Chao-Hsin Lin

Characterizing exhaled airflow from breathing and talking

UNLABELLED The exhaled air of infected humans is one of the prime sources of contagious viruses. The exhaled air comes from respiratory events such as the coughing, sneezing, breathing and talking. Accurate information on the thermo-fluid characteristics of the exhaled airflow can be important for prediction of infectious disease transmission. The present study developed a source model to provide the thermo-fluid conditions of the exhaled air from the breathing and talking processes. The source model is a set of equations obtained from the measurements of the flow rate, flow direction, and area of mouth/nose opening with human subjects. It was found that the exhaled flow rate over time can be represented as a sinusoidal function for breathing and a constant for talking. The flow rates can be calculated by physiological parameters of a subject. The direction of the exhalation jet did not vary much between subjects and the area of mouth/nose opening could be regarded as a constant. Though the mouth/nose opening size varied among subjects, they were not correlated with the physiological parameters of the subjects. If combined with appropriate virus and droplet distribution information, the model can be used to describe the disease source due to breathing and talking. PRACTICAL IMPLICATIONS Accurate prediction of airborne disease transmission, and the infection prone zones, can aid in identifying and implementing the control strategies. With the recent advancements, Computational Fluid Dynamics (CFD) has become a powerful tool in predicting the disease transmission. Accurate prediction of the transmission by these CFD simulations requires information on sources and sinks of infectious viruses and models for dispersion of these viruses. The exhaled air of an infected human is one of the prime sources of disease viruses. In the present study, measurements of the flow were conducted on human subjects to develop models for the flow boundary conditions for the exhalation and inhalation during breathing and talking.

Flow dynamics and characterization of a cough

UNLABELLED Airborne disease transmission has always been a topic of wide interests in various fields for decades. Cough is found to be one of the prime sources of airborne diseases as it has high velocity and large quantity of droplets. To understand and characterize the flow dynamics of a cough can help to control the airborne disease transmission. This study has measured flow dynamics of coughs with human subjects. The flow rate variation of a cough with time can be represented as a combination of gamma-probability-distribution functions. The variables needed to define the gamma-probability-distribution functions can be represented by some medical parameters. A robust multiple linear regression analysis indicated that these medical parameters can be obtained from the physiological details of a person. However, the jet direction and mouth opening area during a cough seemed not related to the physiological parameters of the human subjects. Combining the flow characteristics reported in this study with appropriate virus and droplet distribution information, the infectious source strength by coughing can be evaluated. PRACTICAL IMPLICATIONS There is a clear need for the scientific community to accurately predict and control the transmission of airborne diseases. Transportation of airborne viruses is often predicted using Computational Fluid Dynamics (CFD) simulations. CFD simulations are inexpensive but need accurate source boundary conditions for the precise prediction of disease transmission. Cough is found to be the prime source for generating infectious viruses. The present study was designed to develop an accurate source model to define thermo-fluid boundary conditions for a cough. The model can aid in accurately predicting the disease transmission in various indoor environments, such as aircraft cabins, office spaces and hospitals.

Transport of expiratory droplets in an aircraft cabin.

UNLABELLED The droplets exhaled by an index patient with infectious disease such as influenza or tuberculosis may be the carriers of contagious agents. Indoor environments such as the airliner cabins may be susceptible to infection from such airborne contagious agents. The present investigation computed the transport of the droplets exhaled by the index patient seated in the middle of a seven-row, twin-aisle, fully occupied cabin using the CFD simulations. The droplets exhaled were from a single cough, a single breath, and a 15-s talk of the index patient. The expiratory droplets were tracked by using Lagrangian method, and their evaporation was modeled. It was found that the bulk airflow pattern in the cabin played the most important role on the droplet transport. The droplets were contained in the row before, at, and after the index patient within 30 s and dispersed uniformly to all the seven rows in 4 minutes. The total airborne droplet fraction reduced to 48, 32, 20, and 12% after they entered the cabin for 1, 2, 3, and 4 min, respectively, because of the ventilation from the environmental control system. PRACTICAL IMPLICATIONS It is critical to predict the risk of airborne infection to take appropriate measures to control and mitigate the risk. Most of the studies in past either assume a homogenous distribution of contaminants or use steady-state conditions. The present study instead provides information on the transient movement of the droplets exhaled by an index passenger in an aircraft cabin. These droplets may contain active contagious agents and can be potent enough to cause infection. The findings can be used by medical professionals to estimate the spatial and temporal distribution of risk of infection to various passengers in the cabin.

