Supply Air Parameters Research Articles

Parametric study and optimization on exhaled particle dispersion in a ward heated by impinging jet ventilation using orthogonal-based grey relational method

During the heating season with high-frequency infection events, an appropriate ventilation method is critical to a healthy hospital environment. In this study, impinging jet ventilation (IJV) was proposed to reduce cross-infection risk in a two-bed ward for winter heating. An Eulerian-Lagrangian approach validated by experimental data was employed to simulate exhaled particle dispersion. Using a full factorial design method, under air changes per hour (ACH) of 6–15 h−1 and supply air temperature (Ts) of 24–30 °C, the effects of supply air parameters on particle dispersion was analyzed. A correlation model was subsequently established to delineate the relationship between supply air parameters and particle elimination. With an orthogonal-based grey relational method, this study compared the contribution and significance of supply air parameters and two uncontrollable factors (i.e., source location and outdoor air temperature), and then optimized the supply air parameters of IJV. The results indicated that the contribution percentage of supply air parameters was higher than 70 % for particle removal and residence time. With an appropriate supply air parameter, the airflow of IJV could comply with human body plume, enhancing removal of fine particles (≤20 μm). However, with a low Ts (lower than 26 °C) or an excessive ACH (more than 12 h−1), the number of fine particles moving upwards might be reduced. To achieve a better performance in preventing cross-infection, ACH and Ts of IJV were recommended to be set at 9 h−1 and 28 °C, respectively. The findings were expected to provide guidance for ward ventilation design.

Ventilation and air conditioning design approach based on ASHRAE psychrometric chart and Mollier diagram

Society needs long-term sustainability and healthy building projects, and indoor air quality assurance engineering systems play a pivotal role in the energy performance of buildings. Therefore, when designing heating, ventilation, and air conditioning systems, it is crucial to make the most technically sound decisions in terms of energy consumption and assess their impact on the building’s energy performance. This article delves into the design of ventilation and air conditioning systems, presenting a method for evaluating their performance. The foundation of project development is an agreement on the design criteria, which are developed based on a preliminary analysis of the building concept. This agreement ensures cohesive collaboration among all stakeholders: the client, the architect, the system designer, the contractor, and ultimately the personnel responsible for commissioning, operating, and maintaining the systems post-construction. We suggest conducting a comprehensive analysis of the processes occurring within the space without initially linking them to room air exchange. From this analysis, we derive the angular coefficient for the direction of the air condition change on both a psychrometric chart and a Mollier diagram. The process line on the psychrometric chart provides insights into how the performance factor of the air distribution system will influence the desired supply air parameters. We can then evaluate how significantly the gap between the supply air and the exhaust air parameters expands if the room’s air exchange volume is reduced for budgetary reasons. The article showcases this design methodology using a simplified case study.

Assessment of COVID-19 infection Risk, thermal Comfort, and energy efficiency in negative pressure isolation wards with varied ventilation modes

Negative pressure isolation wards (NPIWs) play a crucial role in providing care to COVID-19 patients during a pandemic. However, the exhalation of patients releases aerosols containing pathogens, posing a potential infection risk for healthcare workers (HCWs). While robust ventilation systems within NPIWs can help mitigate this risk, they may also lead to increased energy consumption and reduced thermal comfort for patients. Therefore, it is imperative to strike a delicate balance between HCW safety, patient comfort, and energy efficiency when optimizing airflow within NPIWs. This study introduces TARGETING, a novel index designed to assess the efficiency of aerosols removal of ventilation systems in NPIWs. The primary goal of TARGETING is to enhance the precision of ventilation systems, consequently reducing the required air changes per hour (ACH) and minimizing energy consumption. The research delves into the impact of various supply air parameters, including ACH and temperature, as well as different ventilation modes. Through a comprehensive evaluation utilizing an array of metrics such as the Air Diffusion Performance Index (ADPI), Predicted Mean Vote (PMV), TARGETING, infection risk assessment, and energy consumption estimation measured by cooling load (Lcool), this study employs an Analytic Hierarchy Process to assess the aforementioned indices. The findings highlight that air curtain ventilation (ACV) emerges as the most favorable choice, delivering comprehensive benefits, including an infection risk of less than 0.03%, an ADPI score of 90.2%, a PMV close to zero, TARGETING at 1.3, and energy savings ranging from 35.1% to 57.3%.

