This paper deals about the presentation of a new software RUNEOLE used to provide weather data in buildings physics. RUNEOLE associates three modules leading to the description, the modelling and the generation of weather data. The first module is dedicated to the description of each climatic variable included in the database.

The experiments involving clothed subjects are conducted to reproduce the situation in which people enter an air-conditioned room just after sweating, and analyzed using a combined model, which consists of two-node model for thermophysiological response of human body and simultaneous heat and moisture transfer model for thermal and hygric behavior of clothing. The experimental and calculated results of the skin temperatures, the clothing temperatures and the weight are compared.

The cooling effect caused by long wave radiation between the roof surface and the sky is studied here. The external surfaces may cool down below the dew point of the air and the condensation may form [1]. Typically, the covering of cold roofs has a low thermal resistance and the condensation may form also on its downside. These phenomena are quantified and discussed here. It is shown that the amount of condensation could be surprising high, even by temperatures of external air about 0 oC and higher.

This paper proposes a dynamic optimization technique for building heating and cooling systems. The proposed algorithm returns trajectories for space temperature setpoints throughout a specified period that will minimize objective functions such as running cost or peak energy consumption. It can be applied to buildings for which the thermal mass allows various choices of temperature setpoints. The algorithm also specifies an optimal on-off schedule for HVAC equipment. The discussion includes modeling of the building's thermal characteristics, optimization techniques, and example studies.

Energy Conservation Buildings are very effective for restraint of global warming, because they can reduce CO2 emissions in building operation, which account for 70% of Life Cycle emissions. To find the most suitable strategies for energy conservation, it is necessary to assess various combinations of energy conservation techniques based on both environmental and economic viewpoints. Since these assessments are laborious and time consuming, an assessment tool has been desired.

Changing working processes not only in manufacturing and assembly but also in office work require advanced buildings which allow a maximum of flexibility towards building structure and all its services (HVAC, telecommunications etc.). To gether with the growing importance of shared tenant services in intelligent buildings, theattempt to reach low-energy consuming buildings despite of their required flexibility in supplying a good infrastructure leads to a growing importance of "building performance".

This research is aimed to improve indoor air quality (IAQ) in the building by using the expert system (ES) based on the artificial intelligence (AI). The diagnosis tool of IAQ and ventilation design tool corresponding to 9 kinds of pollutants were developed. For diagnosis the concentration calculated from pollution generation rate and outdoor air is compared to the standard. For designing, the ventilation rate is provided from allowed concentration and pollutant generation rate.

This paper is focused on the development of measuring equipment of Effective Leakage Area (ELA) by AC pressurization method. The formula to design the measuring system is derived according to the governing equation of the leakage, e.g. in terms of flow rate through the leakage, volume changing, sinusoidal pressurization, etc.

Optimization of thermal storage tank operation is one of the major areas for energy conservation in HVAC systems. In the present paper, an algorithm is developed for optimum operation of thermal storage tank, by minimizing non-linear cost function. Results are validated under stationary and random load conditions. It is concluded that the present algorithm is quite robust and provides an optimal scheme of operation.

For effective energy use and level off electricity demand throughout the day, thermal energy storage system is getting popular in HVAC systems in Japan. Load profile prediction can provide information to plan optimal operation, and now, various prediction approaches have been developed, for example, Autoregressive Integrated Moving Average (ARIMA) model, Topological Case Based Modeling (TCBM), Artificial Neural Network (ANN), and other approaches.