variables, efficient processing of path and terminal constraints, and adaptive adjustment of the distribution point density. GPOPS-II is able to efficiently adapt to the MDFTO method. The simulation results show that the GPOPS-II can accurately capture the MAV’s dynamic response. Its adaptive node adjustment mechanism effectively balances computational efficiency with solution accuracy, especially during flight phases where state changes drastically, ensuring the reliability of results. The MDFTO method successfully achieves the optimal solution, and the generated trajectory strictly follows the laws of vehicle dynamics and kinematics. This method provides an effective and engineering feasible technical approach for the trajectory optimization of the MAV under complex constraints, and has important theoretical and practical value for improving its strike accuracy, maneuverability and comprehensive combat effectiveness.
An, ZhichaoMing, ChaoWen, Guangbao
In order to meet the demand for missile miniaturization and simplify the system complexity, this paper designs a guidance control integration method according to sliding mode control based on the longitudinal plane motion model, which is combined with the theory of sliding mode control. The design realizes tracing of attack angle to line-of-sight angle through sliding mode control of the outer loop, and the tracking of the control volume rudder deflection angle to the virtual control volume angle of attack through the sliding mode control of the inner loop. The stability of the guidance law is also verified by the Lyapunov function. The simulation results show that the guidance law can hit the target successfully, which verifies the feasibility and effectiveness of the design method.
Bai, JiajunMing, ChaoAn, ZhichaoNiu, ZhaoqiWen, Guangbao
With the increasing demand for multi-unmanned aerial vehicle (UAV) cooperative operations, the design of guidance laws with time and angle synchronization constraints has become a critical technology to enhance strike precision. This paper focuses on a UAV-launched multi-missile cooperative attack scenario, proposing a composite guidance law that integrates the advantages of existing optimal time/angle control guidance laws. By introducing a time error feedback term and an angle constraint term, combined with an adaptive disturbance observer to compensate for aerodynamic errors and target maneuvers, the proposed guidance law ensures a terminal miss distance of less than 0.5 m while achieving a time error ≤0.6 s and an incidence angle deviation ≤2° among multiple missiles. Simulation and test results both demonstrate that the four-missile cooperative attack achieves time dispersion within 1s, satisfying engineering practicality and anti-interference requirements.
Xie, LijunWang, DeshuangYang, XiaodongZhang, TingtingLi, Yang
This paper proposes a UAV combat simulation method integrating AFSIM and DoDAF to address the complexity of UAV combat systems. DoDAF establishes a multi-view architecture mode to clarify logical relationships between UAVs and weapon systems, laying a structured foundation. AFSIM implements dynamic simulation of combat processes by mapping DoDAF’s static architecture to its dynamic elements, simulating UAV maneuver, situation awareness, and strikes. A UAV search-and-strike mission scenario test shows the method accurately simulates collaborative behavior in target searching, tracking, and engaging. This method features a high degree of standardization and normalization, providing a foundation for the evaluation of UAV combat effectiveness and strategy optimization.
Sun, ZhenleiYang, Longquan
This paper constructs a reinforcement learning framework based on the PPO algorithm for drone air combat to solve 1v1 pursuit-evasion in 2D beyond-visual-range air combat. Firstly, the mission scenario is modeled, defining key roles of ATA and AA. Then, state transition models of pursuer and evader are built based on flight kinematics. To handle reward sparsity in policy network training, a dense reward function combining distance and angle rewards is designed to guide the agent in learning tail-chasing and interception strategies. Using the Actor-Critic architecture, deep neural networks implement the decision-making and evaluation modules. The PPO algorithm trains the pursuing drone in a simulation. Results show that after ~5 million steps, the agent learns a stable strategy, completing tasks promptly and generalizing well in unseen scenarios. This research offers ideas for drone combat and guidance, and supports autonomous decision-making in complex air battles.
Yu, KangjieGong, ZhengHu, RunchangLiu, Huixiang
As a critical component of unmanned naval warfare, Unmanned Underwater Vehicles (UUVs) have garnered significant attention from major military powers. When navigating through pycnoclines—a widespread vertical density stratification in marine environments—UUVs generate volume effect internal waves that influence hydrodynamic resistance. Therefore, investigating the hydrodynamic characteristics of UUVs in pycnoclines is essential. Despite substantial research progress, most studies focus on internal wave patterns and their impacts on submerged vehicles, with limited exploration of UUV resistance and surface pressure distribution. This work establishes a numerical method according to the Reynolds-Averaged Navier-Stokes (RANS) equations, employing the Realizable k-ε turbulence model and the Volume of Fluid (VOF) method to capture fluid density interfaces, thereby analyzing the hydrodynamic characteristics of UUVs in pycnoclines. Furthermore, a numerical method was constructed, and the convergence regarding the grid and time-steps were verified. Additionally, numerical experiments under varying navigation speeds and depths are conducted to investigate the total resistance, frictional resistance, wave-making resistance coefficients, and spatial variation of surface pressure. Based on the results, the total resistance of a UUV is positively correlated with its navigation speed. When navigating in the upper seawater layers, the total resistance also exhibits a positive correlation with navigation depth. However, when operating in the lower seawater layers, the total resistance initially increases and then decreases with increasing depth, reaching its peak level at a navigation depth of 13 m. Both increasing navigation speed and approaching the density interface can enhance the sensitivity of total resistance to navigation depth. The alteration in total resistance stems primarily from changes in wave-making resistance while showing a weaker correlation with frictional resistance. The UUV’s speed positively correlates with pressure at locations with abrupt curvature changes on its surface, but it has a negligible influence on pressure distribution in smooth surface regions. Besides, navigation depth positively correlates with surface pressure magnitude yet exerts a limited impact on pressure distribution patterns. The findings contribute to a more complete picture of the hydrodynamic properties of UUVs navigating through pycnoclines, offering valuable references for optimizing UUV design and operational strategies.
