Search Results (56)

Cyclic nitramine explosives such as octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX), hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), and 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20) are xenobiotics that are utilized in a variety of propellants and traditional weapons. The primary source of water contamination is the industrial use of these hazardous substances in propellants and wastewater generated from munitions production facilities. These chemicals have a negative impact on human health and ecosystems. It is necessary to remove these toxic compounds from the environment safely because their production and usage have seriously contaminated soil and groundwater. Although there are no widely adopted WHO or US federal Maximum Contaminant Levels (MCLs) for military explosives, the health advisory limits for RDX in drinking water are 2 µg/L, and for HMX are 400 µg/L. Numerous traditional treatment approaches that incorporate physical, biological, and chemical processes have been used to decontaminate explosive wastewater. However, contaminants are not completely mineralized by these methods. Complete reduction of these chemicals can be accomplished by combining suitable methods. For the remediation of explosive effluent, integrated treatment systems that combine the effectiveness of biological and physical-chemical methods have shown promising results. This review discusses the toxicity and some physical–chemical–biological and combined treatment processes of wastewater polluted by these explosive contaminants. Full article

Prolonged conflicts in Iraq over the past four decades have profoundly disrupted environmental systems, not only through immediate post-conflict emissions—such as residues from munitions and explosives—but also via long-term infrastructural collapse, population displacement, and unsustainable resource practices. Despite growing concern over air quality in conflict-affected regions, comprehensive assessments integrating long-term data and localized measurements remain scarce. This study addresses this gap by analyzing the environmental consequences of sustained instability in Mosul, focusing on air pollution trends using both remote sensing data (1983–2023) and in situ monitoring of key pollutants—including PM_2.5, PM₁₀, TVOCs, NO₂, SO₂, and formaldehyde—at six urban sites during 2022–2023. The results indicate marked seasonal variations, with winter peaks in combustion-related pollutants (NO₂, SO₂) and elevated particulate concentrations in summer driven by sandstorm activity. Annual average concentrations of all six pollutants increased by 14–51%, frequently exceeding WHO air quality guidelines. These patterns coincide with worsening meteorological conditions, including higher temperatures, reduced rainfall, and more frequent storms, suggesting synergistic effects between climate stress and pollution. The findings highlight severe public health risks and emphasize the urgent need for integrated urban recovery strategies that promote sustainable infrastructure, environmental restoration, and resilience to climate change. Full article

The increasing frequency and intensity of wildfires in hard-to-reach and hazardous areas represents a significant challenge for traditional firefighting methods. Wildfires pose a growing threat to the environment, property, and human lives. In many cases, conventional suppression techniques prove ineffective, highlighting the need for innovative and efficient solutions. Recent fires in the Bohemian Switzerland National Park in the Czech Republic; the Los Angeles area in California, USA; and the southeastern region of South Korea have underscored the necessity for alternative wildfire mitigation strategies. This article explores the potential of employing military technologies, such as artillery systems and specialized munitions, in wildfire suppression. The analysis includes a review of previous experiments, the research into non-standard methods, and an assessment of the risks and limitations associated with these approaches. Based on the research and simulations, it was found that one salvo (eight rounds) of fire-suppressant shells can cover up to 650 m² of terrain with suppressant. Finally, this article proposes a direction for further research aimed at integrating military and civilian technologies to enhance the effectiveness of wildfire response. This work contributes to the ongoing discussion on the integration of artillery capabilities into crisis management and provides a foundation for the future research in this field. Full article

