Supply Air Temperature Research Articles

Impact of ventilation system type on indoor thermal environment and human thermal comfort in a ceiling cooling room

A ceiling cooling (CC) system integrated with a mechanical ventilation system is an advanced HVAC system for the modern office building with glass curtain wall. In this paper, considering the influence of heat transfer of external envelope, the indoor thermal environment and human thermal comfort were objectively measured and subjectively evaluated in a CC room with mixing ventilation (MV) or underfloor air distribution (UFAD). Indoor physical parameters and human skin temperatures were measured as the chilled ceiling surface temperature and supply air temperature were 17.1-17.6? and 22.2-22.6?. Simultaneously, 16 subjects (8 males and 8 females) were selected to subjectively evaluate the thermal environment. The results showed that the difference between mean radiant temperature and air temperature in the occupied zone was 0.8? with CC + MV and 1.2? with CC +UFAD, and the indoor air velocity was 0.17 m/s with CC + MV and 0.13 m/s with CC + UFAD. In addition, the calculated and measured thermal sensation votes with CC + MV were all slightly less than those with CC + UFAD. Therefore, ventilation system type had a slight impact on the indoor thermal envi?ronment and human thermal comfort in the CC room.

Effect of Different Ventilation Systems on Concentrations of Indoor Particle Emitted from Floor of the Office

A three-dimensional numerical simulation of airflow, temperature, and pollutant concentration distributions with underfloor air distribution (UFAD) system and displacement ventilation (DV) systems are presented for different operating conditions. Since the particles deposited on the floors can be re-introduced into the air through re- suspension and then constitute a threat to human’s health, an optimal ventilation system is required to reduce the indoor air particle concentrations. In the present study, the effects of different systems on the concentrations of indoor particles are numerically investigated by an Eulerian-Lagrangian method, and the RNG k-ε model is adopted for the simulation. Three different supply air velocities (0.2-0.4 m/s) and different supply air temperatures (20 ℃, 22 ℃ and 24 ℃) are considered in the simulation. Meanwhile, the thermal effect of the human body on the micro-environment and its interaction with the surrounding environment are comprehensively evaluated. The simulation results shows that for the UFAD and DV systems, good performance of particle removal is obtained with the high air supply speed for the DV system, while under larger temperature gradient of the indoor environment, the UFAD system is capable of reducing the concentration of the particles emitted from the floors with lower air supply speed.

Research and Application of Evaporative Cooling Ventilation and Salty Moisture Corrosion Prevention Technology for Steam Turbine House

This paper focus on Pakistan Hub coal-fired 2×660MW power project which located in the coast areas with high temperature and high salty moisture. The category of corrosivity of atmosphere in Pakistan Hub is C5. The high salty moisture will increase the corrosion of indoor equipment and structures in turbine house, which threaten the safe and stable operation of power plant. Direct evaporative cooling (DEC) technology is used to cool the centralized supply air for the turbine building. To prevent the salty moisture air being supplied into turbine building causes corrosion for indoor equipment and structures, the desalting moisture filter has been developed and combined with the evaporating cooling unit, which realized the large-scale engineering application. The efficiency of desalting moisture filter reaches more than 93% tested in Tongji University and VTT in Finland, under the condition of the design outdoor temperature of 38.9 °C in Karachi, the supply air temperature is 24.4 °C, which ensures the operating environments of working area and meeting the occupational hygiene requirements and anti-salt spray corrosion requirements.

Respiratory infection risk based ventilation and room conditioning design method with year-round thermal comfort control in modern office buildings

The new decade will be a major challenge for built environment to satisfy building users and owners demands for superior IEQ in the work environment and tackle infection risk issues brought by SARS-CoV-2 pandemic. We collected thermal comfort and IAQ data from modern Estonian office buildings showing that improvements are needed in whole chain of the HVAC science, engineering and manufacturing because current solutions in these buildings have led to many complaints of draught and readjustments of supply air temperature have typically compromised energy performance. To achieve Category II or I IEQ, more systematic design methodologies are needed. Additionally, ventilation rate and air distribution dimensioning based on respiratory infection risk has to be taken into use as a complementary method of existing ones for office space AC and ventilation design, where both net floor area and occupant number define the required ventilation. Based on air velocity and temperature (operative, supply air and local) measurements conducted in five office buildings a new IEQ design methods were developed to satisfy the thermal comfort indices leading to low occupant complaints and not compromising energy performance at the same time. In well ventilated Category I and II office spaces, control of draught risk is an extensive design task for which new methodology was developed. Our method focuses separately on IEQ parameters during heating, cooling and midseason, from which the latter one is the longest and the most dominating one. The design method is presented by connecting thermal comfort and infection risk with ventilation rate. Infection risk based air flow rate selection diagram and corresponding air velocity diagrams for an open plan office and 3-person room showing the possibilities to size ventilation for the event reproduction number of R = 0.5 were constructed.