Zhang, YinXue, LeileiGuo, LiqiangFu, XiaoZhang, XiaofangLiu, ZhihaoHan, Guoxin
This paper presents a monocular vision-based system for high-precision missile pose measurement using ArUco markers and Perspective-n-Point (PnP) algorithms. By deploying 6 × 6 ArUco markers on a cylindrical missile mock-up, the system establishes 3D-2D correspondences between structured-light-scanned models and camera images to solve the PnP problem. The proposed approach integrates optimized ArUco marker recognition — leveraging adaptive thresholding, contour simplification, and grid-based validation — with the Efficient PnP (EPnP) algorithm to achieve real-time pose estimation. Experimental validation demonstrates angular accuracy of ± 0.3° in roll/pitch/yaw and positional accuracy of ± 2 mm within a 2 m range under controlled conditions. The system exhibits robustness against partial occlusions and motion blur, with degraded performance (± 1.2°, ± 5 mm) in extreme scenarios. Key innovations include a streamlined marker detection pipeline and adaptive pose refinement using Levenberg-Marquardt optimization. This work provides a cost-effective, non-contact solution for flight tests, with potential applications in weapon separation testing.
Wang, RuiyangZhang, Chaofan
In modern warfare, military control of the airspace determines aircraft survivability against the most widespread missile threats. The aero-engine exhaust system is an important source of infrared (IR) signatures from the rear aspect, particularly in the 2–3 μm and 3–5 μm IR bands. Two-dimensional (2D; non-axisymmetric) nozzle exits with high aspect ratio (AR > 5) are widely used in stealth aircraft engines due to their low IR signature, ease in thrust vectoring, and high maneuverability and agility. This analytical study compares the specific thrust (for choked and unchoked flow regimes) and the visible planar areas of a 2D nozzle exit with different ARs with those of a circular nozzle, as seen from the direct rear view. The nozzle’s isentropic efficiency (ηis,noz) is obtained in terms of the total pressure ratio, and the effect of AR on ηis,noz is examined for 1 ≤ AR ≤ 15. It is found that ηis,noz decreases with increasing AR, but this decrease is more rapid in unchoked flow than in choked flow. For the same value of nozzle exit cross-sectional area, the corresponding visible planar areas of aero-engine hot parts are compared for a 2D nozzle exit with different AR with that of the baseline case (circular nozzle), from bore-sight. This study shows that the optical blocking of aero-engine hot parts by a round-to-rectangular nozzle of AR ≤ 4 is almost the same as that of a circular nozzle, from bore-sight.
Baranwal, Nidhi
Air Traffic Management (ATM) must be familiar with the exact Aircraft Take-off Weights (ATOWs) of airplanes to make the most use of runways, maintain safety margins high, and keep utilization and resources in balance. This paper aims to present a dependable ATOW forecasting methodology that can assist the air transport industry in enhancing operational decision-making. This research used datasets acquired from the EUROCONTROL Performance Review Commission (PRC) 2024 Aircraft Take-Off Weight Estimation dataset featuring 527,000 flights over Europe containing aircraft details, air trips and flight conditions. Technique comprises structured data input, inspection of missing data, timestamp aggregation to identify demand cycles over time, and domain-specific feature engineering using distance_per_minute, block_minutes, taxiout_ratio, and a strong wake turbulence metric The two supervised learning models used were Linear Regression (LR) for understanding and XGBoost for performance prediction In comparison to LR's 4,409 kg MAE (mean absolute error), 7,061 kg RMSE (root mean square error), and 0.9825 R2 value, XGBoost significantly excelled with validation results showing an R2 value of 0.9992 and an RMSE of 1,514 kg In the absence of labelled test targets, cross-validation nevertheless showed a constant degree of generalizability The residual diagnostics showed that the model was reliable for practical execution with low-variance deviations that were unbiased An accurate ATOW estimate improves the demand-capacity balance and On-Time Performance (OTP) in ATM, which in turn affects the runway schedule, wake turbulence diversion, slot allocation, and fuel planning The results highlight the need to include ATOW predictions in both tactical and strategic planning to reduce delays, increase airspace usage, and promote sustainable aviation operation and possesses significant improvements will consist of weather and runway conditions, stochastic ambiguity computation, and drift monitoring to keep up with ever-changing operating variables while maintaining accurate forecasts.
