Defense Applications Research Articles

Mechanical and Ballistic Properties of Epoxy Composites Reinforced with Babassu Fibers (Attalea speciosa).

The mechanical and ballistic performance of epoxy matrix composites reinforced with 10, 20, and 30 vol.% of babassu fibers was investigated for the first time. The tests included tension, impact, and ballistic testing with 0.22 caliber ammunition. The results showed an improvement in tensile strength, elastic modulus, and elongation with the addition of babassu fiber, and the 30 vol.% composite stood out. Scanning electron microscopy analysis revealed the fracture modes of the composites, highlighting brittle fractures in the epoxy matrix, as well as other mechanisms such as fiber breakage and delamination in the fiber composites. Izod impact tests also showed improvement with increasing babassu fiber content. In ballistic tests, there was an increase in absorbed energy. All composites surpassed plain epoxy by over 3.5 times in ballistic energy absorption, underscoring the potential of babassu fiber in engineering and defense applications.

Microstructure transformations and improving wear resistance of austenitic stainless steel additively fabricated by arc-based DED process

In this study, austenitic stainless steel (ASS) was additively fabricated by an arc-based direct energy deposition (DED) technique. Macrostructure, microstructure, mechanical characteristics at different spatial orientations (0°, 90°, and 45°), and wear characteristics were evaluated at the deposited structure top, middle, and bottom regions. Results show that austenite (γ) and delta-ferrite (δ) phases make up most of the microstructure of additively fabricated SS316LSi steel. Within γ matrix, δ phase is dispersed both (within and along) grain boundaries, exhibiting a fine vermicular morphology. The bottom, middle, and top regions of WAAM deposited ASS exhibit similar values to those of wrought SS316L in the tensile and impact test findings. Notably, a drop in hardness values is observed as build height increases. During SEM examinations of fractured surfaces from tensile specimen, closed dimples were observed, indicating good ductility of as-built structure. Wear test findings show signs of mild oxidation and usual adhesive wear. By depositing a mechanically mixed composite layer, an increase in the oxidation percentage was discovered to facilitate healing of worn surfaces. The findings of this study will help in design, production and renovation of products/components that are prone to wear. WAAM-deposited ASS has remarkable strength and ability to withstand impacts; it can be used in the production of armour plates for defence applications, mainly military vehicles and aircraft.

Using resonant ultrasound spectroscopy to characterize thermally conditioned high explosive materials

The ability to nondestructively quantify changes in mechanical properties of granular high explosive materials due to thermal conditioning is of importance for a myriad of civil and defense applications and could lead to better understanding of environmental aging-related effects for explosive material performance and safety. In this study, we report the first demonstration of using resonant ultrasound spectroscopy (RUS) to quantify the bulk elastic properties of granular high explosive materials at different bulk pressing densities and degree of thermal conditioning. Monitoring elastic property changes in granular explosive pressings has not yet been demonstrated using RUS, which is an appealing nondestructive characterization tool since it requires only dry point contact with the explosive material and can be applied to explosives with small form factors. Here, explosive material was studied in the form of binderized plastic bonded explosive pressings and unbinderized neat pressings, both of which are used commercially. Elastic stiffness coefficients calculated from the RUS measurements on the binderized and neat pressings show a significant increase for the post-conditioned samples compared to the pre-conditioned samples. This trend of increasing elastic properties with thermal conditioning was consistent for different density pressings and different thermal exposure conditions. [This work was performed by LLNL under Contract No. DE-AC52-07NA27344 and document release number LLNL-ABS-858868.]

Power characteristics of a high-performance helix traveling wave tube

Traveling Wave Tubes (TWT) are most widely used in civil, defense, and space applications as power amplifiers over a wide range of frequency. When a TWT works at a higher bandwidth, it suffers from nonlinearities, which affects the overall performance of the tube and hence the required results aren't achieved. So, optimization of a TWT is required, mainly in terms of its power characteristics. Power characteristics of the TWTs are specified in terms of output power at different input drive levels, AM/PM transfer and AM/PM conversions, input, and output back-off, gain at saturation, etc. Some of the linearity factors like 3rd order inter modulation product (IMP), and the 1 dB compression point are also optimized. An exhaustive study has been made to achieve the optimum performance of a 140W TWT in Ku-Band. The result has been validated by experimental results.

