Battlefield Environment Research Articles

Research on tribological properties of new Ni-based single crystal alloy containing Re

Abstract The particles in high-temperature and high-speed airflow in the battlefield environment will form sliding friction and wear on the aeroengine turbine blades, thus reducing the service performance of the blades. However, few studies has been reported on the tribological properties of Ni-based single crystal alloy. Accordingly, the tribological properties of Ni-based single crystal alloys with different contents of Re (0 wt%, 1.5 wt%, 2.5 wt%, 3.5 wt%, 4.5 wt% and 5.5 wt%) are investigated by tribological experiments and molecular dynamics simulations in this paper. The results of tribological experiments show that Ni-based single crystal alloy without Re exhibits the characteristics of abrasive wear and adhesive wear, while the wear state is significantly improved after adding Re element. In particular, the worn surface of Ni-based single crystal alloy containing 5.5% Re (NSCA5) is the smoothest and only a few minor defects are observed. In addition, the micro-tribological characteristics of Ni-based single crystal alloy are analyzed by molecular dynamics simulations, the results show that Re atoms can inhibit the dislocation movement and reduce the system potential energy, which enhance the stability and hardness of Ni-based single crystal alloy, thereby the wear resistance of the material are improved.

Stochastic Evolutionary Analysis of an Aerial Attack–Defense Game in Uncertain Environments

Aiming at the problem of random environment interference in the process of strategy interaction and the behavioral evolution of an aerial attack–defense game, this paper considers the influence of the difference in the performance and value between both game players in terms of strategy evolution; explores the randomness of the complex battlefield environment, the uncertainty of the behavioral state of game players, and the limitations of the emergent situation; constructs a mathematical model of the stochastic evolution of an aerial-coordinated attack–defense game in uncertain environments; and studies the stability of the strategy interaction and behavioral decision-making process of both players of the aerial attack–defense game. Simulation results show that many factors of the performance and value between both game players have a greater impact on the strategy evolution trend in both game players, which not only causes changes in the results of the strategy selection but also affects the rate of strategy evolution for the game players. In addition, random environmental factors cause a certain degree of interference to the strategy evolution process of the game players, which usually accelerates the game players’ strategy evolution rate and greatly affects the evolution process of the game players’ strategy. This study can provide a theoretical basis and feasible reference for improving mission decision-making, response mechanisms, and system modeling of an aerial attack–defense game, which has important theoretical value and practical significance.

Proximity ligation-triggered DNAzyme for selective fluorescent aptasensing of methicillin-resistant Staphylococcus aureus

There is an urgent need for novel strategies to accurately and reliably detect pathogenic bacteria to address the global epidemic of antibiotic resistance. This study proposes an innovative approach combining dual aptamer-based target recognition and proximity ligation assay (PLA) triggered DNAzyme recycling cleavage. This method allows for the precise identification and reliable detection of methicillin-resistant Staphylococcus aureus (MRSA). The fluorescence probe labeled with a fluorophore is modified on gold nanoparticles (AuNPs), resulting in the quenching of the fluorescent signal by the AuNPs. The interaction between MRSA and two aptamers leads to forming a Mg2+-dependent DNAzyme. The DNAzyme cleaves the fluorescence probe, causing the fluorescent fragment to detach from the surface of the AuNPs, in which the quenched fluorescence signal in the fluorescence probe reappears. The DNAzyme-assisted cleavage and rebinding process generates a processive strolling along the surface track of AuNPs. Consequently, the fluorescence intensity experiences a substantial recovery. A strong linear correlation is observed between the fluorescence intensity and MRSA concentration within 50 cfu/mL to 106 cfu/mL. We believe that implementing the novel integrated strategy will broaden the range of bacterial detection methods in the battlefield environment and stimulate the creation of potential new drugs in the future.

A Dynamic Topology Optimization Method for Tactical Edge Networks Based on Virtual Backbone Networks.