Senthilkumar, N.S, GopalakrishnanGopinath, S
Submarine-launched missiles with domed nose cones are highly vulnerable to cavitation erosion as they travel at high speed through an underwater launch tube and then into the air from the sea surface. The collapse of vapour cavities crystallizes intense damage on the vehicle surfaces so that the vehicle structure and aerodynamic performance are threatened. In this work, we show the full 3D numerical and analytical analysis of surface protection concepts for the reduction of cavitation damage on such an axisymmetric dome-shaped body. A computational methodology was developed by importing a complex computer-aided design (CAD) model of a dome and the connecting tubular structure into a high-fidelity simulation environment. The geometry was simplified by omitting non-essential details to facilitate the generation of quality mesh for CFD analysis. Simulations have been carried out to analyze the flow field and pressure distribution under two critical stages, at two angles of attack of 0° and 12° and different launch depths. This investigation focuses on a passive mitigation technique that bonds an optimised rubber padding to the dome's exterior surface. The impact forces from collapsing cavitation bubbles are thought to be absorbed and dissipated by the rubber due to its viscoelastic nature, leading to a reduction of the impulsive stress on the substrate. The results show that the controlled introduction of such a compliant material dramatically changes the surface response to cavitation implosions. The suggested rubber padding is demonstrated to be an efficient and practicable means of protecting the surface; thus, the risk of cavitation erosion is diminished considerably, and the service life and reliability of the underwater projectile vehicle can be improved.
Velayudhan, GauthamP S, PremkumarS, Suhail AhmedP, KrishnakumarVasantharaj, C
Grid fins are non-conventional aerodynamic lifting and control surfaces which are made of a frame supporting lifting surfaces positioned in the form of a lattice structure. Grid fins are also called as lattice fins and are used as control surfaces in launch vehicles, crew escape systems, missiles etc. to achieve static stability. Each panel of the grid fin acts as fin and it produces force which increases stability of the vehicle. For a crew escape system module, grid fins are used as a passive aerodynamic control surfaces to achieve static stability. Grid fins are positioned at the end of crew escape system module to provide required static margin by increasing moment arm. In contrast to conventional fins, grid fins incorporate a distinctive waffle-like pattern or grid pattern configuration, offering superior aerodynamic performance in supersonic regimes and enabling compact storage in stowed position during launch followed by deployment at the time of exigency. In case of an emergency, crew escape system is activated and it will take crew escape module away from the launch vehicle during atmospheric regime. In this scenario, grid fins are deployed simultaneously along with firing of high-thrust, fast-acting solid rocket motors (SRMs) which provide the impulsive force needed for clean separation. Grid fins help to stabilize the crew escape system module by counteracting aerodynamic instabilities, especially when the module is moving through the atmosphere at high speeds. The primary structural loads acting on grid fins include deployment forces (hinge forces, locking), aerodynamic, and inertial forces. Additionally, the exhaust plumes from the firing of SRMs impinge directly upon the grid fins, generating intense thermal loads characterized by rapid temperature gradients and localized heating. The simultaneous presence of thermal and structural loads influences displacements, stresses, interface joints integrity and maximum buckling loads. Furthermore, elevated temperatures degrade mechanical properties such as yield strength, ultimate strength, and Young’s modulus, therefore a thermo-structural analysis is carried out to study the effects of these combined loads on grid fins. This paper presents typical grid fin configuration, thermo-structural formulation, finite element model details, and thermo-structural analysis results including stress margins, deformations, buckling load factors and preload variations for the maximum design load case.
Mali, Somanath NanduSundar Raj, RSundaresan, MKR, Suresh
Nasa Tech Briefs: May 202626AERP055/7/2026
How Machina Labs is Reshaping Defense Manufacturing with AI-Driven 7-Axis Robotics Engineering at the Speed of Conflict: The New Era of Defense Testing MyDefence Expands Production, Validation of Wearable and Mobile Counter-UAS Systems Keeping Pace with Changes in Defense Technology: Why Embedded Systems Must Deliver Agility, Resilience, and Endurance From Autonomous Vehicles to Ship-to-Shore to: Designing 60 GHz Networks for Tactical Applications Defense Research Program Developing Tactical Clocks for GPS-Free Navigation The Drone Equation: Proportional Response to the UAS Threat High-end interceptors. Low-end threats. The answer isn't bigger missiles but smarter integration. Virginia Tech Experts Accelerate Skydio Drone Flights Over People and Vehicles Researchers recently helped Skydio, the leading U.S. drone manufacturer, demonstrate compliance to the Federal Aviation Administration's rules for safe flights over people and vehicles. Teaching Robots to Fly Like Birds Rutgers researchers replace motors with smart materials in an innovative approach to flight. RPI Researchers Harness Agentic AI for Smarter, Faster Aerospace Design Funding from Google and the U.S. Department of Energy helped a team of researchers develop an assortment of agentic AI-enabled tools to help optimize traditional aerospace design processes. Can Multi-Fingered Robots Transform Shipboard Operations and Autonomous Maintenance? USC Viterbi researcher received Office of Naval Research's Young Investigator Program award with Study on dexterous robotics. Can Multi-Fingered Robots Transform Shipboard Operations and Autonomous Maintenance? USC Viterbi researcher received Office of Naval Research's Young Investigator Program award with Study on dexterous robotics.
