Efficient Air Conditioning Systems Research Articles

Experimental analysis of an innovative geo-exchange system installed on the island of Ischia, in southern Italy

The need to use efficient and eco-friendly air conditioning systems is a fundamental requirement for today’s society. In this context, low and medium enthalpy geothermal energy plays a crucial role. The research and development activities carried out in the present work have made it possible to successfully design and analyze an innovative technology capable of supplying thermal energy to environments without pumping fluid from the subsoil. The proposed system is based on the use of a downhole heat exchanger (DHE). The authors have developed an innovative system for the sustainable use of low and medium enthalpy geothermal energy, installed on the island of Ischia, near Napoli, in southern Italy. The proposed system is based on the use of an ad hoc designed DHE, capable of optimizing the heat transfer with the subsoil, without the need to withdraw fluid from the aquifer. A numerical finite element model was developed to study the interaction between the DHE, the well and the surrounding aquifer. The experimental set-up consists of the heat exchanger and an above ground system, necessary to test the efficiency of the exchanger. The DHE is inserted inside a geothermal well made with a steel casing, equipped with a filtering section in correspondence of the DHE, in order to increase the heat transfer performance due to increased convection with the surrounding aquifer. The experimental data show that the DHE allows to exchange more than 40 kW with the ground, obtaining overall heat transfer coefficient values larger than 450 W/m2 K.

Toward residential decarbonization: Analyzing social-psychological drivers of household co-adoption of rooftop solar, electric vehicles, and efficient HVAC systems in Georgia, U.S.

The marketplace of climate solutions has grown considerably. Three technologies, in particular, exhibit strong potential for disruptive change and advancement in the residential sector: electric vehicles (EVs), rooftop photovoltaics (RPVs), and efficient heating, ventilation, and air conditioning (HVAC) systems. Many scholars have studied the adoption of these technologies; we address their co-adoption. Using a survey conducted in Georgia, we examine pro-environmental behavior, risk tolerance, and energy-related knowledge as social-psychological drivers for the co-adoption of RPVs, EVs, and efficient HVACs (including heat pumps). We conclude that some but not all of these drivers are relevant to the adoption and co-adoption of the three transformational climate solutions. Pro-environmental behaviors, for instance, appear to create conditions for “positive spillover,” propelling consumers toward adopting multiple climate solutions, whereas energy knowledge has no clear relationship with co-adoption. At the same time, the = influence of these drivers are unique to different combinations of technologies – one notable example is the significance of risk tolerance when RPV is added to technology bundles. Our paper contributes to the literature by broadening the understanding of the adoption of bundled (or co-adopted) climate solutions.

Barriers to BIM Implementation in the HVAC Industry: An Exploratory Study

In recent times, the rise of urbanization, industrialization, population growth, food security, and the COVID-19 pandemic have led to an increased demand for indoor spaces with efficient air conditioning systems. As a result, there is a growing interest in creating more complex HVAC systems to improve indoor spaces. Building information modeling (BIM) offers numerous benefits to the HVAC industry, such as clash detection, budget and time reductions, and increased efficiency. However, its implementation is currently hindered by various challenges. This research aims to identify the major barriers to BIM implementation in the HVAC industry in Turkey, using a questionnaire survey of 224 domain experts working in 42 different companies across various fields of the HVAC industry. The study utilized several statistical analyses to categorize and prioritize the most critical barriers, including reliability tests, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), the Kaiser–Meyer–Olkin (KMO) test, Bartlett’s test, and ranking of factors (IRI). The results indicate that the “Deficiencies of Infrastructure and Lack of Qualified Personnel (DIP)” factor group constituted the most significant barrier, followed by “Lack of Documentation and Specifications (LDS)”, “Deficiencies of Case Studies and Project Drawings (DCP)”, and “Lack of Motivation and Resistance to BIM (LMR)”. Moreover, our research revealed that 60% of the participants’ companies allocate less than 40% of their budgets to technological infrastructure, which hinders the adoption of BIM. To promote BIM in the HVAC sector, we recommend enhancing personnel capacity building, improving skills and knowledge about BIM, promoting guidelines, and providing free access to documentation for practitioners.

Experimental investigation of a thermo-responsive composite coated heat exchanger for ultra-low grade heat utilization

There is a growing interest in desiccant coated heat exchanger (DCHE)-based systems due to characteristics of isothermal dehumidification and compact structure. To enhance the dehumidification efficiency and reduce the regeneration temperature of DCHE-based systems, a thermo-responsive composite desiccant coated heat exchanger (PSLCHE) was developed. This study focuses on investigating the influence of operating parameters (such as air temperature, relative humidity, regeneration temperature and adsorption/desorption time ratio) on the dynamic performance, average dehumidification capacity (Davg) and thermal coefficient of performance (COPth) of the system. Under the air condition of 30 °C & 60% RH, the PSLCHE demonstrates remarkable performance with the Davg of 7.3 g·kg−1 and COPth of 0.93 at 40 °C. This study provides a route to the design of highly efficient air conditioning systems using thermo-responsive composite for ultra-low grade thermal energy at 40 °C.

