Accumulated salt-the main impurity of sweat-in clothing can have significant influences on the transport of heat and moisture: the more concentrated salt water is, the lower the vapour pressure of water; it also affects the liquid water transfer. The former report of this research experimentally demonstrated that salt water penetrates more slowly than pure water, which corresponds to the fact that salt lowers the chemical potential of water. This paper shows the numerical model of heat, moisture and salt transfer in cloth in order to quantify the salt influences on the heat and moisture transfer. The experimental data provided in the former report are numerically analysed with the model proposed here and it was shown that the numerical analysis with the model implemented can reasonably explain the heat and moisture transfer in the cloth which contains salt in it.

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In the previous study, the authors regard the steady flow field as a linear system, and establish a formulation of the three-dimensional transient concentration calculation method based on concentration response factor. As the first stage, the authors carried out examples of the simulation using a single-room model, and the same degree of accuracy as one using a numerical fluid analysis code was obtained in a much reduced calculation time. In general, buildings are composed of multiple rooms, and the structure of airflow might be regarded as a network. In this study, we develop a model that couples three-dimensional transient pollutant transport in a room into a flow network model with the aim of calculating the three-dimensional transient concentration transition in a building composed of multiple rooms. In the coupling model, the air transports between each room are calculated using a flow network model, and the three-dimensional transient pollutant transports between each element (e.g. contaminant generation point, opening, air outlet, air inlet,) are calculated using a method based on the response factor. Here we present the calculation method as well as examples of the simulation, and report on the results.

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In the course of this study, we have developed an algorithm for outputting the optimum suitable temperature for indoor thermal environments by inputting the mathematical elements of the predicted mean vote (PMV), which is a thermal comfort index, in order to create better thermal environments. We also developed software for the execution of this algorithm. The validity of this algorithm was then confirmed through simulations for the output of optimum temperature using this software. Furthermore, this software was implemented in a DDC controller, and a prototype control unit incorporating this DDC controller was fabricated. A verification test was performed using actual equipment with this control unit, and the potential of this air-conditioning control system has been confirmed using the optimum temperature output as the desired value.

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