A numerical tool for assessing human thermal safety and thermal comfort in cold-weather activities.

This paper describes a newly developed software tool to evaluate human thermal safety and thermal comfort in cold-weather activities aimed at guiding users to arrange activity plans and select appropriate clothing ensembles. The software inputs include conditions of activity, environment, human body, and clothing ensemble. It outputs physiological temperatures, cold injury risks, thermal sensations, and thermal comforts in intuitive ways like cloud maps and curves. The software tool is characterized by (1) integration of a thermoregulatory model that predicts human thermophysiological responses under exercise conditions in cold environments, (2) the functions of clothing ensemble database and individual parameter database, (3) the human centric outputs that directly reflect human physiological and mental status, and (4) the user-friendly operation interface and output interface, as well as a wide applicability. The software is validated with human test studies covering ambient temperatures from - 30.6 to 5 °C, clothing ensembles from 1.34 to 3.20 clo, and activity intensities from 2 to 9 Mets. The average prediction RMSEs of core temperature, mean skin temperature, thermal sensation, and thermal comfort are 0.16 °C, 0.45 °C, 0.58, and 1.41, respectively. The software is an advanced expansion to current standards and guidance of cold exposure assessment and a meaningful tool for the fields of occupational health care, cold protection, and environmental ergonomics.

Public opinion changing patterns under the double-hazard scenario of natural disaster and public health event.

In the context of the COVID-19 epidemic, a "double-hazard scenario" consisting of a natural disaster and a public health event occurring simultaneously is likely to arise. Focusing on this double-hazard scenario, this study developed a new opinion dynamics model that verifies the effect of opinion dynamic in practical applications and extends the realistic meaning of the logic matrix. The new model can be used to quickly identify changing trends in public opinion about two co-occurring public safety events in China, helping the government to better anticipate and respond to these real double-hazard scenarios. The new model was tested with three real double-hazard scenarios involving natural disasters and public health events in China and the simulation results were analyzed. Using visualization and Pearson correlation coefficients to analyze more than a million items of network-wide public opinion data, the new model was found to show a good fit with reality. The study finally found that in China, public attention to both natural hazards and public health events was greater when these public safety events co-occurred (double-hazard scenario) than when they occurred separately (single-hazard scenarios). These results verify the coupling phenomenon of different disasters in a multi-hazard scenario at the information level for the first time, which is greatly meaningful for multi-hazard research.

Multi-person movement-induced airflow and the effects on virus-laden expiratory droplet dispersion in indoor environments.

The multi-person movement might cause complex induced airflow and affect the virus-laden expiratory droplet transmission in indoor environments. Using the dynamic mesh model in computational fluid dynamics, the multi-person movement with different personnel location distributions was realized. The induced airflow patterns, virus-laden droplet dispersion, and concentration distribution were investigated in detail. The results show that multi-person movement might intensify inter-regional convection, which has been rarely found in single-person movement conditions. Side-by-side distribution and ladder distribution of moving persons could cause a connected low-pressure area behind the moving persons, which might enhance lateral virus transport, especially where droplets might suspend at the height of the breathing zone. Not only 1-10 µm aerosols but also some 20-50 µm droplets are carried by the multi-person movement-induced airflow to over 3 m. Since the width of induced airflow is about 0.6-1.0 m, moving persons should keep enough horizontal distance (>1.0 m) to limit the air mixing and virus-laden droplet transmission. This paper could provide a detailed reference for the numerical study of multi-person movement-induced airflow patterns, droplet dispersion, and indoor infection control.

COVID-19 virus released from larynx might cause a higher exposure dose in indoor environment.

COVID-19 virus can replicate in the infected individual's larynx independently, which is different from other viruses that replicate in lungs only, e.g. SARS. It might contribute to the fast spread of COVID-19. However, there are few scientific reports about quantitative comparison of COVID-19 exposure dose (inhalation dose and adhesion dose) for the susceptible individual when the viruses were released from the larynx or lungs. In this paper, a typical numerical model was built based on a breathing human model with real respiratory tract. By using a computational fluid dynamics (CFD) method, two kinds of virus released sites in the infected individual's respiratory tract (larynx, lungs), seven kinds of particle sizes between 1 and 50 µm, three kinds of expiratory flow rates: calm (10 L/min), moderate (30 L/min) and intense (90 L/min) were used to compare the particle deposition proportion and escape proportion. The inhalation dose and the adhesion dose of the susceptible individual were quantified. The results showed that COVID-19 virus-containing droplets and aerosols might be released into the environment at higher proportions (39.1%-44.2%) than viruses that replicate in lungs only (15.3%-37.1%). The exposure doses (inhalation dose and adhesion dose) of the susceptible individual in different situations were discussed. The susceptible individual suffered a higher exposure dose when the viruses were released from the larynx rather than lungs (the difference for 1 µm particles was 1.2-2.2 times). This study provides a possible explanation for the higher transmission risk of COVID-19 virus compared to other viruses and some control advice of COVID-19 in typical indoor environments were also discussed.

