Computer-Aided Design A CAD system for multi ... - Semantic Scholar

Computer-Aided Design 40 (2008) 916–930

Contents lists available at ScienceDirect

Computer-Aided Design journal homepage: www.elsevier.com/locate/cad

A CAD system for multi-style thermal functional design of clothing Mao Aihua a , Li Yi a,∗ , Luo Xiaonan b,c , Wang Ruomei a,c , Wang Shuxiao a a

Institute of Textiles and Clothing, Hong Kong Polytechnic University, Hung Hom, Hong Kong

b

Department of Computer Science, Zhongshan University, Guangzhou, China

c

Key Laboratory of Digital Life (Sun Yat-sen University), Ministry of Education, Guangzhou, China

article

info

Article history: Received 28 March 2008 Accepted 30 June 2008 Keywords: Clothing multi-style thermal design Virtual human body Wearing scenarios

a b s t r a c t Designing clothing with good thermal functional performance is very demanding and time-consuming if we follow traditional design methods. An innovative method consisting of a CAD system, allowing the designer to perform multi-style clothing thermal functional design on a customized virtual human body, is presented in this paper. The new functionalities of the virtual system provide the abilities to perform intelligent design of different clothing styles and materials for different body parts according to individual design requirements, namely design of various categories of clothing, such as hat, coat, trousers, gloves and shoes in the same design scheme. The designed clothing can be worn on a virtual human body and set in various wearing scenarios. The thermal behaviors in the human body-clothingenvironment are simulated to predict the thermal performance of clothing and thermal response of the human body at multi-parts. 2D/3D visualization and animation of the simulation results are presented to help the designers to preview and determine whether the thermal performance of clothing is satisfactory and then obtain feedback to improve their designs iteratively. © 2008 Elsevier Ltd. All rights reserved.

1. Introduction With the virtual space provided by the CAD tools for clothing design and simulation, designers now are able to implement their design schemes effectively and preview their design conception immediately by computational simulation and graphic visualization. Currently many CAD packages have been available, targeted at garment construction, fashion design, physical fitting simulation and even animation of the clothing on characters [1,2]. Not only can clothing be simulated and animated with remarkable realism today, but also speed and quality are being improved by developing or refining models and algorithms [3–9]. However, these pioneer achievements are mainly focused on the mechanical behavior of clothing. Currently, there is still lacks of a CAD system for clothing design focusing on thermal behavior, with which the user can perform virtual thermal design and thermal performance analysis. Although some CFD software tools provide a possible pathway to simulate the fluid distributions within the clothing, the structural features of textile materials and the coupled heat and moisture transfer processes in fabrics, which are related to the physical properties and chemical compositions of textile materials, can not

∗

Corresponding author. Tel.: +852 34003361. E-mail addresses: [email protected] (A. Mao), [email protected] (Y. Li).

0010-4485/$ – see front matter © 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.cad.2008.06.002

be taken into consideration. This causes the simulation results to be distorted from reality. In order to diffuse the CAD technology into clothing thermal functional design and to respond to the urgent demands from designers and manufacturers of thermal functional textile products, a virtual CAD system, named P-smart, has been previously reported for clothing thermal functional design [10]. It enables the user in a virtual environment to design the clothing with wearing scenarios and preview its thermal performance throughout the simulated scenarios. Compared to the traditional clothing design method, this new design aid provided by this virtual system shows many advantages, such as shortening the design cycle and avoiding realistic design trials. As the world’s first system providing the designer with a CAD tool especially for clothing thermal functional design [11], the P-smart system developed the framework of computational engineering design for thermal functional performance of clothing, particularly for designing multi-layer garments, as shown in Fig. 1. Using the P-smart system, the effect of individual layers on the thermal comfort performance of the whole clothing assembly can be investigated and visualized. However, the P-smart system was developed on the basis of a two-node human regulation model, from which the thermoregulation and heat balance of human body at different body parts can not be simulated. Therefore, it can only simulate and predict the overall thermal performance of clothing and the thermal responses of the human body, which is good enough for designing multi-layer clothing systems, as reported previously.

A. Mao et al. / Computer-Aided Design 40 (2008) 916–930

Nomenclature Bn cb cv cn Cf Cn cv En Eres Mn mrsw ms hvap pa pa0 hl↔g hc ht Kmix Kn mrsw ms Pea Psat Psk Rea Resk S S0 Sv Rea Rn RH RH 0 T T0 T∞ ¯a m D

