Change in departure time for a train trip to avoid crowding during the COVID-19 pandemic: A latent class study in the Netherlands

The energy-efficient plate heat exchanger (PHE) and refrigerant R1234yf, which has a low global warming potential (GWP), can be used to realize an energy efficient heat pump (HP) system for electric vehicles (EV), extending their driving range. Therefore, the characteristics of R1234yf in an offset-fin strip (OSF) flowstructured PHE are critical for heat-exchanger design. This study investigates the condensation heat transfer coefficient (C-HTC) and two-phase frictional pressure drop (2P-FPD) of R1234yf during condensation in an OSF flow-structured PHE under various operating conditions. First, a modified Wilson plot method was used to determine the multiplier (C) and Reynolds number exponential (n) for the coolant side as -0.426 and 0.494, respectively. When the heat flux (q), average vapor quality (xa), and mass flux (G) increased, the C-HTC increased, whereas it decreased with saturation temperature (Tsat). Despite the force-convective condensation flow regime, the C-HTC increment was minimal with G at lower xa owing to the lesser significance of the shear effect. Additionally, the 2P-FPD was unaffected by q but increased considerably with an increase in xa and G and a decrease in Tsat. Based on the current experimental database, empirical correlations for forecasting friction factor and Nusselt number were developed with a 91% predictability.

Discovering spatiotemporal flow patterns: where the origin–destination map meets empirical orthogonal function decomposition

Flows are usually represented as vector lines from origins to destinations and can reflect the movements of individuals or groups in space and time. Revealing and analyzing the spatiotemporal flow patterns are conducive to understanding information underlying movements. This paper proposes a new method called the OD–EOF (Origin–Destination–Empirical Orthogonal Function) to discover important spatiotemporal flow patterns on the premise of maintaining the pairwise connections between origins and destinations. We first construct a spatiotemporal flow matrix that contains connection information between origins and destinations and temporal flow information by adding a temporal dimension to the OD map. Then, we decompose the spatiotemporal flow matrix into spatial modes and corresponding time coefficients by EOF decomposition. The decomposition results depict the prominent spatial distribution of and temporal variation in flows, with most of the spatiotemporal characteristics highly concentrated into the first few spatial modes. The method is evaluated by five synthetic datasets and a user study and subsequently applied to analyze the impact of the COVID-19 pandemic on the spatiotemporal patterns of human mobility in China during the Spring Festival travel rush in 2020 and 2021. The results show the prominent spatiotemporal patterns of human mobility during these periods under the influence of the COVID-19 pandemic outbreak and the normalization of pandemic prevention and control. © 2023 Cartography and Geographic Information Society.

Optimal position of air purifiers in elevator cabins for the improvement of their ventilation effectiveness

Ventilation in confined spaces is essential to reduce the airborne transmission of viruses responsible for respiratory diseases such as COVID-19. Mechanical ventilation using purifiers is an interesting solution for elevator cabins to reduce the risk of infection and improve the air quality. In this work, the optimal position and blowing direction of these devices to maximize ventilation and minimize the residence time of the air inside two cabins (large and small) is studied. Special attention is devoted to idle periods when the cabin is not used by the passengers, in order to keep the cabin ambient safe and clean, avoiding that the trapped air in the cabin (after its use) could suppose a reservoir for contaminants. CFD numerical models of two typical cabin geometries, including the discretization of small slots and grilles for infiltration, have been developed. A full 3D URANS approach with a k-epsilon RNG turbulence model and a non-reactive scalar to compute the mean age of air (MAA) was employed. The CFD results have been also validated with experimental measurements from a home-made 1:4 small-scale mock-up. The optimal position of the purifier is on the larger sidewall of the cabins for a downward blowing direction (case 1 of the database). Flow rates in the range of 0.4–0.6 m3/min, depending on the size of the cabin, are sufficient to assure a correct ventilation. Upward blowing may be preferable only if interaction of the jet core with the ceiling or other flow deflecting elements are found. In general, the contribution of infiltrations (reaching values of up to 10%), and how these secondary flows interact with the main flow pattern driven by the purifier, is relevant and not considered previously in the literature. Though an optimal position can improve ventilation considerably, it has been proven that a good choice of the purification flow rate is more critical to ensure an adequate air renewal. © 2022 The Authors