Swarm intention identification via dynamic distribution probability image

In the realm of decision-making for defense and security applications, it is paramount to swiftly and accurately identify the intentions of incoming swarms. Conventional identification methods predominantly focus on single-target applications and overlook the perturbations introduced by measurement noise. In this study, we propose a novel concept: the Dynamic Distribution Probability (DDP) image, which is constructed using the estimated state and its covariance matrix. Each grayscale pixel value within the image signifies the probability of the presence of the agent within the swarm. Our proposed identification scheme integrates the use of Extended Kalman Filter (EKF), Convolutional Neural Network (CNN), Back Propagation (BP) network, and Gated Recurrent Unit (GRU) network. Specifically, the DDP image is processed through a CNN to distill the formation characteristics, and the estimated swarm state from EKF is inputted into a BP network to deduce the kinematic information. The outputs from both networks are summed and subsequently channeled into a GRU network to capture temporal dynamics. Extensive numerical simulations and flight experiments are presented to demonstrate the robust anti-noise capability of the proposed scheme compared with conventional methods, as well as its superior training efficiency.

Real-Time Scalable System For Face Tracking In Multi-Camera

Face detection and tracking have become increasingly popular in recent years. It has critical importance in security, defense, and robotics applications uses encountered in everyday life. For this purpose, many decision support or expert systems have been developed using artificial intelligence and machine learning. Thanks to the developments in the field of deep learning and hardware many effective and reliable face tracking systems have been realized. However there are still very few real-time scalable end-to-end systems. Also, the realization of this system on multiple cameras is a real challenge. In this study, a real-time, multi-camera, deep learning-based face tracking system has been developed. In the realized system, SCRFD model is used for face detection, ArcFace model is used for face recognition, and an updated DeepSORT algorithm is used for more stable face tracking. In addition, Apache Kafka stream processing system and Socket.IO bidirectional communication library were used to process multi-camera data in real-time and scalable. In the proposed system, when an image is input into the system, it can be displayed on the web page after approximately 127 ms

Smart Fabric Textiles Using Nanomaterials: A Contemporary Overview

Recent years have witnessed the pivotal role of nanotechnology in shaping the landscape of smart fabric design. Nanomaterials have emerged as integral components, introducing sustainable attributes such as antimicrobial, ultraviolet resistant, electrically conductive, optical, hydrophobic, and flame-retardant properties into textiles and garments. The integration of nanomaterial-based smart devices into textiles has further expanded functionalities, encompassing energy harvesting and storage, sensing, drug release, and optics. Beyond the fashion industry, these advancements hold promise for applications in defense, healthcare, and on-body energy harnessing. This review aims to provide a comprehensive overview of the current trends in utilizing nanotechnology within modern textile industries, serving as both an informative resource and a catalyst for future research endeavors. Focusing on on-body electronics, the review delves into the potential of nanomaterials in achieving total energy reliance through innovative textile applications. Key scientific concepts explored include methods for nanomaterial functionalization and integration into textiles, with a keen emphasis on cost-effectiveness, comfort, wearability, energy conversion efficiency, and eco-sustainability. Recent developments are in nanogenerators, super capacitors, and photo electronic devices integrated into fabrics, with a specific focus on their efficiency and wearability. The discussion extends to possible remediation measures. Finally, the paper outlines the future outlook, envisioning further progress in the integration of smart nano-devices onto textile fabrics.

