Abstract ：

As infectious respiratory diseases are highly transmissible through the air, researchers have improved traditional total volume air distribution systems to reduce infection risk. Multi-vent module-based adaptive ventilation (MAV) is a novel ventilation type that facilitates the switching of inlets and outlets to suit different indoor scenarios without changing ductwork layout. However, little research has evaluated MAV module sizing and air velocity selection, both related to MAV system efficiency in removing contaminants and the corresponding level of protection for occupants in the ventilated room. Therefore, the module-source offset ratio (MSOR) is proposed, based on the MAV module size and its distance from an infected occupant, to inform selection of optimal MAV module parameters. Computational fluid dynamics simulations illustrated contaminant distribution in a two-person MAV equipped office. Discrete phase particles modelled respiratory contaminants from the infected occupant, and contaminant concentration distributions were compared under four MAV air distribution layouts, three air velocities, and three module sizes considered using the MSOR. Results indicate that lower air velocities favour rising contaminant levels, provided the ventilation rate is met. Optimal contaminant discharge can be achieved when the line of outlets is located directly above the infected occupant. Using this parameter to guide MAV system design, 85.7% of contaminants may be rendered harmless to the human body within 120 s using the default air vent layout. A more appropriate supply air velocity and air vent layout increases this value to 91.4%. These results are expected to inform the deployment of MAV systems to reduce airborne infection risk.

Keyword ：

computational fluid dynamics computational fluid dynamics infection control infection control indoor air quality indoor air quality multi-vent module-based adaptive ventilation multi-vent module-based adaptive ventilation

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Abstract ：

Multi-energy supply systems for office buildings have been rapidly developed. Although some combinations of distributed energy sources have been applied in office buildings, there is a lack of research on the collaborative matching of office building multi-energy supply systems that integrate random electric vehicles (EVs), stationary battery (STB), photovoltaic (PV), and the power grid (PG). Therefore, in this study, we propose a method for the collaborative matching of supply and demand for multi-energy systems integrated with random EVs, STB, PV, and PG in office buildings to minimize the net operating cost of the system. To this end, we first constructed an objective function, including system operating cost and operating revenue. We then modeled the supply and demand sides of the system. On the supply side, the travel parameters of EVs around the office building were investigated, and the randomness of EVs was quantified using the Monte Carlo algorithm. On this basis, the charging and discharging capacity of EVs was determined. Additionally, an STB charging and discharging model and PV power generation model were established. On the demand side, a prediction model of office building power consumption was constructed using the Random forest (RF) algorithm. Next, the energy supply and demand of office buildings for the following 24 h were matched collaboratively using nonlinear programming. Finally, the proposed collaborative matching method was applied to a real case study. The results showed that the matching method can reduce the net operating cost of the system by up to 92% compared with the Basic scenario.

Keyword ：

Electric vehicles Electric vehicles Collaborative matching method Collaborative matching method Randomness Randomness Multi-energy supply system Multi-energy supply system Photovoltaic Photovoltaic Random forest Random forest

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Abstract ：

In the context of indoor environmental control, users have varying preferences with respect to their ventilation demands. Currently, the design and control of ventilation schemes do not consider user preferences adequately. To optimize the ventilation strategies based on user demands, the weight coefficients of occupant ventilation demands were extracted in this study using questionnaire surveys. The distinctive characteristics of ventilation preferences among individuals were then analyzed. Computational fluid dynamics (CFD) was used to simulate ventilation schemes with multiple air supply parameters within an office environment, and a database of ventilation performance under different conditions was generated. A multi-index evaluation was conducted to determine the recommended air supply scheme. Finally, a backpropagation neural network was employed to establish a personalized recommendation model for the ventilation scheme. The model inputs include the environmental weight coefficients assigned by the occupants and objective environmental parameters. Its outputs include the ventilation performance and air supply parameters. The results demonstrate that the recommended model can align with user demands, providing suitable ventilation performance and air supply parameters. For user-oriented indoor environment construction, this method enables the rapid and accurate determination of recommended air supply parameters and performance, facilitating the creation of a healthy built environment.

Keyword ：

Demand-oriented control Demand-oriented control BP neural network BP neural network Personalized recommendation Personalized recommendation Ventilation method Ventilation method CFD CFD

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Abstract ：

Cities comprise many residential districts, facing environment and energy problems. Therefore, the retrofit of these existing residential districts is the main part of city renewal. Some retrofit strategies may affect the thermal microclimate environment and lead to changes in the energy demand of buildings. Few studies had evaluated these retrofit effects, which has brought the motivation for this study, to determine the microclimate changes surrounding buildings due to residential district retrofits and the corresponding impact on the cooling load of buildings. The most general retrofit strategies were selected, including greening rate, ground pavement materials, wall materials and roof materials. They were applied to a prediction model for the selected residential district in the simulation tool. The mean reduction of air temperature around the building has been used to evaluate the impact of retrofit strategies on the microclimate in the district. The results showed that greening had the greatest impact on the mean air temperature around buildings, followed by the pavement material, the roof and the wall material. Ground greening, wall material and roof material decreased the total cooling load, while pavement material increased it.

