| 1. |
- Dong, Jiankai, et al.
(författare)
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An experimental study on a novel radiant-convective heating system based on air source heat pump
- 2018
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Ingår i: Energy and Buildings. - : Elsevier BV. - 0378-7788 .- 1872-6178. ; 158, s. 812-821
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Tidskriftsartikel (refereegranskat)abstract
- Air source heat pump (ASHP) has been widely applied to many parts of the world due to its simple structure and low initial cost. To save energy consumed for spacing heating and enhance the indoor thermal environment, improving the performances of ASHP has become one of the research focus in the relevant field. Currently, the most conventional heating terminal of ASHP system for spacing heating is finned tube heat exchanger coupled with air fan, which may cause strong draught sensation and dry eye problem and make users feel uncomfortable during convective heating. On the other hand, radiant heating is attracting more and more attention due to its comfortable indoor thermal environment. In this paper, a novel radiant-convective heating terminal was presented and coupled into an ASHP system. Both the operating characteristics and heating performances of the novel system were experimentally investigated. The experimental results showed that the novel system took about 28 min to enter a steady operating stage, during which the radiant panel surface temperature and outlet air temperature for the novel heating terminal, and COP of the novel system were 40.9 degrees C, 32.1 degrees C, and 3.11, respectively, under a standard heating condition. In addition, all parameters mentioned above saw a linear increase when the outdoor air temperature increased from -4.0 to 10.0 degrees C, and their respective rising rates were 0.41 degrees C, 0.28 degrees C and 0.04 per increased outdoor air temperature. Furthermore, the experimental results also demonstrated that adjusting the indoor air flow rate could effectively allocate the amount of heat generated by different heat transfer modes, which may have significant effects on the indoor thermal environment.
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| 2. |
- Ma, Shengyuan, et al.
(författare)
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Comparison of the time-dependent characteristics between particle mass and particle number emissions during oil heating and emission mitigation strategies
- 2023
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Ingår i: Building and Environment. - : Elsevier BV. - 0360-1323 .- 1873-684X. ; 242
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Tidskriftsartikel (refereegranskat)abstract
- It is important to understand the cooking particles emitted over time to mitigate cooking pollution, but current control strategies fail to consider both particle mass and number emissions. Therefore, this study was designed to compare the differences in time-dependent characteristics of particle mass and number emissions and to propose comprehensive mitigation strategies that consider both characteristics. For this purpose, the effects of various factors on both emissions were analyzed, and time-dependent emission rate models were developed. The time-dependent models obtained were statistically significant (P < 0.001), with most R2 values greater than 0.90. The masses and numbers of particles emitted often varied in the opposite direction. During the smoking stage, corn oil exhibited low particle mass emissions while its particle number emission rate (TERn) reached 109#/s. However, at higher temperatures (T > TDM), the percentage difference in TERn with increasing oil volume decreased from 7.1% to 3.5%, while that in PM2.5 emission rate with decreasing oil volume was almost more than 25%. This indicated that the increased oil volumes were more effective in reducing the particle masses emitted from corn oil than in increasing the numbers of particles emitted, and similar conclusions were also drawn for decreasing oil surface area. Overall, oils exhibiting lower particle mass emissions and lower cooking temperatures were recommended for cooking. Lower oil volumes and larger pans should be used at relatively lower temperatures (T < TDM) primarily to mitigate particle number emissions, while higher oil volumes and smaller pans should be used at higher temperatures to control particle mass emissions.
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| 3. |
- Ma, Shengyuan, et al.