Evaluation of heating performances of different ventilation methods in an office

In this study, 12 cases were investigated in an office-layout room using experiments and computational fluid dynamics (CFD) simulations. The heating performances of four ventilation methods (i.e. mixing ventilation (MV), stratum ventilation (SV), deflection ventilation (DeV) and impinging jet ventilation (IJV)) were comprehensively compared by various evaluation indexes (i.e. predicted mean vote (PMV), draught rate (DR), vertical air temperature difference (△T), air diffusion performance index (ADPI), energy utilization coefficient (EUC), air change efficiency (ACE) and contaminant removal efficiency (CRE)). Better thermal comfort was found in rooms heated by SV and DeV. The PMV, DR and △T under SV and DeV complied with Category B of ISO 7730:2005, and the ADPI was in full compliance with the stipulation of ANSI/ASHRAE 113-2022. For the energy-saving characteristic, the targeted-occupied-zone ventilation methods (i.e. SV, DeV and IJV) can effectively deliver warm air to the occupied zone, with the EUC values higher than unity and thus providing a good potential for energy saving. SV and IJV showed slightly higher ACEs in the breathing zone. The contaminant removal effectiveness of SV, DeV and IJV was comparable. Under the combined influence of occupant thermal plumes and locations of exhausts, MV showed a high CRE. However, the CRE under MV decreased significantly when the exhausts were not above occupants. In the case of supply air parameters in this study, the entropy-weight method indicated that DeV and SV had a better overall performance for winter heating, followed by IJV and then MV.

Optimization of Supply Air Parameters Control Based on Gappy POD Method for Creating Non-Uniform Temperature Fields

This paper explores the implementation and application of non-uniform ambient fields from two perspectives: constant heat source and abrupt heat source variation. On the one hand, the proper orthogonal decomposition (POD) method is used to find the optimum air supply parameters for different target temperatures at multiple demand points. The one-parameter, two-parameter and three-parameter cases were considered, respectively, and the parameters obtained from the search for optimisation were verified, yielding mean deviations of 0.405 K, 0.368 K and 0.380 K and mean errors of 1.48%, 1.61% and 1.68%, respectively. The accuracy of the reconstructed results of the POD method and the reliability of the POD method for finding the best results are verified step by step with the help of the experimental platform. The validation results show that the average error between the reconstructed data and the experimental data for the POD method does not exceed 5%; the average errors between the measured and set demand temperatures at the target point are 1.2% and 0.8%. On the other hand, the gappy POD method is used to accurately fill in the elements of the system with arbitrary missing data and to reconstruct the flow field in the presence of missing (gappy) data with a limited number of sensors combined with POD. The errors of the gappy POD method reconstruction are 0.54% and 1.75%. POD and gappy POD methods can better create non-uniform temperature fields in practical scenarios according to actual needs. The results of the study can provide a methodological reference for real-time reconstruction and real-time control of the indoor flow field environment. It also serves as a help and suggestion for the actual project in terms of end-regulation system and reverse design method.

