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The subgrid-scale (SGS) modeling in large-eddy simulation (LES) which accounts for the effect of unsteadiness and nonequilibrium state in the SGS is considered. Unsteadiness is incorporated by considering the spectral evolution in the forced homogeneous isotropic turbulence using the transport equation for the SGS energy. As for the unfiltered spectrum, perturbative expansion of the Kovasnay spectral model about the Kolmogorov −5/3 energy spectrum which constitutes a base equilibrium state in the inertial subrange, yields the extra components with −7/3 and −9/3 powers. It is shown that these spectra are actually extracted in the direct numerical simulation (DNS) data and these components govern the unsteady energy transfer. As for the SGS real-space representation of the spectral model, we consider the SGS one-equation model. The perturbation expansion is applied to the one-equation model by setting the base SGS energy as the standard Smagorinsky model, which assumes the equilibrium state in the SGS and its spectral counterpart is the Kolmogorov −5/3 spectrum. The solution yields the terms whose spectral counterparts are the components with −7/3 and −9/3 powers. These additional terms are induced by temporal variations of the base SGS energy. In the temporal variations of the grid-scale energy, SGS energy, SGS production term, and SGS dissipation which are obtained by applying the filter to the DNS data, it is shown that these quantities lag in time in this order. This time-lag is not realized in the standard Smagorinsky model and the one-equation model because the SGS dissipation is defined so that it instantaneously adjusts to the SGS energy. In the one-equation model, the direction of the energy cascade in the initial period is opposite to that obtained in the DNS data. To retrieve correct time-lag and direction of energy transfer, we relax this instantaneous adjustment and propose the nonequilibrium Smagorinsky model. In this nonequilibrium model, the SGS energy incurred by the −7/3 spectrum is added to the base Smagorinsky energy. Assessment in actual LES shows that the time-lag predicted using the standard Smagorinsky and the one-equation models is inaccurate, whereas good agreement with the DNS data is achieved in the nonequilibrium Smagorinsky model. Extraction of the grid-scale nonequilibrium energy spectrum yields the −7/3 and −9/3 components in addition to the base −5/3 spectrum. In the nonequilibrium Smagorinsky model, continuation of the grid-scale spectra into the SGS is established for the −5/3 and −7/3 components. As a result, the unsteady energy transfer is more accurately predicted, whereas the standard Smagorinsky model does not have the SGS counterpart for the −7/3 component. Feasibility of employing the eddy-viscosity approximation to account for the transfer in the period in which −9/3 spectrum prevails is discussed.

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This paper reviews the recent progress in studies on the nonequilibrium statistics of turbulence. The structure of the energy spectrum in the inertial subrange is studied using direct numerical simulation (DNS) data for turbulence in a periodic box at high Reynolds numbers. A perturbation expansion for the energy spectrum about a base Kolmogorovk 5 3 steady state yields additional -7 3 and -9 3 power components that are induced by the fluctuation of the dissipation rate ε and represents a nonequilibrium state. The nonequilibrium component is extracted by applying a conditional sampling on e d dt to the DNS data, and it is shown that the deviation from the base -5 3 spectrum fits the -7 3 and -9 3 power slopes. The temporal development of the spectrum is divided into two regimes, phases 1 and 2. The large amount of energy contained in the low-wavenumber range in Phase 1 is cascaded to the small scales in Phase 2. This energy transfer is accomplished by the reversal in the sign of the −7/3 power component. Correlation of the appearance of the nonequilibrium spectrum and the transition in the mode of the configuration of the stretched spiral vortex is discussed. Occurrence of transition is identified using the helicity. Subgrid-scale (SGS) modeling in LES that accounts for the effect of unsteadiness and nonequilibrium state is considered by employing the transport equation for the SGS energy (one-equation model). Perturbation expansion about the Kolmogorov −5/3 energy spectrum which constitutes a base equilibrium state in the inertial subrange yields −7/3 spectrum as in the unfiltered case. These spectra are extracted in the DNS data, and their roles in the generation of the energy cascade are revealed. The SGS energy spectrum which governs the one-equation model is sought in a perturbative manner.Besides the base -5 3 spectrum assumed in the Smagorinsky model, -7 3

Methods:In this mixed-methods study, we used incident reporting data from the Japan Council for Quality Health Care. Of the 232 medical device-related reports that were downloaded, 34 (14.7%) were ventilator-associated incidents. Data related to patients, situations, and incidents were collected and coded. Results:The frequencies of ventilator-associated accidents were 20 (58.8%) during the daytime and 14 (41.2%) during the night/early morning. Ventilator-associated accidents occurred more frequently in the hospital room (n = 22 [64.7%]) than in the intensive care unit (n = 4 [11.8%]). Problems with ventilators occurred in only 4 cases (11.8%); in most cases, medical professionals experienced difficulty with the use or management of ventilators (n = 30 [88.2%]), and 50% of them were due to misuse/ misapplication of ventilators (n = 17 [50.0%]). Ventilator-associated accidents were caused by an entanglement of complex factors-hardware, software, environment, liveware, and liveware-liveware interaction. Communication and alarm-related errors were reported to be related, as were intuitiveness or complicated specifications of the device. Conclusions:Our study revealed that ventilator-associated accidents were caused by an entanglement of complex factors and were related to inadequate communication among caregivers and families. Moreover, alarms were overlooked owing to inattentiveness. Mistakes were generally caused by a lack of experience, insufficient training, or outright negligence. To reduce the occurrence of ventilator-associated accidents, hospital administrators should develop protocols for employment of new devices. Medical devices should be developed from the perspective of human engineering, which could be one of the systems approaches.