To address the issues of low survivability and communication efficiency in wireless sensor networks caused by frequent node movement or damage in highly dynamic and high-mobility battlefield environments, we propose a dynamic topology optimization method based on a virtual backbone network. This method involves two phases: topology reconstruction and topology maintenance, determined by a network coverage threshold. When the coverage falls below the threshold, a virtual backbone network is established using a connected dominating set (CDS) and non-backbone node optimization strategies to reconstruct the network topology, quickly restore network connectivity, effectively improve network coverage, and optimize the network structure. When the coverage is above the threshold, a multi-CDS scheduling algorithm and slight position adjustments of non-backbone nodes are employed to maintain the network topology, further enhancing network coverage with minimal node movement. Simulations demonstrate that this method can improve coverage and optimize network structure under different scales of network failures. Under three large-scale failure operational scenarios where the network coverage threshold was set to 80%, the coverage was enhanced by 26.12%, 15.88%, and 13.36%, and in small-scale failures, the coverage was enhanced by 7.55%, 4.90% and 7.84%.

Designing the Prolonged Field Care Kit (PFAK) to Address the Logistical Challenges of Future Combat Casualty Care.

Prolonged Casualty Care (PCC) is a military adaptation aimed at providing pre-hospital care in austere settings when evacuation is delayed or even impossible. Current lack of standardized medical equipment and size/weight restrictions of military packs during dismounted operations hinder effective PCC. We sought to design a standardized, practical, and effective prolonged field care kit (PFAK) to enable widespread implementation of PCC. We reviewed Joint Trauma System Clinical Practice Guidelines to generate a list of potential contents of the PFAK. We obtained Institutional Review Board (IRB) exemption and then conducted stakeholder surveys of combat casualty care experts across the Joint Trauma System using a modified Delphi survey approach. We established a civil-military working group that provided in-depth qualitative feedback on the PFAK contents and provided an initial design of a long-range medical rucksack (LMR) to house it. Responses were analyzed using mean rank scores to help determine initial components of the PFAK. Tactical subject-matter experts tested and evaluated the PFAK and LMR prototype in austere conditions to refine the design. Review of the PCC Clinical Practice Guidelines generated 49 medications and 301 potential supplies as potential PFAK contents. The first Delphi survey was sent to 100 stakeholders (overall response rate of 60%). After the first survey, contents were narrowed to a list of the most essential 27 medications and 105 other components. Iterative prototypes of the PFAK and LMR were tested to determine ergonomics, portability, flexibility, and equipment compartmentalization to facilitate use in emergencies. The prototype was optimized to address the clinical, logistical, and tactical requirements of PCC across a variety of platforms and environmental conditions. Given the changing battlefield environment, efficient and effective PCC will play an increasingly important role in the management of combat trauma. The PFAK can meet this need by providing a practical and standardized resuscitation kit generated by expert military and trauma personnel consensus, carried conveniently in the LMR.

Research on Information Fusion Method for Human Computer Interaction Interface of Command and Control System in MR Environment

In response to the challenge of high cognitive pressure and difficulty for commanders in cross-layer operations during the transition from traditional two-dimensional command and control system interfaces to mixed reality human-computer interaction interfaces, this paper conducts research on the information fusion display method for the human-computer interaction interface of the mixed reality command and control system. First, based on the findings of previous research, we developed a five-layer human-computer interaction interface for a mixed reality command and control system in typical combat scenarios. An evaluation experiment was designed and the resulting data analyzed. This analysis revealed that there are problems with low work efficiency and high cognitive load in the information acquisition process in cross-layer interaction operations. Consequently, we conducted research into the methods of integrating and displaying interactive interface information, integrating and displaying interactive and display interface information, and integrating and displaying complex situation interface information. The research findings indicate that: (1) The optimal display ratio for mixed reality 2D interface integration is 3:2. (2) The optimal display scheme for mixed reality 2D interface fusion is a combination of the main and secondary interfaces, with the main interface table displaying global information and the secondary interface displaying accurate information. (3) The optimal display scheme for mixed reality 2D and 3D interface fusion is the display of overall class information in 2D and the accurate identification of class information in 3D. The findings of this research can be applied to the design of human-computer interaction interfaces for mixed reality command and control systems in complex battlefield environments.