Thermal comfort and retail sales: A big data analysis of extreme temperature's impact on brick-and-mortar stores

The effect of weather on retail sales has long been of great interest to both the business and academic fields. This study investigated the impact of extreme temperatures on brick-and-mortar retail stores in Seoul, Korea. Using a comprehensive credit card transaction dataset, high-resolution weather data, and a semiparametric model, we found a significant increase in sales during extreme temperature events: 4% during heatwaves exceeding 35 °C and 11% during cold spells below −15 °C. This finding is supported by the thermal comfort hypothesis in retail sales, which suggests that consumers are driven to temperature-controlled indoor environments and are inclined to purchase products that provide thermal comfort, such as hot or cold beverages. As extreme weather events become more frequent owing to climate change, accurate sales forecasting during such conditions becomes crucial for retailers. Insights from our research enable retailers to better predict sales under extreme temperature conditions and to strategize accordingly, such as by highlighting thermal comfort products or ensuring optimal indoor temperatures with efficient air conditioning or heating systems.

Integrated Room Monitoring and Air Conditioning Efficiency Optimization Using ESP-12E Based Sensors and PID Control Automation: A Comprehensive Approach

This study addresses the critical need for efficient room monitoring and air conditioning systems, particularly in educational settings like the STMIK STIKOM Indonesia campus. The paper introduces a novel approach that combines ESP-12E based sensors with Proportional-Integral-Derivative (PID) control automation to optimize air conditioning efficiency. Utilizing an ESP-12E microcontroller, the study designed and implemented a room monitoring tool equipped with DHT22 and BH1750 sensors for accurate measurement of temperature, humidity, and light intensity. We also explores the integration of a PID control system into an existing air conditioning (AC) unit. The PID controller was fine-tuned to maintain a stable indoor temperature of 25oCelsius, even when subjected to external heat loads, such as ten LED lamps. The effectiveness of this system was quantified through real-time monitoring of temperature, humidity, and energy consumption, both pre- and post-implementation. Results indicated a rapid and stable response from the PID controller, achieving an amplitude of 1 within 0.08 seconds, thereby confirming its successful tuning and adaptability. We found that this study has broader implications for enhancing energy efficiency and creating conducive learning environments. However, it is worth noting that the research was conducted under specific conditions, and further studies could explore its applicability in different settings.

Performance analyses of a novel free-cooling assisted air conditioning system applied to electrical vehicles

Air conditioning system of electrical vehicles7 consumes much electricity for cooling. Using natural cooling source could effectively reduce energy consumption and extend mileage. In this paper, cooling load characteristics of electric vehicles were analyzed considering influences of climate conditions, and energy saving potential of using natural cooling sources were investigated to provide guidelines for the design of efficient air conditioning systems. First, a typical electrical vehicle was designed as the studying object, and a numerical model was established to calculate vehicle’s cooling load. Utilization ratio of natural cooling in severe cold regions, cold regions, and mild regions ranged from 36.7 % to 47.8 %, while the value was only 2.5 % in hot summer and warm winter areas. Then, a novel natural cooling assisted air conditioning system was proposed, and parametric studies were carried out to study energy-saving ratio and improvement of traveling hours. Average coefficient of performance of the novel system ranged from 4.47 to 6.08 with the air flow rate being 700 m3/h, and ranged from 5.78 to 7.71 with the air flow rate being 2000 m3/h. The values are 7.3 % to 65.8 % higher than the traditional air conditioning system. The electric consumption during cooling period could be reduced by up to 83.7 % in mild regions and by 24.9 % to 57.4 % in severe cold regions, cold regions, and hot summer and cold winter regions. Increasing setting temperature and enlarging air flow rate of the air conditioning system could effectively improve the energy-saving ratio. Traveling hours could be extended by 2.0 % to 15.8 %.

An insight into environmental footprints of emerging air-conditioning systems towards sustainable cities

In this study, the environmental impacts of six conventional and modern air conditioning systems, including vapor-compression air conditioning (VAC), hybrid membrane-based air conditioning (HMBAC), desiccant enhanced evaporative air conditioning (DEVap), solar HMBAC, solar DEVap, and inverter VAC, are analyzed using a cradle-to-gate life cycle assessment (LCA) approach. The assessment is based on climate change, ozone depletion, terrestrial acidification, freshwater eutrophication, human toxicity, photochemical oxidant formation, ecotoxicity, water depletion, and fossil fuel depletion impacts. The LCA findings reveal that membrane-based systems (HMBAC and DEVap) are highly environmentally-friendly in comparison to the regular VAC systems (household split coolers), showing the capability of membranes in developing efficient air conditioning systems. In addition, solar-assisted systems reduce seven out of eleven environmental impacts, while they cause severe eutrophication, marine and freshwater ecotoxicity, and human toxicity consequences. Furthermore, it is unveiled that the inverter can reduce up to 38% of the environmental impacts of VAC systems which are the most common air conditioning system in buildings. Therefore, the manipulation of the inverter system in VACs can be considered as one of the short-term solutions in reducing the environmental footprints of air conditioning. Finally, the sensitivity analysis is applied to show the reliability of the outcomes.

