Risk evaluation of ballistic penetration by small caliber ammunition of live-fire shoot house facilities with comparison to numerical and experimental results

2021 ◽  
pp. 204141962098855
Author(s):  
Brad Gregory Davis ◽  
Jacob Thompson ◽  
William Morningstar ◽  
Ean McCool ◽  
Vishnu Peri ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Numerical Study ◽  
Target Material ◽  
Experimental Tests ◽  
Probability Of Failure ◽  
Accurate Estimate ◽  
Depth Of Penetration ◽  
Ballistic Resistance ◽  
Simulation Techniques ◽  
Steel Panels

The development of advanced small caliber weapon systems has resulted in rounds with more material penetration capabilities. The increased capabilities may mean that existing live-fire facilities will no longer be adequate for the training and certification of military and law enforcement personnel. Constraints on training in many live-fire shoot house facilities are already in place, with some allowing only single round impact during training. With little understanding of the probability of perforation, or failure, of existing containment systems, this study evaluates risk by studying the single round impact of small caliber ammunition against live-fire shoot house containment systems constructed from AR500 steel panels with two-inch ballistic rubber covering. An analytical and numerical study was conducted using an existing model for steel penetration developed by Alekseevskii-Tate and the EPIC finite element code. A modified form of the advancing cavity model for the ballistic resistance of the target material was used to account for the relatively unconfined material resulting from the studied impacts. These results are then compared to experimental tests conducted by Goodman for rounds of various small calibers impacting live-fire facility containment systems. Projectile and target characteristics were then modeled as continuous random variables, and Monte Carlo simulations were conducted using the validated analytical model to estimate the probability of a single round impact perforating the live-fire facility containment system. An importance sampling scheme was used to reduce the variance of the solution and provide a more accurate estimate of the probability of failure. The Alekseevskii-Tate model was found to provide accurate estimates of the depth of penetration when compared to experimental and numerical results at ordnance velocities and an estimate of the probability of failure is on the order of 1x10-5. This study provides useful tools for the analysis of existing live-fire facilities against future and existing ammunition, and for the design of new facilities. When coupled with Monte Carlo simulation techniques, a risk-based approach to certify live-fire facilities for use with any variety of small arms ammunition can be applied.

scholarly journals Contribution to numerical study of vehicle vertical stochastic vibration

2018 ◽  
Vol 157 ◽  
pp. 03015
Author(s):  
Alžbeta Sapietová ◽  
Milan Sága ◽  
Dana Stančeková ◽  
Milan Sapieta
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Computational Model ◽  
Numerical Study ◽  
Model Parameters ◽  
Vehicle Model ◽  
Stochastic Response ◽  
Simulation Techniques ◽  
Random Character ◽  
Kinematics Parameters

The goal of the paper is to present an application of the software MB_DYN inbuilt in MATLAB for stochastic response of the chosen vehicle computational model. The input kinematics parameters will be road irregularity with random character. The dynamic model parameters are considered as deterministic. The analysed vehicle model assumes 10 DOF. The stochastic response in time and frequency domain was solved by program MB_DYN in MATLAB using Monte Carlo method. Applying the simulation techniques the influence study of the vehicles speed and road quality in chosen points was realised.

scholarly journals A Bayesian approach to estimating the population prevalence of mood and anxiety disorders using multiple measures

2021 ◽  
Vol 30 ◽  
Author(s):  
Jordan Edwards ◽  
A. Demetri Pananos ◽  
Amardeep Thind ◽  
Saverio Stranges ◽  
Maria Chiu ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Anxiety Disorders ◽  
Administrative Data ◽  
Population Based ◽  
Accurate Estimate ◽  
Service Planning ◽  
Prevalence Estimate ◽  
Population Prevalence ◽  
Mood And Anxiety Disorders ◽  
Prevalence Estimates

