Air Temperature Control Research Articles

Intelligent System Design for Oyster Mushroom Cultivation Using Mamdani Fuzzy Inference with Internet of Things (IoT)

Oyster mushroom (Pleurotus ostreatus) has great potential in agricultural development with increasing global market demand. This research develops an intelligent cultivation system based on Mamdani fuzzy and IoT to control air temperature, air humidity, and soil moisture automatically and in real-time, using DHT22 sensor, resistive soil moisture sensor, and ESP32 as microcontroller. The test results show a high level of accuracy, with an average sensor error of 1% for air temperature, 3.8% for air humidity, and 9.3% for soil moisture. The validation of watering, humidification, and fan prediction times compared to MATLAB calculations is excellent, with MAPE values of 1.52%, 1.43%, and 1.43%, respectively. This system offers a more accurate and responsive automated solution compared to conventional cultivation management. Further testing on actual oyster mushroom farms is required to determine whether the system can adapt to varying environmental conditions. The system relies heavily on a stable internet connection to optimally perform the real-time Mamdani fuzzy calculation function.

Performance study of the rapid heating drying system based on the reverse Brayton air cycle for agricultural application

Air temperature and humidity control are important for crop storage. Current drying methods in agriculture include solar heating and air source heat pumps, whereas solar heating may lead to poor quality of the dried product and air source heat pumps may not reach the desired temperature when the environment is harsh. In this paper, a rapid heating and drying system based on reverse Brayton air circulation is proposed to obtain high temperature and low humidity air quickly by adjusting the pressure ratio to achieve an adjustable crop drying process. An improved rapid heating and drying system with a water cooler is also proposed to increase the drying efficiency of the system. The results show that the total dehumidification rate of the improved system can reach 11.51 g/s, which is 1.48 g/s higher than that of the rapid heating and drying system without a water cooler, and the dehumidification energy efficiency of the improved system can reach 1.26 kg/(kW.h), which is 0.11 kg/(kW.h) higher than that of the rapid heating and drying system without a water-cooling device.

A concept for non-uniform thermal irradiation emulation in an immersive virtual environment

This study addresses the challenge of emulating human thermal environments without the need to build physical mock-ups. The aim is to complement the established technology of emulating visual environments with head-mounted displays. For the user, the virtual environment (VE) emulates an arbitrary indoor environment including visual and thermal aspects. In contrast to conventional climate chambers, we describe a concept to emulate arbitrary non-uniform environments and room geometries without the need to construct or modify separate physical mock-ups for each scenario being tested. By fully emulating air temperatures as well as the thermal irradiation, a user can experience the same thermal sensation as in the actual environment. An air conditioning system and nine supply air diffusers are used for the air temperature and humidity control. For thermal radiation, 45 temperature-controlled surfaces are arranged in a hemicube around the user. An arbitrary environment’s thermal irradiation is emulated by a projection of temperatures on the hemicube surface elements. This study compares two methods for setting the surface temperatures in the VE to emulate thermal irradiation. Finally, it presents the results of computational fluid dynamic simulations that benchmark the capability of the VE to emulate a non-uniform indoor thermal environment. For the non-uniform thermal environment benchmark scenario, the assumption of a uniform enclosure (using the surface average radiant temperature) resulted in a surface root mean square error of 2.2 K (local deviation of up to 4.6 K) of radiant temperature on the person dummy surface. The projection method was implemented for the VE, utilising temperature-controlled surfaces. Depending on the projection method used to determine the surface temperatures, it was possible to decrease the root mean square error of the radiant temperature in the emulated environment to a range of 0.4 K to 0.7 K.

Large-scale energy cost optimization and performance analysis for dedicated outdoor air system: simulation results from ASHRAE RP-1865

