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Objective: Aim: To explore the capabilities of the modern 3D modeling method for various elements of gunshot wounds caused by 9 mm caliber bullets, intending to integrate these findings into the theory and practice of forensic medicine., Patients and Methods: Materials and Methods: The research began with a series of experimental shots, during which the morphological features were examined through their 3D spatial reconstruction. The entire series of experimental shots was conducted using an automatic pistol IZH 70-01 equipped with 9.0 mm caliber bullets. The ballistic clay Roma Plastilina No.1, manufactured in the USA, was utilized as a material for conducting standard ballistic tests according to the standards of the NIJ (National Institute of Justice) and HOSDB (Home Office Scientific Development Branch)., Results: Results: The research was continued during the performance of forensic examinations involving actual cases of gunshot injuries. The dimensions of individual elements of the wound channel were measured in both experimental and expert cases using conventional measuring tools, as well as after their 3D modeling, utilizing graphic editors such as "Agisoft Photoscan" and "3ds max"., Conclusion: Conclusions: In the course of creating and studying experimental and expert 3D models, the dimensions of individual morphological elements of the wound channel were recorded with an accuracy that exceeded the results obtained through measurements using traditional measurement methods by ten times.

The full combustibility and strong discontinuity characteristics of module charge result in significant differences from conventional mode, making it challenging for traditional two-fluid methods to effectively reveal its particle dispersion mechanism. In this study, the particle element method for module charge were developed and applied for modeling the interior ballistics to overcome above drawback. Firstly, based on the characteristics of module charge and particle aggregation, criteria for dividing particle elements and methods for motion calculation are proposed. Next, particle element solver and CFD solver are constructed and mutually coupled for solution. Finally, validation is conducted under the condition of three modules charging. The computational results show that the particle element method can effectively predict the pressure and velocity inside the chamber, consistent with experimental results, the pressure error is 5.55 % and the velocity error is 0.79 %. The particle element method reproduces the combustion process with variable particle mass, accurately presenting the distribution of the flow field and temperature. Moreover, it fundamentally explains that pressure fluctuations occur due to the presence of free space and changes in the flow field caused by the movement of the propellant bed. The particle element method can provide scientific research methods and technical support for the development of module charge technology.

The large compositional space of high entropy alloys (HEA) often presents significant challenges in comprehensively deducing the critical influence of atomic composition on their mechanical responses. We propose an efficient nonparametric kernel-based probabilistic computational mapping to obtain the optimal composition of HEAs under ballistic conditions by exploiting the emerging capabilities of machine learning (ML) coupled with molecular-level simulations. Compared to conventional ML models, the present Gaussian approach is a Bayesian paradigm that can have several advantages, including small training datasets concerning computationally intensive simulations and the ability to provide uncertainty measurements of molecular dynamics simulations therein. The data-driven analysis reveals that a lower concentration of Ni with a higher concentration of Al leads to higher dissipation of kinetic energy and lower residual velocity, but with higher penetration depth of the projectile. To deal with such conflicting computationally intensive functional objectives, the ML-based simulation framework is further extended in conjunction with multi-objective genetic algorithm for identifying the critical elemental compositions to enhance kinetic energy dissipation with minimal penetration depth and residual velocity of the projectile simultaneously. The computational framework proposed here is generic in nature, and it can be extended to other HEAs with a range of non-aligned multi-physical property demands. [ABSTRACT FROM AUTHOR]

Machine learning (ML) is well suited for the prediction of high-complexity, high-dimensional problems such as those encountered in terminal ballistics. We evaluate the performance of four popular ML-based regression models, extreme gradient boosting (XGBoost), artificial neural network (ANN), support vector regression (SVR), and Gaussian process regression (GP), on two common terminal ballistics’ problems: (a) predicting the V50 ballistic limit of monolithic metallic armour impacted by small and medium calibre projectiles and fragments, and (b) predicting the depth to which a projectile will penetrate a target of semi-infinite thickness. To achieve this we utilise two datasets, each consisting of approximately 1000 samples, collated from public release sources. We demonstrate that all four model types provide similarly excellent agreement when interpolating within the training data and diverge when extrapolating outside this range. Although extrapolation is not advisable for ML-based regression models, for applications such as lethality/survivability analysis, such capability is required. To circumvent this, we implement expert knowledge and physics-based models via enforced monotonicity, as a Gaussian prior mean, and through a modified loss function. The physics-informed models demonstrate improved performance over both classical physics-based models and the basic ML regression models, providing an ability to accurately fit experimental data when it is available and then revert to the physics-based model when not. The resulting models demonstrate high levels of predictive accuracy over a very wide range of projectile types, target materials and thicknesses, and impact conditions significantly more diverse than that achievable from any existing analytical approach. Compared with numerical analysis tools such as finite element solvers the ML models run orders of magnitude faster. We provide some general guidelines throughout for the development, application, and reporting of ML models in terminal ballistics problems.