A novel occupant-centric stratum ventilation system using computer vision: Occupant detection, thermal comfort, air quality, and energy savings

Traditional ventilation and air conditioning systems typically operate on a predetermined schedule with fixed operating parameters. Occupant-centric control (OCC) strategies have been proposed to reduce system operation energy consumption without sacrificing thermal comfort. Indoor occupancy detection in real time is a critical step in successfully implementing the OCC strategy. Thus, the deep learning-based computer vision method was adopted in the first step of the study, and the detection performance and camera position were analyzed in an office scenario. Next, the proposed OCC strategy was used to regulate the supply air parameters and outdoor air volume in stratum ventilation based on the monitored occupant number. The traditional static control strategy was then compared to two control strategies: constant air volume and variable air volume. Occupant detection performance results showed the mean NRMSD for the five most common relative positions of the occupants and camera was 0.1109, with sitting back to camera having the lowest accuracy. Subjective response results demonstrated that, when compared to the traditional control strategy, thermal comfort was improved by 43%–73%, perceived air quality was maintained at an acceptable level, CO2 concentration was less than 700 ppm, and energy could be saved by 2.3%–8.1%. Furthermore, the lower the occupancy, the greater the improvement in comfort and the greater the energy savings. This research focused on how the stratum ventilation system responds to dynamic changes in occupancy and provided insights into reducing unnecessary energy waste while maintaining comfort.

An efficient design method of indoor ventilation parameters for high-speed trains using improved proper orthogonal decomposition reconstruction

The ventilation parameters inside a compartment of a high-speed train (HST) are of great significance to the thermal comfort and air quality around passengers. Additionally, parameter design relying on traditional numerical simulations takes considerable time and resources. This study proposed an improved inverse design approach based on proper orthogonal decomposition (POD) to the design of supply air parameters of a compartment for an HST; this method was combined with the radial basis function (RBF) model and the orthogonal experimental design (OED) to facilitate the process. The feasibility and accuracy of this improved method applied to ventilation design inside the HST were validated by experimentally verified numerical simulations. Three design parameters (i.e., the temperature of the inlets, the ratio of the upper air supply, and the angle of the upper inlets) and evaluation indexes (i.e., predicted mean vote, draught rate and air age) were taken into consideration, and the sensitivity of the design parameters to the evaluation indexes was analysed by orthogonal cases using range analysis. The proposed POD reconstruction method has a remarkable advantage over traditional numerical simulation methods with respect to the time and efficiency of design and can take approximately 40% less time than the current POD method to obtain numerical simulation samples. Moreover, the reconstructed results by the RBF model were more consistent with the actual simulation data, and the average determination coefficients (R2) of all test cases for all evaluation indexes are more than 0.97.

Experimental and numerical investigation on thermal performance of data center via fan-wall free cooling technology

With the rapid increase in the scale of data center (DC) construction, DC air conditioning energy consumption has attracted wide attention over the past years. As the DCs are located in the mild climate regions, the air-side free cooling technology that combined with the fan wall air supply demonstrates excellent energy-saving potential. However, there are quite few reports on the environmental thermal response of air conditioning in fan-wall DCs. In this article, the effect of both supply air volume (SAV) and supply air temperature (SAT) on the temperature control performance of the DC are tested through a newly built small fan-wall DC facility. The effect of supply air parameters and the DC’s total power (DCTP) are further investigated through numerical simulation. The results show that the server inlet air temperature increases linearly with the SAT and the DCTP, whereas decreases logarithmically with the SAV. The optimal SAV is 0.5 m3/s for a single rack with 2.5 kW when the SAT is 27 °C. Based on the Rack Cooling Index (RCI) evaluation method, an empirical SAV correlation is established and verified against other numerical cases for fan-wall DCs when taking the SAV, the SAT, and the DCTP into account. In the current study, according to the developed model, approximately 34% energy consumption of fans could be saved for fan-wall DCs.