¯v m ¯v m

mw

ε ρa ρv∞ ρv ρv0 ρvs (T ) ρw λ grad div

Γ

heat loss by blood flow in each node [W] thermal capacity of the blood in each node [Wh/◦ C] volumetric heat capacity of the fabric [J/m3 K] thermal capacity in each node [Wh/◦ C] water vapor concentration in the fibers of the fabric [kg/m3 ] heat loss by convection in each node [W] volumetric heat capacity of the fabric [kJ/m3 /K1 ] heat loss by evaporation through the skin surface in each node [W] latent respiration heat loss in each node [W] metabolic heat generation in each node [W] regulatory sweating in each node [g/s1 /m2 ] sweating accumulation on the skin surface [g/m2 ] evaporation heat of water [J/kg] pressure of gas phase[kg/m s2 ] initial value of pa [kg/m s2 ] mass transfer coefficient for evaporation and condensation [m/s] convection mass transfer coefficient [m/s] convection heat transfer coefficient [J/m2 K] effective thermal conductivity of the fabric [W/m/K] heat loss by thermal conduction in each node [W] regulatory sweating [g/s/m2 ] sweat accumulation on the skin surface in [g/s/m2 ] water vapor pressure of ambient temperature [Pa] saturation water vapor pressure on the skin temperature [Pa] water vapor pressure on the skin surface [Pa] evaporation heat resistance on the skin surface [m2 Pa/W] evaporation resistance of the skin [m2 Pa/W] liquid water volumetric saturation (liquid volume/pore volume) initial value of S specific area of the fabric [1/m] evaporation heat resistence on the skin surface in [m2 Pa/W] heat loss by thermal radiation in each node [W] relative humidity [%] initial relative humidity [%] temperature of the fabric [K] initial temperature of fabric [K] temperature of environment [K] the mass flux of dry air under gas pressure gradient driving the vapor diffusion under vapor partial pressure gradient driving the vapor diffusion under total gas pressure gradient driving diffusion mass flux of liquid water porosity of the fabric density of dry air [kg/m3 ] environmental density of air [kg/m3 ] water vapor density in the air filling the inter-fiber void space [kg/m3 ] Initial value of ρv [kg/m3 ] saturated water vapor density at T [kg/m3 ] density of liquid water [kg/m3 ] heat of sorption or desorption water or vapor by fibers [J/kg] gradient divergence boundary

917

When coming to the case where the designer needs to consider the effect of different clothing styles, such as short, medium and long sleeves, and short, medium and long trousers/skirts, P-Smart can not help, as illustrated in Fig. 1. We need to consider, in the case of sportswear design, how the different fabric materials covering different parts of the body should be used according to the amount of heat generated and the sweating rates of the individual body parts. Thus, it is essential that the CAD software is able to simulate the heat balance and thermoregulation of individual body parts and the blood flow among them in correspondence with the heat and moisture transfer in the fabric material worn on all body parts. In this paper, we report the development of a new CAD system (T-smart) that allows the designer to carry out thermal functional design considering the effect of different clothing styles. Using this new system, the designer can investigate the effects of using different materials and styles for different body parts (i.e. hats, underwear, jackets, trousers, gloves, socks etc.) by simulating and previewing the thermal performance of clothing during different wearing scenarios. This system has been developed by integrating the clothing model and multi-node thermoregulation model of the human body, and development of the thermal interaction multisocket to represent the thermal behavior in the human bodyclothing-environment (HCE) system. Subsequent efforts have been made: development of computational algorithms and user interfaces with engineering design methods, encapsulation of classes for models, visualization of simulation results, as well as the supporting engineering database. 2. The framework of the human body-clothing-environment system Considering that the role of clothing is to provide a crucial thermal protection for the human body in various thermal environments by the highly interactive micro-climate between clothing and the human body, it is essential to build up a framework that regards the clothing, human body and environment as an integrated thermal system to simulate the thermal behavior of clothing materials. That means it should consider not only the heat and moisture transfer processes in clothing, but also the thermoregulatory system of the human body, as well as the interactions between the human body, clothing and environment. In the human body-clothing-environment (HCE) system, the predominant thermal behaviors in human body and clothing involve:

• The biological thermal activities in the human body, such as the metabolic heat generation by muscles and organs, blood circulations between different parts of the body to transfer energy, sweating and shivering, and the interactive thermal activities between the human body and the external environment through the skin, such as heat conduction, convection and radiation, as well as heat evaporation of moisture through perspiration and sweating. • The heat transfer process in clothing materials, including heat conduction, convection and radiation, as well as the latent heat of various phase changes in clothing materials, such as the heat transferred by the processes of condensation/evaporation and freezing/melting. • The moisture transfer process in clothing, involving water vapor diffusion and convection in the void space of textile material, moisture diffusion in fibers, liquid water diffusion through capillary pores, as well as moisture condensation/evaporation and freezing/melting. • The thermal barrier between the human body and the environment formed by the clothing and enclosed air to influence the heat and mass loss from human body to the environment in the form of heat and moisture transfer processes.

918


Fig. 1. The critical analysis of the P-Smart system.

Fig. 2. Schematic of the thermal HCE system.

In fact the heat and moisture transfer processes are normally coupled under transient situations. The schematic representation of the HCE system is illustrated in Fig. 2. To enable the computational simulation of thermal behaviors in the HCE system, the framework of this virtual HCE system is developed, as shown in Fig. 3, it involves mathematical models, the interactions between the HCE system, the numerical solution algorithm, as well as the support of the engineering database. The description of the mechanism for modeling thermal behavior in clothing materials and the human body can be found in the references [3,12–17], which are the theoretical foundation laid for the computational simulation in this framework. 3. Mathematical models for simulation According to the framework of the virtual HCE system, the selection and modification of the mathematical models to numerically represent thermal behaviors in the HCE system are predominately important. With the aim of achieving the clothing multi-style thermal design, the T-smart system adapted a 25-node model for describing the thermoregulatory system of a human body and a coupled heat and moisture transfer model for clothing.

Fig. 3. Framework of the virtual HCE system.

