Skip to main content
SpringerLink
Log in

Impact of human body shape on forced convection heat transfer

  • Original Paper
  • Published:
International Journal of Biometeorology Aims and scope Submit manuscript

Abstract

Predicting human thermal comfort and safety requires quantitative knowledge of the convective heat transfer between the body and its surrounding. So far, convective heat transfer coefficient correlations have been based only upon measurements or simulations of the average body shape of an adult. To address this knowledge gap, here we quantify the impact of adult human body shape on forced convection. To do this, we generated fifty three-dimensional human body meshes covering 1st to 99th percentile variation in height and body mass index (BMI) of the USA adult population. We developed a coupled turbulent flow and convective heat transfer simulation and benchmarked it in the 0.5 to 2.5 m·s−1 air speed range against prior literature. We computed the overall heat transfer coefficients, hoverall, for the manikins for representative airflow with 2 m·s−1 uniform speed and 5% turbulence intensity. We found that hoverall varied only between 19.9 and 23.2 W·m−2 K−1. Within this small range, the height of the manikins had negligible impact while an increase in the BMI led to a nearly linear decrease of the hoverall. Evaluation of the local coefficients revealed that those also nearly linearly decreased with BMI, which correlated to an inversely proportional local area (i.e., cross-sectional dimension) increase. Since even the most considerable difference that exists between 1st and 99th percentile BMI manikins is less than 15% of hoverall of the average manikin, it can be concluded that the impact of the human body shape on the convective heat transfer is minor.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data availability

The manikin models are available on the ASU Dataverse website (dataverse.asu.edu/dataverse/thermal-manikins).

Abbreviations

\({h}_{overall}\) :

Overall heat transfer coefficient, (W·m−vK−v)

\(\nu\) :

Air speed (m·s−1)

\(BMI\) :

Body mass index (kg·m−2)

References

  • Belghazi K, Elabbassi EB, Tourneux P, Libert J (2005) Assessment of whole body and regional evaporative heat loss coefficients in very premature infants using a thermal mannequin: influence of air velocity. Med Phys 32:752–758

    Article  Google Scholar 

  • Bergman TL, Lavine AS, Incropera FP, Dewitt DP (2011) Fundamentals of heat and mass transfer. John Wiley & Sons Inc, New York

    Google Scholar 

  • Coull NA, West AM, Hodder SG et al (2021) Body mapping of regional sweat distribution in young and older males. Eur J Appl Physiol 121:109–125

    Article  Google Scholar 

  • Daniell N, Fraysse F, Paul G (2012) How does the size and shape of local populations in China compare to general anthropometric surveys currently used for product design? Work 41:4088–4090

    Article  Google Scholar 

  • Davoudiantalab AHDA, Meshkani M, Nourian S, Mofidi AA (2013) Anthropometric dimensions of Iranian male workers and comparison with three Asian countries. Int J Occup Hyg 5:166–171

    Google Scholar 

  • de Dear RJ, Arens E, Hui Z, Oguro M (1997) Convective and radiative heat transfer coefficients for individual human body segments. Int J Biometeorol 40:141–156

    Article  Google Scholar 

  • Defraeye T, Blocken B, Koninckx E et al (2011) Computational fluid dynamics analysis of drag and convective heat transfer of individual body segments for different cyclist positions. J Biomech 44:1695–1701

    Article  Google Scholar 

  • Dreyfuss H (1993) The measure of man and woman: human factors in design, 2nd edn. Whitney Library of Design, New York

    Google Scholar 

  • Ebi KL, Capon A, Berry P et al (2021) Hot weather and heat extremes: health risks. Lancet 398:698–708

    Article  Google Scholar 

  • Ebi KL, Vanos J, Baldwin JW et al (2021) Extreme weather and climate change: population health and health system implications. Annu Rev Public Health 42:293

    Article  Google Scholar 

  • Elabbassi EB, Chardon K, Bach V et al (2002) Head insulation and heat loss in naked and clothed newborns using a thermal mannequin. Med Phys 29:1090–1096

    Article  Google Scholar 

  • Fanger PO (1972) Thermal comfort. McGraw-Hill Book Company, New York

    Google Scholar 

  • Fiala D, Havenith G (2015) Modelling human heat transfer and temperature regulation. The mechanobiology and mechanophysiology of military-related injuries. Springer, Cham, pp 265–302