State-of-the-art methods for studying air distributions in commercial airliner cabins

Abstract Air distributions in commercial airliner cabins are crucial for creating a thermally comfortable and healthy cabin environment. This paper reviews the methods used in predicting, designing, and analyzing air distributions in the cabins, among which experimental measurements and numerical simulations are the two popular ones. The experimental measurements have usually been seen as more reliable although they are more expensive and time consuming. Most of the numerical simulations use Computational Fluid Dynamics (CFD) that can provide effectively detailed information. Numerous applications using the two methods can be found in the literature for studying air distributions in aircraft cabins, including investigations on more reliable and accurate models. The review in the paper shows that the studies using both experimental measurements and computer simulations are becoming popular. And it is necessary to use a full-scale test rig to obtain reliable and high quality experimental data. What’s more, the hybrid CFD models are found to be rather promising for simulating air distributions in airliner cabins.

Risk assessment of airborne infectious diseases in aircraft cabins

UNLABELLED Passengers in an aircraft cabin can have different risks of infection from airborne infectious diseases such as influenza, severe acute respiratory syndrome (SARS), and tuberculosis (TB) because of the non-uniform airflow in an aircraft cabin. The current investigation presents a comprehensive approach to assessing the spatial and temporal distributions of airborne infection risk in an aircraft cabin. A case of influenza outbreak was evaluated in a 4-h flight in a twin-aisle, fully occupied aircraft cabin with the index passenger seated at the center of the cabin. The approach considered the characteristics of the exhalation of the droplets carrying infectious agents from the index passenger, the dispersion of these droplets, and the inhalation of the droplets by susceptible passengers. Deterministic and probabilistic approaches were used to quantify the risks based on the amount of inhaled influenza virus RNA particles and quanta, respectively. The probabilistic approach indicated that the number of secondary infection cases can be reduced from 3 to 0 and 20 to 11, for influenza cases if N95 respirator masks are used by the passengers. The approach and methods developed can easily be implemented in other enclosed spaces such as buildings, trains, and buses to assess the infection risk. PRACTICAL IMPLICATIONS Airborne infectious disease transmission could take place in enclosed environments such as buildings and transport vehicles. The infection risk is difficult to estimate, and very few mitigation methods are available. This study used a 4-h flight as an example in analyzing the infection risk from influenza and in mitigating the risk with an N95 mask. The results will be useful to the airline industry in providing necessary protection to passengers and crew, and the results can also be used for other enclosed spaces.

Experimental study of gaseous and particulate contaminants distribution in an aircraft cabin

Abstract The environment of the aircraft cabin greatly influences the comfort and health of passengers and crew members. Contaminant transport has a strong effect on disease spreading in the cabin environment. To obtain the complex cabin contaminant distribution fields accurately and completely, which is also essential to provide solid and precise data for computational fluid dynamics (CFD) model validation, this paper aimed to investigate and improve the method for simultaneous particle and gaseous contaminant fields measurement. The experiment was conducted in a functional MD-82 aircraft. Sulfur hexafluoride (SF6) was used as tracer gas, and Di-Ethyl-Hexyl-Sebacat (DEHS) was used as particulate contaminant. The whole measurement was completed in a part of the economy-class cabin without heating manikins or occupied with heating manikins. The experimental method, in terms of pollutant source setting, sampling points and schedule, was investigated. Statistical analysis showed that appropriately modified sampling grid was able to provide reasonable data. A small difference in the source locations can lead to a significant difference in cabin contaminant fields. And the relationship between gaseous and particulate pollutant transport was also discussed through tracking behavior analysis.

