Functional design of protective clothing with intelligent elements.

Loghin, Maria Carmen ; Ionescu, Irina ; Hanganu, Lucian Constantin 等

1. INTRODUCTION

The main target in clothing functional design is to simulate as accurately as possible the level adjustment mechanisms for the human body functions in general and skin in particular. In the case of clothing for protection against hostile environments the target is the extension of these functions and the addition of functions that correspond to other human senses or even more functions for which the human body has no equivalent.

The need to partially or totally simulate the functions, as well as to extend these functions led in different stages to the design and manufacture of clothing with different capacities of response to the requirements imposed by destination.

In our days we are confronted with a new challenge coming from the necessity of facing new conditions for hostile environments, with high risk threatening human health and life. As a result, the requirements for protection and safety functions of specific equipments are increasing. Furthermore, in case of an environment with high risk factors that cannot be identified by human body senses, the protective clothing must have the capacity to fulfill special protective functions.

2. THE PRINCIPLE OF INTELLIGENT PROTECTIVE CLOTHING

Monitoring function is one of the main functions of intelligent protective clothing. The monitoring and control of the environment and the protective equipment user are carried out through sensors, processors and actuators.

A sensor records the input signal and processes it in order to measure it, amplify it, to transform it into a signal of a different nature or to compare it to a critical value. A classification of sensors requires more criteria. According to the nature of stimulus there are 8 main types of sensors: physical, mechanical, chemical, thermal, electric, magnetic, radiation and biological.

The development in the field of micro- and nano-technologies, makes possible to realize the intelligent sensors with low power consumption and small dimensions. Also, the wireless technology permitted to realize a sensors networking and their connection with a collection and controlling data center. The intelligent sensors represent the nodes of a network and they are spread on a large area. They are considered intelligent sensors because these sensors incorporated elements for signals local processing, before the transmission to other elements of the network (fig.1).

[FIGURE 1 OMITTED]

The sensor transforms the physical characteristic in a proportional analogical electric signal. The analogical data provide by sensor is transformed in a numeric representation that can be processed by the local processor. The processor provides the command sequence to the execution element according to the software application existing in the processor memory. The processor implements the communication protocol with the receiver that receives by the wireless network the commands for the execution element.

In fig. 2 it is represented the block schema of an application with intelligent sensors and execution elements, integrated in an intelligent clothing product. The sensors and the intelligent execution elements are connected in a wireless network star type. The central node of the network is the processing and control center with a interface with the wireless network.

[FIGURE 2 OMITTED]

3. THERMAL ANALYSIS OF THE PROTECTIVE STRUCTURES

To dimension the intensity of thermal stimulus, a modeling and the analysis of thermal model it is recommended. The most common method is with Finite Element Analysis software (FEM), and in this paper it is used ALGOR V19 software and the typical procedure. The followed stages for FEM thermal analysis are:

1. Model creation in SuperDraw. Number assignation for surfaces (convection, radiation, heat flux). Material characteristics establishing and "Applied Temperatures" and "Initial Temperatures" assignation.

2. Selection of analysis type: Stationary Heat Transfer or Transitory Heat Transfer.

3. Selection of element type, elements data, the materials' properties, and the surface efforts.

4. Verification and running of the thermal analysis.

5. Results verification in SuperDraw.

6. Boundary conditions adding, temperatures in nodes and other necessary elements.

7. Initial data adding for each element groups. The temperature value is less than the critical temperature (the heat transfer is without dilatation or thermal efforts).

8. Effort global multiplications adding for each finite element.

9. "Source of Temperature in Nodes" adding (the same number for each node, both in thermal model and effort model).

10. Verification and running of efforts analysis. In this stage, the temperatures will be transferred from the thermal model in the efforts model.

To develop the thermal analysis of protective structures, a number of four finite elements models (FEMs) have been created, for the following real situations:

* low temperature environment (between -30 and -40[degrees]C):

** two layers: 4,9 mm textile materials and 4,1 mm equivalent air;

** two layers: 8,2 mm textile materials and 6,8 mm equivalent air.

* high temperature environment (between +35 and +45[degrees]C):

** two layers: 3 mm textile materials and 2,5 mm equivalent air;

** two layers: 4,9 mm textile materials and 4,1 mm equivalent air.

The models are constituted from 2928 3D "brick" finite elements and 4396 nodes; the finite elements have been divided in two groups: group 1 (green) that materializes the air layer, and the group 2 (red) for textile structure (fig. 3). It was considered the known physical--mechanical characteristics for air and textile materials, and the topography of temperatures of human body. The temperature is considered on the model by the changing of surface color. In fig. 4 it is represented the "color map" of the selected surfaces.

[FIGURE 3 OMITTED]

[FIGURE 4 OMITTED]

An example of the analysis results, for up-mentioned conditions, are presented in fig. 5 (ex. low temperature environment (between -30 si -40[degrees]C), model for two layers: 4,9 mm textile materials and 4,1 mm equivalent air).

The results of thermal analysis (temperature chart and heat transfer rate chart) are useful for temperature sensors choose and positioning.

[FIGURE 5 OMITTED]

4. TEMPERATURE MONITORING

The main problem in the case of the applications that imply networks of intelligent nodes is to minimize of power consumption. At physic level, the CMDA (Cod Division Multiple Access) communication technique was adopted. For the communication with environment, the TDMA (Time Division Multiple Access) was adopted, respectively the protocol PicoRadioMAC. The schema of temperature sensor is presented in fig.6.

[FIGURE 6 OMITTED]

This schema of the temperature sensor can be integrated easily in the same chip with the processing logic using CMOS technology. The electric tension obtained at the amplifier exit level is proportional with the temperature T, adjustable in the domain -20[degrees]C and 120[degrees]C.

5. CONCLUSIONS

1. Monitoring function is one of the main functions of intelligent protective clothing. The monitoring and control of the environment and the protective equipment user are carried out through sensors, processors and actuators.

2. To dimension the intensity of thermal stimulus, a modeling and the analysis of thermal model it is recommended. The most common method is with Finite Element Analysis software (FEM), and in this paper it is used ALGOR V19 software and the typical procedure.

6. ACKNOWLEDGMENTS

This research was conducted within the framework of the PNCDI II Project 81050/2007 for which the authors acknowledge financing authority--The Ministry of Education and Research of Romanian Government.

7. REFERENCES

Finol, C.A., Robinson, K. (2006). Thermal modeling of modern engines: a review of empirical correlations to estimate the in-cylinder heat transfer coefficient, Heat Transfer, Macmillan Publishing Company, New York

Constantin, G. et al. (2007).Thermal Conduction Process Analysis Using Furrier Model, Buletinul Institutului Politehnic, Iasi, Tomul LIII (LVII), fasc.5, Iasi, Romania

Ciobanu, L. et al. (2008). 3D Surface Controlled Structures for Fluid Flow Improvement, First World Conference on 3D Fabrics and Their Applications, Manchester, GB, April, 10-11