Electrothermal actuators, with their simple structure, small size, strong anti-interference ability, and easy integration, have emerged as a promising solution for micro-drive technology. However, deploying them in extreme environments, such as the fuze systems—which demand exceptional reliability under high mechanical overloads. In this study, a device based on multi-electrothermal co-actuation is designed for the fuze system of loitering munition. The overall structure and work principle of the multi-electrothermal co-actuation device is discussed. Considering application environments, the effect factors of V-beam numbers, air gap, type of contact surface, external load force, periodic voltage and gas damping on the output performance of the multi-electrothermal co-actuation device are systematically addressed via simulation and experimental method. Furthermore, the high overload resistance performance of the co-actuation device applied in loitering munition is studied. The results show that the proposed multi-electrothermal co-actuation device could operate stably under a high overload (12,000 g/73.79 μs) environment, fully meeting the demanding requirements of fuze system for loitering munition. In addition, this study identifies laser processing-induced thermal gradients and mechanical stresses as critical fabrication challenges. This study provides significant insights into the design and optimization of multi-electrothermal actuation systems for next-generation fuze applications, establishing a valuable framework for future development in this field. Full article

Industrial munition facilities are increasingly manufacturing insensitive high explosives (IHEs) to improve safety. The explosive residues in wastewater from these facilities are treated to meet regulatory standards. However, the resulting effluent contains elevated levels of mineralized nitrogen species. This study evaluated the potential of vetiver grass (Chrysopogon zizanioides), a non-invasive perennial species, to remove high concentrations of nitrate, nitrite, and ammonium from munition plant wastewater. Vetiver was grown hydroponically in synthetic wastewater containing high levels of nitrogen compounds simulating munitions plant effluents. Vetiver plants were treated with one nitrogen species at a time, with concentrations ranging from 165 to 24,700 mg N/L of nitrate, 100 to 4000 mg N/L of nitrite, and 260 to 39,000 mg N/L of ammonium. Nitrogen concentrations in the media and plant responses were monitored over time. The results showed significant nitrogen removal at lower concentration ranges. When concentrations exceeded 3800 mg N/L of nitrate, 800 mg N/L of nitrite, and 2600 mg N/L of ammonium, the removal rates declined after 7 days. At higher nitrogen levels, vetiver exhibited stress symptoms such as chlorosis and elevated antioxidant enzyme activity. Our study demonstrates the potential of vetiver grass in treating nitrogen-rich wastewater from the munition industry and provides a baseline for future large-scale studies to optimize the technology. Full article

The dynamic mechanical properties and damage behaviors of polymer-bonded explosives (PBXs), as a kind of highly particle-filled polymer composite, must be known to ensure the safe use of related weapons and munitions. The high particle volume fraction of PBXs, which can reach approximately 95%, makes it difficult to investigate their mechanical properties and damage behavior via conventional methods. In this study, a microstructural model was developed by employing the Voronoi correction method to achieve a highly particle-filled PBX. Additionally, a bilinear model was used to accurately represent the nonlinearity of the stress–strain curve, while a zero-thickness cohesive zone model was incorporated to effectively describe the damage mechanism. The dynamic mechanical properties and damage behavior of PBXs with high particle fractions were elucidated to comprehensively understand the effects of strain rate, interface strength, and particle volume fraction on peak stress, failure strain, and damage extent. The numerical results exhibit excellent concurrence with existing experimental measurements and other computational simulations. The mechanical behavior of PBXs was also described by developing a viscoelastic model based on damage, which incorporated the equations associated with macroscopic and microscopic damage evolution. Overall, the proposed numerical technique is effective for comprehending the mechanical behavior and microscopic damage response of PBXs subjected to dynamic compression. Full article

Remediation of formerly used war zones requires knowledge of the depth of burial (DoB) of unexploded ordnances (UXOs). The DoB can vary greatly depending on soil and ballistic conditions, and their associated uncertainties. In this study, the well-known physics-based Poncelet equation is used to set a framework for stochastic prediction of the DoB of munitions in sandy, clayey sand, and clayey sediments using Monte Carlo simulations (MCSs). First, the coefficients of variation (COVs) of the empirical parameters affecting the model were computed, for the first time, from published experimental data. Second, the behavior of both normal and lognormal distributions was investigated and it was found that both distributions yielded comparable DoB predictions for COVs below 30%. However, a lognormal distribution was preferred, to avoid negative value sampling, since COVs of the studied parameters can easily exceed this threshold. Third, the performance of several MCS sampling techniques, including the Pseudorandom Generator (PRG), Latin Hypercube Sampling (LHS), and Gaussian Process Response Surface Method (GP_RSM), in predicting the DOB was explored. Different probabilistic sampling techniques produced similar DoB predictions for each soil type, but GP_RSM was the most computationally efficient method. Finally, a sensitivity analysis was conducted to determine the contribution of each random variable to the predicted DoB. Uncertainty of the density, drag coefficient, and bearing coefficient dominated the DoB in sandy soil, while uncertainty in the bearing coefficient controlled DoB in clayey sand soils. In clayey soil, all variables under various distribution conditions resulted in approximately identical predictions, with no single variable appearing to be dominant. It is recommended that Monte Carlo simulations using GP_RSM sampling from lognormally distributed effective variables be used for predicting DoB in soils with high COVs. Full article