(författare)
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Indoor thermal environment in a rural dwelling heated by air-source heat pump air-conditioner
- 2022
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Ingår i: Sustainable Energy Technologies and Assessments. - : Elsevier BV. - 2213-1388 .- 2213-1396. ; 51
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Tidskriftsartikel (refereegranskat)abstract
- Air-source heat pumps (ASHP) are increasingly used to improve space heating. However, few relevant studies have focused on the rural residential buildings that use ASHP air-conditioners for heating conditions. Therefore, this paper presents experiments and numerical simulations to analyse the impact of ASHP air-conditioners on the indoor thermal environment of a rural dwelling during heating seasons. In this study, the influences of different air-supply parameters (temperature, angle and velocity of air supply) and the position of the ASHP airconditioner on the local thermal comfort were evaluated. The influence weights of both the above factors and their interaction were obtained. The simulation results showed that the temperature differences between the head and foot region (Delta Th-f) in most cases exceeded 3.0celcius, demonstrating the thermal comfort in the rural dwelling was more unacceptable than the urban buildings. Moreover, the results of orthogonal design indicated that air-supply velocity had the most significant impact on the Delta Th-f values, followed by the air-supply temperature, air-supply angle and installation height. Reducing any air-supply parameter or enhancing the installation height might improve the thermal comfort performance. This research can provide practical strategies for improving the indoor thermal environment of rural dwellings, and guide the design of ASHP air-conditioning systems.
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| 4. |
- Ma, Shengyuan, et al.
(författare)
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Temperature-dependent particle mass emission rate during heating of edible oils and their regression models
- 2023
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Ingår i: Environmental Pollution. - : Elsevier BV. - 0269-7491 .- 1873-6424. ; 323
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Tidskriftsartikel (refereegranskat)abstract
- Particulate matter emitted by heated cooking oil is hazardous to human health. To develop effective mitigation strategies, it is critical to know the amount of the emitted particles. The purpose of this research is to estimate the temperature-dependent particle mass emission rates of edible oils and to develop models for source strength based on the multiple linear regression method. First, this study examined seven commonly used oils by heating experiments. The emission rates of PM2.5 and PM10 were measured, and the effects of parameters such as oil volume and surface area on the emission rates were also analysed. Following that, the starting smoke points (Ts') and aggravating smoke points (Tss') of tested oils were determined. The results showed that oils with lower smoke points had greater emission rates. Notably, the experiments performed observed that peanut, rice, rapeseed and olive oil generated PM2.5 much faster at 240 degrees C (2.22, 1.50, 0.82 and 0.80 mg/s, respectively, at the highest emission conditions) than that of sunflower, soybean, and corn oil (0.15, 0.12 and 0.11 mg/s, respectively). The temperature, volume, and surface area of oils all had a significant impact on the particle mass emission rate, with oil temperature being the most influential. The regression models obtained were statistically significant (P < 0.001), with the majority of R2 values greater than 0.85. Using sunflower, soybean and corn oils, which have higher smoke points and lower emission rates, and smaller pans for cooking is therefore recom-mended based on our research findings.
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| 5. |
- Ma, Shengyuan, et al.
(författare)
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Temperature-dependent particle number emission rates and emission characteristics during heating processes of edible oils
- 2023
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Ingår i: Environmental Pollution. - : Elsevier BV. - 0269-7491 .- 1873-6424. ; 333
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Tidskriftsartikel (refereegranskat)abstract
- The goal of this research is to investigate the temperature-dependent emission rates of particle numbers and emission characteristics during oil heating. Seven regularly used edible oils were studied in a variety of tests to attain this objective. First, total particle number emission rates ranging from 10 nm to 1 μm were measured, followed by an examination within six size intervals from 0.3 μm to 10 μm. Following that, the impacts of oil volume and oil surface area on the emission rate were investigated, and multiple regression models were developed based on the results. The results showed that corn, sunflower and soybean oils had higher emission rates than other oils above 200 °C, with peak values of 8.22 × 109#/s, 8.19 × 109#/s and 8.17 × 109#/s, respectively. Additionally, peanut and rice oils were observed to emit the most particles larger than 0.3 μm, followed by medium-emission (rapeseed and olive oils) and low-emission oils (corn, sunflower and soybean oils). In most cases, oil temperature (T) has the most significant influence on the emission rate during the smoking stage, but its influence was not as pronounced in the moderate smoking stage. The models obtained are all statistically significant (P < 0.001), with R2 values greater than 0.9, and the classical assumption test concluded that regressions were in accordance with the classical assumptions regarding normality, multicollinearity, and heteroscedasticity. In general, low oil volume and large oil surface area were more recommended for cooking to mitigate UFPs emission.
