Time Spent Working in Custody Influences Work Sample Test Battery Performance of Deputy Sheriffs Compared to Recruits

This study determined the influence of years spent working in custody on fitness measured by a state-specific testing battery (Work Sample Test Battery; WSTB) in deputy sheriffs. Retrospective analysis was conducted on one patrol school class (51 males, 13 females) divided into three groups depending on time spent working in custody: DS24 (<24 months; n = 20); DS2547 (25–47 months; n = 23); and DS48+ (≥48 months; n = 21). These groups were compared to a recruit class (REC; 219 males, 34 females) in the WSTB, which comprised five tasks completed for time: 99-yard (90.53-m) obstacle course (99OC); 165-pound (75-kg) dummy drag; six-foot (1.83-m) chain link fence (CLF) and solid wall (SW) climb; and 500-yard (457.2-m) run (500R). A univariate analysis of covariance (ANCOVA) (controlling for sex and age) with Bonferroni post hoc determined significant between-group differences. DS48+ were slower in the 99OC compared to the REC (p = 0.007) and performed the CLF and SW slower than all groups (p ≤ 0.012). DS24, DS2547, and DS48+ were all slower than REC in the 500R (p ≤ 0.002). Physical training should be implemented to maintain fitness and job-specific task performance in deputy sheriffs working custody, especially considering the sedentary nature of this work

Uncertainty quantification in steady state simulations of a molten salt system using polynomial chaos expansion analysis

Uncertainty Quantification (UQ) of numerical simulations is highly relevant in the study and design of complex systems. Among the various approaches available, Polynomial Chaos Expansion (PCE) analysis has recently attracted great interest. It belongs to nonintrusive spectral projection methods and consists of constructing system responses as polynomial functions of the stochastic inputs. The limited number of required model evaluations and the possibility to apply it to codes without any modification make this technique extremely attractive. In this work, we propose the use of PCE to perform UQ of complex, multi-physics models for liquid fueled reactors, addressing key design aspects of neutronics and thermal fluid dynamics. Our PCE approach uses Smolyak sparse grids designed to estimate the PCE coefficients. To test its potential, the PCE method was applied to a 2D problem representative of the Molten Salt Fast Reactor physics. An in-house multi-physics tool constitutes the reference model. The studied responses are the maximum temperature and the effective multiplication factor. Results, validated by comparison with the reference model on 103 Monte-Carlo sampled points, prove the effectiveness of our PCE approach in assessing uncertainties of complex coupled models