Study on ballistic impact performance of bionic fish scale protective armor

Composite bulletproof armor used in modern battlefield environments is mostly composed of ceramic/ultra-high molecular weight polyethylene (UHMWPE). In order to further improve its bulletproof performance, this study draws on the superposition of fish scales. The upper layer of the flexible protective armor consists of composite scale layers stacked on top of each other, and the lower layer consists of UHMWPE plates with grooved structures at the corresponding locations of the scales, where a single composite scale consists of an upper SiC ceramic layer and a lower UHMWPE layer. Finite element simulation is used to analyze the protective performance of the protective armor. The effects of back plate thickness, scale tilt angle, and impact location on the protection performance are investigated. The results show that the 8 mm thick back plate can effectively resist the impact of Type 53 7.62 mm armor-piercing incendiary ammunition, and the protective effect is best when the scale tilt angle is 30°. The maximum depression depth of the backplane is 12.4 mm, and the deformation of the backplane is reduced by 3 mm when the bullet hits the overlapping area of the scale compared with the central area of the target scale, accounting for 32.67% of the total deformation. The research work has guided the development of new bionic flexible protective armor.

A threat assessment method based on correlation-similarity information and three-way decisions in interval intuitionistic fuzzy environment

Threat assessment of targets is a critical component of combat decision-making. Existing threat assessment methods only consider specific dimensions of information. When information is missing or abnormal, they may fail to provide accurate assessment results. Moreover, most methods can only obtain the threat level of targets without providing target threat levels based on the battlefield environment. Therefore, in the context of interval intuitionistic fuzziness, this paper proposes a threat assessment method based on Grey Correlation Analysis and Technique for Order Preference by Similarity to an Ideal Solution (GCA-TOPSIS) and three-way decisions. This method utilizes interval intuitionistic fuzzy entropy to calculate attribute weights. It simultaneously considers information on both similarity and correlation between targets. By introducing grey correlation coefficients to balance the similarity and correlation between targets and the ideal solution, the method computes threat degrees based on the information from both dimensions. Through fuzzy evaluation information, it constructs loss functions, calculates decision thresholds, and thereby determines the threat levels of the targets. This approach is better suited for the complex and dynamic battlefield environment, providing decision-makers with target threat levels. Finally, we conducted simulation experiments under both complete data and data anomaly conditions. The results indicate that when the data noise reaches 0.5 dB, the absolute error of GCA-TOPSIS is only 0.08. When 66.67% of the data is missing, the error is 0.16. In both scenarios, the error is much smaller than that of other threat assessment methods. This demonstrates the method's strong robustness and its suitability for complex battlefields.

Q-learning based on strategic artificial potential field for path planning enabling concealment and cover in ground battlefield environments

Q-learning based on strategic artificial potential field for path planning enabling concealment and cover in ground battlefield environments

Radar antenna scanning type identification based on the fusion of multiple temporal features

Identifying the antenna scanning type (AST) of radar signal aims to deeply analyze the parameters of radar waveform and accurately judge the AST of the radar signal. Traditional methods rely heavily on domain priors and expert experience to set classification thresholds, which introduces human errors. Moreover, the generalization and anti-noise interference abilities are relatively weak, and it is difficult to deal with complex battlefield environments. The model based on the convolutional neural network (CNN) is limited by the receptive field of the convolution kernel, which makes the model unable to make full use of the global information of the signal. To fully exploit the global timing characteristics of radar signals, we propose a radar AST recognition method based on the fusion of multiple temporal features. Specifically, for the time series characteristics of the radar antenna scanning signal, a 1D CNN branch is first built to extract its short time series features. Given the limited receptive field of the convolutional network and the inability to fully consider the overall characteristics of the radar signal, we propose a transformer network branch to extract the global timing features fully. The recognition of radar AST based on multi-time series feature fusion can fully model the local and global sequence attributes, thereby improving the cognitive recognition ability of radar signals. Our method attains state-of-the-art results based on experimental findings.