    Chapter  Google Scholar 

  • Fiala D, Lomas KJ, Stohrer M (1999) A computer model of human thermoregulation for a wide range of environmental conditions: the passive system. J Appl Physiol 87(5):1957–1972

    Article  CAS  Google Scholar 

  • Fournet D, Ross L, Voelcker T et al (2013) Body mapping of thermoregulatory and perceptual responses of males and females running in the cold. J Therm Biol 38:339–344

    Article  Google Scholar 

  • Fromuth RC, Parkinson MB (2008) Predicting 5th and 95th percentile anthropometric segment lengths from population stature. Proceedings of the ASME 2008 Int Des Eng Tech Conf Comput Inf Eng Conf, Brooklyn, NY, pp 581–588

    Google Scholar 

  • Hannouch A, Habchi C, Lemenand T, Khoury K (2020) Numerical evaluation of the convective and radiative heat transfer coefficients for preterm neonate body segments inside an incubator. Build Environ 183:107085

    Article  Google Scholar 

  • Haslam RA, Parsons KC (1987) A comparison of models for predicting human response to hot and cold environments. Ergonomics 30:1599–1614

    Article  CAS  Google Scholar 

  • Hilpert R (1933) Heat transfer from cylinders. Forsch Geb Ingenieurwes 4:215

    Article  CAS  Google Scholar 

  • Ichihara M (1997) Measurement of convective and radiative hear transfer coefficients for the standing and sitting human body using a thermal manikin. J Archit Plann Environ Eng, AIJ 501:45–51

    Article  Google Scholar 

  • Ito K, Hotta T (2006) Development of virtual manikins and its grid library for CFD analysis.Trans Soc Heat, Air Cond Sanitary Eng Japan 113:27–33

  • Li C, Ito K (2012) Numerical analysis of convective heat and mass transfer around human body under strong wind. Int J High-Rise Build 1:107–116

    Google Scholar 

  • Lin Y-C, Wang M-JJ, Wang EM (2004) The comparisons of anthropometric characteristics among four peoples in East Asia. Appl Ergon 35:173–178

    Article  Google Scholar 

  • Mao N, Song M, Pan D, Deng S (2017) Computational fluid dynamics analysis of convective heat transfer coefficients for a sleeping human body. Appl Therm Eng 117:385–396

    Article  Google Scholar 

  • Martinho N, Lopes A, Silva MCG et al (2007) Human numerical model for evaluation of thermal comfort in vehicles. 1th European Automotive Congress - Automobile for the Futur, Budepest, pp 1–10

    Google Scholar 

  • Mora C, Dousset B, Caldwell IR et al (2017) Global risk of deadly heat. Nat Clim Chang 7:501–506

    Article  Google Scholar 

  • Nishi Y, Gagge AP (1970) Direct evaluation of convective heat transfer coefficient by naphthalene sublimation. J Appl Physiol 29:830–838

    Article  CAS  Google Scholar 

  • Oguro M, Arens E, Zhang H, Katayama T (2002) Convective heat transfer coefficients and clothing insulations for parts of the clothed human body under airflow conditions. J Architec Plan 67:21–29

    Article  Google Scholar 

  • Oliveira AVM, Gaspar AR, Francisco SC, Quintela DA (2014) Analysis of natural and forced convection heat losses from a thermal manikin: comparative assessment of the static and dynamic postures. J Wind Eng Ind Aerodyn 132:66–76

    Article  Google Scholar 

  • Ono T, Murakami S, Ooka R, Omori T (2008) Numerical and experimental study on convective heat transfer of the human body in the outdoor environment. J Wind Eng Ind Aerodyn 96:1719–1732

    Article  Google Scholar 

  • Ostrowski Z, Rojczyk M (2018) Natural convection heat transfer coefficient for newborn baby. Heat Mass Transf 54:2395–2403

    Article  CAS  Google Scholar 

  • Parkinsons M (n.d.) Open Design Lab Manikin Fether. http://tools.openlab.psu.edu/tools/fetcher.php. Accessed 22 Mar 2023

  • Parsons K (2014) Human thermal environments: the effects of hot, moderate, and cold environments on human health, comfort, and performance. CRC Press

    Book  Google Scholar 

  • Parsons K (2019) Human heat stress. CRC Press

    Book  Google Scholar 

  • Rykaczewski K, Bartels L, Martinez DM, Viswanathan SH (2022a) Human body radiation area factors for diverse adult population. Int J Biometeorol 66:2357–2367

