THERMODE 193: AN ENHANCED STOLWIJK THERMOREGULATION MODEL OF THE HUMAN BODY

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1 THERMODE 193: AN ENHANCED STOLWIJK THERMOREGULATION MODEL OF THE HUMAN BODY Francesca Romana d Ambrosio Alfano 1, Boris Igor Palella 2, Giuseppe Riccio 2 1 Università degli Studi di Salerno, DIMEC, Via Ponte Don Melillo Fisciano (Salerno), Italy fdambrosio@unisa.it 2 Università degli Studi di Napoli Federico II, DETEC, P.le V. Tecchio 80, Naples, Italy Summary: This paper presents the results obtained improving the original Stolwijk model by introducing some changes suggested by the remarkable advances in thermoregulation physiology and in the study of the effects of the clothing on the thermal comfort. The model is able to predict the local skin temperatures and the core temperatures of the human body with a satisfactory degree of accuracy, as widely shown by comparing the model results with the experimental runs in a climatic chamber. Keywords: thermoregulation models, thermal comfort, manikins Category: Human indoor environment interaction, Human thermal physiology and mathematical models, clothing. 1. Introduction Numerical models for the human response prediction to heat and cold exposures are widely used both to improve the comfort of the thermal environment and to assess the risk of exposures or to evaluate preventive measures (i.e. protective clothing). Over the past 60 to 70 years, many attempts have been made in order to develop a reliable mathematical model of the human thermoregulation system with the aim to predict man s response to the thermal environment. Stolwijk s 25 node model, formulated in 1970 for NASA Skylab and Apollo programmes [1], set out the fundamental concept, algorithm, physical constants and physiological control sub-systems for many multi-nodes models. However the assumptions made by the author strongly reduced the applicability of the model to a naked subject living in a homogeneous environment. In the last fifteen years, an increasing need for predicting thermal behaviour of the human body under typical indoor environment situation and in cars resulted in the formulation of new thermoregulation models [2,3] and in a significant enhancement of Stolwijk model [4,5,6]. Such models appear not only useful tools for the indoor environments characterization, but they are starting to take a crucial place for the prediction of the thermal sensation in outdoor situations also [3]. On this side, COST action 730 [8] leads together physiologists and meteorologists from Europe and the rest of the world to develop a new weather index, the Universal Thermal Climate Index (UTCI), able to inform the public of how the weather feels, taking into account the main factors affecting the human thermal response to the weather [9]. This paper deals with an advanced thermoregulation model derived by the early THERMODE (THERmoregulation MOdel for Disuniform Environments) model developed in cooperation with the LPPE (Laboratoire de Physiologie et de Psychologie Environnementales) of the French CNRS [4]. In this enhanced version, called THERMODE 193, several changes have been introduced. In detail, the model on a thorough division of the human body made by 48 body segment is based on in order to predict the man response both in standing and in sitting position. About the heat transfer modelling, the effect of body movements on the static clothing insulation has been taken into account [7]. Moreover, the active system has been revised in order to improve its performances especially under slightly cold situations and with respect to the need for an enhanced thermal response prediction of hands and feet. THERMODE 193 is able to predict the local skin temperatures and the core temperatures of the human body with a satisfactory degree of accuracy, as shown by comparing the model results with previous LPPE s experimental runs obtained in a climatic chamber under moderate situations (-1 PMV +1) and literature data. 2. The THERMODE 193-Node model The first THERMODE model, formulated in 1993 in