Now that Modular Open Systems Approaches (MOSA) are being incorporated into the development of weapon systems that are acquired by the U.S. Department of War (DoW), attention is turning to transitioning disparate standalone weapon systems into an enterprise portfolio of weapon systems, a Family of Systems (FoS), whereby the effective management of a common constraining, or reference, architecture can aid in realizing the objective of 'develop once, reuse many times.' This is particularly challenging when enduring fleet legacy weapon systems are involved in addition to new development systems. Model Based Systems Engineering (MBSE) methodologies and techniques have now become the norm in system developments. It is, therefore, imperative to effectively employ MBSE techniques in establishing a FoS. This paper proposes an MBSE-based Product Line Engineering (PLE) method for implementing FoS architectures that enables controlled architectural variation while preserving enterprise reuse and architectural consistency.
Zook, KeithDuBois, Tom
Army researchers recently developed a 3D-printable, easy-to-assemble drone designed to enhance intelligence, surveillance and reconnaissance capabilities. Army Research Laboratory, Adelphi, MD Researchers at the U.S. Army Combat Capabilities Development Command, or DEVCOM, Army Research Laboratory (ARL) harnessed bottom-up Soldier innovation to develop an experimental 3D-printed small unmanned aerial system, or drone, that was demonstrated at the inaugural U.S. Army Best Drone Warfighter Competition in Huntsville, Alabama. Known as the Soldier Portable Autonomous Reconnaissance Transitioning Aircraft, or SPARTA, the drone was developed at DEVCOM ARL in collaboration with Soldiers. By incorporating Soldier feedback early in the design process and leveraging ARL's world-class research facilities, researchers developed a 3D-printable, easy-to-assemble drone designed to enhance intelligence, surveillance and reconnaissance capabilities. ARL is actively working to partner the technology with industry to get into the hands of the warfighter.
On a clear afternoon over a contested airspace, a drone suddenly appears on radar. Within seconds, more follow, and they're small, fast, and unpredictable. For the U.S. Army's air and missile defense operators, every moment counts. The difference between mission success and mission failure is measured in milliseconds. During that brief window, sensors must connect instantly, embedded systems must process floods of data at the edge, and command links must hold steady even under electronic interference.
The convergence of highly capable edge AI models and advanced commercial-off-the-shelf (COTS) edge AI accelerators is reshaping how computation is deployed across defense, aerospace, and commercial platforms. Mission-critical decisions increasingly must be made at the edge, onboard vehicles, satellites, and infrastructure nodes, where latency, connectivity, and power availability are constrained.
The modern battlefield is increasingly characterized by the use of small drones. As such, military vehicles must now be designed to account for this threat. This paper presents a model-based systems engineering approach to identify vehicle vulnerabilities and generate new vehicle requirements to mitigate them. This approach uses a standard set of System Modeling Language diagrams. A vehicle’s primary roles are captured in a series of use cases. Each use case is characterized by a sequence of activities performed by the vehicle. These activity sequences are captured in an activity diagram, which are used to wargame how a drone can exploit the vehicle at each phase. Each potential exploitation is assigned likelihood and severity scores, which feed into a risk index. This risk index is then used to prioritize each vulnerability. From these vulnerabilities, a set of operational requirements are derived, which then informs the development of system requirements. As the system matures, the physical system architecture can also be used to identify drone vulnerabilities. In particular, the small payloads carried by drones are most effective when targeting interfaces. Internal block diagrams and domain diagrams are used to evaluate each interface to determine its vulnerability to drone attack, which can then be incorporated into the design requirements. This paper applies the methodology to an autonomous pontoon bridging system intended to move military vehicles across a wet-gap. A number of key vulnerabilities are identified, leading to a series of new design requirements.
Ells, AlecWerntz, BrysonSaulsberry, TaylorWilkinson, CooperMittal, Vikram
Wet-gap crossings, which involve moving military forces across rivers and other water obstacles, remain among the most difficult operations to plan and execute. These maneuvers are complicated by choke points, fast-flowing water, and the exposure of forces and equipment to enemy fire. Despite these challenges, wet-gap crossings are critical to maintaining operational momentum during large-scale combat operations. This study examines doctrinal approaches to wet-gap crossings and explores the relationship between these operations and observed vehicle losses in the Russia-Ukraine War. Using a mixed-method approach, the analysis integrates daily operational reports from the Institute for the Study of War with visually confirmed equipment loss data from Oryxspioenkop. A custom Wet-Gap Relevance Score (WGRS) was developed using Natural Language Processing techniques to quantify the degree to which each ISW report focused on crossing operations. Statistical analysis shows that pontoon losses cluster within two days of major crossing events, confirming long-standing engineering doctrine regarding the vulnerability of bridging assets. However, the overall correlation between WGRS scores and total daily vehicle losses is weak, suggesting that broader attrition patterns obscure the distinct impact of crossing operations. These findings provide new empirical insight into how doctrinal principles manifest in modern conflict and underscore the design implications for future military vehicles. Effective wet-gap crossings require a diverse fleet: amphibious vehicles to establish bridgeheads, light vehicles that can be rafted to sustain momentum, and heavier vehicles that depend on bridging to continue the assault.
