“…A seven-row cockpit model with a geometric model complexity coefficient (λ) of 3.67 was selected to compare different grid types. 61 The aircraft model and internal structure are shown in Figure 8.Figure 8.Geometric model of the aircraft cabin.…”
Proper meshing is critical for accurate computational fluid dynamics (CFD) simulation. In the three stages of CFD simulation, pre-processing accounts for about 40–60% of the total time. In this study, the performance of the grid for a large number of numerical simulations was analyzed, and base mesh sizes were recommended for different indoor geometric models. The simulation results for temperature, velocity, mesh resolution and computation time were compared, and mesh types were recommended for different models. Considering factors such as wall function, wall y+, face quality of the mesh, grid volume change rate and prism layer setting, a semi-empirical mesh strategy was presented. This strategy was verified in three cases with different geometric complexity. The verification results showed that the mesh strategy can yield reasonable simulation results. The root-mean-square error of the velocity simulation results of the optimized grid can be reduced by nearly 20%. This strategy can save nearly 50% of the mesh adjustment time. Through analysis and fitting of the grid results, the evaluation criteria for this mesh strategy were obtained. The criteria can be used to evaluate the cases using this mesh strategy.
“…A seven-row cockpit model with a geometric model complexity coefficient (λ) of 3.67 was selected to compare different grid types. 61 The aircraft model and internal structure are shown in Figure 8.Figure 8.Geometric model of the aircraft cabin.…”
Proper meshing is critical for accurate computational fluid dynamics (CFD) simulation. In the three stages of CFD simulation, pre-processing accounts for about 40–60% of the total time. In this study, the performance of the grid for a large number of numerical simulations was analyzed, and base mesh sizes were recommended for different indoor geometric models. The simulation results for temperature, velocity, mesh resolution and computation time were compared, and mesh types were recommended for different models. Considering factors such as wall function, wall y+, face quality of the mesh, grid volume change rate and prism layer setting, a semi-empirical mesh strategy was presented. This strategy was verified in three cases with different geometric complexity. The verification results showed that the mesh strategy can yield reasonable simulation results. The root-mean-square error of the velocity simulation results of the optimized grid can be reduced by nearly 20%. This strategy can save nearly 50% of the mesh adjustment time. Through analysis and fitting of the grid results, the evaluation criteria for this mesh strategy were obtained. The criteria can be used to evaluate the cases using this mesh strategy.
“…The review by Liu et al 23 , 25 concluded that it is necessary to use a full‐scale test rig to obtain reliable, high‐quality experimental data, and that hybrid CFD models should be used for simulating air distributions in airliner cabins. Figure 2 depicts the airflow distribution in a single‐aisle airliner cabin mock‐up with seven rows of seats, from a study by Cao et al 26 The investigation compared the airflow simulated by CFD with experimental data measured by ultrasonic anemometers.…”
Section: State‐of‐the‐art In Cabin Air Environment Designmentioning
confidence: 99%
“…The design of the cabins was intended to provide better thermal comfort, but it may facilitate the transmission of airborne infectious diseases. Figure 3 shows that droplets generated by a passenger can be transmitted to the entire cross section and several rows before and after an index patient in a cabin 26 , 50 .…”
Section: State‐of‐the‐art In Cabin Air Environment Designmentioning
According to the International Air Transport Association, 1 air transportation was a very popular mode of travel in 2019, as 4.5 billion people flew to various destinations around the world. However, the COVID-19 pandemic placed air travel on hold in 2020, when only 1.8 billion passengers flew, a decrease of 60.2% from the previous year.The worst month was April 2020, when airlines experienced a 94% reduction in passenger capacity worldwide. 2 A study by Boeing 3 showed that the global risk of COVID-19 transmission during air travel was 1 in 1.7 million. However, other studies have reported an attack rate of 9.7% to 62%. 4,5 The flying public has reasonable doubts about the ability of modern airliners to protect them from infection by airborne diseases such as COVID-19. Airborne infectious diseases are not the only source of concern for the flying public. Cabin air quality has become a very popular topic for research. The National Research Council in the United States 6 conducted a comprehensive review of the airliner cabin air
“…Yan et al [17] investigated the cough flow and its time-dependent jet effects on the transport of contaminants in a three-row Boeing 737 cabin. Cao et al [18] investigated the impact of the turbulence model, ventilation system, geometry simplification, particle simulation method, and boundary condition assignment on the airflow and particles distribution in airliner cabins with various ventilation systems. Ahmadzadeh et al [19] studied the impact of mechanical and natural ventilation on the distribution, transmission, and shelf life of COVID-19 particles inside a classroom due to coughing and speaking.…”
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