Predicting personalized thermal comfort in stratified micro-environments using turbulent jet theories and data-driven models

Stratified micro-environments offer different air distribution stratifications for each occupant and work as a solution for satisfying individual thermal preferences and improving energy efficiency. It is essential to accurately predict the thermal comfort provided in the micro-environments for efficient control. A computational fluid dynamics (CFD) model, validated against experimental measurements, is used to generate data with different conditions of operations systematically. Two acknowledged jet theories, the Abramovich and the Koestel systems, are applied with linear regression models to predict the predicted mean vote (PMV) and the draft rating (DR). Data-driven models include (1) back propagation neural network (BPNN), as a presentative of artificial neural network (ANN), and (2) support vector machine (SVM), as a presentative of non-ANN, are compared with the jet theory models. The demarcation value of the Archimedes number (Ar) between the free-jet condition and the non-free-jet condition is 0.0625. Jet theory models are applied for thermal comfort predictions with free-jet conditions, achieving low mean absolute error (MAE) values of the PMV and the DR, i.e., below 0.2 and 3%, respectively. A sufficient accuracy is also reached for experimental measurements in published studies, with the lowest MAE values of 0.09 for the PMV and 2.10% for the DR. Data-driven models are capable of similarly accurate predictions, advancing their generality for both the free-jet and non-free-jet conditions. The input sets handled by jet theory models perform better than the monitored supply air parameters, showing their value for improving data-driven models with limited data size.

Investigation into effect of non-uniform thermal environment on thermal sensation under stratum ventilation for heating by using interpolation-based multi-level fuzzy comprehensive evaluation

Stratum ventilation for heating is applied to provide satisfactory indoor thermal environments with great potentials in winter. Indoor non-uniform environments are important for both overall and local thermal sensations in the same occupied subzone (i.e., vertical spaces) as well as different subzones of the occupied zone (i.e., horizontal spaces) under the effect of supply air jets. This study carried out field chamber experiments to consider the effect of non-uniform environments on both overall and local thermal sensations under stratum ventilation for heating using the multi-level fuzzy comprehensive evaluation (MFCE) method. This method has a multi-level structure to simultaneously investigate thermal sensation in both vertical spaces and horizontal spaces. The interpolation models of thermal sensation are helpful to enlarge the experimental sample size investigated by MFCE. The results showed that the interpolation-based MFCE method can quantitatively analyze the effect of non-uniform environments on thermal sensation in different subzones of the occupied zone from vertical spaces and horizontal spaces under the effect of supply air parameters. Compared with supply air temperature, supply air velocity has the opposite influence on the variation range of both integrated thermal sensations of feet, head and overall body and local thermal sensation of feet between the occupied subzones 1 and 2. Supply air temperature and velocity of 25–27 °C and no less than 1.1 m/s were recommended to improve the non-uniformity of thermal environments.

Numerical investigation of the thermal and ventilation performance of a combined impinging jet ventilation and passive chilled beam system

Impinging jet ventilation (IJV) systems provide high ventilation efficiency and good indoor air quality (IAQ) in the cooling mode. However, they have a limited cooling capacity. Passive chilled beam (PCB) systems are widely used in indoor environments with high cooling loads and can potentially address the limitation of low cooling capacity of IJV. In this study, the possibility of combining IJV and PCB systems is investigated using computational fluid dynamics (CFD) simulations. The effects of two main factors, namely the percentage of cooling load removed by the PCB system (η) and supply air parameters (Lm) of the IJV system, on the thermal and ventilation performance of the IJV–PCB system are examined. The results indicate that the PCB system enhances the mixing of indoor air and effectively reduces the vertical temperature gradient in the IJV room. An optimal range of η that improves the cooling capacity and maintains the high ventilation performance of IJV is determined. This range for an IJV–PCB system is 0.15 ≤ η ≤ 0.45, considering thermal comfort, IAQ, and energy saving potential. In addition, the IJV–PCB system offers a wide selection range for Lm (0.4–1.2) compared with that of the IJV, and a high ventilation efficiency and good IAQ are maintained in the room in this range.

Modelling Analysis of a Membrane-Based Fresh Air Processing System.