3.1. Description of model for heat and moisture transfer in clothing The thermal performance of clothing basically is decided by the heat and moisture transfer processes in the clothing materials, which are the main approaches for changing the temperature


and relative humidity of clothing. The heat and moisture transfer processes commonly happen in the ways of heat conduction, convection and radiation, moisture diffusion and convection, as well as diffusion of liquids in the textile. The involved physical mechanism of heat and moisture transfer processes within textile materials and the description of models have been reported by many researchers [13,15,18–20]. Some of them, with the support of computer technology, have paid attention to more interactive micro-processes of heat and moisture transfer and more factors which may potentially influence the thermal performance of clothing, such as the coupled actions between dynamic heat and moisture transfer, moisture absorption/desorption in fibers, moisture condensation/evaporation, and the heat absorption/release by the advanced functional materials (e.g. nano-particles, nano/microfibers, phase change materials). Besides the mathematical models for clothing in the P-smart system [10], the T-smart system further considers the factors of atmospheric pressure gradient and heating fabrics in order to make the simulation more realistic and robust for various design cases [21]. The pressure factor often needs to be considered when the atmospheric pressures at the inside and outside of clothing are different, such as in a running scenario or windy weather. The heating fabric is usually used in smart clothing design to keep the clothing’s temperature above a certain degree by releasing heat energy controlled by a settled temperature switch [22]. Eqs. (3.1)–(3.4) give mathematical descriptions of the thermal behaviors in clothing, which consist of a series of partial differential equations and are established according to the conservation of mass and heat energy. Some detailed information of these equations can be found in the related references. [21,23]. Mass balance equation of water vapor

∂ [ε ((1 − S ) ρv )] ∂ Cf (1 − ε) + ∂t ∂t − ε(1 − S )Sv hl→g [ρvs (T ) − ρv ] ¯ Dv + div (−m ¯ v) . = div −m

(3.1)

Mass balance equation of liquid water

∂ [εS ρw ] ¯ w) . + ε(1 − S )Sv hl→g [ρvs (T ) − ρv ] = div (−m ∂t

(3.2)

Energy balance equation cv

∂T ∂ Cf − λ(1 − ε) + hvap ε(1 − S )Sv hl→g [ρvs (T ) − ρv ] ∂t ∂t + W − q(x, t ) = div [Kmix (grad T )] .

(3.3)

Pressure balance equation

∂ [ε ((1 − S ) ρa )] ¯ Dv + div(−m ¯ a ). = div m ∂t

3.2. Description of model for the thermoregulatory system of the human body Human beings are able to live and perform various physical activities in a wide range of thermal environments from −40 ◦ C to 40 ◦ C. The main reason this is possible is that, except for the thermal protection from clothing, there exists an effective internal temperature regulatory system in the human body. With this system, the body core temperature can be kept at approximately 37 ◦ C by a series of regulatory behaviors (sweating, vasodilatation, shivering, vasoconstriction) whenever in hot or cold external thermal environments. Mathematical models describing the thermoregulatory system of the human body have been the subject of research for years [24], these are characterized following classification by node division of the human body, such as one-node, two-node and multi-node thermal models. In order to consider the thermal interactions between the human body and clothing at different parts so as to enable clothing multi-style thermal functional design, theoretically, the mathematical description model for the human body thermoregulatory system should be able to produce the physiological response of the body pertained to the different body parts, and develop communication sockets between the clothing model and the human body model to realize the interactions. Meanwhile, the limitation of the description model for body thermoregulatory system also needs to be taken into account, such as there being too many empirical parameters in the model and so limiting its application range, lack of available input data, the accuracy of the simulation results and the computational intensity aroused by the complexity of the model. Based on these considerations, a 25-node model, as reported by Stolwijk and Hardy [25], is adopted to represent the thermoregulatory system in a human body, this is a lumped parameter multinode model and has been applied in many fields to simulate the thermal behaviors of the human body [26]. In this model, the entire body is divided into six parts comprising head, trunk, arms, hands, legs and feet, and each part is expressed by four concentric layers individually representing the core, muscle, fat and skin layers of the human body, as illustrated in Fig. 4, in which all layers are connected by a central blood pool representing the large arteries and veins in the body. The thermoregulatory model of the body is described with reference to the forms of the heat balance equations in each layer and the blood pool, as shown in Eqs. (3.5) and (3.6). Additionally, the sweating accumulation on the skin is considered in this model [24], and is listed as Eq. (3.7), to expand the ability of the model to simulate the circumstances where the human body is sweating. For each layer cn

(3.4)

In Eq. (3.1), the three terms on the left state, respectively, the vapor storage within the interstices between fibers, the vapor storage within the fiber, and the evaporation/condensation flux of the water in the void space of inter-fibers. The right-hand side of the equation expresses the water vapor diffusion, namely the vapor diffusion under vapor partial pressure gradient driving ¯ Dv ) and under total gas pressure gradient driving (m ¯ v ). Similarly, (m Eqs. (3.2)–(3.4) represent the mass balance of liquid water, energy and pressure. The term q(x, t ) in Eq. (3.3) is the heat released/absorbed by the phase change material (PCM) in the freezing/melting process. W denotes the power rate of the heating fabric which means the volume of heat produced per unit area of the heating fabric in unit time.

919

dTn

= Mn − Bn − Kn − Rn − Cn − (En + Eres ) dt n = 1, 2, . . . , 24.

(3.5)

For blood pool cb

dTb dt

=

24 X

Bn .

(3.6)

n=1

Sweat accumulation on skin surface dms,i dt

= mrsw,i +

Psat ,i − Psk,i Resk,i hfg

−

Psk,i − Pea,i Rea,i hfg

.