Munition disposal practices have significant effects on microbial composition and overall soil health. Explosive soil contamination can disrupt microbial communities, leading to microbial abundance and richness changes. This study investigates the microbial diversity of soils and roots from sites with a history of ammunition disposal, aiming to identify organisms that may play a role in bioremediation. Soil and root samples were collected from two types of ammunition disposal (through open burning and open detonation) and unpolluted sites in Machachi, Ecuador, over two years (2022 and 2023). High-throughput sequencing of the 16S rRNA gene (for bacteria) and the ITS region (for fungi and plants) was conducted to obtain taxonomic profiles. There were significant variations in the composition of bacteria, fungi, and plant communities between polluted and unpolluted sites. Bacterial genera such as Pseudarthrobacter, Pseudomonas, and Rhizobium were more abundant in roots, while Candidatus Udaeobacter dominated unpolluted soils. Fungal classes Dothideomycetes and Sordariomycetes were prevalent across most samples, while Leotiomycetes and Agaricomycetes were also highly abundant in unpolluted samples. Plant-associated reads showed a higher abundance of Poa and Trifolium in root samples, particularly at contaminated sites, and Alchemilla, Vaccinium, and Hypericum were abundant in unpolluted sites. Alpha diversity analysis indicated that bacterial diversity was significantly higher in unpolluted root and soil samples, whereas fungal diversity was not significantly different among sites. Redundancy analysis of beta diversity showed that site, year, and sample type significantly influenced microbial community structure, with the site being the most influential factor. Differentially abundant microbial taxa, including bacteria such as Pseudarthrobacter and fungi such as Paraleptosphaeria and Talaromyces, may contribute to natural attenuation processes in explosive-contaminated soils. This research highlights the potential of certain microbial taxa to restore environments contaminated by explosives. Full article

Commonly found landmines, such as the TM-62M, MON-100, and PDM-1, in the recent Russia–Ukraine war confirm the continued use of metals in munitions. Traditional demining techniques, primarily relying on handheld metal detectors and Ground Penetrating Radar (GPR) systems, remain state of the art for subsurface detection. However, manual demining with handheld metal detectors can be slow and pose significant risks to operators. Drone-based metal detection techniques offer promising solutions for rapid and effective landmine detection, but their reliability and accuracy remain a concern, as even a single missed detection can be life-threatening. This study evaluates the potential of an airborne metal detection system as an alternative to traditional handheld detectors. A comparative analysis of three distinct metal detectors for landmine detection is presented: the EM61Lite, a sensitive airborne metal detection system (tested in a pseudo-drone-based scenario); the CTX 3030, a traditional handheld all-metal detector; and the ML 3S, a traditional handheld ferrous-only detector. The comparison focuses on the number of metallic targets each detector identifies in a controlled test field containing inert landmines and UXOs. Our findings highlight the strengths and limitations of airborne metal detection systems like the EM61Lite and emphasize the need for advanced processing techniques to facilitate their practical deployment. We demonstrate how our experimental normalization technique effectively identifies additional anomalies in airborne metal detector data, providing insights for improved detection methodologies. Full article