Lynch, BenjaminDosan, LoganMittal, Vikram
Formation control simplifies minimizing multi-robot cost functions by encoding a cost function as a shape the robots maintain. However, by reducing complex cost functions to formations, discrepancies arise between maintaining the shape and minimizing the original cost function. For example, a Diamond or Box formation shape is often used for protecting all members of the formation. When more information about the surrounding environment becomes available, a static shape often no longer minimizes the original protection cost. We propose a formation planner to reduce mismatch between a formation and the cost function while still leveraging efficient formation controllers. Our formation planner is a two-step optimization problem that identifies desired relative robot positions. We first solve a constrained problem to estimate non-linear and non-differentiable costs with a weighted sum of surrogate cost functions. We theoretically analyze this problem and identify situations where weights do not need to be updated. The weighted, surrogate cost function is then minimized using relative positions between robots. The desired relative positions are realized using a non-cooperative formation controller derived from Lyapunov’s direct approach. We then demonstrate the efficacy of this approach for military-like costs such as protection and obstacle avoidance. In simulations, we show a formation planner can reduce a single cost by over 75%. When minimizing a variety of cost functions simultaneously, using a formation planner with adaptive weights can reduce the cost by 40-60% . Formation planning provides better performance by minimizing a surrogate cost function that closely approximates the original cost function instead of relying on a shape abstraction.
Cornwall, ChazBos, Jeremy
Traditionally, ground vehicle design is based on identifying engineering solutions that fulfil the requirements and specifications put forth by the stakeholders. Although a vehicle is a single entity, it is composed of many subsystems and thousands of parts that must operate together in unison to meet all design goals. A System of Systems (SoS) design approach enables the consideration of subsystem performance within a framework of overall system operation, which includes possible tradeoffs. This collaborative approach to subsystem and primary system design draws upon modelling, optimization, tradespace analysis and virtual studies. In this paper, a system of system design approach will be investigated for a collection of multi-domain vehicles assembled to undertake coordinated search and rescue operations on land and water. A host ground vehicle, an unmanned aerial drone, an unmanned marine drone and an unmanned tracked vehicle constitute the family of multi-domain vehicles which will be used for the search and rescue mission. A digital twin for this family of vehicles will be created to support numerical design studies. The System of Systems approach will enable tradeoffs in vehicle and family design to be evaluated using optimization tools. To visualize the designs, tradespace analysis tools will be key to identifying the tradeoffs and performance at the system level and the individual vehicle level. A case study is undertaken to simulate the trajectory of an aerial drone for a search and rescue operation and calculate its - ilities for such a scenario. In the future, the same exercise will be performed for three other models highlighted above and incorporate their -ilities to incorporate into the subsequent steps of optimization and tradespace analysis. This paper showcases the System of Systems approach and highlights the advantages and challenges faced in implementing such an approach for the purposes of achieving a specific mission through the collaborative and diverse vehicles used.
Somanchi, AnangAbeynayake, ChandimaDeshmukh, MrunalSuresh, JohirRamnath, SatchitTurner, CameronSchmid, MatthiasCastanier, Matthew P.Rapp, StephenJaczkowski, Jeffrey J.Wagner, John
Robust perception systems for autonomous vehicles rely heavily on high-quality, labeled data, particularly in off-road and unstructured environments. However, the performance of the perception model is often degraded by data chaos resulting from limitations in automated segmentation. Foundation models, such as SAM2, while powerful, typically generate masks based on low-level visual cues, including color and texture gradients. In complex off-road scenes, this leads to semantic fragmentation. A single object, like a moss-covered log, can be split into not only dozens of segments for its bark and moss but also hundreds of smaller, meaningless patches based on minor color variations. This paper introduces a context-aware annotation agent to resolve this issue. Our workflow integrates a vision-language model (Florence-2) for scene understanding with a segmentation model (SAM2) for mask generation. Instead of segmenting indiscriminately, our agent leverages Florence-2 to comprehend the image holistically, localizing complete objects. For example, after Florence-2 identifies a ”moss-covered log,” its semantic context guides the generation of masks for the entire entity or meaningful sub-components, such as moss patches and bark, not just fragmented color variations. This initial mask, generated in seconds, provides annotators with an excellent starting point, significantly reducing the manual effort required for vertex-by-vertex outlining. Annotators retain complete editing control, with the ability to adjust polygon vertices for a pixel-perfect mask and features such as drawing a bounding box or sketch to automatically segment an object. This agent provides a framework that utilizes the complementary strengths of scene understanding and segmentation models. Deploying each model for its own specialized task makes it possible to make more consistent, high-quality automotive datasets faster, which speeds up the creation of safer perception systems.
Patil, AshishMikulski, DariuszMwakalonge, JudithJia, Yunyi
Digital Twin technology can significantly improve the engineering product design process, especially when considering ground vehicle applications. Data-driven computer studies can assist engineers and key stakeholders in evaluating performance, durability, and other system design tradeoffs. To enable this process, the availability of relevant, numerically generated, laboratory, and/or field data is required. Proper data use enables the digital exploration of “what-if” scenarios, reducing necessary field testing and allowing for the examination of hard-to-test operating conditions. When considering the Digital Twin toolset, a collection of models and simulations are assembled to supplement virtual testing endeavors. These models include surrogate, CAD/CAE, and others. In this paper, an off-road track vehicle design is reviewed through the fusion of numerical and field data to evaluate future design enhancements. Preliminary results demonstrate that subtle feature upgrades can produce measurable performance gains without compromising listed requirements and specifications. The proposed design framework establishes a methodology for virtual engineering practitioners. In addition, a simulation is able to generate design and solution space visualizations for the assessment of design tradeoffs, optimizing three Key Performance Indices (KPIs) or Key Design Specification (KDS) objectives.