Scenario for Analysing Student Interactions and Orchestration Load in Collaborative and Hybrid Learning Environments

Educational environments have been affected by the COVID-19 pandemic and have evolved to support classes, which involve in some cases synchronous hybrid learning environments. These environments enable students attend classes online and on-site simultaneously. Synchronous hybrid environments provide a greater flexibility for students but, in contrast, are likely to increase teachers’ orchestration load and decrease interactions between students, especially between those online and those on-site. This study proposes a scenario to explore the factors affecting the orchestration load and the student interactions in collaborative and synchronous hybrid learning environments. The scenario involves the use of a collaborative learning flow pattern (jigsaw) and the technologies that will enable the data collection to understand such factors affecting to orchestration load and interaction. The outcomes from the implementation of this scenario will provide useful insights to further understand the benefits and limitations of synchronous hybrid learning environments. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Numerical evaluation on indoor environment quality during high numbers of occupied passengers in the departure hall of an airport terminal

The rapid development of airports and the rapid spread of coronavirus disease 2019 (COVID-19) have brought increased attention to indoor environment quality, airflow organization, key pollutant dispersion, and ventilation modes in airport terminals. However, the characteristics of these parameters, especially carbon dioxide (CO2) and aerosol diffusion, are not fully understood. Therefore, in this study, the airflow patterns;CO2 and aerosol dispersion;and several thermal environment indices, including temperature, wind velocity, and predicted mean vote (PMV), of an airport terminal departure hall with high numbers of occupied passenger were numerically evaluated using the realizable k-epsilon and passive scalar models. The efficacies of three common ventilation modes, namely, up-supply and up-return, up-supply and down-return with different sides, and up-supply and down-return with the same side, were evaluated based on the CO2 removal efficiency and spreading range of aerosols. The results indicated that under high numbers of occupied passenger conditions, these ventilation modes vary slightly, with respect to create a comfortable and healthy environment. In particular, the up-supply and down-return with different sides mode was the best among the modes considered, when comparing the indices of temperature, wind speed PMV, and CO2 emission efficiency. Conversely, with respect to decreasing the risk of aerosol exposure, the up-supply and down-return with the same side mode was the best. Overall, the results from this study provide fundamental information for predicting CO2 and aerosol exposure levels and will act as a reference for the design and operation of ventilation systems in airport terminal buildings.

A Numerical Study on Indoor Air Quality (IAQ) Designs for Hospital Waiting Room in the Context of COVID-19 for Hot and Warm Humidity Climate

COVID-19 is a virus originated from Corona Virus which can severe acute respiratory syndrome (SARS) symptoms such as chest pain, dry cough, fever, and difficulty breathing. The AC and ventilation system is not only important for the thermal comfort occupants but to ensure the room is safe and free from infectious virus. Thermal comfort is important measurement in indoor space which influenced by temperature, Relative Humidity (RH), airflow velocity and others. This research was executed and focused on lecture room in Bilik Persatuan 10, Universiti Malaysia Perlis (UniMAP) instead of real hospital waiting room. It comes with the room dimensions 11.87m (Length) x 5.17m (Width) x 2.93m (Height) for the numerical study. In addition, Computational Fluid Dynamics (CFD) analysis is used to investigate the air flow pattern and temperature distribution inside the room. By using software Ansys FLUENT 19, field experimental and simulation work can be compared which have 14.55% difference in temperature distribution. It is expected by increasing the air velocity of the AC inlet diffuser influence the pattern of airflow in the room, but average temperature remains same for all these conditions. © 2021 Institute of Physics Publishing. All rights reserved.