The current standard of residential buildings is based on well-insulated and airtight construction as an effective way to reduce primary energy consumption. On the other hand, this intensifies the issue of the indoor air quality. In this paper, the applicability of a hybrid dehumidification/evaporative cooling system for the processing and supply of fresh air is evaluated. The proposed novel system employs cross-flow hollow-fiber membrane modules. To provide a better insight into this novel approach, the system’s performance is numerically investigated using a validated mathematical model. The proposed fresh air processing system provides supply air parameters in or close to the summer comfort range. The analyzed system is characterized by a high coefficient of performance (COP) of up to 33.2 at an outdoor air temperature in the range of 30 °C to 38 °C and a humidity ratio in the range of 8 g/kg to 14 g/kg. Moreover, a temperature difference of up to 9.7 °C can be obtained after the two-stage membrane processing and the mixing process.

Investigation of supply air parameters of a new method to control the condensation risk in radiant cooling panels

Condensation is prone to occur in radiant cooling systems caused by moisture infiltration through doors and windows. Ensuring condensed droplets evaporate entirely at the end of the shutdown period is critical to the effectiveness of the new adjustment method for metal radiant panels, based on the principle that no dripping occurs. A numerical model of the radiant ceiling system validated by experiment is utilized to explore the evaporation characteristics of surface droplets at different initial radiant panel temperatures and different supply air parameters, and suitable air supply parameters based on indoor thermal comfort are further discussed. According to the simulation results, the evaporation time of droplets decreased to 754s, 746s, and 739s after supplying air at the initial panel temperatures of 18°C, 20°C, and 22°C. Evaporation time is 2971s, 1453s, 739s, 325s, supply air speeds is 0 m/s, 0.5 m/s, 1 m/s, 2 m/s. The mean values of PPD are 15.1%, 5.5%, 17.2%, and 42.6% at supply air temperatures of 24°C, 26°C, 28°C, and 30°C, respectively. Therefore, supplying 26°C of air at a speed of 1 m/s can effectively accelerate the evaporation and meet the indoor thermal comfort. In addition, a new regulation strategy based on PWM is proposed to improve the cooling capacity of the radiant system and maintain a comfortable environment, which can provide some reference for practical operation control.

Stratified micro-environments using a sidewall air supply: An experimental and simulation study

The idea of providing stratified micro-environments in a shared environment by utilizing a sidewall air supply is proposed, to provide different thermal comfort and air quality levels to satisfy individual needs at different occupied positions. Experimental cases with various supply air parameters and room layouts are conducted in a mock consultation room consisting of two face-to-face occupants. Further, parametric studies using computational fluid dynamics (CFD) are performed. Overall thermal sensation and local thermal comfort are both evaluated. Tracer gas (i.e., CO2) concentration distributions are investigated experimentally, while the air age is used as an indicator in CFD simulations. The results show that the proposed strategy simultaneously provides displacement ventilation (DV) and stratum ventilation (SV) in a shared environment, satisfying individual preferences and needs. The demarcation thermal length of the supply air jet between DV and SV is around 0.8 m. The normalized contaminant concentration at the breathing level is 0.00–0.30 with both table and floor contaminant sources. Better air quality is achieved in the area served by a higher thermal length. The local discomfort and “lock-up” effect under DV is reduced, by the interaction between the supply air jets, which is validated, as the partition impeding the interaction brings a significant influence. Short jet spacing of 0.75 m implies that multiple stratified micro-environments can be provided in a medium room, while a medium distance between the occupant and the supply air terminal (i.e., 1.7 m) is the most efficient in cooling and renewing the air age.

Ventilation impacts on infection risk mitigation, improvement of environmental quality and energy efficiency for subway carriages