This is the first journal article from the ASHRAE research project RP 1865, “Optimizing Supply Air Temperature Control for Dedicated Outdoor Air Systems,” focusing on the large-scale energy performance evaluation of the optimal control of dedicated outdoor air systems (DOAS). DOAS is a type of air handling system that is installed in buildings to ensure proper ventilation for the built environment. It is acknowledged that DOAS with proper operation strategies can provide sufficient ventilation and dehumidification while achieving energy efficiency. In this regard, there have been efforts to develop advanced control sequences (e.g., optimal control) for DOAS. Still, limited studies have demonstrated the effectiveness of such DOAS controls on a larger scale under varying climate zones with different DOAS configurations. To fill the research gap, this study aims to quantify the energy-saving potentials of applying an optimal supply air temperature (SAT) control strategy for DOAS considering diverse configurations of HVAC systems in various climate conditions across the United States. For this study, we first developed a total of 180 EnergyPlus models accommodating different types of buildings (i.e., detailed medium-sized office and primary school) and HVAC systems (i.e., DOAS types, DOAS sizes, and terminal units) under varying ASHRAE climate zones (i.e., 2A, 3B, 4A, 4C, 6A, and 6B). Next, genetic algorithm (GA)-based optimizations were conducted to determine the optimal DOAS SAT control that would minimize the energy cost of the entire HVAC system operation. Our study of comparing the optimal control to a typical rule-based control (i.e., outdoor air temperature-based reset control) revealed approximately 4–34% of energy cost saving potential by optimizing the DOAS SAT control sequence.

Experimental and numerical investigation of the effects of passive radiative cooling-based cool roof on building energy consumption

Passive radiative cooling is an energy-efficient method that reduces indoor temperature and cooling load in buildings, thus contributing to significant energy savings. This study investigates the thermal performance of the passive radiative cooling-based cool roof (PRC-CR) based on experimental and numerical analysis in terms of indoor air temperature and space cooling load indicators. Two experiment rooms constructed from concrete are developed with an indoor air temperature control system. One is the PRC-CR room with the roof covered by a passive radiative cooling metamaterial and the other is the reference room with a concrete roof. Long-term testing results in Hefei show that the indoor air temperature of the PRC-CR room is 5.5 °C lower in maximal and 1.8 °C lower on average than that of the reference room in summer when the indoor air temperature control system is off. Besides, when the indoor air temperature control system is switched on, the PRC-CR room achieves a 29.1% reduction in daily cooling load in summer and a 4.1% increase in daily heating load in winter, which suggests that passive radiative cooling can indeed save energy in cooling season (i.e., hot season) but cause overcooling in heating season (i.e., cold season). In addition, a simulation building model is developed to further investigate the effect of the PRC-CR on the energy consumption of buildings in different locations. The predicted results show that PRC-CR reduces the total load of buildings in cooling load prevailing regions (e.g., tropical zones, subtropical zones, and the vast majority of warm temperate zones), while increasing the total load of buildings in heating load dominant regions (e.g., most middle temperate zones, cold temperate zones, and plateau climate zones). In summary, this work demonstrates both the positive and negative effects of PRC-CR, providing valuable insights into PRC-CR applications.

Multi-objectives occupant-centric control of thermostats and natural ventilation systems in cold climate conditions using real-time occupant-related information

Recently, Occupant-Centric Controls (OCCs) have attracted great attention. Many studies have applied OCCs to mechanical ventilation systems, while natural ventilation systems have gathered much less attention. The natural ventilation effect, driven by opening windows or vents, can be effective in improving indoor air quality, however, result in a leakage of interior heating energy in winter in cold climates. Therefore, the controls of thermostats and natural ventilation systems shall be designed well so that satisfying levels of thermal comfort, air quality and energy conservation can be simultaneously guaranteed. This study proposes an OCC and applies it to thermostats and natural ventilation systems for indoor thermal comfort, air quality and heating energy management. The strategy comprises three controllers: occupancy-based on-off controller, controller of setpoint of indoor air temperature and window openness controller. First, real-time profiles of heat gains from occupants and window openness were collected by employing vision-based detection. Second, a parametric building simulation study was conducted, and then simulation data were generated to develop predictive shallow artificial neural networks for forecasting the indoor conditions and energy performance of the investigated room. Third, the performance of the proposed strategy was examined. Compared to the baselines, the control could offer a decrease in building heating loads by between 43.4% and 63.8 % and an improvement of predicted mean vote levels by 0.36–0.37. The proposed OCC could also maintain indoor CO2 concentrations below 1000 ppm for about 91 % of the studied time, while 84.2 % of the time with several peaks over 3000 ppm in the baseline cases.