A Risk Assessment Method for Multi-Hazard Coupling Disasters.

Multi-hazard coupling disasters, in which multiple hazards occur simultaneously and interact to compound the consequences, are a common phenomenon. The assessment of the individual risk in multi-hazard coupling disasters faces several difficulties due to the nonlinear additivity of risks from multiple hazards. This article presents the Choquet integral multiple linear regression model as a method of overcoming the problems of nonlinear additivity. Using this method, the nonlinear additive individual risks of multi-hazard coupling disasters can be superposed with the nonadditivity of the fuzzy measure during the Choquet integral and the nonlinearity of the Choquet integral itself. This method also takes into account the effects of magnification on the severity of disasters and the vulnerability of victims in multi-hazard disasters. It provides the magnification coefficients to quantitatively calculate the risks of all disasters. To examine the efficacy of the risk-assessment measure, this article uses as a case study the severe fire and explosion disaster that occurred in a port at Tianjin, China, in 2015. From this case study, it can be concluded that the composite individual risk of multi-hazard coupling disasters is greater than that of the simple addition of the risk of each hazard. This finding indicates that multi-hazard coupling disasters are more severe than disasters involving single hazards. Moreover, this risk-assessment method provides guidance in preventing, estimating, and dealing with multi-hazard coupling disasters. It can also provide solutions to complex risk-analysis problems in fields, such as finance, economics, and information science.

Experimental study on individual risk in crowds based on exerted force and human perceptions.

Frequent and intense interactions between individuals inevitably occur in crowd disasters. Previous studies indicate that the primary risk evaluation parameters for individuals in crowds during these interactions are exerted force and its duration. In this study, a series of controlled laboratory experiments simulating static and fluctuant loads were conducted to obtain real-time exerted force data and the associated individual subjective feelings. An individual risk evaluation method is then established to assign a specific individual risk value to each data set of exerted force and its duration according to the individuals' feelings. This method divides the range of risk value into three zones: comfortable zone, uncomfortable zone and crisis zone. The transition from an uncomfortable zone to crisis zone is not a single numerical value but a range that considers individual differences. The method presented in this paper can assist in developing pedestrian simulation models as well as managing crowd events. Practitioner summary: Accident surveys indicate that casualties and injuries usually occur under a long-term static load or heavy dynamic load. We tested human body extrusion experiments in four conditions, measured the real-time load intensity and duration of the individual's action on the thoracic cavity during the mutual extrusion process, and an individual risk evaluation method has been established based on the force exerted on the body and its duration to prevent crowd disasters. Abbreviations: NIST: National Institute of Standards and Technology; IREM: individual risk evaluation method; CPR: cardiopulmonary resuscitation.

Fate of the inhaled smoke particles from fire scenes in the nasal airway of a realistic firefighter: A simulation study.

Understanding the inhalation, transport and deposition of smoke particles during fire missions are important to evaluating the health risks for firefighters. In this study, measurements from Underwriters Laboratories' large-scale fire experiments on smoke particle size distribution and concentration in three residential fire scenes were incorporated into models to investigate the fate of inhaled toxic ultrafine particulates in a realistic firefighter nasal cavity model. Deposition equations were developed, and the actual particle dosimetry (in mass, number and surface area) was evaluated. A strong monotonic growth of nasal airway dosages of simulated smoke particles was identified for airflow rates and fire duration across all simulated residential fire scene conditions. Even though the "number" dosage of arsenic in the limited ventilation living room fire was similar to the "number" dosage of chromium in the living room, particle mass and surface area dosages simulated in the limited living room were 90-200 fold higher than that in the ventilated living room. These were also confirmed when comparing the dosimetry in the living room and the kitchen. This phenomenon implied that particles with larger size were the dominant factors in mass and surface area dosages. Firefighters should not remove the self-contained breathing apparatus (SCBA) during fire suppression and overhaul operations, especially in smoldering fires with limited ventilation.

Review on modeling heat transfer and thermoregulatory responses in human body.