Abstract Aims There is currently no universally accepted measure for population-based surveillance of mood and anxiety disorders. As such, the use of multiple linked measures could provide a more accurate estimate of population prevalence. Our primary objective was to apply Bayesian methods to two commonly employed population measures of mood and anxiety disorders to make inferences regarding the population prevalence and measurement properties of a combined measure. Methods We used data from the 2012 Canadian Community Health Survey – Mental Health linked to health administrative databases in Ontario, Canada. Structured interview diagnoses were obtained from the survey, and health administrative diagnoses were identified using a standardised algorithm. These two prevalence estimates, in addition to data on the concordance between these measures and prior estimates of their psychometric properties, were used to inform our combined estimate. The marginal posterior densities of all parameters were estimated using Hamiltonian Monte Carlo (HMC), a Markov Chain Monte Carlo technique. Summaries of posterior distributions, including the means and 95% equally tailed posterior credible intervals, were used for interpretation of the results. Results The combined prevalence mean was 8.6%, with a credible interval of 6.8–10.6%. This combined estimate sits between Bayesian-derived prevalence estimates from administrative data-derived diagnoses (mean = 7.4%) and the survey-derived diagnoses (mean = 13.9%). The results of our sensitivity analysis suggest that varying the specificity of the survey-derived measure has an appreciable impact on the combined posterior prevalence estimate. Our combined posterior prevalence estimate remained stable when varying other prior information. We detected no problematic HMC behaviour, and our posterior predictive checks suggest that our model can reliably recreate our data. Conclusions Accurate population-based estimates of disease are the cornerstone of health service planning and resource allocation. As a greater number of linked population data sources become available, so too does the opportunity for researchers to fully capitalise on the data. The true population prevalence of mood and anxiety disorders may reside between estimates obtained from survey data and health administrative data. We have demonstrated how the use of Bayesian approaches may provide a more informed and accurate estimate of mood and anxiety disorders in the population. This work provides a blueprint for future population-based estimates of disease using linked health data.

scholarly journals Evaluation of Bearing Capacity of Strip Footing Using Random Layers Concept

2015 ◽  
Vol 37 (3) ◽  
pp. 31-39 ◽  
Author(s):  
Marek Kawa ◽  
Dariusz Łydżba
Keyword(s):  
Monte Carlo ◽  
Bearing Capacity ◽  
Failure Mechanism ◽  
Design Theory ◽  
Cohesive Soil ◽  
Probability Of Failure ◽  
Mean Value ◽  
Strip Footing ◽  
Random Field Theory ◽  
The Mean

Abstract The paper deals with evaluation of bearing capacity of strip foundation on random purely cohesive soil. The approach proposed combines random field theory in the form of random layers with classical limit analysis and Monte Carlo simulation. For given realization of random the bearing capacity of strip footing is evaluated by employing the kinematic approach of yield design theory. The results in the form of histograms for both bearing capacity of footing as well as optimal depth of failure mechanism are obtained for different thickness of random layers. For zero and infinite thickness of random layer the values of depth of failure mechanism as well as bearing capacity assessment are derived in a closed form. Finally based on a sequence of Monte Carlo simulations the bearing capacity of strip footing corresponding to a certain probability of failure is estimated. While the mean value of the foundation bearing capacity increases with the thickness of the random layers, the ultimate load corresponding to a certain probability of failure appears to be a decreasing function of random layers thickness.

A numerical study of the sedimentation of fibre suspensions

1998 ◽  
Vol 376 ◽  
pp. 149-182 ◽  
Author(s):  
MICHAEL B. MACKAPLOW ◽  
ERIC S. G. SHAQFEH
Keyword(s):  
Monte Carlo ◽  
Steady State ◽  
Monte Carlo Simulations ◽  
Numerical Study ◽  
Point Particle ◽  
Hydrodynamic Interactions ◽  
Dynamic Simulations ◽  
Slender Body Theory ◽  
Fibre Suspensions ◽  
The Mean