(3.7)

The corresponding meaning of each node number (n) in the model can be found in Table 1. In Eq. (3.5), the left-hand side is the energy storage of each node, which is equal to the result of metabolic heat generation Mn minus the heat loss by blood flow Bn , thermal conduction Kn , thermal radiation Rn and thermal

920


Fig. 4. 25-node body thermoregulatory system.

Table 1 Node number of the body Number k k k k k k

=1 =2 =3 =4 =5 =6

Segment

Number

Head Trunk Arm Hand Leg Foot

n n n n

= 4k + 1 = 4k + 2 = 4k + 3 = 4k + 4

Layers in each segment Core Muscle Fat Skin

convection Cn , as well as evaporation and respiratory. Eq. (3.6) describes the hypothesis that the heat capacity of blood is the summation of all the connective heat by blood flow from all the nodes. In Eq. (3.7), the left-hand side is the sweat accumulation rate, which is equal to the regulatory sweating mrsw,i minus the volume of sweat removed by evaporation, namely, the second and third terms on the right-hand side. The real-time temperature of each node will be compared with a standard value to generate hot or cold signals, which will be transferred to the brain and integrated as hot or cold sensations. Subsequently, the corresponding regulatory behaviors are activated to balance the body temperature. 3.3. Development of the communication sockets With the intention of realizing the simulation of thermal behaviors in the HCE system, the clothing model and human body model play the dominating roles in numerically representing the thermal activities of clothing and body. Meanwhile, the interactions between the clothing and the human body also require a numerical representation for computational simulation. The analysis of the heat and mass exchanges taking place in the thermal interactions, such as heat conduction, convection and radiation, sweat evaporation, the data flow representing the exchanged heat and mass in the interactions and the communication sockets is developed, through which the data can be transferred smoothly into or out of the models. The sockets for the data flow between the human body, clothing and environment models are built up as shown in Fig. 5. During the wearing period, the interactive communications between clothing and the human body, and clothing and the

Fig. 5. Communication sockets for data flow in the HCE system.

environment primarily happen through the boundary between the body skin and the inner layer of the clothing close to the skin, and the boundary between the outer layer of clothing exposed to the environment and the environment. The sockets for communication between the models take their effect at the boundaries between them, and the data flows are automatically updated through the sockets when the values of interactive thermal variables exchanged among models are dynamically generated by the clothing and body models, as well as when the wearing scenario changes. As the clothing model is composed of a series of partial differential equations, the communication sockets are realized by the development of initial condition and boundary condition equations, individually as listed in Eqs. (3.8) and (3.9) [24]. T = T0

ρv = ρv0 S = S0 pa = pa0 Cf = f (RH0 , T0 )

(3.8)


921

Fig. 6. Architecture of the T-smart system.

¯ Dv |Γ + m ¯ v |Γ = hc (ρv − ρv∞ ) m ¯ w |Γ 2 = hl↔g ε(1 − S )Sv (ρvs (T ) − ρv∞ ) m Kmix grad T |Γ = ht (T − T∞ ) pa |Γ = paΓ .

(3.9)

In the boundary condition equation, considering the inner fabric layer close to the skin, the water vapor flux to clothing is equal to the evaporation water flux from the skin and the heat flux to clothing is equal to the sum of the evaporation, conduction and radiation heat flux from the skin; and as to the outer fabric layer exposed to the external environment, ρv∞ means the water vapor concentration of the environment and T∞ means the temperature of the external environment. The heat transfer coefficient (ht ) and the mass transfer coefficient (hc ) are determined by the wind velocity surrounding the clothing. Meanwhile, the thermal variables of the fabric layer close to the skin (Tf , pa ) and the climatic variables of the environment (air temperature, air relative humidity and air pressure) will be input to the thermoregulatory model of the human body through the sockets. Due to the fact that the interactions between the clothing and human body are considered at all the divided body parts, the communication sockets between the clothing and human body are developed for each body part, respectively: head, trunk, arms, hands, legs and feet. The simulation of heat and moisture transfer processes in textile materials thus needs to be executed concurrently for all the parts to generate their thermal status for communicating with each part of the body. The interactive thermal behaviors in the HCE system pertaining to each body part are thus represented numerically with the computational solution of the clothing and human body models. As a matter of fact, the multipart division of body in the 25-node model has increased the computational intensity, and the concurrent simulation in multipart clothing is comparatively time-consuming. 4. Virtual CAD system With the foundation of the framework for the virtual HCE system and the mathematical description models for simulating the thermal behaviors in the HCE system, the virtual CAD system (T-smart) is realized with the presentation of a user-friendly simulation procedure and interfaces, computational algorithms, as well as the object-oriented encapsulation of the simulation models for the flexible integration of the involved models responsible for