Keyword ：

Retrofit Retrofit Residential district Residential district ENVI-met ENVI-met Strategies Strategies Energy demand Energy demand

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Abstract ：

Infectious respiratory diseases are known to have high levels of airborne transmissibility. However, traditional ventilation methods based on perfect mixing often lead to the diffusion of airborne pathogens. A ventilation method that can reduce air mixing is necessary. The ventilation system should also be able to adapt to changes in the use scenario of a given room. For this reason, a new type of ventilation method, referred to as multi-vent module-based adaptive ventilation (MAV), is proposed, and its performance in contaminant diffusion control is evaluated in this study. Computational fluid dynamics (CFD) is applied to investigate the contaminant distribution in a two-desk office with MAV. Tracer gas (CO2) is used to simulate coughed contaminants from an infected person. For three different MAV air distributions (vertical, parallel, and cross mode) and traditional mixing ventilation (MV), the contaminant concentration distributions and contaminant variations in the oronasal areas of the occupants are compared. The results show that MAV results in a smaller contaminant diffusion area and lower contaminant diffusion speed. Furthermore, MAV can reduce the peak contaminant concentrations at the oronasal areas of the occupants to 12% of that of MV. The levels of performance of the three MAV modes are different because of the different airflow patterns that they create. For the tested location of the infected person, the vertical mode has the best performance. The average cumulative inhalation of contaminants in the vertical mode is 23.7% lower than that in the cross mode and 36.5% lower than that in the parallel mode.

Keyword ：

Computational fluid dynamics (CFD) Computational fluid dynamics (CFD) Indoor contaminants Indoor contaminants Cross-infection Cross-infection Probable cumulative inhalation Probable cumulative inhalation Multi-vent module-based adaptive ventilation (MAV) Multi-vent module-based adaptive ventilation (MAV)

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Abstract ：

Current buildings are facing different environmental demands, such as improving thermal comfort and energy efficiency and reducing exergy loss. However, conventional mixing ventilation (MV) cannot satisfy the different demands; therefore, advanced ventilation modes utilizing a non-uniform environment have gained attention. Multiple scenarios with different occupant activity levels cause difficulties in ventilation control. For these multi factor and multi-objective oriented problems, two issues exist: 1) how to change the operational mode when the scenarios and demands change simultaneously, and 2) how to evaluate the overall ventilation performance under different scenarios and demand conditions. Therefore, this study proposes an approach for assisting in the decision making of ventilation strategies in different scenarios under single or multiple demand conditions. Using a typical office, three occupancy conditions were predesigned by combining MV, displacement ventilation (DV), and stratum ventilation (SV) solutions. Computational fluid dynamics simulations were performed to calculate the indicators for a single demand, namely, heat removal efficiency (HRE), contaminant removal efficiency (CRE), air diffusion performance index (ADPI), and modified index of mixing (IOM*). In the case of multiple demands, the Z-score was applied for standardization and ranking. The result showed that different scenarios with different demand orientations require different ventilation modes. Taking the HRE and IOM* as objectives, DV performed best for the scenario of independent working, whereas SV performed best for discussion and meeting. When considering four demands simultaneously, SV performed best in the scenario of meeting, while MV performed best in the remaining scenarios. This study has verified the effectiveness of using a multi-indicator evaluation method for ventilation strategy optimization under multi-factor and multi-scenario conditions.

Keyword ：

Decision-making analysis Decision-making analysis Multi-indicator evaluation Multi-indicator evaluation Z-score Z-score CFD CFD Multi-scenario Multi-scenario

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Abstract ：

In recent years, in order to promote the construction of low-carbon communities (LCCs) in China, many scholars have proposed an evaluation indicator system of LCC. The existing indicator systems are mostly established from the macro perspective of environmental impact and resource conservation, but few are from the micro technical perspective. Thus, the aim of this study is to construct a micro technical evaluation indicator system for LCCs. Firstly, the index system was divided into three categories: low-carbon building, low-carbon transportation, and low-carbon environment. Then, the technical indicators were selected through empirical analysis. The indicator weights were assigned by the improved analytic hierarchy process (AHP) and the multi-level fuzzy comprehensive evaluation method was used as the evaluation method of the indicators. Finally, in order to examine the practicality of the indicator system, two typical communities in Tianjin and Shanghai were selected as case studies. The results showed that the indicator system gave a reasonable low-carbon level for the two communities, which was in line with the actual low-carbon construction status of each community. In addition, the evaluation results pointed out that the low-carbon community (LCC) in Tianjin needs to further strengthen the construction of the low-carbon environment, including community compactness, rainwater collection and utilization, and waste recycling. For the LCC in Shanghai, it was pointed out that the construction of the low-carbon building and low-carbon transportation needs to be strengthened. The indicator system can be used as a tool for urban planning and construction personnel to evaluate the construction progress and low-carbon degree of LCC.

Keyword ：

low-carbon community low-carbon community improved analytic hierarchy process improved analytic hierarchy process technical indicators technical indicators multi-level fuzzy comprehensive evaluation method multi-level fuzzy comprehensive evaluation method

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Abstract ：

In data center, using outdoor low-temperature air as free cooling is one of the most effective ways to increase the energy efficiency of the heat source system. At the same time, optimizing the indoor air organization to reduce the energy consumption of fans is considered as another effective way of saving energy. In this study, a new cooling system for data center by using evaporation and condensation of CO2 as free cooling is proposed. Also, the system is optimized by organizing the cooling airflow with natural convection and small distributed fans on the indoor side. This paper mainly focuses on optimization of cooling airflow, especially that around racks. CFD is used to analyze the temperature distributions and flow distributions by adjusting power of small distributed fans and shape of the cooling unit. The results show that small distributed fans and natural convection can generate the desired distribution of cooling airflow. © 2020, Springer Nature Singapore Pte Ltd.

Keyword ：

Energy efficiency Energy efficiency Temperature Temperature Computational fluid dynamics Computational fluid dynamics Carbon dioxide Carbon dioxide Green computing Green computing Energy utilization Energy utilization Cooling systems Cooling systems Natural convection Natural convection Thermoelectric equipment Thermoelectric equipment Air conditioning Air conditioning Cooling Cooling

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