Backward-Eulerian Footprint Modelling Based on the Adjoint Equation for Atmospheric and Urban-Terrain Dispersion.

This study developed a backward-Eulerian footprint modelling method based on an adjoint equation for atmospheric boundary-layer flows. In the proposed method, the concentration footprint can be obtained directly by numerical simulation with the adjoint equation, and the flux footprints can be estimated using the adjoint concentration based on the gradient diffusion hypothesis. We first tested the proposed method by estimating the footprints for an ideal three-dimensional boundary layer with different atmospheric stability conditions based on the Monin-Obukhov profiles. It was indicated that the results were similar to the FFP method (Kljun et al. in Boundary-Layer Meteorol 112:503-523, 2004, 10.1023/B:BOUN.0000030653.71031.96; Geosci Model Dev 8:3695-3713, 2015, 10.5194/gmd-8-3695-2015) for convective conditions and the K-M method (Kormann and Meixner in Boundary-Layer Meteorol 99:207-224, 2001, 10.1023/A:1018991015119) for stable conditions. The proposed method was then coupled with the Reynolds averaged Navier-Stokes model to calculate the footprints for a block-arrayed urban canopy. The results were qualitatively compared to the results from the Lagrangian-Large-Eddy-Simulation (LL) method (Hellsten et al. in Boundary-Layer Meteorol 157:191-217, 2015, 10.1007/s10546-015-0062-4). It was shown that the proposed method reproduced the main features of footprints for different sensor positions and measurement heights. However, it is necessary to simulate the adjoint equation with a more sophisticated turbulence model in the future to better capture turbulent effects in the footprint modelling.

Numerical modeling of sneeze airflow and its validation with an experimental dataset.

In this study, we aimed at providing datasets using experimental results to validate the sneeze airflow. In addition, the boundary conditions for the sneeze simulation that could reproduce the sneeze airflow in the experimental results are presented and reviewed. The validation datasets were created by performing ensemble-average analysis with the experimental results of particle image velocimetry, and these were used to explore the boundary conditions to reproduce the sneeze airflow. As a result of the sneeze airflow reproduced by computational fluid dynamics simulation, the magnitude ranges of maximum velocity at the interface were observed to be 21.1-23.9 m/s for males and 17.9-20.3 m/s for females, which were higher than those of coughing. Compared with the experimental results, the root-mean-square error range for the overall airflow distribution was 0.19-0.23 m/s, whereas the error range for the magnitude of the maximum velocity at a criterion point was 0.03-0.08 m/s. The total sneezing airflow volume was in the range of 0.36-0.48 L, which was relatively low compared with that of coughing. Thus, this study provides important fundamental boundary conditions for computational fluid dynamics analysis, validated by experimental results, to interpret the spread of infectious particles by sneezing.

Experimental measurements of airflow features and velocity distribution exhaled from sneeze and speech using particle image velocimetry.

Airflow exhaled from sneeze and speech is an important source of viruses and droplets in daily life and may cause imperceptible virus propagation. The velocities of sneeze and speech airflow exhaled from 10 healthy young participants repeatedly using high-frequency (2986 Hz) particle image velocimetry are measured. The parameters for describing the dynamic process of sneeze airflow, such as sneeze duration time (SDT), peak velocity time (PVT), maximum velocities, and sneeze spread angle, are analyzed. The sneeze airflow lasts 430 ms (SDT) and reaches the peak velocity in the first 20 ms (PVT). The maximum sneeze airflow velocity is approximately 15.9 m/s. The temporal variation of the sneeze velocity exhibits the gamma distribution. For speech airflow, the maximum instantaneous velocity and maximum time-averaged velocity are reported. The maximum instantaneous velocity is approximately 6.25 m/s, whereas the time-averaged value is only 0.208 m/s owing to the extremely small airflow velocity among syllables. The vertical/horizontal spread angles of the airflow are 15.1°/15.4° for sneeze and 52.9°/42.9° for speech. The difference in airflow features based on gender is generally slight for both sneeze and speech. Subsequently, an ensemble-average operation is conducted to obtain the general and representative velocity distributions. We report each component of the temporal and spatial velocity distributions of the sneeze airflow and the time-averaged velocity distribution of the speech airflow. These detailed distribution data can provide a comprehensive understanding of sneeze and speech airflow movement mechanisms as well as a detailed database for future sneeze and speech computational fluid dynamics simulations.

Recent research on expiratory particles in respiratory viral infection and control strategies: A review.

The global spread of coronavirus disease 2019 poses a significant threat to human health. In this study, recent research on the characteristics of expiratory particles and flow is reviewed, with a special focus on different respiratory activities, to provide guidance for reducing the viral infection risk in the built environment. Furthermore, environmental influence on particle evaporation, dispersion, and virus viability after exhalation and the current methods for infection risk assessment are reviewed. Finally, we summarize promising control strategies against infectious expiratory particles. The results show that airborne transmission is a significant viral transmission route, both in short and long ranges, from infected individuals. Relative humidity affects the evaporation and trajectories of middle-sized droplets most, and temperature accelerates the inactivation of SARS-CoV-2 both on surfaces and in aerosols. Future research is needed to improve infection risk models to better predict the infection potential of different transmission routes. Moreover, further quantitative studies on the expiratory flow features after wearing a mask are needed. Systematic investigations and the design of advanced air distribution methods, portable air cleaners, and ultraviolet germicidal irradiation systems, which have shown high efficacy in removing contaminants, are required to better control indoor viral infection.

Measurements of exhaled airflow velocity through human coughs using particle image velocimetry.