Reliable Solder Columns to Replace Solder Balls in Large 2.5D Heterogeneous Packages

Solder balls are well suited for interconnecting normal sized ball grid array (BGA) components to printed circuit boards (PCB). However, solder balls are prone to cracking (failure) caused by excessive stresses inherently found in advanced packaging such as large-sized heterogeneous 2.5D packages where multiple dies are placed side-by-side. The growth trend is to make larger and larger BGA processors exceeding 60x60mm in size for AI and data centers. A plethora of new processor substrate and interposer designs are coming on line such as Chip-on-Wafer-on-Substrates (CoWoS). For that reason, more instances of solder ball delamination and cracking on large-sized BGA packages are probable. Solder columns were produced more than 50 years ago to reduce cracking in large ceramic packages, especially for use in harsh environments found in aerospace and defense applications. However, such legacy solder column technology is limited to Tin-Lead (SnPb) alloys. The challenge is to make Lead Free solder columns that satisfy demand for RoHS compliance, while still providing adequate stress relief (compliancy) for extending the operational life of large sized heterogeneous 2.5D processors for mission critical applications. This paper describes our ongoing work to innovate non-collapsible, compliant Lead-Free Braided Copper Solder Columns to reduce strain caused by the Coefficient of Thermal Expansion (CTE) mismatch between large BGA packages and FR4 PCBs. A braid, consisting of 16 fine copper alloy wires, serves as an exoskeleton sleeve around a solder column to provide mechanical support as well as compliancy. This novel solder column technology supports market trends to scale up the size of chip packaging while maintaining reliability. Our focus was to quickly characterize Lead-Free solder column core materials and braiding alloys by employing “Fail-Fast” destructive accelerated mechanical bend testing in our lab. Since there is an ongoing interest in Tin-Lead alloys, this paper also discusses data on Tin-Lead alloys for comparative purposes.

Reliability Prediction of Radiation Induced Failures in Semiconductor Packages

The growth and usage of semiconductor components has risen greatly due to evolution of applications in industries such as aerospace, defense, and automotive, in both the commercial and government sectors. Among the different types of components that make their way into such applications, digital logic and memory-based devices are of prime importance due to the ever-demanding need to store and compute vast amounts of data. This brings to the forefront the reliability of such components, especially in demanding applications in aerospace and defense where components are exposed to extremely harsh environments where high performance is critical. This is where we find that reliability is largely dependent on the susceptibility of semiconductor components to radiation induced effects - total ionizing dose (TID) and single event effects (SEE). Optimization in design, process, and packaging could make microelectronics more reliable to the radiation effects. Packaging material and thickness affect the incident flux of radiation on microelectronics and can help mitigate both dose and SEE effects in electronics. Additionally, packaging materials should not generate a high flux of secondary particles when exposed to environmental radiation (an example is alpha emissions from impurities in package mold compound or underfill). In this paper, the behavior of semiconductors at the component level due to radiation effects is evaluated. A reduced order model approach is presented where the analysis is performed at the functional block level then aggregated into component. The behavioral model can be used to predict the behavior across different operating, design, and process conditions.

Particle Swarm Optimization of Multilayer Multi-Sized Metamaterial Absorber for Long-Wave Infrared Polarimetric Imaging.

Infrared polarization imaging holds significant promise for enhancing target recognition in both civil and defense applications. The Division of Focal Plane (DoFP) scheme has emerged as a leading technology in the field of infrared polarization imaging due to its compact design and absence of moving parts. However, traditional DoFP solutions primarily rely on micro-polarizer arrays, necessitating precise alignment with the focal plane array and leading to challenges in alignment and the introduction of optical crosstalk. Recent research has sought to augment the performance of infrared detectors and enable polarization and spectral selection by integrating metamaterial absorbers with the pixels of the detector. Nevertheless, the results reported so far exhibit shortcomings, including low polarization absorption rates and inadequate polarization extinction ratios. Furthermore, there is a need for a comprehensive figure of merit to systematically assess the performance of polarization-selective thermal detectors. In this study, we employ the particle swarm optimization algorithm to present a multilayer, multi-sized metamaterial absorber capable of achieving a remarkable polarization-selective absorption rate of up to 87.2% across the 8-14 μm spectral range. Moreover, we attain a polarization extinction ratio of 38.51. To elucidate and predict the resonant wavelengths of the structure, we propose a modified equivalent circuit model. Our analysis employs optical impedance matching to unveil the underlying mechanisms responsible for the high absorption. We also introduce a comprehensive figure of merit to assess the efficacy of infrared polarization detection through the integration of metamaterials with microbolometers. Finally, drawing on the proposed figure of merit, we suggest future directions for improving integrated metamaterial absorber designs, with the potential to advance practical mid-infrared polarization imaging technologies.

