Supply Air Temperature Research Articles

Impact of refrigerant undercharge faults on building indoor conditions and HVAC system operation in residential Buildings: A simulation study

This study investigates the impact of refrigerant undercharge on indoor temperature and HVAC system performance in residential buildings. Simulation models for typical residential buildings in Orlando, FL and Indianapolis, IN were developed using the ResStock database. A refrigerant undercharge fault model was then applied to the simulations with varying levels of fault intensity. The paper offers an extensive analysis, revealing that variations in supply air temperature, equipment runtime, and cooling energy consumption due to the level of refrigerant undercharge faults are notably significant on a summer representative day. Similarly, on a winter representative day, changes in supply air temperature and runtime are significant as well as changes in supplemental heat energy consumption. We find that occupants may remain oblivious to these faults during the cooling season, particularly when the HVAC system is oversized; in that case, supply air temperature data could help detect a fault. Another challenge is that during the heating season, when the supplemental heater operates, it is difficult to identify a refrigerant undercharge fault using only indoor and supply air temperature data. This study finds that supply air temperature, equipment runtime, and supplemental heater energy consumption data can help in detecting refrigerant undercharge faults.

Study of a nano-coated hydrophilic polymer for indirect evaporative cooler from wetting, thermal and corrosion resistance performance

Hydrophilicity and evaporation rate of the wet channels play crucial effects on the cooling performance of an indirect evaporative cooler (IEC). Thus, great efforts are made to develop high-performance wet surface materials for IECs. However, current studies of hydrophilic coatings focus on the moisture diffusion ability of the material itself or the overall thermal performance of an IEC, with less in-depth research on the internal local thermal and quantitative wetting performance under various operating conditions. In this study, a TiO2/SiO2 nano-coating is applied to polypropylene (PP) by three treatment methods to develop a hydrophilic durable and corrosion-resistant PP for IEC application. Firstly, the hydrophilic durability of various samples was tested for 30 days. Secondly, test rigs were built for wetting and thermal performance investigation. The wetting performance was studied by both the drop-impact interaction test and the falling film experiment. The flow pattern, water film thickness, and wettability ratio were investigated under varying water flow rates, air velocity, and water distribution strategies (continuous spray, intermittent spray). The thermal performance including the internal wall temperature and supply air temperature of non-coated and coated IEC were comparatively tested. Finally, the corrosion resistance ability of samples was tested by acid salt spray. The results show that primer-aided TiO2/SiO2 coating on PP can provide durable hydrophilicity and corrosion resistance. Gaining better water retention ability, the thermal performance of nano-coated IEC can be enhanced under intermittent spray with 1.1 °C lower plate temperature and wet-bulb efficiency improved from 74.4 % to 81.4 % compared to the non-coated one.

Leveraging multi-zone building data with machine learning-based models and genetic algorithms to optimize air handling units

Optimizing air handling units (AHUs) in multi-zone buildings presents significant challenges. As buildings become more complex, the demand for tailored temperature control across various zones becomes paramount. This study leverages multi-zone building data with machine learning-based models and optimization techniques to optimize AHUs by specifically integrating deep neural network (DNN) modeling, clustering analysis, and a genetic algorithm (GA). We developed 18 models to predict AHU supply air temperature (Tsa) and 2 models to predict chiller power consumption (P) using DNN. Clustering analysis was applied to the return air temperature (Tra) of each AHU, serving as initial conditions for the GA. The clustering analysis provided insights into the AHU operational behavior, enhancing the optimization process precision. The GA's objective function maintained the AHUs' Tsa and minimized P by adjusting parameters such as valve openings, fan frequencies, chilled water supply temperature, and cooling water flowrate. The results indicated that DNN models demonstrated high predictive accuracy, with 16 models showing an R2 higher than 0.96. The results suggested that AHU411 requires increased capacity during high Tra condition, while AHU212 needs an enhanced model with more diverse training data or the incorporation of additional influencing factors. Validation revealed that this approach improved temperature maintenance across zones, with 96 % of the data falling within demand temperature range (Tset), and achieving Tset required 41 % higher power input.