Stromboli is a volcanic island in a persistent state of activity, located off the northern coast of Sicily. The paroxysms have been the most powerful explosive phenomena at Stromboli in the last 150 years. These explosions can produce ballistic projectiles that can heavily affect trails and observation sites as well as hit inhabited areas at lower elevations, down to the coast. On July 3, 2019, a paroxysm significantly affected a great portion of the island with ballistic projectiles. In particular, many decimeter and meter-sized spatter bombs hit the W flank of Stromboli, and ignited multiple fires. In May 2022, we conducted an Unmanned Aerial System photogrammetric campaign over a sector of the W flank of Stromboli that was heavily affected by the paroxysm. The largest clasts were still preserved after 3 years, not disturbed by significant mass wasting phenomena or human interference, and they were not yet hidden by the post-fire regrowth of the brush vegetation. In this study, we constrained the main sources of uncertainty affecting the bombs distribution on the ground, by characterizing a percentage of uncertain clasts, testing various density estimators, and by modeling an areal buffer around the mapped clasts. We produced a 0.18 km2 wide 1.6-cm resolution orthomosaic, a 10-cm resolution Digital Surface Model, and 2813 outlines of the mapped ballistics. Spatial distribution of the ground cover and associated uncertainty were analyzed as a function of the distance and of the angular direction from the source. [ABSTRACT FROM AUTHOR]

Abstract The large compositional space of high entropy alloys (HEA) often presents significant challenges in comprehensively deducing the critical influence of atomic composition on their mechanical responses. We propose an efficient nonparametric kernel-based probabilistic computational mapping to obtain the optimal composition of HEAs under ballistic conditions by exploiting the emerging capabilities of machine learning (ML) coupled with molecular-level simulations. Compared to conventional ML models, the present Gaussian approach is a Bayesian paradigm that can have several advantages, including small training datasets concerning computationally intensive simulations and the ability to provide uncertainty measurements of molecular dynamics simulations therein. The data-driven analysis reveals that a lower concentration of Ni with a higher concentration of Al leads to higher dissipation of kinetic energy and lower residual velocity, but with higher penetration depth of the projectile. To deal with such conflicting computationally intensive functional objectives, the ML-based simulation framework is further extended in conjunction with multi-objective genetic algorithm for identifying the critical elemental compositions to enhance kinetic energy dissipation with minimal penetration depth and residual velocity of the projectile simultaneously. The computational framework proposed here is generic in nature, and it can be extended to other HEAs with a range of non-aligned multi-physical property demands.

Study of the engraving process is significant for interior ballistics. Due to the high transient and strong nonlinear characteristics of the engraving, research on the engraving mechanism is challenging. In this paper, based on the one-dimensional two-phase flow model of interior ballistics coupled with explicit dynamics software, finite element simulation of the engraving is carried out to obtain the changes of parameters during the engraving process, and the dynamic characteristics of the projectile engraving are discussed. By comparing the simulation results with the experimental data, the accuracy of the coupling method in this paper is verified. The relationship between the structural parameters of the sealing band and the extrusion resistance is revealed, and the influence of the extrusion resistance on the dynamic characteristics of the projectile is demonstrated. The simulation results can provide an essential reference for selecting a reasonable sealing band structure. [ABSTRACT FROM AUTHOR]

This study describes an effective protocol for naturalistic archaeological weapons experiments that improves cross-validation with controlled experiments and allows testing of multiple hypotheses. Stone-tipped atlatl darts and arrows were launched by skilled users against fresh carcasses, with high-speed cameras and radar guns capturing details of ballistic performance, impacts to bone and stone armatures, and other variables. The results pertaining to terminal ballistics in soft tissues are presented, with implications for what made ancient hunting projectiles effective and can be observed archaeologically. Fine-grained knappable stones seem to produce sharper armatures that can dramatically improve penetration, and presumably, lethality. Two commonly used metrics by archaeologists for estimating armature efficacy, tip cross-sectional area (TCSA), and perimeter (TCSP), are not among the significant variables for capturing penetration depth in soft tissues. However, armatures with larger TCSAs tend to be fitted to larger shafts that carry more energy and penetrate more deeply, providing one method for predicting wounding potential. The variability within weapon systems means that isolating efficacy to individual variables, such as tip cross-sectional size of stone armatures, can lead to erroneous interpretations.

