Motivated by the need to characterize the spatio-temporal structure of turbulence in wall-bounded flows, we study wavenumber–frequency spectra of the streamwise velocity component based on large-eddy simulation (LES) data. The LES data are used to measure spectra as a function of the two wall-parallel wavenumbers and the frequency in the equilibrium (logarithmic) layer. We then reformulate one of the simplest models that is able to reproduce the observations: the random sweeping model with a Gaussian large-scale fluctuating velocity and with additional mean flow. Comparison with LES data shows that the model captures the observed temporal decorrelation, which is related to the Doppler broadening of frequencies. We furthermore introduce a parameterization for the entire wavenumber–frequency spectrum $E_{11}(k_{1},k_{2},{\it\omega};z)$ , where $k_{1}$ , $k_{2}$ are the streamwise and spanwise wavenumbers, ${\it\omega}$ is the frequency and $z$ is the distance to the wall. The results are found to be in good agreement with LES data.

The logarithmic law for the mean velocity in turbulent boundary layers has long provided a valuable and robust reference for comparison with theories, models and large-eddy simulations (LES) of wall-bounded turbulence. More recently, analysis of high-Reynolds-number experimental boundary-layer data has shown that also the variance and higher-order moments of the streamwise velocity fluctuations $\def \xmlpi #1{}\def \mathsfbi #1{\boldsymbol {\mathsf {#1}}}\let \le =\leqslant \let \leq =\leqslant \let \ge =\geqslant \let \geq =\geqslant \def \Pr {\mathit {Pr}}\def \Fr {\mathit {Fr}}\def \Rey {\mathit {Re}}u^{\prime +}$ display logarithmic laws. Such experimental observations motivate the question whether LES can accurately reproduce the variance and the higher-order moments, in particular their logarithmic dependency on distance to the wall. In this study we perform LES of very high-Reynolds-number wall-modelled channel flow and focus on profiles of variance and higher-order moments of the streamwise velocity fluctuations. In agreement with the experimental data, we observe an approximately logarithmic law for the variance in the LES, with a ‘Townsend–Perry’ constant of $A_1\approx 1.25$ . The LES also yields approximate logarithmic laws for the higher-order moments of the streamwise velocity. Good agreement is found between $A_p$ , the generalized ‘Townsend–Perry’ constants for moments of order $2p$ , from experiments and simulations. Both are indicative of sub-Gaussian behaviour of the streamwise velocity fluctuations. The near-wall behaviour of the variance, the ranges of validity of the logarithmic law and in particular possible dependencies on characteristic length scales such as the roughness length $z_0$ , the LES grid scale $\Delta $ , and subgrid scale mixing length $C_s\Delta $ are examined. We also present LES results on moments of spanwise and wall-normal fluctuations of velocity.

Resilience after a nuclear power plant or other radiation emergency requires response and recovery activities that are appropriately safe, timely, effective, and well organized. Timely informed decisions must be made, and the logic behind them communicated during the evolution of the incident before the final outcome is known. Based on our experiences in Tokyo responding to the Fukushima Daiichi nuclear power plant crisis, we propose a real-time, medical decision model by which to make key health-related decisions that are central drivers to the overall incident management. Using this approach, on-site decision makers empowered to make interim decisions can act without undue delay using readily available and high-level scientific, medical, communication, and policy expertise. Ongoing assessment, consultation, and adaption to the changing conditions and additional information are additional key features. Given the central role of health and medical issues in all disasters, we propose that this medical decision model, which is compatible with the existing US National Response Framework structure, be considered for effective management of complex, large-scale, and large-consequence incidents. (Disaster Med Public Health Preparedness. 2012;0:1-10)

Burnout symptoms, which are characterized by exhaustion, cynicism, and a reduced sense of professional efficacy, may deleteriously affect cognitive function in military personnel. A total of 32 U.S. Military Special Operations personnel enrolled in Survival School completed measures of trauma history, dissociation, and burnout before training. They then completed the Groton Maze Learning Test (GMLT), a neuropsychological measure of integrative visuospatial executive function during three field-based phases of Survival School—enemy evasion, captivity/interrogation, and escape/release from captivity. Lower pre-training perceptions of professional efficacy were associated with reduced executive function during all of the field-based phases of Survival School, even after adjustment for years of education, cynicism, and baseline GMLT scores. Magnitudes of decrements in executive function in Marines with low efficacy relative to those with high efficacy increased as training progressed and ranged from .58 during enemy evasion to .99 during escape/release from captivity. Pre-training perceptions of burnout may predict visuospatial executive function during naturalistic training-related stress in military personnel. Assessment of burnout symptoms, particularly perceptions of professional efficacy, may help identify military personnel at risk for stress-related executive dysfunction. (JINS, 2011, 17, 494–501)