various design requirements and the compatibility of the models in previous and future versions. The clothing with multi-styles specified on the parametric virtual wearer, in various wearing scenarios, can be designed and its thermal performance can be previewed by the functionalities provided by this virtual CAD system. 4.1. System development The CAD system is developed with the functionalities of virtual clothing design, computational simulation and visualization and analysis. Fig. 6 shows the architecture of this virtual system, from which it can be observed that the mathematical modules of clothing and human body play a crucial role in translating the design data from the user into the computational language, and simulate the involved thermal and mass processes that are happening in the HCE system. Simulation results are continuously generated during the simulation process at each time step and individual grid division from the fabric thickness, which is the necessary setting for the clothing partial differential equations, and will decide the degree of accuracy of the simulated results. Due to the huge volume of data from the design process and computational simulation, the data management in this virtual system is quite important, and also, hard work. The data in a simulation case will be accorded a case ID, which is the name given to the simulation project files and simulation results files. All the generated files with a structured format are able to be stored in a user specified space on the computer, or, alternatively, submitted to an engineering database, which is available behind the system to support and manage the case data. More importantly, the CAD system is a powerful tool to administer the fundamental technical specifications of the raw materials, semi products and final products of clothing. The data flow in the main modules in the T-smart system is illustrated in Fig. 7, in which the input data management module undertakes the significant responsibility to receive the design data either directly from the user through design interfaces or from existing files in the stored space and database, and transfer these numerical specifications of the simulation case to the computational module with categorized data sets. The simulation results files and graphic files recording the visualized data can be stored to the database with the case ID.

922


Fig. 7. Data flow in the main modules in the T-smart system.

Fig. 8. Main class structure in the T-smart system: *PCM-phase change material [27] *MMF-moisture management fabric [28].

The Class encapsulation method is adopted in the T-smart system, which encapsulates the related parameters and behaviors of clothing, human body and wearing scenario, as well as the

necessary data management methods, into packed Classes as individual objects. All the objects have their independence in the data and method management. Meanwhile, they keep in


923

Fig. 9. Life-oriented engineering design process in the T-smart system.

Fig. 10. Structure of numerical algorithm in T-smart.

communication by calling the access system concerning existing associations between each other. The main Class structure in the T-smart system is shown in Fig. 8, in which the Class CDataManage is responsible for acquiring data from the interfaces and storage media and sorting it into the particular datasets for each of the encapsulated objects in the system, then distributing these datasets to all the objects for their initialization before starting the computation simulation. The Class CEquationsSolver acts as the public calling object, which encapsulates various numerical methods for solving the mathematical equations involved in the models of human body, clothing and scenario, by building up the data matrix. As to the Class CNumericalGarment, it is the aggregation of Class CNumericalFabric, which further is the aggregation of Class CFiber, CPCM, CMMF, CMembrane and CHeatingFaric, according to the engineering procedure of clothing production. To provide the user with a friendly enough design wizard, the design interfaces in this system are developed with the concept of answering a few life-oriented questions, such as ‘‘What to do’’, ‘‘Environment’’, ‘‘Wearer’’ and ‘‘Garment’’ [29]. With these questions, the user will be kindly guided to finish the engineering design, including the wearing scenarios, the wearer, and the clothing for the wearer. The information included in these questions will be obtained by the interface operations of the user and transferred to the module of data management, as shown in Fig. 9. During this life oriented engineering design process, the

engineering database is present at each step for querying and saving the technical information of the clothing material, human body and climatic conditions. 4.2. Computational algorithm With the technical specification of the clothing, human body and wearing scenarios, the computational simulation is ready to be executed with the preparation of numerical parameters being input into the mathematical models. Before this happens, the algorithm for fulfilling the computation should be put in the light and be achieved with the consideration of the structure and material composition of the clothing, the mathematical division of the human body, the replacement of wearing scenarios, as well as the interactions between the models of human body and clothing. The finite volume control method is employed in the solution process of the mathematical clothing model to discretize the composed finite differential equations. The computation of the solution of the equations will be implemented at each discretized grid step of all the composed fabrics in the clothing. A more detailed introduction about the discretization and solving process of the partial differential equations can be found in references [21,24]. Fig. 10 shows the structure of the numerical algorithm in the virtual system, in which the center blood node represents the blood

924


Table 2 Material and structure of functional clothing assembly Underwear

Vest (20% PCM1a )

Layer Material

1 Wool blend Cotton

Thickness (mm) Thermal conductivity W m−1 k−1 Water Vapor Permeability gm−2 Day−1

0.988 0.0754

1 Woven Nylon Fabric 0.252 0.0929

a b

329

Coat (20% PCM2b )

2 Nonwoven Polyester Fabric 4.79 0.0511



347

329

2 Nonwoven Polyester Fabric 4.79 0.0511

Outer Jacket 3 Woven Nylon Fabric 0.371 0.0853

1 Mesh Polyster fabric 0.548 0.0628

2 Nonwoven Polyester Fabric

1107

1275

1107

0.371 0.0853

PCM1: Freeze point: 15 ◦ C, Melt point: 28 ◦ C PCM2: Freeze point: 5 ◦ C, Melt point: 15 ◦ C.

Fig. 11. Main algorithm in the computational solver.

flow in the large arteries and veins of the body, accounting for the heat exchange between all the body parts, and the thermal

status of each grid in the clothing is prescribed as the boundary condition for its adjoining ones. The detailed description of the


main algorithm for the computational simulation is illustrated in Fig. 11. The simulation computation runs from the beginning by initializing all the encapsulated Classes, and is iterative at the multi-structured level, including the scenario duration, division of parts of clothing and body, layer number of composed fabrics, and discretized grids of clothing. At each time step, the communication between the Classes of human body, clothing and scenario will take place with the renewed values of their thermal variables for the next time step. Meanwhile, the generated values of these thermal variables at each time step are formatted and stored in data files for post-processing.