Dynamic energy optimization strategy to provide appropriate thermal comfort and fresh air under occupants’ different activity types

An effective strategy for optimizing indoor air distribution in stratum ventilation heating systems under different types of human activity has been proposed, in order to provide appropriate thermal comfort while exploiting the potential for energy savings. The stratum ventilation was optimized using strategy 1 (the optimization strategy of three ventilation performance indicators based on VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR)), the strategy 2 (the optimization strategy with constraint based on VIKOR) and the strategy 3 (the optimization strategy aimed at energy conservation), respectively. These strategies provide optimal indoor air distribution within a stratum ventilation system that is influenced by various factors (i.e. supply air temperature, supply air vane angle, supply air velocity, metabolic rate, clothing insulation and outdoor air temperature). Firstly, the parameters of the stratum ventilation system are obtained using Computational Fluid Dynamics (CFD) software. In addition, using the simulation results as input variables, predictive models of ventilation performance (i.e., PMV, local mean air age (LMAA) and energy consumption) was developed using Artificial Neural Network (ANN). Finally, by optimizing the proposed ANN based strategy 1, strategy 2 and strategy 3, the ventilation performance is output. The proposed strategy 1 provides a comfortable indoor environment and saves energy, and compared to the strategy 1, the strategy 3 saves more energy while ensuring that thermal comfort meets the requirements. In addition, considering the optimization of clothing insulation while providing appropriate thermal comfort also indirectly saves energy. Moreover, these strategies also work well as the outdoor air temperature changes.

Experimental study on the performance of enhanced air-cooled photovoltaic thermal energy-supplied manure treatment technology

Implementing renewable energy technologies for manure treatment to reduce energy consumption and environmental damage is steadily becoming more prevalent. In this work, an air-cooled photovoltaic thermal (PV/T) device was enhanced and constructed to provide energy for bio-composting manure treatment. Experiments were conducted to analyze the performance data such as air supply temperature, energy and exergy efficiency, and mass flow rate. When calculating the mass flow rate of the PV/T-supplied manure treatment technology, factors such as exergy efficiency, and hot air temperature must be considered. The results of the study indicate that the thermal performance of the developed equipment is adequate for manure composting treatment. The thermal exergy efficiencies of the V2, V3, and V4 cases are approximately 1/3 greater than the thermal exergy efficiency of the V1 case, indicating a considerable change in thermal efficiency. The mass flow rate of 0.020 kg/s is determined to be a more suitable set value. Its total exergy efficiency can reach 46.79%, and the apparatus could heat up to 43.63 kg/m2 of compost to begin the bio-composting process. This study lays the groundwork for future research and deployment of PV/T-powered manure treatment devices.

Energy and materials analysis of wet channels structures for evaporative cooling systems manufactured by FFF technique with foam materials

The development of new evaporative cooling technologies can significantly reduce energy consumption and help mitigate the effects of climate change. This study aimed to evaluate the evaporative cooling capacity of air passage channel structures. Six different channels were manufacturing using two types of foam, Wfoam and Bfoam, three of each type, made from polylactic acid added with a chemical blowing agent, employing the Additive Manufacturing (AM) technique of fused filament fabrication and modifying manufacturing parameters. The experimental analysis consisted of two phases: initially, all six channels were tested under constant inlet air conditions; subsequently, the channel exhibiting the highest evaporative cooling capacity was further analysed under different air velocities. The results obtained allowed for an analysis of the relationship between material properties, energy performance, and cooling capacity, with the goal of optimizing and designing more efficient cooling systems. The energy performance of the channels was assessed in terms of heat flux, and sensible and latent powers. The results indicated that the channel made from the type of foam with the highest porosity achieved the lowest supply air temperature and the highest sensible and latent powers. Additionally, this channel demonstrated the highest wet bulb effectiveness, reaching up to 0.86 at the maximum tested air velocity. These findings confirm the feasibility of using AM to generate porosity in evaporative cooling systems manufactured with polymeric materials.