Several mathematical models of human thermoregulation have been developed, contributing to a deep understanding of thermal responses in different thermal conditions and applications. In these models, the human body is represented by two interacting systems of thermoregulation: the controlling active system and the controlled passive system. This paper reviews the recent research of human thermoregulation models. The accuracy and scope of the thermal models are improved, for the consideration of individual differences, integration to clothing models, exposure to cold and hot conditions, and the changes of physiological responses for the elders. The experimental validated methods for human subjects and manikin are compared. The coupled method is provided for the manikin, controlled by the thermal model as an active system. Computational Fluid Dynamics (CFD) is also used along with the manikin or/and the thermal model, to evaluate the thermal responses of human body in various applications, such as evaluation of thermal comfort to increase the energy efficiency, prediction of tolerance limits and thermal acceptability exposed to hostile environments, indoor air quality assessment in the car and aerospace industry, and design protective equipment to improve function of the human activities.

Effect of human movement on airborne disease transmission in an airplane cabin: study using numerical modeling and quantitative risk analysis.

BACKGROUND: Airborne transmission of respiratory infectious disease in indoor environment (e.g. airplane cabin, conference room, hospital, isolated room and inpatient ward) may cause outbreaks of infectious diseases, which may lead to many infection cases and significantly influences on the public health. This issue has received more and more attentions from academics. This work investigates the influence of human movement on the airborne transmission of respiratory infectious diseases in an airplane cabin by using an accurate human model in numerical simulation and comparing the influences of different human movement behaviors on disease transmission. METHODS: The Eulerian-Lagrangian approach is adopted to simulate the dispersion and deposition of the expiratory aerosols. The dose-response model is used to assess the infection risks of the occupants. The likelihood analysis is performed as a hypothesis test on the input parameters and different human movement pattern assumptions. An in-flight SARS outbreak case is used for investigation. A moving person with different moving speeds is simulated to represent the movement behaviors. A digital human model was used to represent the detailed profile of the occupants, which was obtained by scanning a real thermal manikin using the 3D laser scanning system. RESULTS: The analysis results indicate that human movement can strengthen the downward transport of the aerosols, significantly reduce the overall deposition and removal rate of the suspended aerosols and increase the average infection risk in the cabin. The likelihood estimation result shows that the risk assessment results better fit the outcome of the outbreak case when the movements of the seated passengers are considered. The intake fraction of the moving person is significantly higher than most of the seated passengers. CONCLUSIONS: The infection risk distribution in the airplane cabin highly depends on the movement behaviors of the passengers and the index patient. The walking activities of the crew members and the seated passengers can significantly increase their personal infection risks. Taking the influence of the movement of the seated passengers and the index patient into consideration is necessary and important. For future studies, investigations on the behaviors characteristics of the passengers during flight will be useful and helpful for infection control.

Experimental and numerical study of physiological responses in hot environments.

This paper proposed a multi-node human thermal model to predict human thermal responses in hot environments. The model was extended based on the Tanabe's work by considering the effects of high temperature on heat production, blood flow rate, and heat exchange coefficients. Five healthy men dressed in shorts were exposed in thermal neutral (29 °C) and high temperature (45 °C) environments. The rectal temperatures and skin temperatures of seven human body segments were continuously measured during the experiment. Validation of this model was conducted with experimental data. The results showed that the current model could accurately predict the skin and core temperatures in terms of the tendency and absolute values. In the human body segments expect calf and trunk, the temperature differences between the experimental data and the predicted results in high temperature environment were smaller than those in the thermally neutral environment conditions. The extended model was proved to be capable of predicting accurately human physiological responses in hot environments.

Modelling physical contacts to evaluate the individual risk in a dense crowd.

Tumble and stampede in a dense crowd may be caused by irrational behaviours of individuals and always troubles the safety management of crowd activities. Risk evaluation based on pedestrian dynamical models can be regarded as an effective method of preventing crowd disasters. Here, a method depending on a combination of collision impulses and pushing forces was used to model the physical contacts between individuals in a dense crowd, by which the acceleration error during physical contacts caused by a traditional dynamical equation can be avoided. The human domino effect in a dense crowd could be successfully reproduced, and the crushing and trampling risk of a microscopic individual in a crowd could be quantitatively evaluated separately. This method provides a more reliable and integral data foundation for evaluating individual risk that shows better portability and repeatability than macroscopic crowd risk evaluation methods and will also be conducive to preventing crowd disasters.

Numerical study of transient indoor airflow and virus-laden droplet dispersion: Impact of interactive human movement.

