ABSTRACT
While injuries sustained from body armour backface deformation (BFD) have not been well-documented in military injury trauma registries, data from US law enforcement officers, animal tests and currently available data pertaining to military combatants has shown that BFD can not only cause minor injuries, but also result in serious trauma. However, the nature and severity of injuries sustained depends on a multitude of factors including the projectile type, the impact location and velocity, and the specific type of body armour worn. The difficulties involved in current measurement techniques for ballistic testing has led researchers to seek alternative techniques to evaluate the level of protection from body armour, such as the finite element (FE) method. In the current study, a systematic review of the open literature was undertaken using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology. The aim was to summarise the literature pertaining to the development and application of FE models to investigate body armour BFD and behind armour blunt trauma (BABT), and included FE models representing the projectile, clay-based mediums, ballistic gelatine and the human torso. Using the keywords 'behind armour*', 'ballistic blunt trauma', 'BABT', 'backface signature', 'backface deformation', 'BFS', 'BFD', 'wound ballistic', 'ballistic impact testing', 'body armour', 'bullet proof vest', 'ballistic vest', 'Finite Element*' and 'FE', an electronic database search of EBSCOhost, Google Scholar, ProQuest, Scopus, Standards, Web of Science and PubMed was conducted, and included peer-reviewed journal articles, review papers, research reports, conference papers, and MSc or PhD theses. While this research demonstrates the potential of FE analysis for recreating realistic blunt impact scenarios and enhancing the current understanding of BABT mechanisms, a common limitation in most studies is the lack of validation. Thus, in order to address this issue, it is proposed that injury predictions from FE models be correlated with trauma data from soldiers who have sustained BABT. Consequently, pressure and energy distributions within the organs can be used to interpret the effects of non-penetrating ballistic impacts on the human torso. Bridging the gap between simulation and real-world data is essential in order to validate FE models and enhance their utility in optimising body armour design and employing injury mitigation strategies.
ABSTRACT
In light of the COVID-19 pandemic, it is becoming extremely necessary to assess respiratory disease transmission in passenger cars. This study numerically investigated the human respiration activities' effects, such as breathing and speaking, on the transport characteristics of respiratory-induced contaminants in passenger car. The main objective of the present study is to accurately predict when and who will get infected by coronavirus while sharing a passenger car with a patient of COVID-19 or similar viruses. To achieve this goal, transient simulations were conducted in passenger car. We conducted a 3D computational fluid dynamics (CFD)-based investigation of indoor airflow and the associated aerosol transport in a passenger car. The Eulerian-Eulerian flow model coupled with k-ε turbulence approach was used to track respiratory contaminants with diameter ≥ 1 µm that were released by different passengers within the passenger car. The results showed that around 6.38 min, this is all that you need to get infected with COVID-19 when sharing a poorly ventilated car with a driver who got coronavirus. It also has been found that enhancing the ventilation system of the passenger car will reduce the risk of contracting Coronavirus. The predicted results could be useful for future engineering studies aimed at designing public transport and passenger cars to face the spread of droplets that may be contaminated with pathogens.