The sedimentation of fibre suspensions at low Reynolds number is studied using two different, but complementary, numerical simulation methods: (1) Monte Carlo simulations, which consider interparticle hydrodynamic interactions at all orders within the slender-body theory approximation (Mackaplow & Shaqfeh 1996), and (ii) dynamic simulations, which consider point–particle interactions and are accurate for suspension concentrations of nl3=1, where n and l are the number density and characteristic half-length of the fibres, respectively. For homogeneous, isotropic suspensions, the Monte Carlo simulations show that the hindrance of the mean sedimentation speed is linear in particle concentration up to at least nl3=7. The speed is well predicted by a new dilute theory that includes the effect of two-body interactions. Our dynamic simulations of dilute suspensions, however, show that interfibre hydrodynamic interactions cause the spatial and orientational distributions to become inhomogeneous and anisotropic. Most of the fibres migrate into narrow streamers aligned in the direction of gravity. This drives a downward convective flow within the streamers which serves to increase the mean fibre sedimentation speed. A steady-state orientation distribution develops which strongly favours fibre alignment with gravity. Although the distribution reaches a steady state, individual fibres continue to rotate in a manner that can be qualitatively described as a flipping between the two orientations aligned with gravity. The simulation results are in good agreement with published experimental data.

Numerical Investigation of Ductile Fracture in Pipelines Under Complex Loading Using a Phenomenological Damage Model

2021 ◽  
Author(s):  
Iago S. Santos ◽  
Diego F. B. Sarzosa
Keyword(s):  
Ductile Fracture ◽  
Mechanical Response ◽  
Numerical Study ◽  
Damage Model ◽  
Stress Triaxiality ◽  
Numerical Procedure ◽  
Complex Loading ◽  
Experimental Tests ◽  
Compact Tension ◽  
Axial Tensile

Abstract This paper presents a numerical study on pipes ductile fracture mechanical response using a phenomenological computational damage model. The damage is controlled by an initiation criterion dependent on the stress triaxiality and the Lode angle parameter, and a post-initiation damage law to eliminate each finite element from the mesh. Experimental tests were carried out to calibrate the elastoplastic response, damage parameters and validate the FEM models. The tested geometries were round bars having smooth and notched cross-section, flat notched specimens under axial tensile loads, and fracture toughness tests in deeply cracked bending specimens SE(B) and compact tension samples C(T). The calibrated numerical procedure was applied to execute a parametric study in pipes with circumferential surface cracks subjected to tensile and internal pressure loads simultaneously. The effects of the variation of geometric parameters and the load applications on the pipes strain capacity were investigated. The influence of longitudinal misalignment between adjacent pipes was also investigated.

Numerical Characterization of Flow and Heat Transfer in Pre-Swirl Systems

2017 ◽  
Author(s):  
Riccardo Da Soghe ◽  
Cosimo Bianchini ◽  
Jacopo D’Errico
Keyword(s):  
Heat Transfer ◽  
Gas Turbines ◽  
Numerical Study ◽  
Physical Phenomenon ◽  
Computational Procedure ◽  
Operating Conditions ◽  
Simulation Techniques ◽  
Numerical Characterization ◽  
Unsteady Simulation

This paper deals with a numerical study aimed at the validation of a computational procedure for the aerothermal characterization of pre-swirl systems employed in axial gas turbines. The numerical campaign focused on an experimental facility which models the flow field inside a direct-flow pre-swirl system. Steady and unsteady simulation techniques were adopted in conjunction with both a standard two-equations RANS/URANS modelling and more advanced approaches such as the Scale-Adaptive-Simulation principle, the SBES and LES. The comparisons between CFD and experiments were done in terms of swirl number development, static and total pressure distributions, receiving holes discharge coefficient and heat transfer on the rotor disc surface. Several operating conditions were accounted for, spanning 0.78·106<Reφ<1.21·106 and 0.123<λt<0.376. Overall the steady-state CFD predictions are in good agreement with the experimental evidences even though it is not able to confidently mimic the experimental swirl and pressure behaviour in some regions. Although the use of unsteady sliding mesh and direct turbulence modelling, would in principle increase the insight in the physical phenomenon, from a design perspective the tradeoff between accuracy and computational costs is not always favourable.

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