Heating performance of heating floor integrated with impinging jet ventilation system

Radiant floor heating systems provide comfortable indoor thermal environment. Primary air supply systems can be used to remove contaminants in the space heated by radiant floor. In this study, heating performance of integrated system of impinging jet ventilation (IJV) and heating floor was numerically investigated. The lowest floor heating capacity was 0 W/m2 and gradually increased to 50W/m2, and the primary air temperature supplied by IJV were 14, 16 and 18°C, respectively. In terms of contaminant removal efficiency, contaminant removal efficiency (CRE) was applied. The vertical dimensionless temperature distribution was used to analyse the heating performance of HF on supply air. The numerical results showed that the supply air layer of IJV could be heated by 60% to 80% under the heat effect of HF. The same is true for low supply air temperature 14 °C. The integrated system IJV/HF generated the weaken thermal stratification which is beneficial for energy saving. The CRE of IJV/HF system was influenced by the downward airflow of external wall. Sufficient supply air could overcome the downflow and effectively increase the CRE value (> 2).

Actual measurement and analysis of winter thermal environment of a graduate student studio in Shenyang based on Airpak numerical simulation

This paper takes a graduate workshop in shenyang as the research object, and uses Airpak software to conduct numerical simulation analysis on the air distribution and thermal comfort of the fan coil side air supply mode in winter. The measured air supply temperature is 25°C, air supply speed in the x direction for 0.8m / s, 1.5m / s and 2.3m / s three gears, from east to west up to back air supply 3mode. With the increase of air supply speed, the temperature of the working area gradually increases, and the wind speed increases. PMV index and PPD index were used to evaluate the indoor comfort under the three air supply speeds. The air sup 3ply speeds of 1.5m/s and 2.3m/s can meet the requirements of indoor comfort. According to the distribution of personnel, 18 measuring points were set for measurement. The comparison between the simulation results and the measured results showed a consistent trend, which verified the feasibility and accuracy of Airpak for indoor thermal environment comfort analysis.

Airflow management and energy saving potentials at a high-density data center with stepped-like server placement

ABSTRACT This paper proposed and introduced an innovative concept of step-like server placement in data centers (DCs), replacing the traditional servers placed on the same vertical plane with step-like server placement. The studied simplified DC model was established based on an actual operating DC. The feasibility and reliability of the simplified model was validated by on-site experimental results. This paper is analyzed two scenarios: the effects of horizontal spacings (0, 0.01, 0.02, 0.03, and 0.04 m) between adjacent servers and with the effect of different supply air temperatures (SATs) (22.5, 23, 23.5, and 24°C) on the rack hotspot. The results show that step-like server placement can effectively enhance the thermal distribution, while the optimum thermal distribution is achieved with the spacing of 0.01 m in case 2. Under this circumstance, the rack hotspot reduced by 2.5°C, while case 2 is selected for further analysis in scenario 2. In scenario 2, the thermal environment in cases 6–8 are totally better than that in case 1 in terms of rack hotspot and temperature distribution. Although there appears another moderate heat accumulation at the top-side, the overall thermal distribution in the case with SAT of 24°C is still better than that in original case. The electricity consumptions of the CRACs can be saved by approximately 146 and 195 kWhr/day with the most optimal configuration.

Performance evaluation of a novel plate-type porous indirect evaporative cooling system: An experimental study

The traditional indirect evaporative cooler (IEC) needs the consistent working of the pump for water spraying to the secondary air channel wall, which consumes an amount of energy and causes the extra pressure drop. Improving the channel surface water retention capacity has drawn research attentions over the years, and using porous materials is expected to deal with this problem. However, there is still lack of quantitative experimental data on the thermodynamic performance of this environmental-friendly heat exchanger. In this study, a plate-type cross-flow indirect evaporative cooler that sintered the porous layer in each secondary air channel surface (PIEC) was proposed and manufactured. A series of experiments were carried out on an established test rig to assess the performance of the PIEC system. It was observed that the air cooling effect could still be observed over time without water supply owing to the water absorbed and retained in the porous layer, which indicated the feasibility of the intermittent spraying plans. Results showed that the PIEC maintained the supply air temperature up to 2105 s within 0.5 °C fluctuation under the test conditions without spraying water, lessening 94.6% of the operation time of the water system. Therefore, the power consumption was significantly reduced. The coefficient of performances (COPs) were enhanced by 117.5% on average compared with the conventional continuous spraying mode. In addition, the pressure drop of secondary channels was measured to be lower in the non-spraying mode than in the spraying mode. Eventually, the present experimental study recommended to combine the PIEC as a pre-cooling air-conditioning device with the air handling unit to guarantee the required outlet air temperature for the indoor environment.

