Investigation of transient and heterogeneous micro-climate around a human body in an enclosed personalized work environment

Abstract Heterogeneous distribution of indoor environmental quality is known to have a great impact on human health, comfort, and productivity. A personalized work environment, that creates a localized and independent environment with capsules or partitions, is being developed worldwide to provide workers with a space that enables undisturbed concentration on studying and working. However, the minimized interior space of a personalized work environment can immediately cause adverse health impacts for occupant if the air quality and thermal environment in the personalized work environment is not controlled appropriately. Particularly, constant breathing can sharply increase the CO2 concentrations in an interior space with an insufficient ventilation rate. In order to design a healthy and comfortable indoor environment, especially in a personalized work environment, it is important to predict precisely and comprehensively the transient and heterogeneous structure of the indoor environment formed around a human body. With this background, we have developed an in silico human model that integrates a computational human model (virtual manikin combined with thermoregulation models) and respiratory model (virtual airway) for estimating indoor environmental quality, targeting the microclimate around a human body and breathing zone with high accuracy. In this study, we report the applicability of a comprehensive in silico human model to estimate the environmental quality in a personalized work environment. A coupled analysis of heat and contaminant transfer with computational fluid dynamics was conducted targeting the space around the in silico human model installed in a virtual personalized work environment. The informative data including human thermal comfort and breathing air quality were obtained, potentially forming the basis for the development of a digital twin of the personalized work environment and contributing to the design of a healthy, comfortable, and productive personalized work environment.

[1]  P. Wargocki,et al.  Literature survey on how different factors influence human comfort in indoor environments , 2011 .

[2]  Ken-ichi Abe,et al.  A new turbulence model for predicting fluid flow and heat transfer in separating and reattaching flows—I. Flow field calculations , 1995 .

[3]  Takashi Kurabuchi,et al.  CFD Benchmark Tests for Indoor Environmental Problems: Part 1, Isothermal/Non-Isothermal Flow in 2D and 3D Room Model , 2015 .

[4]  Kiao Inthavong,et al.  Particle and inhalation exposure in human and monkey computational airway models , 2018, Inhalation toxicology.

[5]  Kazuhide Ito,et al.  Prediction of convective heat transfer coefficient of human upper and lower airway surfaces in steady and unsteady breathing conditions , 2016 .

[6]  W. Fisk.  HEALTH AND PRODUCTIVITY GAINS FROM BETTER INDOOR ENVIRONMENTS AND THEIR RELATIONSHIP WITH BUILDING ENERGY EFFICIENCY , 2000 .

[7]  Np P. Gao,et al.  Investigating Indoor Air Quality and Thermal Comfort Using a Numerical Thermal Manikin , 2007 .

[8]  Zhu,et al.  A Review of CFD Analysis Methods for Personalized Ventilation (PV) in Indoor Built Environments , 2019, Sustainability.

[9]  Jan A. J. Stolwijk,et al.  A mathematical model of physiological temperature regulation in man , 1971 .

[10]  Ryozo Ooka,et al.  Development of a Computational Thermal Manikin Applicable in a Non-Uniform Thermal Environment—Part 2: Coupled Simulation Using Sakoi's Human Thermal Physiological Model , 2008 .

[11]  Z. Lian,et al.  Effects of thermal discomfort in an office on perceived air quality, SBS symptoms, physiological responses, and human performance. , 2011, Indoor air.

[12]  W. Fisk,et al.  Is CO2 an Indoor Pollutant? Direct Effects of Low-to-Moderate CO2 Concentrations on Human Decision-Making Performance , 2012, Environmental health perspectives.

[13]  Ryozo Ooka,et al.  Development of a Computational Thermal Manikin Applicable in a Nonuniform Thermal Environment—Part 1: Coupled Simulation of Convection, Radiation, and Smith's Human Thermal Physiological Model for Sensible Heat Transfer from a Seated Human Body in Radiant Environment , 2007 .

[14]  Chao-Hsin Lin,et al.  Characterizing exhaled airflow from breathing and talking. , 2010, Indoor air.

[15]  Takashi Kurabuchi,et al.  CFD Benchmark Tests for Indoor Environmental Problems: Part 4, Air-conditioning Airflows, Residential Kitchen Airflows and Fire-Induced Flow , 2015 .

[16]  D P Wyon,et al.  The effects of indoor air quality on performance and productivity. , 2004, Indoor air.

[17]  D N Sørensen,et al.  Quality control of computational fluid dynamics in indoor environments. , 2003, Indoor Air: International Journal of Indoor Environment and Health.

[18]  Kazuhide Ito,et al.  Investigation of flow pattern in upper human airway including oral and nasal inhalation by PIV and CFD , 2015 .

[19]  Takashi Kurabuchi,et al.  CFD Benchmark Tests for Indoor Environmental Problems: Part 2, Cross-Ventilation Airflows and Floor Heating Systems , 2015 .

[20]  J D Hardy,et al.  Partitional calorimetric studies of responses of man to thermal transients. , 1966, Journal of applied physiology.

[21]  Takashi Kurabuchi,et al.  CFD Benchmark Tests for Indoor Environmental Problems: Part 3, Numerical Thermal Manikins , 2015 .

[22]  Kazuhide Ito,et al.  Numerical prediction of tissue dosimetry in respiratory tract using computer simulated person integrated with physiologically based pharmacokinetic–computational fluid dynamics hybrid analysis , 2017 .

[23]  J. A. J. Stolwijk,et al.  Temperature regulation in man — A theoretical study , 1966, Pflüger's Archiv für die gesamte Physiologie des Menschen und der Tiere.

[24]  Kazuhide Ito,et al.  Folded roof house—Design solution to optimize environmental conditions with generic equipment and techniques , 2018 .

[25]  J. Niu,et al.  Transient CFD simulation of the respiration process and inter-person exposure assessment , 2005, Building and Environment.

[26]  Olli Seppänen,et al.  A model to estimate the cost-effectiveness of improving office work through indoor environmental control , 2005 .

[27]  Kazuhide Ito,et al.  Assessment of transient inhalation exposure using in silico human model integrated with PBPK-CFD hybrid analysis , 2018, Sustainable Cities and Society.

[28]  Kazuhide Ito,et al.  Toward the development of an in silico human model for indoor environmental design , 2016, Proceedings of the Japan Academy. Series B, Physical and biological sciences.

[29]  Z. Lian,et al.  Quantitative measurement of productivity loss due to thermal discomfort , 2011 .

[30]  Hui Zhang,et al.  Coupling CFD and Human Body Thermoregulation Model for the Assessment of Personalized Ventilation , 2006 .