Predicting transient particle transport in enclosed environments with the combined computational fluid dynamics and Markov chain method

To quickly obtain information about airborne infectious disease transmission in enclosed environments is critical in reducing the infection risk to the occupants. This study developed a combined computational fluid dynamics (CFD) and Markov chain method for quickly predicting transient particle transport in enclosed environments. The method first calculated a transition probability matrix using CFD simulations. Next, the Markov chain technique was applied to calculate the transient particle concentration distributions. This investigation used three cases, particle transport in an isothermal clean room, an office with an underfloor air distribution system, and the first-class cabin of an MD-82 airliner, to validate the combined CFD and Markov chain method. The general trends of the particle concentrations vs. time predicted by the Markov chain method agreed with the CFD simulations for these cases. The proposed Markov chain method can provide faster-than-real-time information about particle transport in enclosed environments. Furthermore, for a fixed airflow field, when the source location is changed, the Markov chain method can be used to avoid recalculation of the particle transport equation and thus reduce computing costs.

A hybrid model for investigating transient particle transport in enclosed environments

Abstract It is important to accurately model person-to-person particle transport in mechanical ventilation spaces to create and maintain a healthy indoor environment. The present study introduces a hybrid DES-Lagrangian and RANS-Eulerian model for simulating transient particle transport in enclosed environments; this hybrid model can ensure the accuracy and reduce the computing cost. Our study estimated two key time constants for the model that are important parameters for reducing the computing costs. The two time constants estimated were verified by airflow data from both an office and an aircraft cabin case. This study also conducted experiments in the first-class cabin of an MD-82 commercial airliner with heated manikins to validate the hybrid model. A pulse particle source was applied at the mouth of an index manikin to simulate a cough. The particle concentrations versus time were measured at the breathing zone of the other manikins. The trend of particle concentrations versus time predicted by the hybrid model agrees with the experimental data. Therefore, the proposed hybrid model can be used for investigating transient particle transport in enclosed environments.

Inhalation of expiratory droplets in aircraft cabins

UNLABELLED Airliner cabins have high occupant density and long exposure time, so the risk of airborne infection transmission could be high if one or more passengers are infected with an airborne infectious disease. The droplets exhaled by an infected passenger may contain infectious agents. This study developed a method to predict the amount of expiratory droplets inhaled by the passengers in an airliner cabin for any flight duration. The spatial and temporal distribution of expiratory droplets for the first 3 min after the exhalation from the index passenger was obtained using the computational fluid dynamics simulations. The perfectly mixed model was used for beyond 3 min after the exhalation. For multiple exhalations, the droplet concentration in a zone can be obtained by adding the droplet concentrations for all the exhalations until the current time with a time shift via the superposition method. These methods were used to determine the amount of droplets inhaled by the susceptible passengers over a 4-h flight under three common scenarios. The method, if coupled with information on the viability and the amount of infectious agent in the droplet, can aid in evaluating the infection risk. PRACTICAL IMPLICATIONS The distribution of the infectious agents contained in the expiratory droplets of an infected occupant in an indoor environment is transient and non-uniform. The risk of infection can thus vary with time and space. The investigations developed methods to predict the spatial and temporal distribution of expiratory droplets, and the inhalation of these droplets in an aircraft cabin. The methods can be used in other indoor environments to assess the relative risk of infection in different zones, and suitable measures to control the spread of infection can be adopted. Appropriate treatment can be implemented for the zone identified as high-risk zones.

A Markov chain model for predicting transient particle transport in enclosed environments

Abstract Obtaining information about particle dispersion in a room is crucial in reducing the risk of infectious disease transmission among occupants. This study developed a Markov chain model for quickly obtaining the information on the basis of a steady-state flow field calculated by computational fluid dynamics. When solving the particle transport equations, the Markov chain model does not require iterations in each time step, and thus it can significantly reduce the computing cost. This study used two sets of experimental data for transient particle transport to validate the model. In general, the trends in the particle concentration distributions predicted by the Markov chain model agreed reasonably well with the experimental data. This investigation also applied the model to the calculation of person-to-person particle transport in a ventilated room. The Markov chain model produced similar results to those of the Lagrangian and Eulerian models, while the speed of calculation increased by 8.0 and 6.3 times, respectively, in comparison to the latter two models.