A data-assisted first-principle approach to modeling server outlet temperature in air free-cooled data centers

The server outlet temperature is an important thermal condition to the operation of an air free-cooled data center that uses fans to continuously pass the outside air through the server room to cool the computing devices. However, the standard server’s management and monitoring tool cannot read the server’s built-in outlet temperature sensors fast enough to catch up the fast dynamics of the server outlet thermal condition caused by the changing server workload. Moreover, many server models do not have built-in sensors that can measure the server outlet temperature. In this paper, we develop a data-assisted first-principle model that leverages available built-in sensors and server’s operating monitoring tools to achieve low-latency estimation of the server outlet temperature. Specifically, the developed model takes the inlet and processor core temperatures, server’s fan speed, and processor utilization which are measured by hardware/software sensors as inputs to predict the outlet temperature with low latencies. Our extensive evaluation based on real data traces collected from a real air free-cooled data center testbed shows that our model can accurately predict the outlet temperature with an average root mean squared error ranging from 1.21 °C to 1.46 °C under various cold supply air temperatures and processor utilization levels.

A Temperature & Humidity Setback Demand Response Strategy for HVAC Systems

• A T&H demand response strategy that adjusts the temperature & humidity is proposed • Indoor air, supply air and chilled water temperatures are adjusted in the strategy • The energy saving and the peak shedding of the strategy are up to 39.0% and 37.1% • The T&H strategy increases the energy saving by 22.9% compared with the T strategy • The strategy is more effective under lower sensible load or higher latent load Heating, ventilation and air conditioning (HVAC) system plays a significant role in demand response (DR) to reduce the peak load of the grid. Conventionally, only the sensible load is reduced by increasing the indoor temperature during DR periods and the latent load is rarely concerned. This study proposes a temperature & humidity (T&H) setback strategy for HVAC systems to reduce both the sensible and latent cooling loads by adjusting the supply air temperature and chilled water supply temperature simultaneously. The performance of the T&H setback strategy is analyzed from the perspectives of peak shedding, energy saving and indoor thermal comfort and compared with the common temperature setback strategy. The impact of weather conditions and occupant densities on the performance of T&H strategy is assessed. Results show that the energy saving of the HVAC system under the T&H setback strategy can be up to 39.0% and peak shedding can be increased to 37.1%, which are both higher compared with the temperature setback strategy. The peak shedding and energy saving of the T&H setback strategy is larger when the buildings have lower sensible or higher latent load. The T&H strategy can improve the flexibility of buildings during DR periods effectively.

Evaluation of sidewall air supply with the stratified indoor environment in a consultation room

To take advantage of both stratum ventilation and displacement ventilation, while breaking some of their limitations, the sidewall air supply is introduced. Computational fluid dynamics simulations of 16 cases are conducted, to assess the application of the sidewall air supply in a consultation room, referring to thermal comfort, indoor air quality and energy utilization. Two supply air terminal layouts of the sidewall air supply (i.e., single-side supply and double-side supply), four supply air temperatures within 20–26°C, and five air change rates within 2.9–14.7 air changes per hour are applied. The results indicate that the sidewall air supply can provide satisfactory thermal comfort levels up to Category A in ISO 7730, with proper design. Using double-side supply reduces the draft rate by up to 25%, and improves the energy utilization coefficient and contaminant removal efficiency by up to 3.3 and 1.83, compared with the single-side supply. Additionally, for the single-side supply which achieves stratum ventilation, the closer the supply air jet center to the breathing zone, the higher the energy utilization coefficient and contaminant removal efficiency at the breathing zone are. Finally, the energy utilization coefficient and contaminant removal efficiency show a positive relationship for the sidewall air supply. This may be valid for the air distribution methods that provide stratified indoor environments. This study expands the application scenario of displacement ventilation and stratum ventilation, guides to obtain the best thermal comfort, energy utilization and contaminant removal performances simultaneously, while saving the measuring costs of indoor air quality.