Suber II, DarrylBradley, AndrewSingh, ShubhendraTurner, CameronCastanier, Matthew P.Wagner, John
Tracked off-road vehicles operate at low speeds with high tractive effort and frequent skid-steer maneuvers, conditions that push torque and power demand to extremes and exacerbate powertrain efficiency losses. Electrification can improve energy conversion and mobility for such duty cycles. This paper introduces a novel power-split hybrid electric architecture for a tracked vehicle and benchmarks it against three designs: a conventional mechanical driveline, a series hybrid, and a P2 parallel hybrid. To enable fair, architecture-agnostic comparisons, a supervisory controller based on Stochastic Dynamic Programming (SDP) schedules engine operation and power flow across all layouts under representative off-road scenarios, including skid-steer events, with varying terrain and power-demand profiles. Results show higher energy conversion efficiency (lower fuel use) for the proposed power-split architecture, followed by the parallel, then series, and lastly conventional configuration across missions. Beyond efficiency, the proposed architecture offers packaging and robustness advantages: compared with the P2 parallel it eliminates transmission and steering hydraulics, yielding a more compact driveline and compared with the series hybrid it enables smaller traction motors and a smaller battery pack for the same missions. Finally, by allowing the machines to operate below base speed for longer, it extends burst-mode operation without sustained field weakening, thereby reducing demagnetization risk. Study analyzes the reason behind these trends and discusses packaging considerations.
Ghate, AtharvaSundar, AnirudhZhu, QilunPrucka, RobertFigueroa-Santos, MiriamBarron, MorganCastanier, Matthew P.
Leonardo DRS has opened a new naval power and propulsion manufacturing and testing facility in Charleston, South Carolina, expanding its role in delivering next generation electric propulsion, integrated power systems, and high energy payload support for U.S. Navy surface and undersea platforms. The 140,000 square foot site consolidates advanced manufacturing, final assembly, and high fidelity testing for electric power conversion and propulsion systems, while also supporting naval steam turbine design, production, and subsystem integration for programs including the Columbia class ballistic missile submarine. A representative for Leonardo's Naval Power Systems business unit provided emailed statements with details about the type of advanced manufacturing the company will deploy at the new facility.
Military tactical vehicles are increasingly incorporating anti-idle kits as a method to reduce fuel consumption. The larger battery pack associated with the anti-idle kit has the potential to provide new capabilities to the warfighter, who can use the battery pack to power pieces of equipment. This study analyzes a set of these new capabilities derived from the U.S. Army Universal Task List, supplemented with user interviews and doctrinal analysis. These capabilities include powering dismounted soldier systems, counter-drone and surveillance equipment, mobile refrigeration for medical applications, field maintenance tools, and mobile food services. The study then uses geolocation data collected from the U.S. Army’s National Training Center to model daily fuel consumption for soldiers performing each of these activities. The model was subsequently adapted to incorporate an anti-idle kit, revealing significant reductions in fuel usage. The analysis uses the results to define common functional requirements and inform the conceptual design of a modular kit that integrates with anti-idle systems to enable new capabilities, thereby allowing vehicles to serve as mobile energy platforms in addition to their traditional role of providing mobility.
Lusian, TrevonteMummert, TaigeKaiser, CalebGreer, MichaelBlack, NathanielOng, BennettTapahonso, EugeneMittal, Vikram
During the 2025 Association of the United States Army (AUSA) annual meeting and exhibition, Forterra announced several major defense industry vehicle partnerships and introduced four new integrated modules designed to enable autonomy for military vehicles, communications, and more. Headquartered in Clarksburg, Maryland, Forterra develops autonomous mission systems for specific defense applications, including robotics and self-driving vehicles. The company has a new partnership with BAE Systems that will rapidly prototype an autonomous Armored Multi-Purpose Vehicle (AMPV). Separately, Forterra has also collaborated with Oshkosh Defense and Raytheon to develop the “DeepFires” autonomous vehicle launcher technology.
The U.S. Army has selected two companies to develop prototype chassis and plug-in-cards for aviation and ground vehicles. The selection is the Army's latest milestone accomplishment in an effort to feature Modular Open System Approach (MOSA) -aligned embedded computing systems across all of the new investments it makes in technology upgrades for new and legacy vehicles. In a program update posted in September 2025, the Army selected General Dynamics Mission Systems and Pacific Defense as the lead developers for new C5ISR/EW Modular Open Suite of Standards (CMOSS) Mounted Form Factor prototypes. CMOSS is a set of standards developed by the U.S. Army to guide the design of embedded computing networks featured on Army vehicles.
Pyrovalves (also known as pyrotechnic valves) have long been a staple in defense systems, particularly in missile and munition launcher applications. The rapid growth of counter-UAS and missile defense systems makes this an ideal time to explore smarter alternatives to pyrovalves. One of the largest ongoing U.S. military efforts is the Missile Defense Agency's (MDA) Scalable Homeland Innovative Enterprise Layered Defense (SHIELD) Multiple Award Indefinite Delivery/Indefinite Quantity (IDIQ) contract. In December, MDA issued two tranches of SHIELD awards to more than 2,100 companies, including major defense contractors and startups such as Lockheed Martin, Raytheon, Boeing, Shield AI, Anduril, and Virtualitics.