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| 6. |
- Wang, Yuanbo, et al.
(författare)
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Integrating NSGA-II and CFD for enhanced urban airflow prediction: Recalibration of closure coefficients for a nonlinear eddy viscosity model
- 2024
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Ingår i: Building and Environment. - : Elsevier BV. - 0360-1323 .- 1873-684X. ; 259
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Tidskriftsartikel (refereegranskat)abstract
- Accurately predicting urban environmental airflows using the Reynolds-averaged Navier‒Stokes (RANS) approach presents significant challenges due to unsolved closure issues. Previous attempts to address these limitations through coefficient adjustments were constrained by isotropic assumptions, resulting in limited generalizability and reliability, especially for complex building configurations. In this study, we proposed a recalibration approach within a multi-objective optimization framework. Nondominant sorting genetic algorithm-II (NSGA-II) and computational fluid dynamics (CFD) numerical computations were utilized to optimize the closure coefficients of a nonlinear eddy viscosity (NLEV) model, with a focus on improving the accuracy of the mean velocity, turbulent kinetic energy, and airflow characteristic predictions. To ensure the robustness of the model, appropriate objective functions were carefully defined. The proposed approach was evaluated using three-dimensional (3D) building cases related to urban prototypes, and the results demonstrated the necessity of multi-objective optimization. Our findings indicated that the trade-off solution on the Pareto front consistently outperformed the baseline and single-objective optimal versions across different types of urban airflow, demonstrating superior generalizability. The simulation results of this solution exhibited closer agreement with the wind tunnel experimental data and provided more accurate distributions of the time-averaged values and airflow characteristics. The normalized root mean square errors are reduced by about 33 %, 52 %, 35 % and 9 % in velocity, and 31 %, 25 %, 24 % and 11 % in turbulent kinetic energy, respectively. These results underscore the effectiveness of the multi-objective optimization framework in addressing closure issues and improving the prediction accuracy of complex urban environmental airflows.
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| 7. |
- Wang, Yuanbo, et al.
(författare)
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Prediction of urban airflow fields around isolated high-rise buildings using data-driven non-linear correction models
- 2023
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Ingår i: Building and Environment. - : Elsevier BV. - 0360-1323 .- 1873-684X. ; 246
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Tidskriftsartikel (refereegranskat)abstract
- When it comes to predicting urban airflow, steady Reynolds-averaged Navier-Stokes (SRANS) models that rely on Reynolds stress often face a challenge called the closure problem. This problem involves unresolved structural flaws and uncertainties in the closure coefficients used in the models. Previous attempts to recalibrate coefficients for specific urban flows without breaking the linear constitutive relation have resulted in simulation results constrained by the baseline turbulence model. Therefore, this study aims to enhance the performance of SRANS models by addressing these structural flaws. To achieve this, a novel data-driven framework is proposed. It leverages the deterministic symbolic regression algorithm to discover explicit algebraic expressions for a non-linear Reynolds stress correction model. The robustness of the correction model is ensured by maintaining the linear eddy viscosity model for iterative calculations while keeping the non-linear component frozen. The proposed framework is evaluated using three isolated building cases with varying geometric configurations and inflow boundary conditions. Findings demonstrate that computational fluid dynamics (CFD) predictions incorporating the data-driven non-linear correction model consistently align closer to wind tunnel experimental results compared to both standard and non-linear versions of the k-ε turbulence model. This improvement is reflected in reduced reattachment lengths and more accurate mean velocity distributions in the wake of buildings. However, it should be noted that there is a possibility of overpredicting wind velocity in the windward area. This study introduces valuable insights and additional strategies to enhance the prediction accuracy of SRANS models in urban airflow simulations.
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