As a transportation hub, the girder bridge is often an important target for both sides in combat, and it is very important for wartime decision-making and subsequent fire planning to carry out assessment on the effect of the damage to the bridge after the fight. The use of images for target damage assessment is more secure and efficient compared with the traditional method of manual inspection. However, the current image-based damage assessment of girder bridges has the problems of neglecting the damage to bridge piers and the poor stability of the damage features. To address these issues, this paper proposes a functional damage assessment method for beam bridges after being hit by ammunition based on visible light images. This method decomposes the girder bridge into two main sub-targets (the abutment and deck), analyzes its functional characteristics, designs the residual bearing capacity of the bridge and the number of passable lanes in the damage features, proposes an algorithm for conversion from image features to damage features and a fusion algorithm for the damage features, and establishes the rules for the evaluation of the damage level accordingly. The MATLAB experiment verifies that the method is able to extract the residual bearing capacity and the number of passable lanes from the image of the post-fighting girder bridge and to obtain the damage assessment results, which provides a new method for the assessment of the effect of damage to girder bridges. Full article

The Cruising Unmanned Aerial Vehicle (CUAV) exemplifies an advanced system integrating UAV and munitions technology. The primary challenge lies in devising strategies to achieve precision strikes. Achieving precision strikes is a critical combat mission for CUAV and serves as the primary focus of this research. This paper introduces a three-loop pseudo-angle-of-attack acceleration autopilot design with proportional–integral (PI) correction, overcoming the limitations of existing two-loop and three-loop systems. The existing two-loop acceleration autopilot with PI correction suffers from low robustness, whereas the three-loop autopilot exhibits slow response to acceleration deviations. The proposed design overcomes these shortcomings by optimizing the autopilot for high-dynamic and fast-response scenarios. The design methodology leverages pole assignment, referencing the pole co-circle method and accommodating servo bandwidth limitations. A comparison of the designed three-loop acceleration autopilot with PI correction with other acceleration autopilots reveals superior accuracy advantages. The reliability and robustness of the proposed autopilot were validated through flight tests, achieving a drop point accuracy of less than 0.5 m. This study demonstrates the engineering application of a pseudo-angle-of-attack three-loop acceleration autopilot with PI correction, designed using the pole assignment method, on a short-range CUAV. Future efforts will focus on optimizing the autopilot to further enhance its adaptability and robustness. Full article

As an important civil and military infrastructure, airport runway pavement is faced with threats from cluster munitions, since it is vulnerable to projectile impacts with internal explosions. Aiming at the damage assessment of an island airport runway pavement under impact, this work dealt with discrete modeling of rigid projectile penetration into concrete pavement and the calcareous sand subgrade multi-layer structure. First, the Discrete Element Method (DEM) is introduced to model concrete and calcareous sand granular material features, like cohesive fracture and strain hardening due to compression, with mesoscale constitutive laws governing the normal and shear interactions between adjacent particles. Second, the subsequent DEM simulations of uniaxial and triaxial compression were performed to calibrate the DEM parameters for pavement concrete, as well as subgrade calcareous sand. Prior to the multi-layer structure investigations, penetration into sole concrete or calcareous sand is validated in terms of projectile deceleration and depth of penetration (DOP) with relative error ≤ 5.6% providing a reliable numerical tool for deep penetration damage assessments. Third, projectile penetration into the airport runway structure with concrete pavement and calcareous sand subgrade was evaluated with validated DEM model. Penetration numerical simulations with various projectile weight, pavement concrete thickness as well as striking velocity, were performed to achieve the DOP. Moreover, the back-propagation (BP) neural network proxy model was constructed to predict the airport runway penetration data with good agreement realizing rapid and robust DOP forecasting. Finally, the genetic algorithm was coupled with the proxy model to realize intelligent optimization of pavement penetration, whereby the critical velocity projectile just perforates concrete pavement indicating the severest subsequent munition explosion damage. Full article