Introduction. In accordance with the Polish law, pneumatic weapons are weapons that use compressed gas to set a bullet in motion and generate a discharge energy of more than 17J. In recent years, Poland has seen an increase in crimes committed with pneumatic weapons. The research aim of the present study was to measure the velocity of selected 5.5 mm and 6.35 mm caliber shot and to create a model of a human thigh using a pig femur. Material and methods. This study used Air Arms Hi-Power Xtra FAC cal. 5.5 mm and FX Bobcat Mk II cal. 6.35 mm carbines and Haendler& Natterman’s Spitzkugel, Hollow Point and Baracuda cal. 5.5 mm and 6.35 mm lead shot and Excite Apollo cal. 5.5 mm and Black Max Lead-Free cal. 6.35 mm lead-free shot. The velocity of the shot at a distance of 10 m was measured and its kinetic energy was calculated; pig femurs were measured and CT imaging was performed. Results. The 5.5mm caliber shot reached velocities between 253 m/s and 278 m/s, obtaining energies between 27J and 44J. The 6.35 mm cal. shot reached velocities between 242 m/s and 254 m/s and energies between 52J and 59J. Pig femurs had an average weight of 410 g, a length of 239 mm, and a shaft diameter at mid-length of 30.6mm. The thickness of pig femur shaft walls was variable. A ballistic model of the human thigh was created using gelatin available in Poland. Conclusions: 1. The number of registered crimes with pneumatic weapons and the wide access to pneumatic devices with the possibility of design modifications justify the initiation of experimental studies on the assessment of gunshot injuries from pneumatic weapons. 2. The parameters of the shaft of a pig femur obtained from pigs weighing about 115 kg are similar to those of a human adult femur, which makes it possible to create a human thigh model. 3. Of the 5.5 mm cal. shot, the highest impact energies were generated by barracuda type shot, and of the 6.35 mm cal. shot, it was barracuda type and lead-free shot. 4. The thickness of the bony layer of the pig femur shaft is heterogeneous; the posterior wall of the shaft is the thickest, the lateral wall is the thinnest; however, it shows the greatest individual variability.

The use of ordnance gelatine has been widespread in the field of ballistics as a simulant for soft tissue when assessing ballistic threats. However, the traditional method of preparing ordnance gelatine is time-consuming and requires precision to ensure that the final mold meets the required specifications. Furthermore, temperature control is necessary post-production, and there are limitations on its usage duration. To address these issues, manufacturers have developed pre-mixed, gelatine-like products that are stable at room temperature and require less preparation time. Nonetheless, it is uncertain whether these new products can perform in the same manner as the gold standard of ordnance gelatine. This study used five types of blocks, including ordnance gelatine (10% and 20%), Clear Ballistics (10% and 20%) and Perma-Gel (10%) and subjected them to 9 mm, 0.380 Auto fired from a universal receiver and a 5.56 × 45 mm ammunition fired by a certified firearms instructor. Delta-V and total energy dissipation were measured after each test using data collected from ballistic chronographs placed in front of and behind each block. High-speed video was recorded, and a cut-down analysis conducted. The findings revealed variations in energy dissipation and fissure formation within the block, with greater energy based on fissure formation observed in the ordnance gelatine. Additionally, the high-speed video showed the occurrence of secondary combustions occurring in the premixed gelatines., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The study examines the results of numerical simulations of the penetration of a 7,62mm x 63, AP, M2 projectile through a target. Model validation involved a numerical simulation of 7,62mm x 63, AP, M2 projectile penetration through an AA5083H116 target, for which experimental results were available in the literature. The results of the numerical simulation were used for regression analysis - to calibrate the Recht-Ipson model for the given projectile. Furthermore, penetration analyses of 7,62mm x 63, AP, M2 projectiles through various target materials were performed at consistent projectile velocities and mesh sizes. As expected, bainitic steels exhibited the highest resilience, demonstrating that increased material hardness and tensile strength correlate with enhanced projectile penetration resistance.

A detailed mapping of volcanic ballistic projectiles emplaced in a defined area, represents the starting point to derive preparatory data in hazard and risk studies of ballistics phenomena. Considering as case study the 3rd July 2019 paroxysmal eruption occurred at Stromboli volcano, we map and analyse at very high spatial resolution (8 cm) the distribution of the ballistic spatter clasts emplaced on the E flank of the volcano. The resulting map identifies and reproduces as geospatial polygon elements 152,228 spatter clasts with areal dimensions from 0.03 to 4.23 m2. Dispersed on 0.407 km2, the spatters cover an area of 29,000 m2 corresponding to an erupted products volume from 2.3 to 7.0 × 103 m3, calculated here for the first time. Spatial analyses indicate that the area mostly affected by the clasts emplacement is between N67.5 and N135 directions, identifying a preferential deposition between N112.50 and N123.75 directions. The clasts size distribution rapidly decreases with the size increase, highlighting a nearly constant ratio small/large clasts regardless the distance from the vent. Finally, additional investigations reveal that clasts dispersion parameters decrease progressively with the distance from the vent only along one direction (N67.5), highlighting how the morphology influences the deposition and remobilisation of mapped ballistics. [ABSTRACT FROM AUTHOR]

Ballistic wounds, which historically concerned military populations, now also affect civilian practice. Terrorist attacks, urban violence and certain accidents have brought them into the daily routine of some French hospitals. Their frequency fully justifies the need for every health-care professional to be aware of the major issues involved in their management. In this section, we will describe the various penetrating ballistic wounds and their specific features. We will also rectify certain preconceived ideas that should not be peddled by healthcare professionals, in order to maintain a high standard of care., (Copyright © 2023 Elsevier Masson SAS. All rights reserved.)