Procedia Engineering 84 ( 2014 ) 893 – 897
1877-7058 © 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
Peer-review under responsibility of scientific committee of Beijing Institute of Technology doi: 10.1016/j.proeng.2014.10.512
ScienceDirect
“
2014
ISSST”, 2014 International Symposium on Safety Science and Technology
Coupling of a thermal sweating manikin and a thermal model for
simulating human thermal response
YANG Jie*, WENG Wenguo, FU Ming
Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing, 100084, P.R. China
Abstract
This paper is dedicated to simulate human thermal response in transient condition with a coupling system which combines a thermal sweating manikin with a thermal model. The thermal model is applied to provide skin temperature and sweating rate for the thermal sweating manikin, the thermal sweating manikin is used to measure the heat exchange between the human body and the environment. The performance of the coupling system is validated by comparison with human tests from literature. The predicted results show a good agreement with the experimental results in terms of both the tendency and absolute values for mean skin temperature, local skin temperature, and core temperature. The results suggest the coupling system can accurately predict local and overall human thermal response in transient conditions.
© 2014 The Authors. Published by Elsevier Ltd.
Peer-review under responsibility of scientific committee of Beijing Institute of Technology. Keywords: thermal sweating manikin; thermal model; transient condition; human thermal response
1.Introduction
Knowledge of human thermal response in transient environmental conditions is widely used in car industry, military, HVAC systems for buildings, textile industry, and environment protection [1]. Mathematical models and thermal manikins are valuable tools to understand the human thermal response under different environmental conditions.
Since the first manikin was introduced in the early1940s, more and more manikins have been made and used to the study of clothing properties and thermal interface with environment [2]. It is now possible for the manikin to
* Corresponding author. Tel.: +86-1881153901. E-mail address: yangjiesxu@163.com.
© 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).
simulate human behavior such as sweating, breathing, and moving. Huang [3] used a manikin to measure clothing properties which were applied for the prediction of the physiological variables under heat stress conditions. Qian [4] investigated the interaction of surface heat and moisture transfer from the human body under different environment conditions using a sweating manikin. In addition, many international standards related with manikins have been developed to measure clothing properties and assess the tissue burn injury.
Many mathematical models have been used to predict human thermal response in recent years. Stolwijk [5] developed a multi-segment thermal model, in this model human body was divided into six segments and each segment was divided into four layers, representing skin, fat, muscle and core layer. Several multi-segment models have been developed by other authors, e.g. Tanabe [6], Salloum [7], Fiala [8].
The manikin measures heat exchange with environment in a repeatable and accurate way, but are unable to respond dynamically to the thermal environment as real human [9]. The mathematic model can provide signals for the manikin which would feel the thermal environment and response like human [10]. The aim of this work is to develop a coupling system which can simulate human thermal responses in transient environmental conditions. A multi-node thermal model is proposed to provide skin temperature and sweating rate for the manikin. The validation of the coupling system is conducted in a climate chamber, and the simulated results are compared with experimental results.
2.Method
2.1.Thermal model
The thermal model is developed based on the work of Tanabe with several improvements to simulate human thermal response in steady and transient environmental conditions. In this model, the human body is divided into 20 segments (face, head, right upper arm, left upper arm, right foreman, left foreman, right hand, left hand, chest, shoulders, stomach, back, right hip, left hip, right thigh, left thigh, right calf, left calf, right foot, and left foot), each segment consists four layers (core, muscle, fat, and skin layer) and a clothing layer. The central blood compartment is the 81-th node which exchange heat with other nodes convective.
The thermal node model is composed of passive system and active system. The passive system simulates heat exchange between human and environment through evaporation, convection, and radiation. The active system predicts regulatory responses such as sweating, shivering and vasoconstriction. The anthropometric data of the model are from the work of Tanabe and proportionally modified according to the body weight and skin area. The heat balance equation in each node expect for the central blood compartment is defined as follows [6]:
, , , , , 1 , , ( ,4 ,4 ,4) i j i j i j i j i j i j i j i i i dT c Q B D D RES R C E dt (1)
where ci,j is the heat capacity of each node. T is the time. Ti,j is the temperature of each node. Qi,j is the rate of heat production. Bi,j is the heat exchange between each node and central blood node. Di,j and Di,j-1 are the heat exchange by conduction to the neighbor layers within the segment. RESi,j is the heat loss by respiration, which is only for the chest. Ri,4 is the heat loss through radiant from skin. Ci,4 is the heat loss through convection from skin. Ei,4 is the evaporation heat loss from skin.
The heat balance equation of the central blood compartment is defined by the following equation [6]: 20 4 81 81 , 1 1
¦¦
i j i jdT
c
B
dt
(2)where c81 is the heat capacity of the central blood compartment. T81 is the temperature of the central blood compartment.
In the active system, the temperature differences between each node and its set point are the control signals which can regulate human thermal response. The detailed information of thermal response equations can be obtained in the Tanabe’s work, but the coefficients are modified. Human physiological responses such as heat production, blood flow rate, and sweating rate can be simulated through the thermal model.
2.2.Coupling system
The sweating thermal manikin “Newton” (Measurement Technology Northwest, USA) with walking, sweating, and breathing functions has the size of an average adult Asian male body. It has 20 zones that can independently control their temperature, heat flux, and sweating rate. ThermDAC control software provides control capabilities, data recording, and real-time numerical and graphical displays of zone temperature, heat flux, and sweating rate. The manikin can be operated with the constant heat flux, constant skin temperature or thermal comfort modes in each body zones.
