In the current work, the effects of design (groove depth and groove width) and operational (temperature and velocity) parameters on aerodynamic performance parameters (coefficient of drag and coefficient of lift) of an isolated passenger car tire have been investigated. The study is conducted by using neural network-based Monte-Carlo analysis on computational fluid dynamics (CFD). The computer experiments are designed to obtain the causal relationship between tire design, operational, and aerodynamic performance parameters. The Reynolds-averaged Navier–Stokes equations-based Realizable K-ε model has been employed to analyze the variations in flow patterns around an isolated tire. The design parameters are varied over wide range and full factorial design, while considering temperature and velocity is completely explored to draw conclusive results. The multi-layer perceptron type neural network with the back-propagation algorithm is trained to map any non-linearity in causal relationships. The sensitivity analysis is performed to find the relationship between control variables and performance indicators. The importance of control variable is determined by both sensitivity and significance analyses and the paired interaction analysis is performed between selected control variables to find the interactive behavior of corresponding variables. The design parameter of groove width with 6.8% and 41% reduction in drag and lift coefficient, respectively, and conventionally overlooked operational parameter of velocity with 4% and 35% impact on drag and lift coefficient, respectively, are found to be the most significant variables. The air trapped between the longitudinal grooves and the road is found to follow the beam theory. The interaction of the groove depth and width is found to be significant with respect to coefficient of lift based on the air beam concept. The interaction of groove width and velocity is found to be significant with respect to both coefficients of lifts and drag.

Validation of risk models is required by regulators and demanded by management and shareholders. Those models rely in practice heavily on Monte Carlo (MC) simulations. Given their complexity, the convergence of the MC algorithm is difficult to prove mathematically. To circumvent this problem and nevertheless explore the conditions of convergence, we suggest an analytical approach. Considering standard models, we compute, via mixing techniques, closed form formulas for risk measures as Value-at-Risk (VaR) VaR or Tail Value-at-Risk (TVaR) TVaR on a portfolio of risks, and consequently for the associated diversification benefit. The numerical convergence of MC simulations of those various quantities is then tested against their analytical evaluations. The speed of convergence appears to depend on the fatness of the tail of the marginal distributions; the higher the tail index, the faster the convergence. We also explore the behaviour of the diversification benefit with various dependence structures and marginals (heavy and light tails). As expected, it varies heavily with the type of dependence between aggregated risks. The diversification benefit is also studied as a function of the risk measure, VaR or TVaR.

We have collected the parameter of 38 neutron stars (NSs) in binary systems with spin periods and measured masses. By adopting the Boot-strap method, we reproduced the procedure of mass calculated for each system separately, to determine the truly mass distribution of the NS that obtained from observation. We also applied the Monte-Carlo simulation and introduce the characteristic spin period 20 ms, in order to distinguish between millisecond pulsars (MSPs) and less recycled pulsars. The mass distributions of MSPs and the less recycled pulsars could be fitted by a Gaussian function as 1.45±0.42 M⊙ and 1.31±0.17 M⊙ (with 1σ) respectively. As such, the MSP masses are heavier than those in less recycled systems by factor of ~ 0.13M⊙, since the accretion effect during the recycling process.

The thermodynamic properties and some critical properties of the planar rotator model with chiral Dzyaloshinsky-Moriya (DM) interaction on triangular lattice are analyzed using a hybrid Monte Carlo method. It has been shown that there is a XY-like Berezinskii-Kosterlitz-Thouless (BKT) phase transition in this model. The ground state of this spiral system and the effects of size mismatch are also discussed.

Dans ce travail sont présentées quelques activités des groupes SADVI (Service d’Application des Détecteurs Visuels), LAM (Laboratoire d’Analyses et de Mesures) et RaMsEs (Radioprotection et Mesures environnementales) qui se sont succédés à l’IPHC de Strasbourg ces dernières années. Les résultats concernent : la R&D en métrologie des rayonnements ionisants, les applications des détecteurs solides de traces, les émulsions nucléaires en biologie spatiale, la thermoluminescence pour la datation archéologique, la dosimétrie neutron et les mesures de la radioactivité dans l’environnement par spectrométrie α, β et γ.