Performance Analysis of Lake Water Cooling Coupled with a Waste Heat Recovery System in the Data Center

Data centers (DCs) require continuous cooling throughout the year and produce a large amount of low-grade waste heat. Free cooling and waste heat recovery techniques are promising approaches to reduce DC energy consumption. Although previous studies have explored diverse waste heat utilization strategies, there is a significant gap in combining waste heat recovery with lake water cooling in DCs. Therefore, this study proposed a system integrating lake water cooling with waste heat recovery for DCs. To evaluate the energy-saving performance of the suggested system, the influence of waste heat recovery locations and volumes has been investigated. An analysis of the improvement in system parameters is also conducted. The study’s findings highlight that targeted recovery of waste heat from sources like chilled water or air in server rooms can significantly reduce the cooling energy demand of the system. The results show that recovering heat from the return air of IT equipment can yield a remarkable power usage effectiveness (PUE) and coefficient of performance (COP) of 1.19 and 10.17, and the energy consumption of the cooling system is reduced to 10.06%. Moreover, the outcomes reveal the potential for substantial energy savings of up to 26.05% within the proposed system by setting the chilled water and air supply temperatures to 16 and 20 °C, respectively.

Numerical Study of the Influence of Regenerator Structure on the Performance of Hot Blast Stoves

The properties and arrangement of checker bricks in regenerators are crucial for the heat exchange process of hot blast stoves. In this study, a 3D fluid flow heat transfer model is established to analyze the influence of three regenerator layered structures on the combustion and air supply performance of hot blast stoves. The results show that a “silica bricks–high-alumina bricks–clay bricks” three-layer arrangement in regenerators produces a “thermal conduction hindrance effect” at the interface between silica and high-alumina bricks during the 2 h combustion period, which raises the local temperature and improves air supply performance. Compared to the “silica bricks–clay bricks” and “high-alumina bricks–silica bricks–clay bricks” structures, this setup increases the maximum air supply temperature difference to 23 and 64 K, respectively, and extends the effective air supply time by 80 and 320 s, respectively. However, the “thermal conduction hindrance effect” diminishes over longer combustion periods, and by 4 h, the performance across all structures becomes increasingly consistent. Additionally, the study suggests that the temperature level and distribution in the upper part of the regenerator are the key factors determining the air supply performance of hot blast stoves.

Field experiment and simulation of hot air curtain for cold protection in subway aisle in severe cold regions

Harbin Subway is the northernmost subway line in China. In winter, outdoor temperature can reach −37.7 °C. Cold protection has emerged as a critical priority for subway operations in the region. In this paper, taking the aisle of a typical island station in Harbin as the research object, long-term and short-term field experiment on the thermal environment of the aisle were carried out. The field test data of the station and the full-scale model were used to conduct numerical simulations on the effect of supply air temperature, speed, and angle on the aisle environment. The modified PET temperature scale and average power consumption during the operation of the hot air curtain were used to evaluated the cold protection solutions of the air curtain. The results revealed that the average temperature of the cross-sections in the aisle without cold protection measures dropped by 5.4 °C–6.3 °C from its initial level after the train left the station. Without increasing average power consumption, changing the supply air angle of hot air curtain can improve the thermal environment in the aisle. Considering the three aspects of cold protection effect, passenger thermal comfort and power consumption, this paper recommends that the cold protection solution for aisles with a length less than or equal to 76.7 m, L-shaped and similar layouts is 35 °C for the supply air temperature, 9 m/s for the wind speed, and the range of the difference between the supply air angle and the aisle inclination angle is 6° <θ-α < 11°.