Research on Combat Mission Configuration of Unmanned Aerial Vehicle Maritime Reconnaissance Based on Particle Swarm Optimization Algorithm

In recent years, in the classic battles and armed conflicts around the world, battlefield environment reconnaissance and the collection and processing of operational information play an increasingly critical role in the victory and defeat of the battlefield. Unmanned equipment, especially UAV equipment, is used by more and more countries in the field of combat reconnaissance. Meanwhile, the types of UAV are gradually diversified with the change of operational requirements. UAVs adapted to different combat environments shine brightly on the battlefield. In terms of naval battle field, due to the limitations and deficiencies of reconnaissance methods such as surface radar, UAVs play a more prominent role in combat reconnaissance. There are more scenarios for UAVs to be used in combat reconnaissance in naval battle field and higher requirements for UAVs’ combat effectiveness. Therefore, this paper takes UAVs’ naval battle reconnaissance missions as the research object. By using PSO as the research method, this paper studies the combat reconnaissance task configuration of UAVs, hoping to contribute to the improvement of UAVs’ combat reconnaissance capability and combat effectiveness.

A Mobility Based Approach to Strengthen the Network Lifetime of Wireless Sensor Networks in 3D Region

Background: In this era of emerging technologies, Mobile Wireless Sensor Network (MWSN) has emerged as a powerful tool for many applications. Applications such as battlefield and traffic surveillance, agriculture and environment monitoring, smart homes and smart cities require a specific protocol to fulfill a specific purpose. WSN is composed of numerous tiny Sensor Nodes (SNs) along with one or more sinks, where sinks have unlimited sources of energy and SNs are battery- operated. SN tasks are to sense the data and transmit it to sink through the formation of dynamic topology. The SNs nearer to the sink rapidly exhaust their energy due to the heavy burden. Due to this, SNs became dead affecting the performance of the network lifespan. To overcome this problem, the concept of MWSN has been proposed. In MWSN, the sink can move from one location to another, and collect data from SNs. With the help of MWSN, the problem of energy holes can be resolved. An energy hole is a problem in which nodes are alive but they are not able to send the data due to low energy left. To overcome this problem, MWSN plays an important role. MSWN can move around the region and collect the data from SNs. Methods: In this work, we have proposed a Mobile Sink (MS) that can move on fixed or random locations for data collection from SNs. The comparative analysis of various MS strategies such as MS on boundaries, 4 sojourn locations in the region, random position in the region and fixed path to collect the data has been done. Results: SNs become dead in 2246 rounds in static approach. In the MS boundary approach, all SNs are dead in 2593 rounds. In the sojourn location, it lasts up to 4827. But in MS random and fixed location approaches, all SNs are dead in 11568 and 11513 rounds, respectively. Conclusion: The simulation results depict that the MS strategies having fixed or random positions in the region enhanced the network lifetime 4 to 5 times more than the static sink.

Behaviors analysis of on-coming cluster based on knowledge under cluster security requirements

Analysis of cluster behaviors of the on-coming cluster is an essential measure for high value locations on the battlefield. Unlike target tracking and clustering analysis, cluster behaviors analysis under cluster security requirements remains an open issue, which is a joint analysis of clustering, intent reasoning and activity regions. To address this issue, a framework for cluster behaviors analysis is proposed by incorporating expert knowledge and domain knowledge, and a knowledge-assisted score function with is designed to improve the accuracy of intent reasoning network, overcoming the effects of possible knowledge errors. The framework consists of three modules for cluster analysis, intent reasoning and activity region analysis for typical tasks, in which an intent reasoning network is constructed to obtain cluster intents by using a hybrid knowledge and data driven approach. Furthermore, considering the complexity of the battlefield environment, different tasks and corresponding activity region optimization functions are designed for cluster activity region analysis, which are vital elements of cluster behaviors analysis. Simulations demonstrate the effectiveness of the proposed cluster behaviors analysis framework.