An analysis of the Puri Brata Resort & Gallery building’s design from an environmental aesthetics and sustainability perspective

The research paper delves into the implementation of sustainable architectural design practices at Puri Brata Resort & Gallery in Yogyakarta, Indonesia. The primary objective of the study is to analyze the impact of eco-friendly design principles on both the environment and visitor experience within the resort. Data collection for this research involved conducting a comprehensive survey among visitors to the resort, focusing on aspects such as air quality, temperature control, and overall visitor comfort. Additionally, data was gathered on the utilization of green spaces within the resort and the incorporation of local cultural values and aesthetics in the architectural design. The survey responses were then analyzed to evaluate the perceived impact of sustainable design elements on the guest experience and environmental sustainability. The findings of the research indicate that the integration of eco-friendly practices at Puri Brata Resort & Gallery has positively impacted various aspects, including improved air quality, efficient temperature control, and enhanced visitor comfort. The use of recycled materials, renewable energy sources, and green spaces has contributed to creating a harmonious and sustainable environment that enhances the overall guest experience. The study underscores the importance of incorporating sustainable design principles in architectural practices to create spaces that benefit both the environment and visitors. This research provides valuable insights for industry practitioners and policymakers looking to adopt sustainable design practices in the hospitality and tourism sector.

Experimental evaluation of localized air temperature profile and performance of serpentine copper tube heat exchanger for energy-saving crop cultivation

The objective of this study is to examine the localized air temperature profile and heat transfer performance of a serpentine copper tube heat exchanger. Particularly, the air temperature nearby the plants is controlled by the heat exchanger. The novelty of this study is to provide localized climate control only near the plants targeting periodic air temperature control with the proposed heat exchanger. This study focuses on heating and cooling for cultivation in temperate and tropical regions. In contrast to fin-and-tube heat exchangers, the serpentine heat exchanger has a simple design, provides minimal shade for plants, and is easy to maintain. This study was conducted in a laboratory. The experimental system was constructed under with the assumption that a part of actual plant cultivation was being left out. The experiments were implemented by varying the experimental operating conditions such as the inlet fluid temperature and fluid flow rate in the heat exchanger. The pressure drop in the heat exchanger was also measured. The results revealed that this heat exchanger could provide localized air temperature control. The maximum air temperature difference can be obtained at approximately 12 °C during cooling and heating from their initial air temperature even though the heat exchange is simple. The effects of decreasing the inlet fluid temperature for cooling and increasing the inlet fluid temperature for heating were more dominant than the effect of the flow rate. This simple, low-maintenance, and low-cost serpentine copper tube heat exchanger can effectively provide alternate heating and cooling for plant cultivation.

Feedback-linearization decoupling based coordinated control of air supply and thermal management for vehicular fuel cell system

The coordinated control of the coupled system of air supply and thermal management is one of the important ways to improve the efficiency of proton exchange membrane fuel cell (PEMFC) system. The novelty of this paper is to design a feedback-linearization decoupling based coordinated controller combining with active disturbance rejection control (ADRC) method. Aiming at strong coupling of air supply and thermal management system, we have proposed a three-dimensional particle swarm coordinated optimization algorithm to calculate the steady-state reference, then, a feedback-linearization decoupling controller is designed to achieve independent control of air flow, cathode pressure and temperature. Besides, aiming at time-varying, nonlinear interference, we have designed an ADRC based on the decoupled method to achieve better dynamic response and stability. The current step load test reveals that the overshoot and the average tracking error are much smaller under the air flow-pressure-temperature decoupling coordinated controller compared that under the proportional-integral-derivative (PID) controller and the air flow-pressure decoupling controller. The test results under different ambient temperatures indicate that the proposed coordinated strategy reduces the tracking error by over 10 %, the efficiency of fuel cell system is increased by 3.5%–4.5 %.