925

Table 3 Material and structure of the sports wear Garment type

Fiber Thickness (mm) Density (g cm−3 )

Sports T-shirt A, B Cotton1.6

202

Moisture regain (%) 7.5

* A– Sports T-shirt with short sleeves; B–Sports T-shirt with long sleeves.

4.3. Visualization and analysis It is important to present the simulation results of the thermal distribution of clothing and human body in a direct and lively way to help the designer preview and analyze the thermal performance of the clothing. T-smart incorporates a visualization module provided with both 2D/3D charts and virtual animation to view the predicted results, as illustrated in Fig. 12. The thermal variables of the clothing involving all fabric layers and parts of the human body (i.e. head, trunk, arms, hands, legs and feet) throughout the wearing scenarios can be observed for their distribution with the 2D/3D charts. The functionality of the 3D animation also provides a virtual thermal space to animate the thermal distribution of clothing, human body and environment with the 3D virtual models and map the data with real time refreshed color. It is easy to observe the comparison of the thermal distribution in different parts of clothing and human body through the color difference. This gives the designer a direct analysis of how the clothing performs thermally at all the parts in the simulated scenarios, what the thermal response of the human body wearing the clothing is, as well as the interactions and differences between different clothing and body parts, which are caused by the different materials and structures of the clothing covering different body parts. Feedback is obtained before the real production of the clothing so that the design can be improved iteratively. 5. Design cases To investigate the prediction ability and multi-style design functionality of the T-smart system, two design cases specifying the wearing scenarios are discussed with the presentation of visualized results.

Fig. 12. Visualization module in the T-smart system.

materials/technologies were applied in the fabric deign if wanted. The parameters of the virtual human body thermal regulation processes can be referred to the reports of Stolwijk and Hardy [25]. In the laboratory, the real samples of this set of clothing were worn by a group of subjects who performed the activities according to the specified wearing scenarios. During the experimental period, a set of thermal sensors attached to the skin and clothing recorded the thermal data, such as temperature and relative humidity. The results from the experiment are compared with the simulated results from the T-smart system at four points: (1) temperature of vest; (2) temperature of the vest shell; (3) skin temperature of trunk; (4) skin temperature of arm, as shown in Fig. 14, in which the temperature distribution at these points throughout the wearing scenario can be observed at the same time and the acceptable deviation between the experimental and predicted results is seen.

5.1. A design case compared with the experiment

5.2. A multi-style design case

This design case is implemented concurrently using the virtual CAD system and in the laboratory. The design concept of this case is to tailor a set of thermal functional clothing for human beings in an extremely cold climate. The detailed material and structure of the designed clothing in this case is listed in Table 2, in which both the vest and coat were coated with the phase change material (PCM) to obtain a smooth change of clothing temperature when the climatic temperature changes sharply. The wearing scenarios are specified as the human body in a cold environment of −15 ◦ C temperature, 30% relative humidity and 0.1 m/s2 wind velocity with three stages: (1) sitting resting for 30 min; (2) running at a velocity of 6.4 km/h for 30 min; (3) sitting resting again for 30 min. In the T-smart system, the virtual design of this clothing is achieved by the correspondence with the provided design procedure. Fig. 13 shows the interfaces for the design procedure of the virtual clothing, in which the user firstly chose the clothing style and size, garment by garment, to be worn on the virtual human body, then designed each garment by making the fabrics of shell, inter-layer and lining, and the innovated

To show the multi-style design functionality of the T-smart system, a design case was performed with same clothing material and structure but different styles. In this case, a set of sports T-shirts with two styles of short sleeves and long sleeves were designed and worn on the virtual human body to predict the thermal performance of clothing and body thermal response during the wearing scenarios. The material and structure of the sports T-shirt can be found in Table 3 and the design interface can be seen from Fig. 15. For the purpose of examining the thermal performance of this sportswear, the wearing scenarios are assumed in different rooms with different climatic conditions and activities. The detailed protocol is illustrated in Table 4. After the virtual design and computational simulation, the results are visualized with 2D/3D charts and 3D animation to predict the temperature and relative humidity distribution of clothing and human body at different parts during the wearing scenarios, as illustrated in Figs. 16 and 17. From Figs. 16 and 17, the visual presentation of thermal distribution on the animated human body can be observed at the following points:

926


Table 4 Wearing scenarios for the sports T-shirt Scenario

Body activity

Room temperature (◦ C)

Room relative humidity (%)

Wind velocity (m/s2 )

Duration (min)

Stage1 Stage2 Stage3

Sitting (1Met) Running (3Met) Resting (1Met)

25 32 25

40 60 40

0.3 0.1 0.3

15 20 40

(a) Interface for choosing garment style and fitting status.

(b) Interface for garment design through three fabric layers. Fig. 13. Interfaces for garment design.

(a) Temperature distribution of the T-shirt in the trunk. It is easy to see the temperature of T-shirt B is a little higher than that of Tshirt A throughout the whole wearing scenario, and when the human body steps into stage 3 from stage 2 of running status, the temperature of T-shirt B deceases more slowly than that of T-shirt A due to the fact that T-shirt B has more difficulty in emitting heat than T-shirt A.