A New Multi-Target Three-Way Threat Assessment Method with Heterogeneous Information and Attribute Relevance

Target threat assessment provides support for combat decision making. The multi-target threat assessment method based on a three-way decision can obtain threat classification while receiving threat ranking, thus avoiding the limitation of traditional two-way decisions. However, the heterogeneous situation information, attribute relevance, and adaptive information processing needs in complex battlefield environment bring challenges to existing methods. Therefore, this paper proposes a new multi-target three-way threat assessment method with heterogeneous information and attribute relevance. Firstly, dynamic assessment information is represented by heterogeneous information, and attribute weights are calculated by heterogeneous Criteria Importance Through Intercriteria Correlation (CRITIC). Then, the conditional probability is calculated by the heterogeneous weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and the adaptive risk avoidance coefficients are constructed by calculating the uncertainty of the assessment value, and then the relative loss function matrices are constructed. Finally, the comprehensive loss function matrices are obtained by the weighted Heronian mean (HM) operator, and the comprehensive thresholds are calculated to obtain the three-way rules. The case study shows that compared with the existing methods, the proposed method can effectively handle the heterogeneous information and attribute relevance, and obtain the risk avoidance coefficients without presetting or field subjective settings, which is more suitable for the complex mission environment.

Performance and Damage Study of Composite Rotor Blades under Impact.

A military helicopter is easily attacked by bullets in a battlefield environment. The composite blade is the main lifting surface and control surface of the helicopter. Its ballistic performance directly determines the vulnerability and survivability of the helicopter in the battlefield environment. To study the ballistic performance of the composite helicopter blade, the damage characteristics of the impacted composite rotor blade are obtained by experiments. A numerical simulation model is established by applying Abaqus software to predict the blade ballistic damage. The three-dimensional progressive damage failure model is used to analyze the ballistic damage under the experimental conditions. The effectiveness and accuracy of the numerical simulation model are verified through a comparison with the experimental results. The ballistic damage of composite blades under three experimental conditions was investigated. The results show that the ballistic damage type of composite blade mainly includes delamination, fiber breakage, and foam collapse. The damage to the composite material at the position of bullet incidence is mainly local shear fracture, while the damage to the composite material at the exit position is mainly fiber tensile fracture. The ballistic damage size of the composite blade is closely related to the ballistic position, incident angle, and structure characteristics along the ballistic path. The larger the incident angle, the smaller the ballistic damage size of the blade. The greater the structural stiffness of the structure near the exit, the greater the damage size of the exit. The numerical simulation model presented in this paper can provide a reference for research on the ballistic performance of composite helicopter blades.

Burn Wound Care Strategies for the Battlefield and Austere Settings

Burns are commonly encountered in the battlefield environment; however, the availability of burn expertise and specialized supplies is variable. Initial burn care should remain focused on cooling the burn, preventing hypothermia, basic wound cleansing, and evacuation. Key ongoing burn wound management principles include wound debridement, accurate burn size and depth estimation, wound care, ongoing wound evaluation, and treatment of suspected Gram-negative wound infection. Operative management should be limited to urgent procedures, and definitive burn management should be performed only after evacuation to a higher level of care. Flexibility, creativity, and the ability to adapt care to the tactical environment are key to the successful management of burn injuries in battlefield and austere settings.

Shortwave infrared and visible light image fusion method based on dual discriminator GAN

In a tactical warfare setting, the efficacy of target detection becomes profoundly compromised due to prevalent environmental factors such as smoke, dust, and atmospheric interference. Such impediments invariably undermine the precision and reliability of identifying pivotal targets, thereby precipitating potentially dire ramifications. Remarkably, short-wave infrared technology has exhibited unparalleled proficiency in elucidating target attributes even amidst challenging conditions characterized by smoke, fog, or haze. Against this backdrop, the present study delineates a pioneering algorithmic framework that seamlessly amalgamates the imperatives of image registration and fusion. This is achieved through the deployment of an advanced dual-discriminator Generative Adversarial Network (GAN), specifically tailored for amalgamating short-wave infrared and visible light imagery within smoke-obscured contexts. Our methodology commences with the introduction of an augmented Speeded-Up Robust Features (SURF) algorithm, meticulously designed to rectify inherent misalignments within the input imagery. Subsequent enhancements encompass the refinement of the generator’s loss function and the integration of a multi-scale convolutional kernel, thereby facilitating the extraction and amalgamation of a more expansive array of salient features. This concerted effort culminates in the elevation of image fusion quality. To corroborate the efficacy and robustness of our proposed framework, rigorous validation procedures were conducted utilizing a meticulously curated dataset comprising short-wave infrared and visible light images. Empirical evaluations, encompassing both subjective and objective comparative analyses, unequivocally affirm the superior performance metrics of our fusion network. Specifically, our methodology surpasses alternative fusion techniques across multiple dimensions, including visual fidelity, perceptual quality, and structural congruence of synthesized images.