Detection and Prevention of Cyber Defense Attacks using Machine Learning Algorithms

Recent advancements in computing power, memory capacities, and connectivity have led to a corresponding surge in the utilization of big data, online platforms' prevalence, and machine learning's sophistication. Concerns regarding safety and the need for state-of-the-art security tools and methods to counter evolving cybercrime are amplified by the swift digitization of the world. This study investigates defensive and offensive applications of machine learning in cybersecurity. Additionally, it explores potential strategies to mitigate cyberattacks on machine learning models. The focus is on how machine learning facilitates cyberattacks, including developing intelligent botnets, advanced phishing using spear techniques, and deploying stealthy malware. Furthermore, the paper highlights the significance of artificial intelligence in digital safety, emphasizing its role in malware analysis, network vulnerability assessment, and threat prediction.

Rigorous Reliability Testing of an Encapsulated Thermal Pyrolytic Graphite (TPG) Heat Spreader for Passive Thermal Management Applications

Continued microelectronic miniaturization has resulted in higher power density, increasing the need for high performance thermal management. One possible solution for board-level thermal management is to fully encapsulate a high thermal conductivity material, such as Thermal Pyrolytic Graphite (TPG; ~1700 W/mK) in a metal (such as 6061 aluminum), producing an efficient passive heat spreader for thermal dissipation. The metal shell provides sufficient mechanical strength at a small detriment to the overall thermal conductivity. Reliability and consistent performance over time are critical for thermal management systems, especially in Defense and Aerospace applications. MIL-STD-883H provides test parameters for reliability involving exposure to mechanical shock (Method 2002.5), mechanical vibration (Method 2005.2), and thermal shock (Method 1011.9), with traditional evaluation criteria involving microelectronic device performance and/or a visual examination. For this work, the reliability of aluminum encapsulated TPG test coupons was evaluated with more demanding criteria: a visual examination, X-ray inspection, acoustic microscopy, and thermal conductivity performance testing, both before and after the previously discussed MIL-STD-883H exposures. The encapsulated coupons showed excellent robustness; the thermal conductivity properties remained constant with an average value around 965 W/mK, and the non-destructive imaging revealed excellent bond quality for the metal encapsulation, with no evidence of delamination. This more stringent evaluation criteria after MIL-STD-883H testing provides a better way to evaluate the reliability of passive thermal management systems. The study results also demonstrate the metal encapsulated TPG heat spreader as a superior thermal management solution with high performance and high reliability for demanding applications.

Biosignal-integrated robotic systems with emerging trends in visual interfaces: A systematic review.

Human-machine interfaces (HMI) are currently a trendy and rapidly expanding area of research. Interestingly, the human user does not readily observe the interface between humans and machines. Instead, interactions between the machine and electrical signals from the user's body are obscured by complex control algorithms. The result is effectively a one-way street, wherein data is only transmitted from human to machine. Thus, a gap remains in the literature: how can information be effectively conveyed to the user to enable mutual understanding between humans and machines? Here, this paper reviews recent advancements in biosignal-integrated wearable robotics, with a particular emphasis on "visualization"-the presentation of relevant data, statistics, and visual feedback to the user. This review article covers various signals of interest, such as electroencephalograms and electromyograms, and explores novel sensor architectures and key materials. Recent developments in wearable robotics are examined from control and mechanical design perspectives. Additionally, we discuss current visualization methods and outline the field's future direction. While much of the HMI field focuses on biomedical and healthcare applications, such as rehabilitation of spinal cord injury and stroke patients, this paper also covers less common applications in manufacturing, defense, and other domains.

A Review on Security Frameworks for Software Defined Networks

The internet of thins (IoT) framework has helped in design of high speed connected networks which include Wide Area Networks (WANs). Cognitive Radio can be considered to be one of the key enablers of high speed data transfer with evolving generation of wireless networks. Cognitive networks find their applications in military and defence as well with the advent of internet of things and its allied applications in military warfare. Cognitive Radio Networks often share common resources such as bandwidth or spectrum among several users or stations. Due to continued sharing of resources, cognitive networks often come under security attacks, most common of which are jamming and eavesdropping attacks. In this paper, the basics of cognitive IoT networks have been presented with the focus of security aware cognitive IoT networks. Previous work in the allied domain has been discussed along with their salient features. Keywords: Wide Area Network (WAN), Internet of Things (IoT), cognitive radio network (CRN), security aware spectrum assignment, cyber-attacks, false alarm, and throughput.