The U.S. Army Space and Missile Defense Command Technical Center's Aerophysics Research Facility, (ARF), fired a successful hypersonic shot to test its new rainfield simulator. U.S. Army Space and Missile Defense Command Technical Center, Huntsville, AL Zack Perrin, ARF manager and technical lead engineer of the U.S. Army Space and Missile Defense Command (USASMDC's) Targets and Test Resources Branch of the Ronald Reagan Ballistic Missile Defense Test Site, said ARF is SMDC's premier hypersonic flight and hypervelocity impact laboratory. Perrin said their largest gun system, the 254 mm light gas guns, or LGGs, is the fastest gun in the Army and can launch projectiles 6 inches in diameter to speeds up to 3 kilometers per second or smaller projectiles on the order of 2.7 inches in diameter to velocities exceeding 6 km/s. “I like to tell people that the facility is a gun range the size of an aircraft carrier and within the facility are multiple engineering tools, called light gas guns,” Perrin said. “Aerophysics' core mission is to efficiently and affordably provide both the Army and the broader Department of Defense (DoD) engineering community with state-of-the-art hypersonic aerodynamic data, hypervelocity impact physics data, and weapons system performance data.”
RF and fiber have long co-existed within modern military and aerospace systems, with each medium dedicated to separate, mission-critical roles. Increasingly, however, system designers are turning to RF-over-fiber (RFoF) architectures to bridge the gap between over-the-air RF interfaces and the long, interference-resistant transport advantages of fiber. When it comes to over-the-air communications uses like tactical radio or satellite communications terminals, radio frequency (RF) is still the dominant signal format. RF is also commonly used at the front end of radar and electronic warfare, supporting search, tracking, fire control radar, missile seekers, jammers and electronic support measures.
As atmospheric CO₂ concentrations continue to rise at unprecedented rates, the urgent need for breakthrough technologies that can efficiently capture carbon directly from the air and convert it into sustainable synthetic fuels has never been clearer. While numerous capture and conversion methods have been propose, many remain at an early stage of development, facing significant challenges such as low energy efficiency, limited scalability, and high operational costs. This lack of technological maturity underscores a vast, largely untapped potential for innovation and transformative advancement. In response to this gap, the present study compiles and critically examines a wide spectrum of emerging capture and conversion technologies. Through a detailed exploration of their functionalities, potentials, advantages, and challenges, the paper accumulates a comprehensive and well-informed dataset. This holistic understanding not only reveals key bottlenecks but also identifies promising pathways to overcome them, offering a valuable foundation for future research and practical implementation. At its core, the study explores how strategic integration and optimization of capture and conversion systems can significantly enhance overall energy efficiency potentially more than doubling current benchmarks. Through this hypothesis-driven approach, it uncovers new possibilities for elevating technology readiness and achieving commercially viable solutions. Serving as a vital resource for researchers, industry stakeholders, and policymakers, this work advances scientific understanding and offers a clear roadmap to accelerate innovation and investment. The insights presented hold the promise to revolutionize sustainable fuel production, facilitate the global reduction of carbon emissions, and catalyze the transition toward a resilient, circular carbon economy that benefits both society and the environment.
Jain, GauravPremlal, PPathak, RahulGore, Pandurang
Current world conflicts have proven that drones are now indispensable tools in modern warfare. Whether for reconnaissance, loitering munitions, or asymmetric tactics that exploit vulnerabilities in conventional defenses, unmanned aerial systems (UAS) are redefining the rules of engagement.
Since the emergence of the first tanks in World War I, tracked military vehicles have driven the development of increasingly sophisticated control systems, keeping pace with the evolution of technologies and combat tactics. This study aims to develop a longitudinal speed control system for tracked military vehicles using a cascade framework. To this end, a dynamic model based on the bicycle model—commonly employed for wheeled vehicles—has been appropriately adapted to represent the dynamics of tracked vehicles. In the first stage, a Model-based Predictive Controller defines the required traction force to be produced by the track; subsequently, a PID controller determines the necessary torque on the drive pulley to achieve the desired force. Simulations performed in MATLAB, considering a straight trajectory and speeds of up to 20 km/h, demonstrate the effectiveness of the proposed control system, yielding satisfactory results in the regulation of longitudinal speed.
Forte, Marcelo AlejandroPenha, Luiz Roberto Martins SilvaBraga, Matheus Rodrigues PereiraRodrigues, Gustavo SimãoLopes, Elias Dias Rossi
Technological innovations in military vehicles are essential for enhancing efficiency, safety, and operational capability in complex scenarios. Advances such as navigation system automation and the introduction of autonomous vehicles have transformed military mobility. State estimators enable the precise monitoring of critical variables that are not directly accessible by sensors, providing real-time information to controllers and improving dynamic response under variable conditions. Their integration is crucial for the development of advanced control systems. This study aims to develop and compare parameter and states estimators for military heavy vehicles using three methodologies: particle filter, extended Kalman filter, and moving horizon state estimation. Computational simulations employ Pacejka’s magic formula to model tire behavior, and the vehicle modeling is based on a simplified quarter-car model, with an emphasis on longitudinal dynamics. In the end, the estimators are compared through simulated scenarios involving the friction coefficient between the tire and the surface. Their effectiveness, advantages and disadvantages are evaluated, highlighting their ability to provide accurate and robust real-time estimation of parameters and states of the longitudinal dynamics.