Experimental and numerical investigation of the incorporation of an air temperature controller for indirect solar dryers

Solar drying systems often face the challenge of overheating due to uncontrolled solar collectors, which can degrade the quality of dried products by destroying enzymes, vitamins, and their chemical composition. To address this issue, we developed and validated a new control system for stabilizing drying air temperature using both experimental and CFD numerical methods. This system not only effectively maintains the desired air temperature but also extends the lifespan of solar collectors by adjusting their exposure during periods of excessive solar radiation. The experimental results demonstrated that without the control system, the air temperature peaked at 72 °C, leading to potential product degradation. In contrast, the control system has succeeded in stabilizing the air temperature at an optimum level. Additionally, the validated CFD model confirmed the effectiveness of this control technique in various climatic conditions, including cold semi-arid, typically Mediterranean, hot semi-arid, and sub-desert conditions. The findings underline the importance and necessity of temperature control in solar drying systems, as well as the effectiveness of the CFD method in predicting system performance. Furthermore, this work significantly enhances the efficiency and applicability of solar drying technology, offering a practical solution for improving product quality and system durability.

On-site evaluation of indoor thermal comfort and energy performance of a liquid-desiccant assisted air-conditioning system in a high-latent-load building

Indoor humidity control is increasingly important because indoor sensible heat ratio decreases to reduce building energy consumption. However, reference vapor compression cooling systems exhibit energy inefficiency and limitations in maintaining indoor thermal comfort. Therefore, this study proposes an alternative heat-pump-driven liquid-desiccant air-conditioning system, independently controlling air temperature and humidity. The reference and proposed systems are applied to a high-latent-load building to investigate their onsite indoor thermal comfort and energy performance empirically and simultaneously under various outdoor summer conditions. The reference system exhibits a thermal comfort satisfaction ratio of 97% only under limited hot and dry weather. Conversely, the thermal comfort satisfaction ratio sharply drops to 2% or less under humid weather. The proposed system consistently achieves a high thermal comfort satisfaction ratio exceeding 90% under various outdoor summer conditions. In empirical comparisons, the proposed system can maintain a thermally comfortable room for an hour while achieving energy savings exceeding 92.4% and 12.1% under warm and humid (rainy season) and hot and humid outdoor conditions, respectively. The proposed system is concluded to consistently maintain indoor thermal comfort while using energy efficiently, demonstrating its widespread applicability for general high-latent-load buildings characterized by low indoor sensible heat ratio values of 0.56 on average.

Identification of User Requirements and their Influencing Factors Based on Online Reviews and Operational Data

It is crucial for enterprises to clearly identify user needs during the process of formulating product design improvement plans. Therefore, it is essential to comprehensively and accurately identify user needs, explore the reasons behind the emergence of these needs, and incorporate user opinions into the process of product design improvement. A method is proposed to comprehensively and accurately capture user requirements and address the challenge of identifying the underlying causes of user requirements. This method utilizes online comments and operational data to identify user requirements and their influencing factors. First, text sentiment analysis techniques are employed to quantify the importance and performance values of product feature topics. Second, we construct a quadrant model to identify product features requiring improvement, and the original negative comments related to these features are traced. However, the quadrant model alone is insufficient to reflect specific product issues that users are concerned about. Therefore, a functional structure model based on product issues is designed to filter and identify factors that influence user requirements using operational data. Finally, a Bayesian network inference approach is utilized to identify the key influencing factors on user requirements, enabling analysis of the causes behind user requirements and the proposal of product design improvement strategies. The feasibility and effectiveness of the proposed method are validated through experiments conducted on heavy-duty truck data. By analyzing the original negative comments related to the power characteristics, specific user demands regarding the insufficient power of the product were identified, such as “obviously insufficient power when climbing slopes” and other issues. Based on the vehicle power system functional structure model, combined with expert knowledge and operational data, factors related to the state of parts and user behavior that may affect “insufficient vehicle power” were identified. Based on the analysis results, suggestions were made to improve the engine intake air temperature control strategy and to enhance vehicle performance by promoting correct user behavior through informational campaigns.

The effects of personal control and perceived thermal comfort on occupant psychological health at the workplace

Personal control is an important influencing factor for perceived thermal comfort due to its physical and psychological impacts on occupants. However, an increasing body of research on personal control continues to place more emphasis on the physical consequences than the psychological implications for the occupant's health. The objective of this study is to investigate the effects of personal control options and perceived thermal comfort on occupant psychological health in Malaysian office buildings. A total of 221 valid data were obtained through questionnaire survey in three regions in Malaysia, which were then analysed using the partial least squares of structural equation model (PLS-SEM). The findings demonstrated the significantly positive direct relationship between indoor air temperature, relative humidity and personal control on occupant psychological health. The importance of this research work is further highlighted considering the significant role of personal control on the improved quality of thermal comfort and occupant psychological health.

