A multi-segmented human bioheat model for transient and asymmetric radiative environments

Al-Othmani, M; Ghaddar, Nesreen; Ghali, Kamel

doi:10.1016/j.ijheatmasstransfer.2008.04.017

Cited by 68 publications

(24 citation statements)

References 34 publications

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“…In the first case, the Berkeley model [6] provides more accuracy than the present model. Also, in the fourth case, the AUB [14] and the revised AUB [16] models predict the skin temperature more accurate than our simplified model. It should be pointed out again that the present model is a simplified and easy-to-implement model, but the Berkeley, AUB and the revised AUB are more detailed and complex models of the human body.…”

Section: Resultsmentioning

confidence: 76%

“…In Fig. 6, the simulated results of the present model are compared with Stolwijk and Hardy [38] measurements and also simulation results of AUB model [14] and revised AUB model [16] for (a) skin temperature and (b) core temperature. As can be seen in Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Fig. 7 demonstrates the experimental data of Raven and Horvath [39] and simulated results of Berkeley model [6], AUB model [14], revised AUB model [16] and the present model for head skin temperature. A very good agreement between the experimental data [39] and obtained results from the present model is observed.…”

Section: Resultsmentioning

confidence: 99%

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A new simplified thermoregulatory bioheat model for evaluating thermal response of the human body to transient environments

Zolfaghari

Maerefat

2010

Building and Environment

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a b s t r a c tThermal response of the human cutaneous thermoreceptors depends statically upon temperature and dynamically on the temperature change rate at the depth of the thermoreceptors. Therefore, it is very important to estimate the time-dependent thermoreceptors temperature with a good accuracy. On the other hand, the temperature distribution in skin tissue may be significantly affected by thermoregulatory mechanisms such as shivering, regulatory sweating and vasomotion. In the present study, a new simplified thermoregulatory bioheat model is proposed to describe heat transfer in skin tissue. The new model is constructed by combining the well-known Pennes equations with Gagge's two-node model. In this model, the human skin is subdivided into three layers (epidermis, dermis and subcutaneous) and the time-dependent temperature of skin tissue is obtained by solving the bioheat equations taking into account thermoregulatory mechanisms. The model has been verified by extensive comparisons with the published analytical and experimental results where a good agreement was found. Therefore, the present model can estimate the skin temperature under transient environments with a very good accuracy.

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Section: Resultsmentioning

confidence: 76%

Section: Resultsmentioning

confidence: 99%

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A new simplified thermoregulatory bioheat model for evaluating thermal response of the human body to transient environments

Zolfaghari

Maerefat

2010

Building and Environment

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“…swt fg Q m h (16) Where swt m is the regulatory sweat mass flow rate (kg/s) and fg h is the heat of vaporization of sweating = 2430 (kJ/kg). Alsouqi et al [27] have suggested the mathematical relation between sweating flow rate and human body core temperature as follows: 165.75 6084 = − sw cor m T (17) …”

Section: Heat Loss By Evaporation From Skinmentioning

confidence: 99%

“…There are several other researchers that use multisegmented models such as Wissler [4,5], Gordon et al [6], Tikuisis et al [7], Werner [8], Takemori et al [9], Fiala et al [10,11], Huizenga et al [12], Tanabe et al [13], Salloum et al [14], Wan and Fan [15], and Al-Othmani et al [16]. They have used their models in evaluating more advanced situations such as assessing the local thermal comfort and human physiological responses to cold water immersion.…”

Section: Introductionmentioning

confidence: 99%

Heat losses from human body in weather condition of Amman city

Gaith

Sedaghat

Assad

2015

2015 International Conference on Industrial Engineering and Operations Management (IEOM)

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It is wrongly anticipated that the amount of fats burn in human body is related to the amount of sweating, particularly in hot months of the year. In this study, heat losses from human body are studied based on clothing habit, weather condition in Amman city, and the bio-heat transfer mechanisms. The heat losses from human body include breathing (evaporation), conduction, convection, and radiation mechanisms. It is shown that heat losses are largely prevailed by conduction and radiation compared with convection and breathing mechanisms in all months of the year. It is also realized that the heat loss by breathing air is totally depends on the dry bulb temperature of the ambient. The heat loss by convection mechanism depends on many parameters such as clothes temperature, Nusselt number, and heat convection coefficient. The heat loss by radiation mechanism depends mainly on temperature differences between clothes surface and ambient. From the results of this study, the human body losses more heat in spring and winter than summer and autumn. It is also concluded that human body burns more fats during winter and spring seasons than summer and autumn.

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Thermal Indices and Thermophysiological Modeling for Heat Stress

Havenith

Fiala

2015

Comprehensive Physiology

175

184

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The assessment of the risk of human exposure to heat is a topic as relevant today as a century ago. The introduction and use of heat stress indices and models to predict and quantify heat stress and heat strain has helped to reduce morbidity and mortality in industrial, military, sports, and leisure activities dramatically. Models used range from simple instruments that attempt to mimic the human-environment heat exchange to complex thermophysiological models that simulate both internal and external heat and mass transfer, including related processes through (protective) clothing. This article discusses the most commonly used indices and models and looks at how these are deployed in the different contexts of industrial, military, and biometeorological applications, with focus on use to predict related thermal sensations, acute risk of heat illness, and epidemiological analysis of morbidity and mortality. A critical assessment is made of tendencies to use simple indices such as WBGT in more complex conditions (e.g., while wearing protective clothing), or when employed in conjunction with inappropriate sensors. Regarding the more complex thermophysiological models, the article discusses more recent developments including model individualization approaches and advanced systems that combine simulation models with (body worn) sensors to provide real-time risk assessment. The models discussed in the article range from historical indices to recent developments in using thermophysiological models in (bio) meteorological applications as an indicator of the combined effect of outdoor weather settings on humans.

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A multi-segmented human bioheat model for transient and asymmetric radiative environments

Cited by 68 publications

References 34 publications

A new simplified thermoregulatory bioheat model for evaluating thermal response of the human body to transient environments

A new simplified thermoregulatory bioheat model for evaluating thermal response of the human body to transient environments

Heat losses from human body in weather condition of Amman city

Thermal Indices and Thermophysiological Modeling for Heat Stress

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