cooperation with LPPE [4], showed good performances under both comfort and moderate discomfort conditions ( -1 PMV +1), allowing a generally good prediction of the mean skin temperatures and their trends. On the contrary, it exhibited poor performances for hands and feet temperature predictions (especially under slightly cold conditions) where the temperature difference between the experimental and predicted one, often exceeded 1,5 2,0 C. Moreover the body segmentation avoided the possibility of seated position. Aiming to enhance its performances and improve its flexibility, the model has been widely modified trying to take into account the progresses of thermoregulation know-how of the last fifteen years. Although THERMODE 193 is a Stolwijk like thermoregulation model, it has been deeply revised both in the active and in the passive system. Particularly, its

2 thermoregulatory core is made by an active system (including both information and data exchanges and commands), and a passive system, taking into account the human body intrinsic dynamic (Fig. 1). Each node exhibits an energy production due to the metabolic activity (i.e. basal one with the exception of muscles), which increases with the increasing of the activity and in the presence of shivers. The thermal set point activity reference temperature shiver muscles thermal energy generation hypotalamus glands sweat glands evaporative heat loss body thermal capacity body temperature circulatory system blood internal heat transfer temperature sensors Active system Passive system Fig. 1. THERMODE 193: the overall thermoregulation scheme according to Stolwijk. From [1] modified. The passive system With respect to the first version of THERMODE [4], the passive system is now made by 14 blocks (head, trunk, arms, forearms, hands, legs, ankles and feet) instead of 10. Each block is divided into several segments, particularly: head: (upper and lower) each made by four segments (right front, right rear, left front, left rear) for overall 8 segments; trunk, arms, forearms, legs, ankles: each made by 4 segments (according to previously reported for the head) for overall segments. This special segmentation allows the treatment of both stand up and seated position. hands and feet, each made by one part for overall 4 segments. Finally, each segment is made by four layers (skin, fat, muscles, core), for an overall number of 48 x 4 = 192 nodes to which blood has to be added, according to figure 2. 3 A A A-A Fig. 2. THERMODE 193: the active system. Legend: 1) Head; 2) Trunk; 3) R-Hand; 4) R-Forearm; 5) R-Arm; 6) L-Arm; 7) L-Forearm; 8 ) L-Hand; 9) R-Leg; 10) R-Ankle; 11) R-Foot; 12) L-Leg; 13) L-Ankle; 14) L-Foot core muscle fat skin energy exchange takes place: inside of each element of the partition by conduction through layers; on the body-environment interface, by radiation, convection and evaporation; among the 14 compartments, by convection through the blood flow. It is noteworthy remind that trunk and head cores exchange thermal energy also by convection and evaporation due to the respiration. The equations for the calculation of the air saturation pressure, the surface blood flow, the convective bloodtissue exchanges, the regulatory perspiration, the maximum evaporating rate and of the thermoregulation commands have been changed in order to take into account new international standards. THERMODE 193 is formulated taking into account a clothed man. Particularly, the model is able to evaluate the clothing thermal insulation of each dressed body part starting from an overall clothing insulation value corrected by the effect of body movements [7]. The possibility of using different clothing insulation values for each compartment allows the thermal response evaluation in the presence of protective clothing [10], where only a reduced part of the body is interested by special clothing and microclimatic situations. Aiming to simulate a wide series of environment (not necessarily uniform), microclimatic input data are made by a set triplets (ta, tr, pa) for each node. The evaluation of the plane radiant temperature of each compartment has been carried out starting from wall temperatures of a room without windows according to the formula (1) under typical hypotheses of steady and uniform surfaces temperature [11]:

3 where: N 4 r,i = j p,i j j= 1 T T F (1) Tr,i is the plane radiant temperature of the generic i- surface of the body, K; Tj is the surface temperature of a generic surface present into the environment, K; Fp,i-j is the angle factor between the generic i-surface of the body and the generic surface j of the environment, K. Each angle factor according to ISO 7726 standard and on a base of an simplified model of the human body made by 48 blocks whose size (reported in table 2) on anthropometric data reported in table 1 [12] has been calculated [11]. Table 1. Anthropometric data of a Southern Italy standard man used for the modelisation of heat transfer by radiation [11]. Antropometric variable Value [mm] Stature 1729 Cervical height 1487 Radial height 1094 Styloide height 843 Tibial height 465 Cervical height sitting 654 Popliteal height 473 Hind limb length 8 Head length 193 Head breadth 155 Chest depth nipple 217 Abdominal depth 254 Shoulder breadth 379 Hand length 190 Hand breadth 84 Foot length 263 Foot breadth 98 Bi-trochanter breadth 0 Arm length 1 Forearm length 239 Elbow height 248 Arm circumference 0 Forearm circumference 296 Thigh circumference 575 Tibial circumference 294 Buttock-popliteal 480 Tibial distance 95 In figure 3 the software interface devoted to the plane radiant temperature calculation is reported. Particularly, the user geometric data of the room and the subject position has to input. Table 2. Dimensions of blocks modeling heat transfer by radiation of each body part. Body part depth width height [mm] [mm] [mm] Head Forearm Arm Hand Trunk Leg Ankle Foot The active system The active system shows three parts: thermo receptors; a system devoted to the elaboration of signals of thermo-receptors able to choice the nature and amplitude of each signal; the effectors mechanisms turning transforms signals into variations of metabolic energy production, or evaporative flows or the blood flow corresponding to each interested partition. According to Stolwijk s layout [1,13], controller equations have a term consisting of the product of a control coefficient and a central temperature signal, a term consisting of the product of a control coefficient and an integrated skin temperature signal, and, finally, a third term consisting of the product of a control coefficient, a central temperature signal, and a skin temperature signal according to following equations (see table 3 for each term meaning): ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) sweat = csw warm 1 + ssw warms + psw warm 1 warms dilat = cdil warm 1 + sdil warms + pdil warm 1 warms stric = ccon cold 1 scon colds + pcon cold 1 colds chill = cchil cold 1 + schil colds + pchil cold 1 colds (2) Table 3. Meaning and units of control parameters on which equations (2) are based on [1,13]. Symbol Definition Units csw sweating from head core W K -1 ssw sweating from skin control W K -1 cdil vasodilatation from head l h-1 K-1 sdil vasodilatation from skin l h-1 K-1 ccon vasoconstriction from head K -1 scon vasoconstriction from skin K -1 cchill shivering from head core W K -1 schil shivering from skin W K -1 psw sweating from skin and head core W K -2 pdil vasodilatation from skin and head core l h-1 K-2 pcon vasoconstriction from skin and head core K -2 pchil shivering from skin and head core W K -2 warm(1) output for warm due to hypothalamus K warms integrated output from skin warm receptors K cold(1) output for cold due to hypothalamus K colds integrated output from skin cold receptors K sweat total efferent sweat command W dilact total efferent vasodilatation command l h -1 strict total efferent vasoconstriction command n.d. chill total efferent shivering command W The first version of THERMODE model allowed a good skin temperature prediction generally under comfort