The sudden outbreak of coronavirus (COVID-19) has infected over 100 million people and led to over two million deaths (data in January 2021), posing a significant threat to global human health. As a potential carrier of the novel coronavirus, the exhaled airflow of infected individuals through coughs is significant in virus transmission. The research of detailed airflow characteristics and velocity distributions is insufficient because most previous studies utilize particle image velocimetry (PIV) with low frequency. This study measured the airflow velocity of human coughs in a chamber using PIV with high frequency (interval: 1/2986 s) to provide a detailed validation database for droplet propagation CFD simulation. Sixty cough cases for ten young healthy nonsmoking volunteers (five males and five females) were analyzed. Ensemble-average operations were conducted to eliminate individual variations. Vertical and horizontal velocity distributions were measured around the mouth area. Overall cough characteristics such as cough duration time (CDT), peak velocity time (PVT), maximum velocities, and cough spread angle were obtained. The CDT of the cough airflow was 520-560 m s, while PVT was 20 m s. The male/female averaged maximum velocities were 15.2/13.1 m/s. The average vertical/horizontal cough spread angle was 15.3°/13.3° for males and 15.6°/14.2° for females. In addition, the spatial and temporal distributions of ensemble-averaged velocity profiles were obtained in the vertical and horizontal directions. The experimental data can provide a detailed validation database the basis for further study on the influence of cough airflow on virus transmission using computational fluid dynamic simulations.

Line source estimation of environmental pollutants using super-Gaussian geometry model and bayesian inference.

A line is a common geometry for pollution sources, e.g., outdoor traffic pollution, and is thus useful for developing a suitable source term estimation (STE) method. Most existing methods regard the source as a single point that only includes location and strength parameters; however, limited attention has been paid to the geometric information of the source. This negligence may cause errors, or even failure, in the STE. Therefore, this paper proposes a line source estimation method that combines Bayesian inference with the super-Gaussian function. This function can approximate the shape of sources with several intuitive coefficients, which are adjusted to their true value through Bayesian inference. The performance of the proposed method was evaluated through estimation of a line source in two cases: an ideal urban boundary layer, via simulation, and a complex urban square, via a wind tunnel experiment. The results demonstrate that this method is capable of identifying the source information without any prior geometric information regarding the source. Moreover, it was confirmed that the conventional point-based assumption method leads to failure in estimating the line source, which implies that geometry estimation is necessary for STE.

Wind-driven pumping flow ventilation of highrise buildings: Effects of upstream building arrangements and opening area ratios.

Periodic vortex shedding around a building could play an important role in wind-driven single-sided ventilation especially when two free openings are mounted on the leeward wall, in which case "pumping" flow dominates the natural ventilation. In this paper, we investigated the characteristics of vortex shedding and "pumping" flow affected by the arrangements of upstream buildings and opening area ratio of ports on the downstream target building. Computational fluid dynamics (CFD) simulations have been used to predict the instantaneous and mean flow fields. Numerical results indicate that the strength of "pumping" flow could be intensively weakened by two upstream buildings. Vortex shedding from the inner shear layers dominates the vortex shedding from the target building and constrains that from both upstream buildings except at W/B = 0.5, in which case the gap flow is weak and the St is close to that of a single building. The increase of upstream building length leads to decrease of the vortex shedding frequency at the wake of all buildings and ventilation rate of the downstream building. An increase of opening area ratio on the rear wall of the downstream building will raise the Strouhal number but have no positive correlation with ventilation rate. "Pumping" flow oscillating frequency does not have clear correlation with the ventilation rate. Our study on the wake vortex shedding flow across building clusters could benefit the future green design of urban buildings.

Two thermal performance test (TPT) datasets of a single U-tube borehole heat exchanger with inlet setpoint temperatures of 30 °C and 40 °C.

The presented thermal performance test (TPT) datasets were related to the research article "New perspectives in thermal performance test: Cost-effective apparatus and extended data analysis" (Choi et al., 2018), where a new TPT apparatus was developed by adding a solid-state-relay and a proportional-integral-derivative (PID) controller to a thermal response test apparatus. Using the developed apparatus connected to a 50-m-long vertical ground heat exchanger, two TPTs were conducted for 144 h with inlet setpoint temperatures of 30 °C and 40 °C. The raw data were measured at 5 s intervals and consisted of the inlet, and outlet fluid temperatures, and the flow rate. The attached MATLAB script allows users to easily filter the data at user-specified time intervals. Moreover, the execution of code provides two additional quantities: heat injection rate and unit heat exchange rate. The datasets are shared for the following purposes: (1) performance comparison of various ground heat exchangers using the unit heat exchange rate (2) comparison of the control performance of a newly developed TPT apparatus, (3) validation of an analytical or numerical thermal response model, and (4) validation of a parameter estimation algorithm.

Bayesian source term estimation of atmospheric releases in urban areas using LES approach.

The estimation of source information from limited measurements of a sensor network is a challenging inverse problem, which can be viewed as an assimilation process of the observed concentration data and the predicted concentration data. When dealing with releases in built-up areas, the predicted data are generally obtained by the Reynolds-averaged Navier-Stokes (RANS) equations, which yields building-resolving results; however, RANS-based models are outperformed by large-eddy simulation (LES) in the predictions of both airflow and dispersion. Therefore, it is important to explore the possibility of improving the estimation of the source parameters by using the LES approach. In this paper, a novel source term estimation method is proposed based on LES approach using Bayesian inference. The source-receptor relationship is obtained by solving the adjoint equations constructed using the time-averaged flow field simulated by the LES approach based on the gradient diffusion hypothesis. A wind tunnel experiment with a constant point source downwind of a single building model is used to evaluate the performance of the proposed method, which is compared with that of the existing method using a RANS model. The results show that the proposed method reduces the errors of source location and releasing strength by 77% and 28%, respectively.