A practical real-time control strategy for high-performance building HVAC operation concerning potential pandemic outbreaks in post-pandemic era

The lessons learned from the COVID-19 pandemic emphasize the need for building HVAC systems to be adaptable and prepared to adjust their operation for infection risk mitigation for future pandemics. Most guidelines suggest increasing outdoor air fraction in HVAC systems during pandemics. However, this approach is not energy-efficient due to the conditioning of additional outdoor air, and many practical systems face limitations in introducing more outdoor air than normal due to capacity or design constraints. Therefore, there is an urgent need for an alternative solution for HVAC system operation during pandemics that is energy-efficient, can effectively mitigate infection risks and does not require extensive retrofits to existing systems. To meet this need, this study proposes a practical real-time control strategy for high-performance HVAC operation in response to potential pandemic outbreaks. First, a supply air temperature (SAT) reset scheme for infection risk mitigation is proposed based on Mamdani fuzzy inference theory. Then, a coordinated control scheme is proposed to coordinate SAT reset with chilled water temperature adjustment for energy-efficiency enhancement. This strategy does not require system equipment retrofits but only changes in control logic to transition to pandemic operation. The effectiveness of the proposed strategy is validated in a high-fidelity Modelica-based simulation environment under various weather conditions. Results show that, compared to normal operation, the proposed strategy can significantly reduce new infection cases by 32∼46 % without increasing energy use, and may even achieve slight energy savings of 9∼13 %, while maintaining expected occupant comfort.

Research on Thermal Environment of Container Farms: Key Factor Identification and Priority Analysis

Container farms (CFs), a controlled environment agricultural technology designed to solve food insecurity, are receiving increasing attention from researchers. However, the complex geometric structures and artificial lighting used in CFs present challenges in effectively controlling the thermal environment. This study aims to identify the primary factors that impact the thermal environment of CFs while conducting factor ranking and significance analysis, providing a theoretical basis for future thermal environment optimization. The research method of theoretical analysis, CFD simulation, and an orthogonal experimental design were adopted to achieve the above objectives. Theoretical analysis revealed that factors influencing the thermal environment are the HVAC system’s supply air temperature, humidity, flow rate, and the light source used. Four evaluation indices, including the mean value and range between layers of temperature and moisture content, were used. The results revealed that supply air temperature and light source are significant for mean temperature, while supply air temperature and humidity are significant for mean moisture content. In the case of range between layers, supply air flow rate and light source display a significant correlation. These findings suggest that future optimization should prioritize the regulation of the HVAC system’s supply air and light source.

Digital twin-driven energy consumption management of integrated heat pipe cooling system for a data center

The energy consumption management (ECM) for the integrated heat pipe cooling (IHPC) systems has become a significant cost-cutting strategy, given the growing demand for the decreased cooling and maintenance costs in data centers. However, the traditional ECM strategies lack an integration with the real-time information and the automatic feedback control, causing the risks of system operation difficult to diagnose and the potential for energy saving hard to exploit. In this respect, a digital twin approach was proposed to efficiently and automatically implement the ECM strategy for an IHPC system. First, a digital twin architecture was established to enable seamless integration and real-time interaction between the physical system and the digital twin. Secondly, the digital twin models of monitoring, simulation, energy evaluation and optimization were developed to drive the corresponding services. Finally, the approach was verified on an IHPC system operating in a real-life data center. It is found that the approach can automatically detect and justify the abnormal states of the IHPC system. Moreover, the approach can reduce the power consumption by 23.63% while meeting the production requirements. The mean relative errors of the supply air temperature and the cooling capacity between the digital twin simulated and the on-site records are 1.43% and 1.46%, respectively. In summary, the proposed approach provides a digital twin workflow that can significantly improve the efficiency of the ECM strategy deployed on an IHPC system.

Adaptive fuzzy controller design for an air handling unit

An adaptive control method based on a fuzzy state observer is designed for air handling unit (AHU) systems, where the intensity of humidity source and heat load are considered to be uncertain, and approximated by fuzzy logics. Besides, the supply air temperature is unmeasurable, which is observed by a state observer. To avoid the system equilibrium point offset, the prediction errors generated by the system and serial-parallel estimation models are introduced into the controller design based on backstepping. Finally, the superiority of proposed adaptive fuzzy controller is analyzed by simulation comparison with feedback linearization and PID controllers in two cases.