4 (PMV=0) or slightly warm situations (PMV=1) except for lower and upper limbs (hand and feet often reached a 1,0 2,0 C temperature difference with respect to experimental) [4]. Aiming to improve its performances, the effect of active system parameters values on the model prediction has been deeply investigated. Such work into two parallel phases has been carried out: thermoregulation literature has been extensively investigated in order to found a different set of parameters for the active system [2,3,5,12]; starting from Stolwijk parameters [1,4,12] with a try and error technique, parameters have been adjusted in order to reduce the difference between experimental and predicted temperature values. environmental homogeneous conditions (air temperature equal to the mean radiant temperature) corresponding to PMV= -1, 0 and +1 values respectively, have been used [4]. Basic values of clothing insulation where 0,10, 0,60 and 0,85 clo; in all cases, the metabolic rate was M = 1,2 met, the air velocity 0,15 m/s and, finally, the water partial pressure 1,0 kpa. According to fig. 3 curves (PMV = +1), a general agreement between experimental and model time-scale profiles has been found. As a matter of fact, fig. 3 profiles reveals good performances almost for all nodes except for hands and feet where the agreement between experimental and model temperatures appears less Table 4. Steady state temperature differences, T ( C), between model and experimental local skin temperatures for different sets of active system coefficients, clothing insulation and PMV. THERMODE [4] Icl, clo PMV Head Trunk Arm Forearm Hand Leg Ankle Foot -1 +0,3 +1,2 +1,5 +1,5 +2,8-0,4-0,4 +1,8 0,10 0 0,0 +0,6 +0,6 +0,6 +0,8-0,6-0,6-0,3 +1-0,3 +0,2-0,2-0,2 +0,9-1,1-1,1 1,1-1 +0,1 +0,4 +2,0 +2,0 +2,4 +0,8 +0,8 +2,2 0, ,5 +0,7 +1,9 +1,9 +2,6 +0,3 +0,3 +0,7 +1-0,5 0,0 +0,2 +0,2 +1,1-0,1-0,1 +0,5-1 -0,1-0,1 +1,0 +1,0 +1,4 +2,3 +2,3 +3,3 0, ,1 0,0 +0,1 +0,1 +0,9 +1,4 +1,4 +1,2 +1-0,2-0,2-0,1-0,1 +1,0 +0,2 +0,2-0,7 0,10 0,60 0,85 0,10 0,60 0,85 THERMODE ,4 +1,1 +2,0 +2,0 +2,0 0,1 0,1 +0,7 0-0,3 +0,3 +0,2 +0,2 +0,6-0,8-0,8-0,1 +1-0,4 +0,2-0,2-0,2 +0,9-1,1-1,1 1,1-1 +0,1 +0,3 +1,5 +1,5 +2,0 +0,8 +0,8 +2,0 0 +0,3 +0,3 +1,3 +1,3 +1,7 +0,1 +0,1 +0,7 +1-0,5 0,0 +0,1 +0,1 +1,0-0,1-0,1 +0,4-1 -0,1-0,3 +0,7 +0,7 +1,2 +2,2 +2,2 +2,4 0 0,0 0,0 0,0 0,0 +0,9 +1,4 +1,4 +1,2 +1-0,2-0,2-0,2-0,2 +1,0 +0,1 +0,1-0,8 THERMODE 193 with Tanabe parameters [6] -1 +0,2 +2,0 +3,8 +3,8 +5,5 +2,4 +2,4 +3,5 0 0,0 +0,5 +0,5 +0,5 +0,3 +0,7 +0,7 +0, ,4 +0,2 +0,1 +0,1-2,6 +1,1 +1,1-1,7-1 +0,1 +0,4 +1,5 +1,5 +2,0 +0,8 +0,8 +1,8 0 +0,3 +0,7 +0,7 +0,7 +4,8 +0,7 +0,7 +0,7 +1-0,9 0,0 0,0 0,0 +0,6 0,0 0,0 +0,4-1 +0,9 +0,7 +1,5 +1,5 +7,0 +4,3 +4,3 +6,6 0,0 0,0 0,0 0,0 0,0 +0,3 +1,4 +1,4 +0, ,5 +0,5 +0,4 +0,4 +0,6 0,0 0,0 +1,5 The effect of the active system parameters on the steady state temperature of each body node is summarized in table 4 where steady state temperature differences, between model and experimental local skin temperatures for THERMODE, THERMODE 193 and THERMODE 193 with parameters proposed by Tanabe are reported 3. Results and discussion In order to validate THERMODE 193, experimental results obtained in a special climatic chamber at LPPE by exposing 12 adult subjects to three different encouraging. As a matter of fact, model steady state temperature of hands differs to the experimental of about 1,0 C. Anyway, although so high difference, profiles depicted in fig. 3 suggest a transient behavior similar to the experimental since the model prediction appears only shifted to higher temperatures with respect to the measured. Feet model predictions also, due to the lack of counter-current blood heat transfer of Stolwijk models, appears far to the experimental although the steady state temperature seems to be near to the measured one (steady state T is only 0,4 C).

5 HEAD TRUNK HANDS LEGS FEET ARMS Fig. 3. Typical man thermal response in terms of skin temperature predicted by THERMODE 193 (continuous lines) compared with experimental runs (circles). Metabolic rate M =1,2 met; static clothing insulation Icl = 0,60 clo; va = 0,15 m/s; PMV=+1.