Human movement affects indoor airflow and the airborne transmission of respiratory infectious diseases, which has attracted scholars. However, the interactive airflow between moving and stationary people has yet to be studied in detail. This study used the numerical method validated by experimental data to explore the transient indoor airflow and virus-laden droplet dispersion in scenes with interactive human movement. Human-shaped numerical models and the dynamic mesh method were adopted to realize human movement in scenes with different lateral distances (0.2-1.2 m) between a moving person and stationary (standing/sitting) persons. The interactive human movement obviously impacts other persons' respiratory airflow, and the lateral fusion ranged about 0.6 m. The interactive human movement strengthens the indoor airflow convection, and some exhaled virus-laden droplets were carried into wake flow and enhanced long-range airborne transmission. The impact of interactive human movement on sitting patients' exhalation airflow seems more evident than on standing patients. The impact might last over 2 min after movement stopped, and people in the affected area might be at a higher exposure. The results can provide a reference for epidemic control in indoor environments.

Transient and continuous effects of indoor human movement on nanoparticle concentrations in a sitting person's breathing zone.

Particle concentration in a sitting person's breathing zone can be influenced by human movement around the person, and the transient and continuous effects may differ. In this study, a set of full-scale experiments was conducted to sample the nanoparticle concentration in the breathing zone of a sitting thermal breathing manikin (STBM). The transient fluctuation of the nanoparticle concentration was recorded continuously and analyzed. The results showed that when a manikin moved (at 1 m/s) past the STBM, the nanoparticle concentration in the STBM's breathing zone decreased and reached its lowest after the standing manikin had passed, decreasing 37.6 (±5.7) % compared with the peak value. The average concentration in the STBM's breathing zone during influence periods was 5.18 (±0.99) % less than that during non-influence Periods (NP). This finding reflected the fact that the transient inhalation (over several seconds) of the STBM may be reduced by manikin movement. On the other hand, the exposure of the STBM increased 2.88 (±1.24) % when there was a continuously moving manikin compared with the stable state in a 10-min observation. This finding may be explained by the fuller mix of indoor air and nanoparticles caused by manikin movement, as well as the increase of nanoparticle suspension time. The difference in the transient and continuous effects of the manikin movement on the STBM's exposure shows the importance of considering these effects separately in different scenarios.

A Multi-Segmented Human Bioheat Model for Asymmetric High Temperature Environments.

In workplaces such as steel, power grids, and construction, firefighters and other workers often encounter non-uniform high-temperature environments, which significantly increase the risk of local heat stress and local heat discomfort for the workers. In this paper, a multi-segment human bioheat model is developed to predict the human thermal response in asymmetric high-temperature environments by considering the sensitivity of the modeling to angular changes in skin temperature and the effects of high temperatures on human thermoregulatory and physiological responses simultaneously. The extended model for asymmetric high-temperature environments is validated with the current model results and experimental data. The result shows that the extended model predicts the human skin temperature more accurately. Under non-uniform high-temperature conditions, the local skin temperature predictions are highly consistent with the experimental data, with a maximum difference of 2 °C. In summary, the proposed model can accurately predict the temperature of the human core and skin layers. It has the potential to estimate human physiological and thermoregulatory responses under uniform and non-uniform high-temperature environments, providing technical support for local heat stress and local thermal discomfort protection.

Synergic effects in the assessment of multi-hazard coupling disasters: Fires, explosions, and toxicant leaks.

The study of multi-hazard coupling disasters involves various challenges. One of the toughest challenges is analyzing the interactions between incidents, known as "synergic effects." As its research object, this paper takes multi-hazard coupling disasters involving fire, explosions, and toxicant leaks in hazardous chemicals scenarios. It aims to quantitatively analyze the synergic effects in such environments, taking into account the amplification of the severity of the incidents and the delay in the fire brigade intervention. A method based on Monte Carlo simulation and damage analysis was applied to assess the hazard of multi-hazard coupling disasters and demonstrate the impacts of synergic effects. The Monte Carlo simulations presented the cumulative distribution functions of the severities of incidents. To examine the effectiveness of the assessment method, a case study was conducted of the severe fire and explosion that occurred in a chemical plant in Yancheng, China, in 2019. The results show that the currently suggested safety distance from the chemical plant is insufficient due to the failure to take into account the synergic effects of multi-hazard coupling disasters. The influence radius of incidents involving hazardous chemicals may be further than 1500 m, instead of the 500 m safety distance required by the current regulations. The description of synergic effects in this paper may provide guidance in dealing with other multi-hazard coupling disasters.

Investigation of inhalation and exhalation flow pattern in a realistic human upper airway model by PIV experiments and CFD simulations.