Interfacial exchange of airflow and bacteria-carrying particles induced by door opening and foot traffic in an operating room

Maintaining high air cleanliness in operating rooms (ORs) can reduce surgical site infections (SSIs). However, door openings and foot traffic during surgery may allow the intrusion of contaminated air and increase microbial contamination in ORs. In this study, numerical methods were applied to investigate the dynamic airflow and bacteria-carrying particle (BCP) dispersion during sliding door opening and foot traffic in an OR. The door movement and realistic human walking were modeled by the dynamic mesh technique. The interfacial exchange of airflow and BCPs was evaluated as the medical staff entered and exited the OR under fixed supply air temperatures and various differential pressures, respectively. Results showed that walking across the door interface caused a sharp increase in airflow exchange between the OR and the anteroom (ANT). An average walking speed of 1.2 m/s induced a maximum inflow rate of approximately 1.32 times greater when entering the OR than when leaving the OR. Once the door was open, the temperature difference convection effect was more significant than the pressure difference outflow effect. Differential pressure outflow indirectly affected airflow exchange at the door interface by changing the direction and temperature of airflow in the ANT. Whether entering or leaving the OR, the BCP intrusion ratios were on average 1.5 times higher at high pressure differentials (15 and 20 Pa) than at low pressure differentials (5 Pa and 10 Pa). This study is expected to improve the understanding of the impact of door opening and foot traffic on OR air quality during surgery.

Thermoeconomic assessment of the air-cooled tropical data center through energy-saving strategies

Rapid developments in the electronic information industry drive the increased energy usage and carbon emission of data center buildings, prompting the focus on the energy efficiency and environmental sustainability. Expanded operation envelopes of tropical data centers is assessed to analyze the potential for the building energy savings and carbon emission reduction through collaborative analysis of operation modes (OMs), supply air temperature (SAT), and outdoor air temperature (OAT). The OMs of compression vary with the setpoints of SAT, in which the average exergy efficiency of compressors at alternate operation mode is 6.8 % and 8.0 % lower than that of double and single compression operations. As SAT rises from 20 °C to 32 °C, the system exergoeconomic factor increases from 5.4 % to 8.0 %, and the average carbon cost decreases by 36.5 %. Additionally, with just an 8.5 % increase in exergy cost (i.e., Case 8) at OAT rising from 30 to 34 °C, the high SAT and low refrigerant charges provide considerable exergy cost advantages versus resisting the OAT fluctuations. Dynamic operation strategies are also proposed and compared to cope with the impacts of tropical environments. Compared to the 26 °C SAT baseline, the average energy savings are 9.1–14.7 %, indicating the ability to fully utilize outdoor and indoor conditions.

Optimization operation of data Center's distributed air conditioning system based on supply-demand matching

A supply-demand matching optimization control of data center's distributed air conditioning system was investigated. For the demand side, an estimation model of a server's cooling air parameters was proposed based on server’ thermal resistance. Test results showed that thermal resistances of servers with power being 6–11 kW were 5.5–9 °C/kW. With the server's heat resistance, chip's temperature and power being known, cooling air outlet temperature and air flow rate can be calculated for different air supply temperature. For the supply side, a mathematic model of the distributed air conditioning system, that combines free cooling and mechanical cooling, was established to calculated energy consumption. Using the above two models, the optimal cooling air supply temperature, which leads to the least power consumption of the air conditioning system can be calculated. Performances of the optimized control method were compared with the conventional control method. Results showed that energy consumption could be saved by 94.4 %, 47.6 % and 31.3 % under the natural cooling mode, the hybrid cooling mode, and the active cooling mode, respectively. Annual energy saving ratios after using the optimized control method in the data center located in Harbin and Kunming were 62.2 % and 45.7 %, respectively.