Barros, Leandro SilvaSousa, Daniel Henrique BrazRodrigues, Gustavo SimãoLopes, Elias Dias Rossi
The present study aims to utilize a tire mathematical model that incorporates multiple contact points between the tire and the ground to provide a more accurate and realistic representation of the vertical and longitudinal dynamics of the Guarani 6x6 Armored Personnel Carrier (APC), a medium-wheeled vehicle used by the Brazilian Army. First, the subsystems involved in the longitudinal dynamics of the Guarani APC are introduced and modeled using TMeasy, a physical-mathematical model for tire slip behavior. Subsequently, the subsystems associated with the vehicle’s vertical dynamics are presented and modeled based on Ageikin’s concepts of obstacle negotiation. Finally, the longitudinal and vertical models are integrated to develop a multi-contact-point model with enhanced completeness, considering their mutual influence on each other. The modeling process is conducted within the Simulink® environment of MATLAB®. In each stage, simulations validate the proposed model’s suitability in representing the vehicle’s behavior under various operating conditions.
Godinho, Gabriel AsvolinsqueCosta Neto, Ricardo Teixeira
Vehicle dynamics encompasses a vehicle’s motion along three principal axes: longitudinal, lateral, and vertical. The vertical component is particularly susceptible to vibrational forces that can impair passenger comfort and overall performance, and the suspension system filters these vibrations. Engineers and designers conduct various studies to enhance quality and develop innovative designs in this context. However, when it comes to military vehicles, this system is often treated as classified. Consequently, the proposed work aims to determine the parameters of this system for a wheeled military vehicle with four axles. To achieve this, a mathematical model is proposed utilizing the concepts of power flow and kinematic transformers through a modular system, intended to serve as the foundation for solving an inverse problem to identify these parameters. This approach employs two stochastic methods, particle swarm optimization (PSO) and differential evolution (DE), and field tests to collect real data from the vehicle. Following the parameter estimation, a comparison between the numerical simulation and the actual dynamic behavior of the vehicle is proposed. Based on these tests, the system is analyzed under several proposed configurations.
de Oliveira, André NoronhaBueno Caldeira, Aldélioda Costa Neto, Ricardo Teixeira
Powertrain architecture is being reshaped by the electrification of heavy-duty military vehicles using hydrogen fuel cell technology, particularly in transmission systems. Unlike conventional internal combustion engines, hydrogen fuel cell electric vehicles (FCEVs) typically use single-speed or direct-drive configurations due to the high torque of electric motors. This paper examines the impact of hydrogen electrification on military vehicle transmissions, focusing on armored multi-role models such as the VBMT-LSR, Guarani, and Leopard 1A5 of the Brazilian Army. The study compares traditional gearboxes with alternative solutions optimized for fuel cells, analyzing the trade-offs in efficiency, durability, and operational adaptability. Additionally, it explores adaptations required for hydrogen internal combustion engines (H2-ICEs), considering their distinct characteristics and demands. The study employs a three-step validation methodology combining computational simulations, technical data analysis, and case studies of military vehicles. MATLAB and similar tools are used to assess efficiency, durability, and torque response under field conditions. Next, specifications from existing military vehicles in the Brazilian Army are analyzed to evaluate the feasibility of hydrogen powertrains compared to diesel-based solutions. Finally, the study examines international military projects that have already integrated hydrogen or electrification, such as GM SURUS and Rheinmetall Mission Master, drawing insights into the applicability of these concepts in the Brazilian military context. This research enhances the understanding of hydrogen-powered transmissions, contributing to the future development of more sustainable powertrain solutions and thus supporting the adaptation of military fleets to alternative energy sources and accelerating the adoption of hydrogen-based mobility in defense applications.
Biêng, Ethan Lê QuangPontes, Guilherme AyrosoConrado, Guilherme Barreto RollembergLopes, Elias Dias RossiRodrigues, Gustavo Simão
Tracked Military Vehicles are well known in armed forces, due to their use and importance in conventional combat, playing a crucial role since World War I until current combats. Also, as it happens in different generations, the environment involved in these wars changes and those vehicles are being used not only in open field situations, but inside residential neighborhoods also. However, despite their relevance, analyses and studies aimed at understanding these vehicles are scarce at the undergraduate level, which creates a gap among the recent graduate engineers that want to learn and understand how tracked vehicles perform in different scenarios. This is important because understanding initial concepts helps to bring more ideas and start more detailed studies in the area. Therefore, to bridge this gap, a detailed dynamic analysis of a tracked military vehicle is conducted using MATLAB with a dynamic model to evaluate performance, level transitions, and acceleration. Additionally, simulations are performed under different scenarios: asphalt, sand, and mud, where conditions in a jam situation are tested.
Dalcin, Pedro Henrique KleimRibeiro, Levy PereiraLopes, Elias Dias RossiRodrigues, Gustavo Simão
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