Design of flight control system of Quad Tilt Rotor UAV based on PID algorithm

This research focuses on the quadrotor tiltrotor unmanned aerial vehicle and considers various usage scenarios such as battlefield and transportation environments, as well as flight stability issues in complex meteorological environments. A PID control algorithm for rotor angle control of quadrotor tiltrotor unmanned aerial vehicles is designed, which is suitable for different usage scenarios and meteorological conditions.

A hospitalization mechanism based immune plasma algorithm for path planning of unmanned aerial vehicles

Unmanned aerial vehicles (UAVs) and their specialized variants known as unmanned combat aerial vehicles (UCAVs) have triggered a profound change in the well-known military concepts and researchers from different disciplines tried to solve challenging problems of the mentioned vehicles. Path planning is one of these challenging problems about the UAV or UCAV systems and should be solved carefully by considering some optimization requirements defined for the enemy threats, fuel or battery usage, kinematic limitations on the turning and climbing angles in order to further improving the task success and safety of autonomous flight. Immune plasma algorithm (IP algorithm or IPA) modeling the details of a medical method gained popularity with the COVID-19 pandemic has been introduced recently and showed promising performance on solving a set of engineering problems. However, IPA requires setting the control parameters appropriately for maintaining a balance between the exploration and exploitation characteristics and does not design the particular treatment and hospitalization procedures by taking into account the implementation simplicity. In this study, IP algorithm was supported with a newly designed and realistic hospitalization mechanism that manages when an infected population member enters and discharges from the hospital. Moreover, the existing treatment schema of the algorithm was changed completely for improving the efficiency of the plasma transfer operations and removing the necessity of IPA specific control parameters and then a novel path planner called hospital IPA (hospIPA) was presented. For investigating the performance of hospIPA on solving path planning problem, a set of detailed experiments was carried out over twenty test cases belonging to both two and three-dimensional battlefield environments. The paths calculated by hospIPA were also compared with the calculated paths of other fourteen meta-heuristic based path planners. Comparative studies proved that the hospitalization mechanism making an exact discrimination between the poor and qualified solutions and modified treatment schema collecting the plasma being transferred by guiding the best solution give a tremendous contribution and allow hospIPA to obtain more safe and robust paths than other meta-heuristics for almost all test cases.

Injectable Self-Expanding/Self-Propelling Hydrogel Adhesive with Procoagulant Activity and Rapid Gelation for Lethal Massive Hemorrhage Management.

Developing hydrogels that can quickly reach deep bleeding sites, adhere to wounds, and expand to stop lethal and/or noncompressible bleeding in civil and battlefield environments remains a challenge. Herein, an injectable, antibacterial, self-expanding, and self-propelling hydrogel bioadhesive with procoagulant activity and rapid gelation is reported. This hydrogel combines spontaneous gas foaming and rapid Schiff base crosslinking for lethal massive hemorrhage. Hydrogels have rapid gelation and expansion rate, high self-expanding ratio, excellent antibacterial activity, antioxidant efficiency, and tissue adhesion capacity. In addition, hydrogels have good cytocompatibility, procoagulant ability, and higher blood cell/platelet adhesion activity than commercial combat gauze and gelatin sponge. The optimized hydrogel (OD-C/QGQL-A30) exhibits better hemostatic ability than combat gauze and gelatin sponge in rat liver and femoral artery bleeding models, rabbit volumetric liver loss massive bleeding models with/without anticoagulant, and rabbit liver and kidney incision bleeding models with bleeding site not visible. Especially, OD-C/QGQL-A30 rapidly stops the bleedings from pelvic area of rabbit, and swine subclavian artery vein transection. Furthermore, OD-C/QGQL-A30 has biodegradability and biocompatibility, and accelerates Methicillin-resistant S. aureus (MRSA)-infected skin wound healing. This injectable, antibacterial, self-expanding, and self-propelling hydrogel opens up a new avenue to develop hemostats for lethal massive bleeding, abdominal organ bleeding, and bleeding from coagulation lesions.