Subway carriages are enclosed for extended periods of time, with a high density of passengers. Providing a safe, healthy, and comfortable cabin environment is a great challenge, particularly during the COVID-19 pandemic. An increase in ventilation rate can potentially reduce infection probability, which may result in worsening environmental quality (e.g., thermal comfort) and larger energy consumption. Thus, exploring the trade-off among infection risk, environmental quality (with regard to ventilation, thermal comfort, and air quality), and energy consumption is important to optimize ventilation systems for carriages. The effect of different supply air parameters (e.g., velocity and temperature) and ventilation modes of mixing ventilation (MV) & Supply air from the Floor and Return air from the Ceiling (SFRC) was studied. The questionnaires were analyzed to explore passenger dissatisfaction with the carriage environment using a MV system. Simulations were performed to predict the velocity, temperature, and CO2 concentration fields. In addition, the comprehensive benefit was evaluated by analytic hierarchy process (AHP), based on infection probability from the revisited Wells–Riley equation, Air Diffusion Performance Index (ADPI), Predicted Mean Vote (PMV), Pollutant Removal Effectiveness (PRE) and energy consumption estimated by cooling load (Lcool). Compared with MV, the optimized SFRC provided softer draft sensation and decreased CO2 concentration by 42%. The SFRC achieved better comprehensive benefits, with an infection risk reduced to 0.4%, ADPI of 80%, PMV approaching zero, PRE up to 16, and energy efficiency increased by 30%. This work contributes to the optimal design of subway carriage ventilation systems in the post-epidemic era.

Modelling indoor environment indicators using artificial neural network in the stratified environments

Ventilation methods that create stratified environments, e.g., stratum ventilation and displacement ventilation, can achieve a satisfactory indoor environment and energy saving. The indoor environment indicators in a stratified environment vary along the heights of a room, making it difficult to monitor and adjust the conditions around the occupants. This study selects the back-propagation (BP) model from artificial neural network (ANN) models to predict the energy performance presented by the energy utilization coefficient, thermal comfort presented by predicted mean vote (PMV) and draft rate (DR), and indoor air quality (IAQ) presented by air age and air change efficiency (ACE), using the air supply and exhaust temperatures. The prediction performances under both heating and cooling conditions are considered and compared. Forty cases by computational fluid dynamics (CFD) with different supply air parameters are conducted to collect data for ANN development. The results show that, the BP neural network model can predict the indoor environment indicators with high accuracy, while the linear regression model is not capable of it. The air velocity information is statistically redundant as input for indoor environment predictions under cooling operation, indicating internal relationships with other inputs. In contrast, it is statistically useful for improving the thermal comfort prediction accuracy under heating. Adding the genetic algorithm brings a small improvement for the indoor air quality prediction under heating. Validation using experimental data shows the robustness and generality for applying the developed ANN models in stratum ventilation and displacement ventilation with varied heat loads and room geometries.

Experimental and numerical analysis of air temperature uniformity in occupied zone under stratum ventilation for heating mode

In warm air heating systems, a good indoor air temperature distribution can provide a comfortable indoor environment and reduce energy consumption. Few studies were conducted for the uniformity of air temperature distributions under stratum ventilation (SV) for heating. In this study, the horizontal and vertical air temperature uniformities in an occupied zone were evaluated under SV heating mode. Different indoor thermal environments were created using both experiments and computational fluid dynamics (CFD) simulations. Results showed that the horizontal air temperature uniformity is generally inferior to the vertical direction. Based on the experimental and simulation cases, the maximum horizontal and vertical air temperature gradient is 3.46 °C/m and 2.44 °C/m, respectively. The uniformity of the air temperature distribution can be significantly affected by supply air parameters. The maximum extremum air temperature difference is 6.26 °C at the height of 0.6 m. However, it can be reduced to less than 0.62 °C by varying the supply air velocity, temperature and angle. Appropriate supply air parameters can provide an energy utilization coefficient (EUC) higher than one, showing the potentials of energy saving. A grey relational analysis revealed that the relational degree of the supply air velocity and temperature on the air temperature uniformity is relatively high, followed by the outdoor temperature and then supply vane angle. The results derived from this study can contribute to better understand the characteristics of indoor air temperature distribution under SV heating mode.