6 Table 4 data allow an in depth analysis of THERMODE 193 also under different situations. Particularly: Under comfort situations (PMV =0): Icl = 0,1 clo Trunk and arms show a significant enhancement such as T is less than 0,5 C. Hands and feet skin temperatures enhance of 0,1 and 0,2 C respectively. On the contrary hand, head and lower limbs exhibit a slight, even though acceptable, worsening ( T < 0,5 C). Icl = 0,6 clo Hands and arms skin temperatures enhance of about 1 C and 0,4 C respectively whereas head and trunk T within required accuracy range can be considered (±0,5 C); Icl = 0,85 clo - Final T prove a quite full agreement between experimental and model values with except for hands and lower limbs; Under slightly warm conditions (PMV = +1): original THERMODE results seem to be shortly affected by modifications introduced by THERMODE 193 with enhancement of T often less than 0,1 C; Under slightly cold situations (PMV = -1) : Icl = 0,1 clo Any significant difference with respect to old results has been revealed; Icl = 0,6 clo Under such conditions arms and forearms skin temperatures enhance of 0,5 C, while hands and feet of about 0,4 and 0,2 C respectively; Icl = 0,85 clo Only slight differences have been revealed between THERMODE and THERMODE 193 model with except for feet temperature. Data reported in table 4 clearly prove also that using Tanabe s parameters [7] for the active system instead of former THERMODE ones results in a general worsening of physiological response predicted by THERMODE 193; as a matter of fact: Under comfort situations (PMV =0): Icl = 0,1 and 0,85 clo a substantial agreement between the two sets has been found; Icl = 0,6 clo similar T values have been found although THERMODE 193 predictions with Tanabe s set appears less reliable since steady hands temperature T reaches 4,8 C. Under slightly warm situations (PMV = +1) : Icl = 0,1 clo Any significant difference with respect to old results has been revealed except for hands where Tanabe s set leads to a hand temperature difference of -2,6 C; Icl = 0,6 clo any remarkable difference has been found; Icl = 0,85 clo Only slight differences have been revealed especially for feet where Tanabe s parameters lead to a foot steady T equal to -1,8 C instead of -0,8 C; Under slightly cold situations (PMV = -1) : Icl = 0,1 clo and Icl = 0,85 A dramatic worsening of the prediction where obtained using Tanabe s set since T can even reach 7,0 C for hands and 6,6 C for feet. Icl = 0,6 clo a general worsening has been revealed although with a mild magnitude. THERMODE 193 performances have been finally compared to those exhibited by Fiala model [3], actually the more advanced thermoregulation model for the human thermal sensation prediction. Temperature profiles reported in fig. 4, obtained both under steady state and transient microclimatic situation, reveal a good agreement between the two models with final temperature predicted by THERMODE 193 very near to measured ( T < 0,5 C). Particularly, profiles of fig 5A and 5B shows interesting performances under hot transient situations also, although data set on which THERMODE 193 has been validated [4] is typical of moderate environments (-1 PMV 1). 4. Conclusions The modifications introduced by THERMODE 193 make this Stolwijk-like model an enough flexible tool for the prediction of the man response to the thermal environment in a wide range of situations. It is able to expose each part of human body to different conditions of air temperature, humidity ratio, air velocity and mean radiant temperature. In particular, the effect of air stratification due to particular heating systems, all phenomena related to draughts running over only some body parts, the effects of the mean radiant asymmetry, are near enough to easily deal with. A so fine body division could help in modelling comfort in environments such as motor vehicle, where, because of the reduced dimensions, the discomfort problems, especially by draughts and radiant asymmetry, can get much importance. Moreover, the possibility of using different clothing insulation values for each compartment allows the thermal response evaluation in the presence of protective clothing, where only a reduced part of the body is interested by special clothing and microclimatic situations. Finally, the good agreement found with literature both experimental and model data lead us to a further update of both the passive and the active system aiming to increase the reliability of the model under slightly cold situations also. From this point of view it would be very interesting promote a round robin test aimed to a cross comparison of thermoregulation models actually available in literature. Obtained results could provide a further step forward for developing reliable tools for the human thermal sensation prediction (i.e. indices and so on) all the more because an International Standard to the thermoregulation models is actually under preparation. Symbols Icl Static clothing insulation, m 2 K/W or clo M Metabolic rate, W/m 2 or met pa Water partial pressure, Pa PMV Predicted Mean Vote, n.d. RH Humidity ratio, n. d. tr Mean radiant temperature, C va Absolute air velocity, m/s

7 .0 RECTUM MEAN SKIN (A) I II III I II III RECTUM MEAN SKIN (B) I II III I II III RECTUM MEAN SKIN.0 (C) Fig. 4. Comparisons between THERMODE 193 predictions for the core temperature and the mean skin temperature (continuous lines) and Fiala model (dash dotted lines) [3]. Experimental runs are also reported ( ). (A) 60 min at ta = tr = 29 C (I), 120 min at ta = tr = 22 C (II), 60 min at ta = tr = 29 C. Icl = 0,10 clo, M = 1 met, RH =40%, va =0,1 m/s. (B) 60 min at ta = tr = 28 C (I), 120 min at ta = tr = 48 C (II), 60 min at ta = tr = 28 C (III). Icl = 0,10 clo, M = 1 met, RH =30%, quiet air. (C) 120 min at ta = 43,3 C, tr = 42,8 C. Icl = 0,10 clo, M = 1,2 met, RH = 50%, va =0,12 m/s.