Series-Hybrid Powertrains: Advancing Mobility Control in Electric Tracked Vehicle Technology

This work focuses on developing a mobility control system for high-speed series-hybrid electric tracked vehicles, which operate with independent traction motors for each track. The scope of this research includes modeling a series-hybrid powertrain specific to military tracked vehicles and conducting an in-depth analysis of its dynamic behavior. Subsequently, this study conducts a critical review of mobility control approaches sourced from the literature, identifying key techniques relevant to high-inertia vehicular applications. Building on foundational models, this study proposes a robust closed-loop mobility control system aimed at ensuring precise and stable off-road vehicle operations. The system’s resilience and adaptability to a variety of driving conditions are emphasized, with a particular focus on handling maneuvers such as steering and pivoting, which are challenging operations for tracked vehicle agility. The performance of the proposed mobility control system is tested through a series of simulations, covering a spectrum of operational scenarios. These tests are conducted in both offline simulation settings, which permit meticulous fine-tuning of system parameters, and real-time environments that replicate actual field conditions. The simulation results demonstrate the system’s capacity to improve the vehicular response and highlight its potential impact on future designs of mobility control systems for the heavy-duty vehicle sector, particularly in defense applications.

A Wideband Circularly Polarized All Textile on Body Antenna for Defense Applications

A Wideband Circularly Polarized All Textile on Body Antenna for Defense Applications

Nuclear resilient and redundant compute and communication integrated network

Future communication networks use computing platforms i.e., data centers for enabling content access. The operation of data centers is evolving to meet new requirements such as reducing the operating cost. The use of data centers is recognized to have significant challenges due to high operating costs. The high operating costs arises due to the necessity of data center cooling. The cooling costs can be reduced by siting data centers in the underwater environment. In the underwater environment, data centers are cooled by freely available cold water. However, siting data centers in the underwater environment exposes them to risk from other underwater applications. The use of underwater data centers is susceptible to service loss due to the launch of missiles from submarines in defense applications. Underwater data centers are susceptible to service loss from the launch of missiles from submarines. Hence, it is necessary to design a network architecture that ensures continued service delivery when nuclear attacks occur. The presented research proposes a novel network architecture enabling service continuity in the underwater data center. The proposed architecture incorporates resiliency and comprises terrestrial and non–terrestrial data centers. The proposed network architecture incorporates redundancy and utilizes terrestrial and non-terrestrial data centers. In addition, the research presents a protocol enabling co-existence between underwater data centers and missile launching submarines used in defence applications. The research formulates and evaluates the operational duration, number of packets forwarding paths, and computing resource utilization as the metrics. Performance evaluation shows that the proposed network architecture improves the operational duration and computing resource utilization by an average of (27.7–71.5)% and (23.5–44.2)%, respectively. Furthermore, the proposed network architecture enables the realization of more resilient paths. The use of more resilient paths enhances packet transmission. Evaluation shows that the proposed network architecture enhances the number of resilient packets forwarding paths by (18.2–57.4)% on average.

