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A new experimental methodology is presented to show the effect of water supply temperature, mass flow rate and thermal load distribution on the radiant ceiling capacity and thermal comfort conditions. Computerized fluid dynamics simulated vertical temperatures and velocities profiles were validated by a comparison with experimental results and the difference was within 10%. Uniform surface temperature distribution was achieved in a 45.6 m3 test room installed with capillary ceiling radiant cooling panels by an increase in water temperature and air supply velocity. When the ventilation system was turned off, the mean ceiling surface temperature rose from 16.9 ± 0.4°C to 21.5 ± 0.3°C with a rise in the inlet water temperature to 20.1°C. The temperature difference between the head and ankle of an occupant was 2.0°C, which complies with the Chinese standard, GB/T 18049-2017. At a height of 1–1.5 m, the maximum temperature fluctuation was 2°C in the horizontal direction. When the ventilation system was turned on, with the air supply temperature and velocity at 19.8°C and 1.11 m s−1, the ceiling surface temperature was increased by 0.5°C. The indoor air temperature has a positive correlation with the air supply temperature and internal heat load but a negative correlation with air supply velocity.

Radon is a radioactive pollutant that could pose hazards to the surrounding environment and people due to its radioactive decay progenies. In this study, numerical simulations of radon dispersion were conducted under natural and mechanical ventilation with an air-purifier for radon. Factors such as the air supply speed, position and air supply angles of the purifier were considered. Results showed that the increase in the air supply speed from the purifier was an effective solution to reduce indoor radon pollution. The effect was better when the purifier was in the middle of the room. The purification effect was similar when the air supply changed under natural ventilation, while purification function was more effective when the air supply angle was 60° under the mechanical ventilation condition. An effective dose estimation involving typical ventilation schemes with radon purifier was evaluated. Using this approach, the radiation effect on occupants was computed. The calculated effective dose was 0.9 mSv y−1 when the air supply speed of the purifier was 0.2 m s−1 under natural ventilation. As a result, the effective dose calculated was under the annual effective dose limit of 3–10 mSv y−1 recommended by the International Commission on Radiological Protection (ICRP) for public exposure.

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Focusing on short-term wind power forecast, a method based on the combination of Genetic Algorithm (GA) and Extreme Learning Machine (ELM) has been proposed. Firstly, the GA was used to prepossess the data and effectively extract the input of model in feature space. Basis on this, the ELM was used to establish the forecast model for short-term wind power. Then, the GA was used to optimize the activation function of hidden layer nodes, the offset, the input weights, and the regularization coefficient of extreme learning, thus obtaining the GA-ELM algorithm. Finally, the GA-ELM was applied to the short-term wind power forecast for a certain area. Compared with single ELM, Elman algorithms, the experimental results show that the GA-ELM algorithm has higher prediction accuracy and better ability for generalization.