(b) Relative humidity distribution of the T-shirt in the trunk. Given the high dependence between the thermal variables of temperature and relative humidity, the analysis of the relative humidity distribution of the T-shirts is similar to that of the temperature distribution. (c) Skin temperature distribution in the trunk. The reason that the short sleeves have better ability to emit heat also results in the


927

Fig. 14. Comparison between the experimental and predicted results. (a) underwear temperature; (b) vest shell temperature; (c) skin temperature of trunk; (d) skin temperature of arm.

(a) Sportswear with short sleeves.

(b) Sportswear with long sleeves. Fig. 15. Design interfaces of sportswear.

skin temperature of the trunk part being a little lower in case A than that in case B. And in the stage 2, the skin temperature in case A decreases earlier than in case B because it evaporates

sweat more easily thus taking away the heat. Consequently, the skin temperature in case B changes more sharply than in case A when the human body stops running at the end of stage 2.

928


Fig. 16. Predicted results of sports T-shirt A (with short sleeves). (a) Temperature distribution of the T-shirt on trunk part; (b)relative humidity distribution of the T-shirt on trunk part; (c) skin temperature distribution on trunk part; (d) skin temperature distribution on arm part.

However, in stage 3, the skin temperature in case B still cools more slowly than in case A. (d) Skin temperature distribution in the arm. The analysis of the skin temperature on the arm part is similar to that on the trunk part. The difference is that the arm part in case B is covered by the clothing while it is exposed directly to the environment in case A. Therefore, the skin temperature in case A cools more quickly than that in case B, and the comparison between these two cases is more observable than that of the temperature on the trunk part. 6. Discussion With the multi-part body division of the simulation models, the simulation of the thermal behaviors in the HCE system is accomplished in detail in six parts: head, trunk, arms, hands, legs and feet. The designer is thus able to perform clothing multi-style thermal design in this virtual CAD system, which is an important advance in terms of considering detailed design with different styles and materials in different parts, and is more applicable to the practical design cases for different applications. With this virtual system, the designer can avoid making real samples in the initial design stage and preview the thermal performance of clothing and the thermal status of the human body in different parts in the simulated wearing scenarios. As illustrated in the design cases, the visual presentation of the simulation results helps the designer to preview directly the thermal distributions of the clothing and human body at different points, and analyze whether the thermal

performance of the clothing conforms to the design concept, then go back to improve and optimize the design. With the ability of multi-style design, T-smart has the following new characteristics: (1) In the design process, the designer is able to consider the clothing style, including various lengths and fitting status, and distinguish the clothing for different body parts, such as hats, vests, gloves, socks, instead of the overall design as in the P-smart system. Therefore, a detailed design concept can be achieved at the design process, such as different clothing material for different parts of the body, different clothing thickness in different parts to take account of the difference of thermal sensitivity and activity flexibility in different body parts. (2) With the support of the engineering database, the designer is able to preview the thermal performance of the clothing on different people with different gender, age and race, and even for an individual person by giving the values of the person’s physical and physiological parameters. The user also can specify the wearing scenarios in any expected place and time by querying the climatic information from the database. That extends the ability of the designer to tailor thermal functional clothing for different people and different environments. For instance, some people may have more sweating accumulation on the back or armpit skin, where the clothing needs more special considerations, such as setting a slide fastener or using breathable materials to help the body breathe. (3) T-smart offers more support for the application of innovative technology on clothing thermal functional design, such as the moisture management treatment, self-heating fabric and phase change material (PCM) nano/microcapsules coating. In


929

Fig. 17. Predicted results of sports T-shirt B (with long sleeves). (a) temperature distribution of the T-shirt on trunk part; (b)relative humidity distribution of the T-shirt on trunk part; (c) skin temperature distribution on trunk part; (d) skin temperature distribution on arm part.

particular, the PCM coating volume on different clothing parts can be adjusted according to the distribution of thermal sensors in the human body, and more volume can be considered at the thermally sensitive part of the body to effectively regulate the thermal microenvironment between the clothing and body. To reiterate, the T-smart system enables multi-style clothing thermal design with expected wearing scenarios and predicts the thermal performance of the clothing and thermal response of the human body during the simulated wearing period. However, the computational load is increased due to the simulation concurrence of the multi-parts of clothing and human body. 7. Conclusion This paper has reported a virtual CAD system named T-smart for multi-style clothing thermal design on a customized virtual human body, which enables the designer to realize the design of various styles and clothing materials for different body parts. In the clothing design process, it is indeed able to differentiate the clothing categories of hat, coat, trousers, gloves and shoes. To achieve this capability, description models for simulating the thermal behaviors in the HCE system are developed with integration of the clothing model and a 25-node human body model. The thermal interactions between the clothing and human body are considered in different parts including head, trunk, arms, hands, legs and feet. The new computational algorithm, the encapsulation of the new integrated mathematical models, new user operational interfaces and the new visualization of the