A customized drone for ocean and atmospheric measurements and its performances

Drones- Unmanned Aerial vehicles (UAVs)- have become more significant across the world for a wide range of commercial and terrestrial defense applications in recent years. The National Institute of Ocean Technology (NIOT)- Ministry of Earth Sciences (MOES)- is exploring UAVs with a specific focus on maritime applications. NIOT has customized a heavy lift category drone, operable in marine environments and capable of withstanding coastal wind conditions of up to 40 kmph. It can lift and carry an instrumentation payload of 10 kg, conduct ocean data collection, and even take seawater samplings. The 10 kg payload of the UAV might hold a Conductivity Temperature Depth (CTD) sensor, a programmable sea water sampler, and a multi-parameter sensor (MPS) for ocean data collections, and a Light Detection and Ranging (LiDAR) device integrated with a high frame rate camera system for coastal mapping and digital elevation model (DEM) developmental applications. The customized hexacopter UAV is capable of withstanding winds of up to 10 m/s and features a waterproof IPX7 thruster with a maximum thrust of 153 N per axis. The UAV system is also interfaced with a Global Positioning System (GPS), a barometric pressure sensor, a compass, a highly accurate gyroscope, a 15 MP surveillance camera, and an accelerometer sensor connected to a reliable cube orange flight controller module with a redundant 32-bit controller through a serial peripheral interface (SPI). The drone structure and frame is composed of carbon fiber composites to provide an excellent weight-to-strength ratio. This paper presents the outcomes of an initial field test, carried out to ensure the drone’s suitability for various marine applications with intended payloads ranging from 5 - 10 kg weight, including coastal demonstrations and ocean data collections performed at Nellore (Andra Pradesh) and Chennai (Tamil Nadu) coastal waters. Highlights A drone is customised to with stand elevated wind conditions of coastal regions Design is fully flexible meeting the ease of transport from one location to other Highly stable mechanical design to sustain winds of up to 45 KMPH Redundant flight control mechanism is evolved to assure fail safe operations of drone Drone built in with redundant GPS module to avoid scenario like NO Geo-reference at any time Design is type certified and UIN registered with DGCA - India

Coupling effects of dielectric loss in N-doped carbon double-shelled hollow particles for high-performance microwave absorption

Microwave absorbing materials with lightweight and high-performance are of great significance for electronic technique, ecological environment and defense applications. The hollow structure of carbon microspheres is beneficial to achievement of high-performance microwave absorption due to high interfacial polarization. However, the key characteristic is still unclear to control interfacial polarization. Herein, double-shelled N-doped carbon hollow particles derived from polypyrrole by self-sacrifice template were synthesized. The polymerization process was controlled by the interface between solid and pyrrole acid liquid in Fe3O4 disperse system, subsequently, micro-nano structure of carbon was tuned. The N-doped carbon double-shelled hollow particles (DSHS) show a strong dielectric loss due to coupling effect of resistance loss and interfacial polarization owing to the double-shelled hollow structure. Thus, DSHS shows a high-performance microwave absorption with minimum reflection loss (RLmin) of −75.10 dB at a thickness of 2.48 mm and effective absorption bandwidth (RL ≤ -10 dB) of 6.08 GHz and 4.05 GHz covering the whole Ku band and almost the whole X with a thickness of 2.21 mm and 3.00 mm, respectively. This work provides a simple approach for synthesizing N-doped carbon particles with distinct micro-nano hierarchical structure, double-shelled hollow microspheres assembled by nanoparticles have potential application as a high-performance MAM.

Demonstrating resonant ultrasound spectroscopy as a viable technique to characterize thermally conditioned high explosive materials

We present results of resonant ultrasound spectroscopy (RUS) measurements applied to granular high explosive materials at different bulk pressing densities and degree of thermal conditioning. The material chosen in this study is a ubiquitously used explosive material known as pentaerythritol tetranitrate (PETN), which is used commercially in civil and defense applications both as a binderized plastic bonded explosive material and an unbinderized neat material. However, changes in granular PETN bulk elastic properties due to thermal conditioning, which could have implications for better understanding environmental aging-related effects, have not been well studied even though it is believed that elasticity may play an important role in explosive material initiation mechanisms. Furthermore, monitoring elastic property changes in granular explosive pressings has not yet been demonstrated using RUS, which is an appealing non-destructive characterization tool that requires only dry point contact with the explosive material. To this end, we report the first study using RUS to quantify the elastic properties of binderized and neat PETN pressings as well as to quantify changes in elastic properties as a function of both thermal conditioning and bulk pressing density. Elastic stiffness coefficients, sometimes more commonly referred to as elastic constants, calculated from the RUS measurements on the different PETN-based materials show a significant increase for the post-conditioned samples compared to the pre-conditioned samples. This trend of increasing elastic properties with thermal conditioning was consistent for different density pressings, different thermal exposure conditions, and even different neat PETN pressings of differing average crystal sizes and/or specific surface areas.