Analysis of Thermal Environment in a Hospital Operating Room

AbstractThis paper presents a computational fluid dynamics (CFD) study for thermal comfort in a hospital operating room. The research aims to analyze indoor thermal comfort using the predicted mean vote (PMV) model which has been presented by ISO7730. The room model includes a patient lying on an operating table with a surgical staff of six members standing around under surgical lights. The airflow is supplied to the room from the ceiling diffuser and exhausted through low-level side walls on both sides. Solutions of distribution of airflow velocity, temperature, relative humidity and so on are presented and discussed. The PMV and PPD are calculated for assessing thermal comfort based on TCM model. The simulation results show that the values of PMV and PPD in some parts of human body are not within the standard acceptable range defined by ISO, but its comfortableness satisfies China national standard GB/T18049 request. It is found that TCM model is a more comprehensive model for thermal comfort analysis

Neural Parametric Fokker-Planck Equations

In this paper, we develop and analyze numerical methods for high dimensional Fokker-Planck equations by leveraging generative models from deep learning. Our starting point is a formulation of the Fokker-Planck equation as a system of ordinary differential equations (ODEs) on finite-dimensional parameter space with the parameters inherited from generative models such as normalizing flows. We call such ODEs neural parametric Fokker-Planck equation. The fact that the Fokker-Planck equation can be viewed as the $L^2$-Wasserstein gradient flow of Kullback-Leibler (KL) divergence allows us to derive the ODEs as the constrained $L^2$-Wasserstein gradient flow of KL divergence on the set of probability densities generated by neural networks. For numerical computation, we design a variational semi-implicit scheme for the time discretization of the proposed ODE. Such an algorithm is sampling-based, which can readily handle Fokker-Planck equations in higher dimensional spaces. Moreover, we also establish bounds for the asymptotic convergence analysis of the neural parametric Fokker-Planck equation as well as its error analysis for both the continuous and discrete (forward-Euler time discretization) versions. Several numerical examples are provided to illustrate the performance of the proposed algorithms and analysis

Experimental Study on Ultrahigh Strength Concrete Filled Steel Tube Short Columns under Axial Load

Based on the project of Modaoxi Bridge, an experimental study on the compressive behavior of ultrahigh strength concrete filled steel tube (UHSCFST) short column was conducted. A total of 9 UHSCFST specimens were tested, and the cube strength (fcu) of the core concrete reached 115.4 MPa. Main parameters were the confining factor (ξ=0.608, 0.919, and 1.015), steel ratio (α=14.67%, 20.02%, and 21.98%), and steel strength (fy = 349 MPa, 352 MPa, and 427 MPa). The axially loading test results showed that the visible damage of steel tube occurred under the ultimate load. The higher the confining effect, the less the damage features. And all specimens basically presented a drum-type failure mode. The confining effect of steel tube effectively changed the brittle failure mode of ultrahigh strength concrete (UHSC) and tremendously improved the load bearing capacity and ductility of specimens. Moreover, the higher the steel ratio and steel strength of the specimens, the stronger the confining effect. Meanwhile the excellent mechanical properties will be obtained. Also it is recommended that the UHSCFST prefers Q345 or above strength steel tube to ensure sufficient ductility, and the steel ratio should be more than 20%. Furthermore, the confining effect of steel tubes can improve the ultimate bearing capacity of the ultrahigh strength CFST short columns