Ventilation performance study of a high-speed train cabin based on displacement ventilation and mixed ventilation

Indoor ventilation systems play an important role in controlling energy consumption, thermal comfort, and airborne pollutants. This work is concerned with whether the combination of displacement and mixed ventilation can overcome these systems' respective shortcomings to improve the ventilation performance of high-speed train cabins. This work is based on computational fluid dynamics. The results show that when more fresh airflow enters the compartment from the top vents, the flow field is mainly driven by mechanical forces, and two vortices are formed. When more fresh airflow enters the compartment from the bottom vents, the flow field is mainly driven by thermal buoyancy. Meanwhile, the airflow mainly spreads upward, with lower cooling energy consumption, lower wind speed, higher ventilation efficiency, and smaller longitudinal diffusion of pollutants, but increased temperature difference. When the ratio of top and bottom supply air flow is 75%/25%, thermal comfort can be improved, while balancing energy consumption and air quality. If there was a disease outbreak, the flow rate of the bottom air supply could be increased appropriately. To further improve the ventilation performance, on the one hand, it is necessary to appropriately increase the temperature of the bottom air supply, and on the other hand, it is necessary to avoid short-circuiting of the airflow, due to the lack of synergy between thermal buoyancy and mechanical force. The results of the study can provide a reference for safeguarding passengers and improving the ventilation design of high-speed trains.

Humidity and temperature nonlinear control based on almost disturbance decoupling and state observers for air-handling units

The almost disturbance decoupling problem for air-handling units (AHUs) containing unmeasurable states is addressed. Firstly, a state observer is introduced to estimate the supply air temperature, which is an unmeasurable state. Secondly, the almost disturbance decoupling technique is utilized to attenuate the influence of unknown disturbances including outdoor temperature, outdoor humidity ratio, heat load, and strength of the humidity source. Finally, compared with the linearization and PID control methods, simulation results verify the superiority and effectiveness of the proposed controller.

Performance Analysis of Liquid-to-Air Heat Exchanger of High-Power Density Racks

Abstract The ability of traditional room-conditioning systems to accommodate expanding information technology loads is limited in contemporary data centers (DCs), where the storage, storing, and processing of data have grown quickly as a result of evolving technological trends and rising demand for online services, which has led to an increase in the amount of waste heat generated by IT equipment. Through the implementation of hybrid air and liquid cooling technologies, targeted, on-demand cooling is made possible by employing a variety of techniques, which include but are not limited to in-row, overhead, and rear door heat exchanger (HX) cooling systems. One of the most common liquid cooling techniques will be examined in this study based on different conditions for high-power density racks (+50 kW). This paper investigates the cooling performance of a liquid-to-air in-row coolant distribution unit (CDU) in test racks containing seven thermal test vehicles (TTVs) under various conditions, focusing on cooling capacity and HX effectiveness under different supply air temperatures (SAT). This test rig has the necessary instruments to monitor and analyze the experiments on both the liquid coolant and the air sides. Moreover, another experiment is conducted to assess the performance of the CDU that runs under different control fan schemes, as well as how the change of the control type will affect the supply fluid temperature and the TTV case temperatures at 10%, 50%, and 100% of the total power. Finally, suggestions for the best control fan scheme to use for these systems and units are provided at the conclusion of the study.

Multi-objective ventilation optimization for indoor air quality, thermal comfort, and energy conservation in the post-pandemic era: A case study for a moving elevator

Cases of respiratory disease transmission in enclosed elevators have been reported frequently. In the post-pandemic era, in order to mitigate the spread of respiratory diseases in moving elevators, a multi-objective genetic optimization method based on a response surface model is used to optimize the elevator ventilation. The ventilation parameters were optimized for three objectives: reducing carbon dioxide concentration, maintaining human thermal comfort, and achieving energy conservation. First, a response surface model is established using the computational fluid dynamics method and the Kriging model to correlate the design variables (air supply velocity in x, y, and z directions and air supply temperature) with the output function (CO2 concentration, average temperature, and average velocity). Subsequently, the Pareto optimal solution set of ventilation parameters was obtained by employing a multi-objective genetic algorithm. Finally, the optimal air supply velocity, angle, and temperature were obtained for both peak periods of elevator traffic (13 passengers) and other situations (4 passengers) when the elevator is moving up and down, which satisfy the objectives of health, comfort, and energy conservation.