simulation results are developed to realize the new functionalities of the T-smart system. Two design cases have been presented to validate the simulation results and show the multi-style design of T-smart. The future research of the clothing thermal design on virtual systems is to develop real 3D simulation for the HCE system and allow real 3D designs, providing a powerful tool for designers to achieve their concepts more freely. Acknowledgement We would like to thank Hong Kong Research Grand Council and Innovation Technology Commission through projects PolyU 5281/03E, the National Science Fund for Distinguished Young Scholars (No.60525213) and the Key Program of NSFC-Guangdong Joint Funds (No.U0735002) for financially supporting this work. References [1] Choi Kwang-Jin, Ko Hyeong-Seok. Research problems in clothing simulation. Computer-Aided Design 2005;37:585–92. [2] Editorial. CAD methods in garment design. Computer-Aided Design 2005;37: 583–4. [3] Breen David E, House Donald H, Wozny Michael J. Predicting the drape of woven cloth using interacting particles. In: Proceedings of SIGGRAPH 94, computer graphics proceedings, annual conference series. 1994. p. 365–72. [4] Volino Pascal, Courshesnes Martin, Magnenat Thalmann Nadia. Versatile and efficient techniques for simulating cloth and other deformable objects. In: Proceedings of SIGGRAPH 95, computer graphics proceedings, annual conference series. ACM; 1995. p. 137–44. [5] Eberhardt Berhard, Weber Andreas, Strasser Wolfgang. A fast, flexible, particle-system model for cloth draping. IEEE Computer Graphics and Applications 1996;16(5):52–9. [6] Baraff David, WitKin Andrew. Large steps in cloth simulation. In: Proceedings of SIGGRAPH 98, computer graphics proceedings, annual conference series. ACM; 1998. p. 43–54.

930


[7] Choi Kwang-Jin, Ko Hyeong-Seok. Stable but resposive cloth. In: SIGGRAPH 2002 conference proceedings, annual conference series. ACM press/ACM SIGGRAPH; 2002. p. 604–11. [8] Cordier Frederic, Magnenat Thalmann Nadia. Real-time animation of dressed virtual humans. Eurographics 2002. [9] Cordier Frederic, Seo Hyewon, Magnenat Thalmann Nadia. Made-to-measure technologies for an online clothing store. IEEE Computer Graphics and Applications 2003;23(1):38–48. [10] Li Yi, Mao Aihua, Wang Ruomei, Luo Xiaonan, Wang Zhong. P-smart-a virtual system for clothing thermal functional design. Computer-Aided Design 2006; 38:726–39. [11] Wang Shuxiao, Li Yi, Tokura Hiromi, HJMA. Computer simulation of multiphase coupled heat and moisture transfer in clothing assembly with a phase change material in a cold environment. Lecture notes in computer science, vol. 3942. 2006. p. 1103–6. [12] ISO. Thermal insulation - determination of steady-state thermal resistance and related properties - guarded hot plate apparatus. Geneva, Switzerland: International Organization for Standardization, 1991. [13] Li Y, Luo ZX. An improved mathematical simulation of the coupled diffusion of moisture and heat in wool fabric. Textile Research Journal 1999;69(10): 760–768. [14] Nishimura TMatsuo. Numerical simulation of moisture transmission through a fiber assembly. Textile Research Journal 2000;70(2):103–7. [15] Li Y, Wang Z. Numerical simulation of the dynamic heat and moisture transfer and thermoregulatory responses of a clothed human body. Journal of Thermal Biology 2002. [16] Wang Z, Li Y, Wong ASW. Simulation of clothing thermal comfort with mathematical models and fuzzy logic. In: The 10th international conference on environmental ergonomics, 2002. [17] Wang Z, Li Y, Yeung CY, Kwok YL. Mathematical simulation of the perception of fabric thermal and moisture sensations. Textile Research Journal 2002;72(4): 327–34.

[18] Farnworth B. Mechanisms of heat flow through clothing insulation. Textile Research Journal 1983;53:717–25. [19] Holcombe BV. A two-stage sorption model of the coupled diffusion of moisture and heat in wool fabric. Textile Research Journal 1992;62:211–7. [20] Luo ZX, Fang J. Heat and moisture transfer with sorption and condensation in porous clothing ssemblies and numerical simulation. Journal of Heat and Mass Transfer 2000;43(16):2989–3000. [21] Li Fengzhi, Li Yi, Liu Yingxi, Luo Zhongxuan. Numerical simulation of coupled heat and mass transfer in ygroscopic porous materials considering the influence of atmospheric pressure. Numerical Heat Transfer 2004;Part B(45): 249–62. [22] Sheng Li, Li Y, Li Fengzhi, Wang Shuxiao. Computational simulation of multiphase coupled heat and moisture transfer in phase change and self-heating porous materials. In: Zeng X, Li Y, Ruan D, Keohl L, editors. Computational textile. Springer; 2007. [23] Li Y, Zhu Q. A model of heat and moisture transfer in porous textiles with phase change materials. Textile Research Journal 2004;74(5):447–57. [24] Li Yi, Li F, Liu Yingxi, Luo Zhongxuan. An integrated model for simulating interactive thermal processes in human-clothing system. Journal of Thermal Biology 2004;29:567–75. [25] Stolwijk JAJ, Hardy JD. Control of body temperature. In: Handbook of physiology-reaction to environmental agents. 1977. p. 45–67. [26] Fu G. A transient, 3_D mathematical thermal model for the clothed human. Kansas State University: Kansas, thesis, 1995: p. 270. [27] Li Y, Zhu QY. A model of heat and moisture transfer in porous textiles with phase change materials. Textile Research Journal 2004;74(5):447–57. [28] Hu Junyan, Li Yi, Yeung Kwok-Wing. Moisture management tester: A method to characterize fabric liquid moisture management properties. Textile Research Journal 2005;75(1):57–62. [29] Mao Aihua, Li Yi, Wang Ruomei. Luo Xiaonan virtual thermal bioengineering system for life-oriented design of textile products, Journal of Fiber Bioengineering and Informatics, 2008 [in press].