    Article  Google Scholar 

  • Rykaczewski K, Bartels L, Martinez DM, Viswanathan SH (2022b) Computational manikin for radiation simulation (male and female models covering 1–99% BMI and height diversity in US. https://doi.org/10.48349/ASU/ZCLKT6. Accessed 22 Mar 2023

  • Rykaczewski K, Vanos JK, Middel A (2022c) Anisotropic radiation source models for computational thermal manikin simulations based on common radiation field measurements. Build Environ 208:108636

    Article  Google Scholar 

  • Sarman I, Bolin D, Holmér I, Tunell R (1992) Assessment of thermal conditions in neonatal care: use of a manikin of premature baby size. Am J Perinatol 9:239–246

    Article  CAS  Google Scholar 

  • Vanos JK, Rykaczewski K, Middel A et al (2021) Improved methods for estimating mean radiant temperature in hot and sunny outdoor settings. Int J Biometeorol 65:967–983

    Article  Google Scholar 

  • Winslow C-E, Ap G, Herrington LP (1939) The influence of air movement upon heat losses from the clothed human body. American Journal of Physiology-Legacy Content 127:505–518

    Article  Google Scholar 

  • Wissler EH (2018) Human temperature control: a quantitative Approach, 1st edn. Springer, Berlin, Germany

    Book  Google Scholar 

  • Xu J, Psikuta A, Li J et al (2021a) A numerical investigation of the influence of wind on convective heat transfer from the human body in a ventilated room. Build Environ 188:107427

    Article  Google Scholar 

  • Xu J, Psikuta A, Li J et al (2019) Influence of human body geometry, posture and the surrounding environment on body heat loss based on a validated numerical model. Build Environ 166:106340

    Article  Google Scholar 

  • Xu J, Psikuta A, Li J et al (2021b) Evaluation of the convective heat transfer coefficient of human body and its effect on the human thermoregulation predictions. Build Environ 196:107778

    Article  Google Scholar 

  • Yu Y, Liu J, Chauhan K et al (2020) Experimental study on convective heat transfer coefficients for the human body exposed to turbulent wind conditions. Build Environ 169:106533

    Article  Google Scholar 

  • Zhang M, Li R, Li J et al (2021a) A 3D multi-segment thermoregulation model of the hand with realistic anatomy: development, validation, and parametric analysis. Build Environ 201:107964

    Article  Google Scholar 

  • Zhang M, Li R, Wu Y et al (2021b) Numerical study of the convective heat transfer coefficient of the hand and the effect of wind. Build Environ 188:107482

    Article  Google Scholar 

  • Zhou S, Niu J (2022) Measurement of the convective heat transfer coefficient of the human body in the lift-up design. In: E3S Web of Conferences. EDP Sciences, p 03001

  • Zou J, Liu J, Niu J, et al (2020) Convective heat loss from computational thermal manikin subject to outdoor wind environments. Build Environ 107469

Download references

Acknowledgements

The authors also acknowledge Research Computing at ASU for providing high-performance computing resources that have contributed to the research results reported within this paper.

Funding

This research was supported by the National Science Foundation Leading Engineering for America’s Prosperity, Health, and Infrastructure (LEAP HI) #2152468 award (KR) and Master’s Opportunity for Research in Engineering from Fulton Schools of Engineering at Arizona State University (SHV).

Author information

Authors and Affiliations

  1. School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe, AZ, 85287, USA

    Shri H. Viswanathan, Daniel M. Martinez, Lyle Bartels, Sai S. Guddanti & Konrad Rykaczewski

  2. Julie Ann Wrigley Global Futures Laboratory, Arizona State University, Tempe, AZ, 85287, USA

    Konrad Rykaczewski

Authors
  1. Shri H. Viswanathan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daniel M. Martinez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lyle Bartels
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sai S. Guddanti
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Konrad Rykaczewski
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization and methodology: KR, SHV, LB, DMM, and SSG. Analysis: KR and SHV. Writing—original draft: SHV and KR. Writing—review and editing: SHV, and KR. Final review and editing: SHV, KR, LB, DMM, and SSG.

Corresponding author

Correspondence to Konrad Rykaczewski.

Ethics declarations

Conflicts of interest

The authors declare no competing interests.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 3631 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Viswanathan, S.H., Martinez, D.M., Bartels, L. et al. Impact of human body shape on forced convection heat transfer. Int J Biometeorol 67, 865–873 (2023). https://doi.org/10.1007/s00484-023-02461-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00484-023-02461-z

Keywords

Search

Navigation