A quantitative understanding of the migration of munitions and canonical objects in the nearshore is needed for the effective management of contaminated sites. Migrations of munitions with a density range of 2000 kg/m³ to 5720 kg/m³ were quantified in a large-scale wave flume. The forcing consisted of six cases of varying wave heights, periods, still water depths, and durations. The cross-shore profile, typical of natural sandy beaches, was sub-divided into swash, surf, and offshore zones. Overall, 2228 migration measurements were recorded with 16% and 84% of the migration observations classified as “motion” (net distance > 0.5 m) and “no motion” (net distance ≤ 0.5 m), respectively. The probability of munitions migration increased with proximity to the shoreline. There was a nearly equal probability of onshore or offshore migration in the swash zone. Migration in the surf zone tended to be offshore-directed (65%), while migration was onshore-dominant (65%) in the offshore zone. Migration in the offshore zone was preferentially onshore due to skewed waves over flat bathymetry. Less dense munitions in the offshore zone may have migrated offshore likely still related to the skewed nature of the wave profile causing transport in both directions through the majority of the wave phase. The largest migration distances occurred in the surf zone likely due to downslope gravity. Migration in the surf and swash zones is a balance between skewed/asymmetric forcing and downslope gravity, with downslope gravity tending to be pronounced provided the forcing is sufficient to initiate motion. An exception was sometimes observed in the swash zone where onshore forcing was sufficient to transport munitions to the seaward side of the berm where they became trapped in a bathymetric depression between the dune and berm. Relating overall migration (Lagrangian) to fixed hydrodynamic measurements (Eulerian) was ineffective. Parameters such as the Shields number, wave skewness, and wave asymmetry estimated from the closest measurement location were insufficient to predict migration. Large scatter in the migration data resulting from competing hydrodynamic, morphodynamic, and munitions response processes makes robust deterministic predictions with flow statistics and dimensionless numbers difficult. Full article

Nowadays, small UAV swarms with the capability of carrying inexpensive munitions have been highly effective in strike missions against ground targets on the battlefield. Effective task allocation is crucial for improving the overall operational effectiveness of these UAV swarms. Traditional heuristic methods for addressing the task allocation problem often rely on handcrafted rules, which may limit their performance for the complicated tasks. In this paper, a NeuroSelect Discrete Particle Swarm Optimization (NSDPSO) algorithm is presented for the Multi-UAV Task Allocation (MUTA) problem. Specifically, a Transformer-based model is proposed to learn design NeuroSelect Heuristic for DPSO to improve the evolutionary process. The iteration of DPSO is modeled as a decomposed Markov Decision Process (MDP), and a reinforcement learning algorithm is employed to train the network parameters. The simulation results are provided to verify the effectiveness of the proposed method. Full article

For the research on real-time accurate testing technology for the explosion point spatial coordinate of munitions, its currently commonly used methods such as acoustic–electric detection or high-speed imaging are limited by the field conditions, response rate, cost, and other factors. In this paper, a method of spatial coordinate testing for the explosion point based on a 2D PSD (position-sensitive detector) intersection is proposed, which has the advantages of a faster response, better real-time performance, and a lower cost. Firstly, a mathematical model of the spatial coordinate testing system was constructed, and an error propagation model for structural parameters was developed. The influence of the position of the optical axes’ intersection as well as the azimuth angle and pitch angle on the test accuracy of the system was simulated and analyzed, thus obtaining the distribution and variation trend of the overall error propagation coefficient of the system. Finally, experiments were designed to obtain the test error of the system for validation. The results show that the system test accuracy is high when the azimuth angle is 20°–50°, the overall error propagation coefficient does not exceed 48.80, and the average test error is 56.17 mm. When the pitch angle is −2.5°–2.5°, the system has a higher test accuracy, with the overall error propagation coefficient not exceeding 44.82, and the average test error is 41.87 mm. The test accuracy of the system is higher when the position of the optical axes’ intersection is chosen to make sure that explosion points fall in the region of the negative half-axis of the $Z_w$-axis of the world coordinate system, with an overall error propagation coefficient of less than 44.78 and an average test error of 73.38 mm. It is shown that a reasonable selection of system structure parameters can significantly improve the system test accuracy and optimize the system deployment mode under the long-distance field conditions so as to improve the deployment efficiency. Full article