In this study, flow field characteristics in the trachea region in a realistic human upper airway model were firstly measured by particle image velocimetry (PIV) in the air under three constant inhalation and exhalation conditions: 36 L/min, 64 L/min and 90 L/min, representing flow rates of 18 L/min, 32 L/min and 45 L/min in real human airway (the model was twice the size of a human airway). Computational fluid dynamics (CFD) analyses were performed on four turbulence models, with boundary conditions corresponding to the PIV experiments. The effects of flow rates and breathing modes on the airflow patterns were investigated. The CFD prediction results were compared with the PIV measurements and showed relatively good agreement in all cases. During inhalation, the higher the flow rates, the less significant the "glottal jet" phenomenon, and the smaller the area of the separation zone. The air in the nasal inhalation condition accelerated more dramatically after glottis. The SST-Transition model was the best choice for predicting inhalation velocity profiles. For exhalation condition, the maximum velocity was much smaller than that during inhalation due to the more uniform flow field. The exhalation flow rates and breathing modes had little effect on the flow characteristics in the trachea region. The RNG k - ε model and SST k - ω model were recommended to simulate the flow field in the respiratory tract during exhalation.

Impact of travel patterns on epidemic dynamics in heterogeneous spatial metapopulation networks.

We report the results of a series of simulations of a susceptible-infected-recovered epidemic model in heterogeneous spatial metapopulation networks with quantitative knowledge of human traveling statistics that human travel behavior obeys scaling laws in the sense of geographical distance and period of waiting time. By tuning the edge length distribution of the spatial metapopulation network, we can conveniently control the distribution of human travel distance. The simulation results show that the occurrence probability of global outbreaks is significantly dependent on the characteristic travel distance, the characteristic waiting time, and the memory effects of human travel. We also present some preliminary results on the effects of travel restrictions in epidemic control.

Assessment of occupant-behavior-based indoor air quality and its impacts on human exposure risk: A case study based on the wildfires in Northern California.

The recent wildfires in California, U.S., have caused not only significant losses to human life and property, but also serious environmental and health issues. Ambient air pollution from combustion during the fires could increase indoor exposure risks to toxic gases and particles, further exacerbating respiratory conditions. This work aims at addressing existing knowledge gaps in understanding how indoor air quality is affected by outdoor air pollutants during wildfires-by taking into account occupant behaviors (e.g., movement, operation of windows and air-conditioning) which strongly influence building performance and occupant comfort. A novel modeling framework was developed to simulate the indoor exposure risks considering the impact of occupant behaviors by integrating building energy and occupant behaviour modeling with computational fluid dynamics simulation. Occupant behaviors were found to exert significant impacts on indoor air flow patterns and pollutant concentrations, based on which, certain behaviors are recommended during wildfires. Further, the actual respiratory injury level under such outdoor conditions was predicted. The modeling framework and the findings enable a deeper understanding of the actual health impacts of wildfires, as well as informing strategies for mitigating occupant health risk during wildfires.

Cellular automata-based systematic risk analysis approach for emergency response.

Emergency response is directly related to the allocation of emergency rescue resources. Efficient emergency response can reduce loss of life and property, limit damage from the primary impact, and minimize damage from derivative impacts. An appropriate risk analysis approach in the event of accidents is one rational way to assist emergency response. In this article, a cellular automata-based systematic approach for conducting risk analysis in emergency response is presented. Three general rules, i.e., diffusive effect, transporting effect, and dissipative effect, are developed to implement cellular automata transition function. The approach takes multiple social factors such as population density and population sensitivity into consideration and it also considers risk of domino accidents that are increasing due to increasing congestion in industrial complexes of a city and increasing density of human population. In addition, two risk indices, i.e., individual risk and aggregated weighted risk, are proposed to assist decision making for emergency managers during emergency response. Individual risk can be useful to plan evacuation strategies, while aggregated weighted risk can help emergency managers to allocate rescue resources rationally according to the degree of danger in each vulnerable area and optimize emergency response programs.

Integrating a human thermoregulatory model with a clothing model to predict core and skin temperatures.

This paper aims to integrate a human thermoregulatory model with a clothing model to predict core and skin temperatures. The human thermoregulatory model, consisting of an active system and a passive system, was used to determine the thermoregulation and heat exchanges within the body. The clothing model simulated heat and moisture transfer from the human skin to the environment through the microenvironment and fabric. In this clothing model, the air gap between skin and clothing, as well as clothing properties such as thickness, thermal conductivity, density, porosity, and tortuosity were taken into consideration. The simulated core and mean skin temperatures were compared to the published experimental results of subject tests at three levels of ambient temperatures of 20 °C, 30 °C, and 40 °C. Although lower signal-to-noise-ratio was observed, the developed model demonstrated positive performance at predicting core temperatures with a maximum difference between the simulations and measurements of no more than 0.43 °C. Generally, the current model predicted the mean skin temperatures with reasonable accuracy. It could be applied to predict human physiological responses and assess thermal comfort and heat stress.