8 5. References [1] Stolwijk J.A.J Mathematical model of thermoregulation. In: Physiological and behavioral Temperature Regulation, 48, (Hardy, Gagge and Stolwijk eds.). Springfield: Charles C. Thomas Publisher. [2] Fiala D., Lomas K., Stohrer M., A computer model of human thermoregulation for a wide range of environmental conditions: the passive system. Journal of Applied Physiology [3] Fiala D., Lomas K., Stohrer M., Computer prediction of human thermoregulatory and temperature responses to a wide range of environmental conditions. International Journal of Biometeorology (45), [4] Candas V., d Ambrosio F.R., Herrmann C A Mathematical model of thermoregulation to evaluate thermal comfort. Capri. International Conference on Energy and Environment towards the Year , 3th-5th june, [5] Grivel F.,Herrmann C., d Ambrosio F. R., Candas V., Theermal comfort analysis: subjective data collection, methodology and reference condition. 2 nd International Conference on Vehicle Comfort: ergonomic, vibrational, noise and thermal aspects, Bologna, Italy, 1992, 371. [6] Tanabe S., Kobayashi K., Nakano J., Ozeki Y., Konishi M Evaluation of thermal comfort using combined multi-node thermoregulation (65MN) and radiation models and computational fluid dynamics (CFD). Energy and Buildings, [7] Parsons K. C., Havenith G., Holmér I., Nilsson H. and Malchaire J The effect of wind and human movement on the heat and vapour transfer properties of clothing. Annals of Occupational Hygiene 43(5), 7-2. [8] Jendritzky G., Havenith G., Weihs P., Batchvarova E. and DeDear R. The Universal Thermal Climate Index UTCI goal and state of COST action. Proceedings of the 12th International Conference on Environmental Ergonomics. August 19-24, 2007, Piran Slovenia, [9] Richards M. and Havenith G. Progress towards the final UTCI mode. Proceedings of the 12th International Conference on Environmental Ergonomics. August 19-24, 2007, Piran Slovenia, [10] F.R. d Ambrosio, G. Riccio. Un modello per la valutazione degli strains termici dovuti all abbigliamento protettivo. Proceedings of 56 th ATI Congress, Naples, Italy 2001 (in Italian). [11] ISO Thermal environments - Instruments and methods for measuring physical quantities. ISO Standard Geneva: International Standardization Organization; [12] Masali M., Montinaro M., Masiero C., Pierlorenzi G., Lovisetto C., Micheletti M., Millevolte A., Riccio G. A survey on anthropometric characteristics of italian population aimed at an ergonomic design. Proceedings of 2 nd International Conference on Vehicle Comfort, Bologna, Italy 1992, [13] Stolwijk J.A.J A Mathematical model of physiological temperature regulation in man. NASA Report CR-1855, Washington DC USA, Acknowledgments This work was funded by the Italian MIUR (Italian Ministry for University and Scientific-Technological Research) in the area of the PRIN COFIN 2005 Project entitled Studio termofluidodinamico di componenti di facciata adattativi per il comfort ed il risparmio energetico. A special thank to Mr. Agostino D Aniello, Mrs. Paola Morra and Mrs. Rosaria Bellarte has to be devoted due to their precious cooperation.