The manikin is coupled with the thermal model to create a dynamic system. At the beginning of the coupling process, the thermal model uses parameters including air temperature, mean radiant temperature, relative humidity, wind speed, heat production and measured heat exchange with environment to predict skin temperature and sweating rate of each human body node. The manikin operates under the constant skin temperature and sweating rate predicted by the thermal model, the measured heat exchange of convective, radiant and evaporation will be the feedback signal for the thermal model to predict thermal response in the next time interval.
3.Results and Discussion
The performance of the coupling system was conducted in the climate chamber (5.0 m length × 3.0 m width × 2.7 m height) in which temperature and humidity was controlled, and the thermal sweating manikin was seated in the wheelchair. The simulated results of the coupling system are compared with experimental results obtained from the work of Munir [11]. The average skin temperature, body core temperature and local skin temperature are selected as the physiological parameters for the validation of the coupling system.
Test protocols and environment parameters of the Munir’s experiments are shown in Table 1.
Table 1. Test environment conditions of validation experiments.
Test protocols Air temperature (oC) Relative humidity (%) Time (min)
Preparation 29.4 46.6 60 Phase-1 29.4 46.6 30 Phase-2 19.1 54.8 20 Phase-3 29.3 47.0 60 Phase-4 39.1 44.1 20 Phase-5 29.4 47.0 20
Before the experiment, subjects wear trunks and seat in the climate chamber with 29.4 oC for 60 minutes. During the experiment, the skin temperature, core temperature, air temperature, relative humidity and wind velocity are measured continually. Fig. 1 compares the local skin temperatures between the experimental data of Munir’s work and the simulated results from the coupling system.
As can be seen from the Fig. 1, it is clear that the simulated local skin temperatures agree well with the experimental results in trend. The coupling system tends to overestimate the temperatures of thighs and underestimate those of the head, trunk, calf and feet. The differences between the measured temperature and simulated values in thigh and foot are greater than other segments. Discrepancies are also observed in the first phase which is thermally neutral, where the role of thermal regulation is minimal. The differences between the measured temperature and simulated values in the other phase are greater than those of the first phase.
The mean skin temperature is calculated using the area-weighted of the local skin temperature. Fig. 2 displays the core and average skin temperatures of human tests and those predicted by the coupling system.
As can be seen from the Fig. 2, the average skin temperatures simulated by the coupling system coincide well with the experimental results in terms of both the trend and the values. The average skin temperature difference between the coupling system and human test data does not exceed 1.0 oC, which shows the coupling system give accurate predictions of the average skin temperature for the conditions ranging from cool to hot temperature. The
deviations of the average skin temperature for the coupling system at hot condition are higher than those for the neutral and cool condition.
The core temperature predicted by the coupling system almost keeps constant at 37.1 oC and don’t change significantly with the environment conditions. The core temperatures simulated by coupling system are agreed well with the human trails both in trend and values, indicating that the coupling system can be used to simulate human core temperature with great accuracy.
There are possibly several reasons contributing to the prediction differences between the coupling system and human tests. All subjects remain sedentary in the experiment, while the manikin is seated on a wheelchair in validation tests. The wheelchair may change the heat exchange between the manikin and environment condition and affect the local skin temperature, especially for the segments directly contact the wheelchair. In addition, physiological parameters in the thermal model are different from that in the experiment, such as basic blood volume and thermal regulatory coefficients, which can affect heat distribution and skin temperature.
(a) Head (b) Trunk
(c) Arm (d) Thigh
(e) Calf (f) Foot
Fig. 1. Local skin temperatures of measured data of Munir’s work and those predicted by the coupling system.
0 30 60 90 120 150 28 30 32 34 36 38 Head t emperature ( q C) Time (min) Simulated Measured 0 30 60 90 120 150 28 30 32 34 36 38 Trunk t emperature ( q C) Time (min) Simulated Measured 0 30 60 90 120 150 28 30 32 34 36 38 A rm temperature ( q C) Time (min) Simulated Measured 0 30 60 90 120 150 28 30 32 34 36 38 T high t e mperat ure ( q C) Time (min) Simulated Measured 0 30 60 90 120 150 28 30 32 34 36 38 Calf temperature ( q C) Time (min) Simulated Measured 0 30 60 90 120 150 28 30 32 34 36 38 Foot temperature ( q C) Time (min) Simulated Measured
(a) Core temperature (b) Average skin temperature
Fig. 2. Core and average skin temperature of human tests and those predicted by the coupling system.
4.Conclusions
The coupling system has been developed and validated. The prediction results of the coupling system showed good agreement with the human tests both for the skin temperature and core temperature. The prediction results suggest the coupling system accurately simulate both the overall and local human physiological response. In this work, the validation tests are for the semi-nude subjects. In the future study, the coupling system will be used in more conditions in which protective clothing will be worn on the manikin under a wide range of temperature.
Acknowledgements
This paper was supported by National Natural Science Foundation of China (Grant No. 51076073), China National Key Basic Research Special Funds Project (Grant No. 2012CB719705), National Science and Technology Support Project of 12th 5-Year Plan ( Grant No. 2011BAK07B03), and Tsinghua University Initiative Scientific Research Program (Grant No. 2012THZ02160), the authors are deeply grateful to the supports.
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0 30 60 90 120 150 36 38 Core temperature ( q C) Time (min) Simulated Measured 0 30 60 90 120 150 28 30 32 34 36 38 Mean ski n t emperature ( q C) Time (min) Simulated Measured