Simplified models for predicting thermal stratification in impinging jet ventilation rooms using multiple regression analysis

Inappropriate thermal stratification characteristics can degrade the ventilation performance of impinging jet ventilation (IJV). In the present study, an analysis method using dimensionless parameters is proposed for predicting the thermal stratification, and the Box-Behnken design method is employed to determine the simulation cases of influencing factors for thermal stratification. The thermal performance in IJV cooling room is investigated by computational fluid dynamics (ANSYS Fluent), and the effects of supply air parameters, inlet area (S*) and height (h*) on thermal stratification are discussed, respectively. A further supply air parameter is represented by the thermal length scale (Lm), which is applied to evaluate the combined effect of inertial force and thermal buoyancy on supply airflow. The results show that the driving force on supply airflow changes from buoyancy dominated to inertial dominated with increasing Lm, leading to the thermal stratification profiles changing from thermal stratification to uniform distribution. For small Lm, the thermal stratification profiles are similar for different inlet areas, while the dimensionless air temperature decreases with increasing inlet area. However, the larger inlet area promotes a more uniform temperature distribution for large Lm. In addition, the thermal stratification profiles are similar regardless of the inlet height for both small and large Lm conditions, indicating that the dimensionless air temperature is a weak function of inlet height. Finally, multiple regression models related to Lm, S* and h* are developed for predicting the thermal stratification, which can provide a reference basis for the determination of temperature distribution in IJV cooling rooms.

Dehumidifying characteristics of air conditioner with reheating coil under mild and humid conditions

• An air conditioner with reheat coil was proposed. • Thermal and dehumidification performances were tested. • The system can work steadily under air condition mode, dehumidification mode 1 and mode 2. • Dehumidification mode 1 has an obvious effective on heating and dehumidifying. • Dehumidification mode 2 owns large moisture-removal capacity and low power. As the conventional dehumidification process in an air conditioner is by subcooling the air, the supply air is insufficient to meet the indoor comfort needs under a mild and humid operating condition. This paper proposed an air conditioner with reheating coil and studied its working performance for varied compressor frequencies under different temperature and humidity conditions, including the supply air parameters and dehumidifying characteristics. As the results shown, the air conditioner with reheating coil worked steadily under air conditioning mode and two dehumidification modes. Other than conditioning the temperature only, it can also regulate the temperature with dehumidification. The largest temperature rise in the supply air was 8.45 °C compared with the inlet air, and the relative humidity was lowered by 51.88%, which indicated that the air conditioner with reheating coil worked sufficient under cold and humid or mild and humid weather. The specific moisture extraction rate increased with the rise of the inlet air temperature and relative humidity, but decreased along with the increase of compressor frequency. The maximum value of the specific moisture extraction rate reached 10.07 kg/kWh.

Effects of Supply Parameters of Stratum Ventilation on Energy Utilization Efficiency and Indoor Thermal Comfort: A Computational Approach

Stratum ventilation shows the significant potential on energy conservation and indoor thermal comfort under cooling applications. Yet, only limited researches focus on the thermal performance of stratum ventilation under heating condition. The heating and cooling operation characteristic of stratum ventilation is different due to the distinct airflow characteristics. Therefore, this paper investigated the parameters that affect energy utilization efficiency and indoor thermal comfort under heating condition served by stratum ventilation via CFD simulations approach. The supply air parameters included temperature, airflow rate, angle, and return air outlet positions. The evaluation indicators adopt ventilation effectiveness and effective draft temperature (EDT) for assessing the energy utilization efficiency and indoor thermal comfort served by stratum ventilation under heating condition. The results demonstrated that, under the heating mode of stratum ventilation, different effects on the thermal performance were made by the mentioned parameters. The ventilation effectiveness was higher when the air supply temperature is 26°C, airflow rate is 7 air change per hour (ACH), and the air supply angle is 45°. The EDT range of the occupied zone is closest to zero K when the air supply temperature is 28°C, airflow rate is 12 (ACH), and the air supply angle is 60°. The related conclusions obtained from this study provide the theoretical basis for the stratum ventilation design and promote its heating application.