Tunicate swarm algorithm-trained multi-layered perceptron for data centre energy demand forecasting and relative percentage contribution analysis of input parameters

PurposeEnergy management is critical to data centres (DCs) majorly because they are high energy-consuming facilities and demand for their services continue to rise due to rapidly increasing global demand for cloud services and other technological services. This projected sectoral growth is expected to translate into increased energy demand from the sector, which is already considered a major energy consumer unless innovative steps are used to drive effective energy management systems. The purpose of this study is to provide insights into the expected energy demand of the DC and the impact each measured parameter has on the building's energy demand profile. This serves as a basis for the design of an effective energy management system.Design/methodology/approachThis study proposes novel tunicate swarm algorithm (TSA) for training an artificial neural network model used for predicting the energy demand of a DC. The objective is to find the optimal weights and biases of the model while avoiding commonly faced challenges when using the backpropagation algorithm. The model implementation is based on historical energy consumption data of an anonymous DC operator in Cape Town, South Africa. The data set provided consists of variables such as ambient temperature, ambient relative humidity, chiller output temperature and computer room air conditioning air supply temperature, which serve as inputs to the neural network that is designed to predict the DC’s hourly energy consumption for July 2020. Upon preprocessing of the data set, total sample number for each represented variable was 464. The 80:20 splitting ratio was used to divide the data set into training and testing set respectively, making 452 samples for the training set and 112 samples for the testing set. A weights-based approach has also been used to analyze the relative impact of the model’s input parameters on the DC’s energy demand pattern.FindingsThe performance of the proposed model has been compared with those of neural network models trained using state of the art algorithms such as moth flame optimization, whale optimization algorithm and ant lion optimizer. From analysis, it was found that the proposed TSA outperformed the other methods in training the model based on their mean squared error, root mean squared error, mean absolute error, mean absolute percentage error and prediction accuracy. Analyzing the relative percentage contribution of the model's input parameters based on the weights of the neural network also shows that the ambient temperature of the DC has the highest impact on the building’s energy demand pattern.Research limitations/implicationsThe proposed novel model can be applied to solving other complex engineering problems such as regression and classification. The methodology for optimizing the multi-layered perceptron neural network can also be further applied to other forms of neural networks for improved performance.Practical implicationsBased on the forecasted energy demand of the DC and an understanding of how the input parameters impact the building's energy demand pattern, neural networks can be deployed to optimize the cooling systems of the DC for reduced energy cost.Originality/valueThe use of TSA for optimizing the weights and biases of a neural network is a novel study. The application context of this study which is DCs is quite untapped in the literature, leaving many gaps for further research. The proposed prediction model can be further applied to other regression tasks and classification tasks. Another contribution of this study is the analysis of the neural network's input parameters, which provides insight into the level to which each parameter influences the DC’s energy demand profile.

Research on the thermal performance of interlayer ventilated PCM component coupled with solar air collector

The application of solar energy for heating in buildings has the problem of heat supply and demand time mismatch. In this paper, an interlayer ventilated phase change material (PCM) component (IVPC) that can be coupled with solar air collector was proposed. The thermal performance of IVPC was tested through experiments. The results show that if IVPC completes latent heat storage, the optimal air supply temperature of solar hot air is 35 ∼ 45℃ and the air supply speed is 3 ∼ 4 m/s. The latent heat release time can be maintained for 5 h. To build an IVPC coupled with solar air collector system (IVPSS) in TRNSYS, to simulate the improvement effect of IVPC on heating temperature fluctuations, a rural building in cold regions of China was selected. IVPSS can maintain the indoor temperature of the building in the range of 8 ∼ 16℃. Compared with buildings without IVPSS, the room temperature throughout the day can be increased by 5 ∼ 8℃. IVPC can effectively use solar energy to peak load shifting, reduce room temperature fluctuations, improve indoor thermal comfort, and provide solutions for farmhouses in cold regions to use clean energy for heating.

Numerical and experimental investigations on thermal management for data center with cold aisle containment configuration

This study proposes the container data center with the featured cold aisle containment (CAC) as effective thermal control strategy. In design, the overhead downward flow system is implemented with a heat exchanger arranged right above the data center on the air side and an evaporative water chiller on the water side to form the cooling approach. The cold airflows and hot exhausts of racks are separately transported by the contained cold and hot aisles to alleviate the problem of cold and hot air mixing. The measurements of air temperature and velocity of racks are used to validate the prediction accuracy of the computational fluid dynamics (CFD) model. The performance metrics in terms of the rack cooling index (RCI), return temperature index (RTI), supply heat index (SHI) are used to examine the design effectiveness of the proposed test data center. The simulations are then extended to assess the air distribution and thermal management at varied supply air temperatures and velocities for a large-scale data center to be built in the green energy technology demonstration site of the Shalun smart green energy science city. Overall, the calculated average PUE of 1.38 for the large-scale data center is notably less than the average PUE of 1.59 from the results of 2020 data center industry survey, indicating the potential savings of cooling energy and cost. This paper demonstrates a generalized approach as an easily adaptable, cost-effective solution for data centers to be deployed in tropical and subtropical areas.