Towards a Digital Representation of Building Systems Controls

Energy monitoring and performance optimization processes play a significant role in ensuring energy-efficient building operation. However, the current implementation of these processes requires substantial time and effort due to the fragmented and non-digital nature of technical building equipment information. To address these challenges, we demonstrate the application of the PLCont methodology within an ongoing monitoring process in a real building. PLCont utilizes Semantic Web Technologies and established RDF ontologies to describe the control topology. The digital representation of control functions aligns closely with the IEC standard 61131-3, and the PLCont ontology establishes a connection between the topology and the control functions. We compare the conventional approach and the PLCont methodol-ogy using the supply air temperature control of an Air Handling Unit (AHU) as a use case. A graphical user interface built upon the PLCont backend provides a comprehensive represen-tation of the system's functionality. It displays the system topology as a digital HVAC schema, the function code exported from the PLC, time-series data plots, and textual descriptions of implemented functions. We demonstrate how this approach enhances transparency and facil-itates the identification and elimination of faulty system behavior, ultimately contributing to the optimization and energy efficiency of building systems.

Model-based optimal control strategy for multizone VAV air-conditioning systems for neutralizing room pressure and minimizing fan energy consumption

Control strategies for variable air volume (VAV) air-conditioning systems play a pivotal role in ensuring indoor environmental quality and energy efficiency. However, conventional approaches, such as static pressure reset (SPR) control, focus on managing indoor air temperature without considering the room pressure, which can lead to unbalanced room pressure and undesirable air leakage. Moreover, with the application of prevalent building pressure control strategies, such as airflow tracking control, to multizone VAV systems, neutralization of the room pressure is difficult across multiple zones in VAV systems. Therefore, this study introduces a model-based optimal control strategy for multizone VAV air-conditioning systems. The proposed strategy uses a multiobjective optimization framework to regulate fan frequencies and damper openings on both the supply and return sides. This holistic approach facilitates the simultaneous control of the indoor air temperature and room pressure while minimizing fan energy consumption. To assess the effectiveness of the proposed strategy, four control strategies were tested using a Python-based simulation testbed. The results demonstrate that the proposed strategy effectively maintains the indoor air temperature, neutralizes room pressure, and reduces fan energy consumption, thereby contributing to the overall efficiency of the VAV system. Moreover, the results highlight the limitations associated with combining airflow tracking control with SPR control for room pressure regulation in multizone VAV systems. This highlights the importance of adopting a model-based approach to address the complexities of concurrent room pressure and indoor air temperature control.

Community-scale changes to landfast ice along the coast of Alaska over 2000-2022

Landfast sea ice that forms along the Arctic coastline is of great importance to coastal Alaskan communities. It provides a stable platform for transportation and traditional activities, protects the coastline from erosion, and serves as a critical habitat for marine mammals. Here we present a full assessment of landfast ice conditions across a continuous 7885 km length of the Alaska coastline over 2000–2022 using satellite imagery. We find that the maximum landfast ice extent, usually occurring in March, averaged 67 002 km2 during our study period: equivalent to 4% of the state’s land area. The maximum extent of landfast ice, however, exhibits considerable interannual variability, from a minimum of 29 871 km2 in 2019 to a maximum of 87 571 km2 in 2010. Likewise, the landfast ice edge position averages 22.9 km from the coastline but, at the community-scale, can range from 2.8 km (in Gambell) to 71.1 km (in Deering). Landfast ice breakup date averages 2 June but also varies considerably both between communities (3 May in Quinhagak to 24 July in Nuiqsut) and interannually. We identify a strong control of air temperature on breakup timing and use this relationship to project future losses of ice associated with Paris Climate Agreement targets. Under 2 °C of global air temperature warming, we estimate the average Alaskan coastal community will lose 19 days of ice, with the northernmost communities projected to lose 50 days or more. Overall, our results emphasize the highly localized nature of landfast ice processes and the vulnerability of coastal Arctic communities in a warming climate.

Effects of post-shooting sprays and bunch covering on yield attributes of Willium banana (Musa paradisiaca L.)

