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The air infiltration rate of buildings strongly influences indoor environment and energy consumption. In this study, several traditional methods for determining the air infiltration rate were compared, and their accuracy in different scenarios was examined. Additionally, a method combining computational flow dynamics (CFD) with the Swami and Chandra (S-C) model was developed to predict the influence of the surrounding environment on the air infiltration rate. Two buildings in Dalian, China, were selected: one with a simple surrounding environment and the other with a complex surrounding environment; their air infiltration rates were measured. The test results were used to validate the accuracy of the air infiltration rate solution models in different urban environments. For the building with a simple environment, the difference between the simulation and experimental results was 0.86%–22.52%. For the building with a complex environment, this difference ranged from 17.42% to 159.28%. We found that most traditional models provide accurate results for buildings with simple surrounding and that the simulation results widely vary for buildings with complex surrounding. The results of the method of combining CFD with the S-C model were more accurate, and the relative error between the simulation and test results was 10.61%. The results indicate that the environment around the building should be fully considered when calculating the air infiltration rate. The results of this study can guide the application of methods of determining air infiltration rate. [ABSTRACT FROM AUTHOR]

Heating and cooling in buildings accounts for over 20% of total energy consumption in China. Therefore, it is essential to understand the thermal requirements of building occupants when establishing building energy codes that would save energy while maintaining occupants' thermal comfort. This paper introduces the Chinese thermal comfort dataset, established by seven participating institutions under the leadership of Xi'an University of Architecture and Technology. The dataset comprises 41,977 sets of data collected from 49 cities across five climate zones in China over the past two decades. The raw data underwent careful quality control procedure, including systematic organization, to ensure its reliability. Each dataset contains environmental parameters, occupants' subjective responses, building information, and personal information. The dataset has been instrumental in the development of indoor thermal environment evaluation standards and energy codes in China. It can also have broader applications, such as contributing to the international thermal comfort dataset, modeling thermal comfort and adaptive behaviors, investigating regional differences in indoor thermal conditions, and examining occupants' thermal comfort responses. [ABSTRACT FROM AUTHOR]

Computational fluid dynamics (CFD) methods are being increasingly used for predicting airflow fields around buildings, but personal computers can still take tens of hours to create a single design using traditional computing models. Considering both accuracy and efficiency, this study compared the performances of the conventional algorithm PIMPLE, fast fluid dynamics (FFD), semi-Lagrangian PISO (SLPISO), and implicit fast fluid dynamics (IFFD) in OpenFOAM for simulating wind flow around buildings. The effects of calculation parameters, including grid resolution, discrete-time step, and calculation time for these methods are analyzed. The results of the simulations are compared with wind tunnel tests. It is found that IFFD and FFD have the fastest calculation speeds, but also have the largest discrepancies with test data. The PIMPLE algorithm has the highest accuracy, but with the slowest calculation speed. The calculation speeds of the FFD, SLPISO, and IFFD models are 6.3, 3 and 13.3 times faster than the PIMPLE model, respectively. The calculation accuracy and speed of the SLPISO model are in between those of the IFFD, FFD and PIMPLE models. An appropriate algorithm for a project may be chosen based on the requirements of the project. [ABSTRACT FROM AUTHOR]

The pressure difference in buildings under natural state is usually below 10 Pa, and the air change rate at 50 Pa (ACH50) is often used to evaluate building airtightness. There is a dearth of research on air infiltration predictive model at different pressures in China. Moreover, the airflow coefficient (C), a key parameter for air infiltration, is necessary to determine ACH50. Based on prior experimental data, several methods including ordinary least squares (OLS), stepwise regression, partial least squares (PLS) and nonlinear fitting with independent variable screening methods, were employed to establish an airflow coefficient model. The determination coefficient (R2) and the variation coefficient of the root-mean-square error (CV(RMSE)) of these models were compared. The simulation results show that R2 of the airflow coefficient models for apartments and villas increased by a maximum of 25.9% and 2.3%, respectively, using PLS method. The improvement with nonlinear fitting was weaker. Based on K-P model, a conversion model between ACH50 and ACH4 was developed as an air infiltration predictive model under natural state. Blower door and tracer gas tests were conducted to verify the conversion model. The expected error was approximately 10%, which may be caused by measurement errors and shielding from surrounding obstructions. Further studies need to focus on obtaining more experimental data for building airtightness and developing a conversion model for high-rise residential buildings. [ABSTRACT FROM AUTHOR]

The building energy consumption per unit area continuously decreases in recent years so that the ground-coupled heat pump system (GCHPS) with the horizontal ground heat exchanger (HGHE) no longer requires excessive underground area when they are applied to buildings. This phenomenon contributes to the popularity of the horizontal GCHPS. In this context, a simulation model of the horizontal GCHPS is developed to investigate their main design factors from the economic point of view. Taking the annual cost of GCHPS as the evaluation index, the orthogonal experiment design (OED) method and the analysis of variance (ANOVA) are applied to determine the influence degree of each factor on the economic aspects of the GCHPS. Then the control variable method is employed to analyze the effect of each factor on the performance and the economy of the GCHPS. The results of the present study show that the main affecting factors of the problem are the pipe length, pipe spacing, buried depth and pipe diameter of HGHE. Moreover, it is found that the flow rate of the heating medium has negligible impact on the HGHE. It is concluded that these factors in the order of importance are the pipe spacing, pipe diameter, pipe length, buried depth of the HGHE and the flow rate of the heating medium. Increasing the aforementioned parameters in accordance with the order of significance can improve the performance and reduce the operational expense of the horizontal GCHPS, but it increases the overall cost of the system. [ABSTRACT FROM AUTHOR]

Chinese Kangs are widely used for home space heating in rural residences. However, the energy efficiency of a traditional Kang is less than 20%. Thus, the hot-wall Kang is gradually becoming popular in Jilin, Heilongjiang and Inner Mongolia of China because of its higher energy efficiency, comfortable indoor thermal environment and flexibility of application. The hot-wall Kang has three operation modes. The heat transfer model of Kang in previous studies was developed based on the three assumptions, which include the uniform Kang surface temperature, the neglect of the radiation effect of gas and the thermal storage of ash soil layer. However, the model of hot-wall Kang in this paper was improved with respect to the three assumptions, which were discussed in this paper. Then, the model was validated by experiments and applied to optimize the thermal performance of the hot-wall Kang. The results showed that the simulation results were in good agreement with the measurement results. Furthermore, based on the verified model, the better thickness and material of the cover board were found to be 0.06 m and foam concrete, respectively. [ABSTRACT FROM AUTHOR]