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.

Field measurements and numerical analysis on operating modes of a radiant floor heating aided by a warm air system in a large single-zone church

Space heating can constitute 60–80% of the total energy use of buildings in cold climates. Efficient heating techniques in buildings still rely on operating strategies. In this paper, a church with radiant floor heating in a cold climate is taken as a case of a large single-zone building to analyze the energy use for heating. Field measurements and numerical analysis are both used in the study. Different operating modes of heating, including intermittent heating and constant set-point heating, are compared for energy saving, reliability on indoor climate, and thermal comfort. The intermittent heating by an all-air system with supplied air temperature control results in the highest energy use. The constant set-point air temperature radiant floor heating aided by a warm air system (return air temperature control) is least affected by outdoor temperature with the best reliability and met the thermal comfort requirements throughout the heating season. The main novelty is that an operating mode of cyclic set-point air temperature is proposed. It is found that the small thermal inertia of heating systems should be preferred when the operating mode of cyclic set-point temperature is used to reduce the warm-up period. The results suggest how to operate and reduce the energy use of radiant floor heating systems in a large single-zone building.

Optimal Control Method of Variable Air Volume Terminal Unit System

This study reviewed the existing studies on the types of variable air volume (VAV) terminal units, control and operation methods, prediction models, and sensor calibration methods. As a result of analyzing the existing research trends on the system type, characteristics, and control method of VAV terminal units studies such as theoretical verification and energy simulation were conducted to improve the existing control methods, reset the set value using a mathematical model, and add a monitoring sensor for the application of control methods. The mathematical model used in the study of VAV terminal unit control methods was used to derive set values for minimum air volume, supply temperature, ventilation requirements, and indoor comfort. The mathematical model has a limitation in collecting input information for professional knowledge and model development, and development of a building environment prediction model using a black box model is being studied. The VAV terminal unit system uses a sensor to control the device, and when an error occurs in the sensor, indoor comfort problems and energy waste occur. To solve this problem, sensor calibration techniques have been developed using statistical models, mathematical models, and Bayesian statistical models. The possibility of developing a method for calibrating the variable air volume terminal unit sensor using the prediction model was confirmed. In conclusion, the VAV terminal unit system is one of the most energy efficient systems. The energy saving potential of current VAV systems can still be improved through control methods, the use of predictive models, and sensor calibration methods.

Experimental investigation of occupants’ thermal sensation under a personalized ventilation system

By considering the importance of providing proper indoor environment conditions for occupants and also due to energy costs, one of the solutions for indoor local air-conditioning is Personalized Ventilation System (PVS). In this paper, the occupants’ thermal sensation was experimentally studied for body segments that are mostly affected by the PVS. The local sensation of head, chest, arm, and hand at two supply air temperatures of 16 and 32°C were investigated. Eight volunteer subjects participated in this survey. The subjects reported the most thermal satisfaction on their hands. Also, the arms were the segments with the coolest thermal sensation (-1.28, between slightly cool and cold). Results indicate that the head’s thermal sensation at both supply air temperatures was neutral and the hand was the only body part that experienced warm thermal sensation during the test. Also, by increasing the supply air temperature to 32°C whole body thermal sensation changed from -0.46 to -0.09 on the seven-point scale, which means that the cooling system worked properly for occupants’ cooling. In this system, cooling occurred at 32°C instead of the common 16°C supply air temperature, which results in energy-saving and decreases annual running costs.

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.

Impact of domain discretization on the accuracy of a 2D model of PCM module for ventilation application

Optimal selection of domain discretization for numerical Phase Change Material (PCM) models is useful to establish confidence in model predictions and minimize the time consumption for conducting design analysis. Very detailed and geometrically complex models are usually applied utilizing several million cells. A 2D numerical PCM model of a climate module for thermal comfort ventilation is investigated. The mesh independence was conducted on 22 different mesh sizes ranging from 70 to 10.870 nodes. Convergence criteria was evaluated based on average air supply temperature and total heat transfer between the PCM and the air within the simulation time interval. Less than 0.1 % change in the air supply temperature and the heat transfer between the PCM and the air was achieved with 5250 and 9870 nodes, respectively. Thereby highlighting that a relatively small amount of nodes can be considered to achieve sufficient accuracy to conduct analysis of PCM applications.