This research investigates the synergistic effects of post-shooting sprays and bunch covering materials on the growth, development, and yield of Willium banana (Musa paradisiaca L.). Gibberellic acid (GA3) at 100 mg/l emerges as a potent post-shooting spray, significantly enhancing bunch length, finger length, girth of finger, bunch weight, and overall fruit yield. The study highlights the pivotal role of GA3 in promoting both cell division and elongation, contributing to increased fruit size and weight. Non-woven material bag covering proves superior in creating an optimal microclimate, fostering enhanced air circulation, temperature control, and light interception. This material significantly boosts finger length, girth, bunch weight, and fruit yield. These findings provide valuable insights for banana cultivation, emphasizing the strategic use of GA3 and appropriate covering materials to optimize environmental conditions and hormonal balance for improved crop outcomes. The study contributes to the evolving field of banana cultivation practices and offers practical implications for enhancing fruit quality and yield.

Effects of different zoning thermostat controls on thermal comfort and cooling energy consumption in reading rooms of a library

This study assessed thermal comfort and energy consumption in indoor environments controlled by air or operative temperature. Reading rooms in a library were divided into several zones based on the distribution of operative temperature. Using air temperature of the inner zone in thermostat control yielded the lowest energy consumption but the poorest thermal comfort level. Conversely, using operative temperature of the least favorable exterior zone resulted in higher energy consumption and comfort levels. The suggested optimal control based on switching boundary temperature minimized energy consumption while satisfying the thermal comfort requirement. The switching boundary temperature range on the top floor is 0.7 °C lower than on the middle floor due to the influence of the roof. The thermostat control modes had similar effects on the east and west reading rooms. The switching boundary temperature ranges of north room was 2.0 °C higher than those of the south room. Zoning control using air temperature control in the inner zone and operative temperature control in the exterior zone was recommended as a much simple mode to keep thermal comfort with low energy use. This study provides insights about the use of operative temperature in zoning thermostat control and theoretical guidance for practical implementation.

Comparison of Local Mean Age of Air between Displacement Ventilation System and Mixing Ventilation System in Office Heating Conditions during Winter

A novel displacement ventilation system (DVS) was designed using a four-way cassette fan coil unit (FCU) and air purifiers (APs) for supplying clean air. The proposed DVS in this study involved drawing indoor air through the FCU and diffusers installed in the ceiling, controlling air temperature using the FCU, and then discharging it back into the office through the APs placed on the floor. The comparative ventilation system considered was the typical mixing ventilation system (MVS) that intakes and exhausts indoor air using diffusers installed on the ceiling. The local mean age of air was used as an index to compare indoor air quality between DVS and MVS under winter heating conditions. It was found that the DVS was more effective in improving indoor air quality in winter than the MVS. Moreover, compared to the MVS, utilizing the DVS designed in this study resulted in the advantage of a much more uniform air temperature variation in the office space. Therefore, it is anticipated that modifying the structure of an indoor space with an FCU installed in the ceiling and APs on the floor to use the DVS designed in this study would greatly assist in enhancing indoor air quality.

Deep learning-based intelligent control of moisture at the exit of blade charging process in cigarette production

Abstract Currently, in the production of cigarettes in the blade, charging export moisture control means is relatively single and can not effectively guarantee the excellent quality of cigarette filament. In this paper, first of all, the working principle of the tobacco blade charging machine is introduced, and the moisture of the tobacco leaf for the charging machine is dynamically analyzed, and the influence of the return air temperature control of the charging machine on the export moisture of the blade charging process is explored. Secondly, based on the traditional PID controller, an adaptive fuzzy PID controller is established by combining adaptive fuzzy rules, and then the stacked noise-reducing self-encoder in deep learning is combined with the adaptive fuzzy PID control to design the intelligent control structure of export moisture of leaf charging process. Finally, the effectiveness of export moisture intelligence control, process capability index, and the effect before and after application were analyzed in controlled experiments, respectively. The results show that the difference between the predicted value and the real value of blade export moisture in this paper’s method is only 0.5%, and the process capability index of this paper’s method is improved by 1.48 compared with the PID controller, and it can control the temperature of the return air of the charging machine in the range of 56.86℃~57.21℃. The intelligent control method of export moisture introduced by deep learning can accurately control the export moisture of the leaf dosing process, which effectively ensures the quality of tobacco filament making.