Modeling of advanced combat helmet under ballistic impact

The use of combat helmets has greatly reduced penetrating injuries and saved lives of many soldiers. However, behind helmet blunt trauma (BHBT) has emerged as a serious injury type experienced by soldiers in battlefields. BHBT results from nonpenetrating ballistic impacts and is often associated with helmet back face deformation (BFD). In the current study, a finite element-based computational model is developed for simulating the ballistic performance of the Advanced Combat Helmet (ACH), which is validated against the experimental data obtained at the Army Research Laboratory. Both the maximum value and time history of the BFD are considered, unlike existing studies focusing on the maximum BFD only. The simulation results show that the maximum BFD, the time history of the BFD, and the shape and size of the effective area of the helmet shell agree fairly well with the experimental findings. In addition, it is found that ballistic impacts on the helmet at different locations and in different directions result in different BFD values. The largest BFD value is obtained for a frontal impact, which is followed by that for a crown impact and then by that for a lateral impact. Also, the BFD value is seen to decrease as the oblique impact angle decreases. Furthermore, helmets of four different sizes - extra large, large, medium, and small - are simulated and compared. It is shown that at the same bullet impact velocity the small-size helmet has the largest BFD, which is followed by the medium-size helmet, then by the large-size helmet, and finally by the extra large-size helmet. Moreover, ballistic impact simulations are performed for an ACH placed on a ballistic dummy head form embedded with clay as specified in the current ACH testing standard by using the validated helmet model. It is observed that the BFD values as recorded by the clay in the head form are in good agreement with the experimental data.QC 20151130</p

AlGaN-based MQWs grown on a thick relaxed AlGaN buffer on AlN templates emitting at 285 nm

International audienceWe report on the growth of Al 0.57 Ga 0.43 N/Al 0.38 Ga 0.63 N MQWs grown on a relaxed Al 0.58 Ga 0.42 N buffer on AlN template by Metal Organic Vapor Phase Epitaxy. The MQW structure is designed so that the strain in the quantum wells induced by their lattice mismatch with barriers is sufficient to enhance TE polarized emission (E-field ⊥ c). A 630-nm thick relaxed Al 0.58 Ga 0.42 N buffer grown on AlN template serves as a pseudo-substrate to release the strain in the barriers and to avoid related defects or composition fluctuation in the active region. Thin (< 2 nm) quantum wells allow preservation of the overlapping of electron and hole wavefunctions considering the strong quantum-confined Stark effect in AlGaN-based MQW structures. Scanning transmission electron microscopy (STEM) coupled to energy-dispersive X-ray spectroscopy (EDX) analysis is used to optimize the growth conditions and to determine the composition of wells and barriers. Optical characterizations of the grown structure reveal a well-defined band-edge emission peak at 285 nm. Based on macro-transmission measurements and simulations, the absorption coefficient of the wells is estimated to be 3 × 10 5 cm −1 (E-field ⊥ c), attesting that the oscillator strength is preserved for these AlGaN MQWs with high Al content, which is promising for efficient surface-emitting devices in the deep ultra-violet (DUV) region

Application of Spin Labels for Research of Vanadyl Acetylacetonate Concentration in Model Bilayer Membranes by EPR Spectroscopy

The compounds and complexes of vanadium are used to treat diabetes and cancer. Research on the effectiveness and mechanism of action of new derivatives of vanadium, and their toxicity is currently very intense. The research shows that the vanadium(IV) acetylacetonate complex [VO(acac)2] shows a synergism with insulin in treating diabetes, high pharmacological activity and low toxicity. In order to improve the effectiveness of drugs and minimize their toxicity, the active compounds are often closed in the liposome membranes. The objective of the work was preparation of bilayer liposomes from egg yolk phosphatidylcholine (EYPC), closing the complex VO(acac)2 in these membranes and estimating the concentration of vanadium complex after incorporation into liposomes membranes. Due to the paramagnetic properties of vanadium(IV) the concentration of this metal complex can be determined directly by EPR. Entering the spin label CTPO in the water phase into the studied arrangement allows for the indirect measurement of the concentration of complex, on the basis of changes of the EPR spectrum of the spin label caused by the presence of the vanadium(IV) complex. In the work the dependence of the α parameter based on the analysis of CTPO EPR spectra on the concentration of VO(acac)2 was determined. To demonstrate the presence of the complex in the membrane directly by measuring the EPR sulfate(IV) sodium was used in order to remove the EPR signal of vanadium(IV) from the water phase. The presence of vanadium(IV) in the membrane was also demonstrated indirectly using a spin label 12-SASL. Based on the results of EPR spectroscopy the concentration of the complex in the membrane was determined together with the partition coefficient of VO(acac)2 between the membrane and outer water environment of the membrane

A north-south worldwide gradient in systemic activity of primary Sjögren syndrome: increased severe disease in patients from southern countries

International audienc

Fluid–structure interaction simulation of the brain–skull interface for acute subdural haematoma prediction

Traumatic brain injury is a leading cause of disability and mortality. Finite element-based head models are promising tools for enhanced head injury prediction, mitigation and prevention. The reliability of such models depends heavily on adequate representation of the brain–skull interaction. Nevertheless, the brain–skull interface has been largely simplified in previous three-dimensional head models without accounting for the fluid behaviour of the cerebrospinal fluid (CSF) and its mechanical interaction with the brain and skull. In this study, the brain–skull interface in a previously developed head model is modified as a fluid–structure interaction (FSI) approach, in which the CSF is treated on a moving mesh using an arbitrary Lagrangian–Eulerian multi-material formulation and the brain on a deformable mesh using a Lagrangian formulation. The modified model is validated against brain–skull relative displacement and intracranial pressure responses and subsequently imposed to an experimentally determined loading known to cause acute subdural haematoma (ASDH). Compared to the original model, the modified model achieves an improved validation performance in terms of brain–skull relative motion and is able to predict the occurrence of ASDH more accurately, indicating the superiority of the FSI approach for brain–skull interface modelling. The introduction of the FSI approach to represent the fluid behaviour of the CSF and its interaction with the brain and skull is crucial for more accurate head injury predictions.QC 20180906</p