Unsteady heat transfer characteristics of R-407C in the subcooled flow boiling stemming from the oscillating refrigerant flow rate

The objective of this experiment is to investigate the unsteady heat transfer of R-407C subcooled flow boiling (SCFB) due to the oscillating refrigerant flow rate within a narrow tube oriented horizontally for application in energy efficiency air conditioning system. The refrigerant flow rate is input in the cycle of triangular oscillations. Influences of oscillation amplitude (ΔG/G‾) and oscillation period (tp) of the periodic flow rate on SCFB heat transfer are studied. The present results disclose that either ΔG/G‾ or tp has minor impact on time-average SCFB heat transfer performance. However, obvious changes in the temporal variations of the wall temperature on the pipe (Tw) and convective heat transfer coefficient (hr) are found, leading to three heat transfer mechanisms of single phase convection, intermittent nucleate boiling, and persistent subcooled boiling for various input heat fluxes. The Tw of persistent subcooled boiling presents the reversed tendency compared to that of single phase convection due to the variation of the triangular R-407C oscillation. In the case of intermediate heat flux, the unusual boiling phenomenon, called intermittent nucleate boiling, can be obtained depending on the R-407C mass flux. The visualized bubble images are also provided to further describe the intermittent nucleate boiling.

Determination of the optimal location and the number of sensors for efficient heating, ventilation, and air conditioning system operation in a mechanically ventilated pig house

Determination of the optimal location and the number of sensors for efficient heating, ventilation, and air conditioning system operation in a mechanically ventilated pig house

Impact of Building Energy Mitigation Measures on Future Climate

As cities are increasing technological efficacy on greenhouse gas (GH) emission reduction efforts, the surrounding urban ecosystems and natural resources may be affected by these measures. In this research, climate indicators such as heat index, extreme heat events, intensified urban heat islands (UHIs), and sea breeze are projected for the middle and end of the 21st century to understand the climate change signal on these variables with and without building energy mitigation measures. Cities amplify extreme heat and UHI impacts by concentrating large populations and critical infrastructure in relatively small areas. Here, we evaluate the combined climate and building energy mitigation impacts on localized climate metrics throughout the 21st century across extreme emission scenarios (RCP8.5) for the tropical coastal city of San Juan. The analysis of statistically downscaled global circulation model outputs shows underestimation for uncorrected summer daily maximum temperatures, leading to lower extreme heat intensity and duration projections from the present time which are corrected using bias-corrected techniques. High-resolution dynamic downscaling simulations reveal a strong dependency of changes in extreme heat events in urban settings, however, the intensities shift to lower-level grasslands and croplands with energy mitigation measures (combination of white roof, tilted photovoltaic roof, and efficient heating ventilation and air conditioning systems). The building energy mitigation measures have the potential of reducing the UHI intensities to 1 °C and 0.5 °C for the 2050 and 2100 climate periods, respectively.

Enhancing sustainability and performance of automated air conditioners through optimizing product recovery in closed-loop supply chains

This article investigates the use of closed-loop supply chains (CLSC) to im?prove the sustainability and performance of automatic air conditioning systems. With the growing use of automated air conditioning systems in automobiles, it is necessary to analyze and optimize their efficiency even after their life span. To reliably anticipate the performance of automatic air conditioning systems, the suggested method employs a unique soft computing technology based on support vector machines (SVM). Furthermore, the research focuses on the deployment of CLSC, which allows for optimal product recovery and resource utilization. To optimize the multi-product, multi-time, multi-echelon network, a generalized CLSC model is built, considering costs, product recovery possibilities, unknown parameters, and environmental performance. The study sheds light on reverse logistics decision-making, such as centre placement and allocation, as well as cultivation of supplier relationships. Overall, this study?s incorporation of CLSC and the SVM-based performance prediction approach supports sustainable manufacturing practices. It emphasizes the significance of resource efficiency, waste minimization, and environmental effect mitigation in air conditioning system design, manufacture, and operation. Manufacturers may increase not just their environmental sustainability but also the performance and durability of their air conditioning systems by optimizing product recovery and utilizing CLSC. This study provides industry stakeholders with practical information, supporting the adoption of sustainable practices and contributing to a more sustainable and efficient manufacturing ecosystem.

Use of membrane energy exchanger in ventilation: Odour sensory measurement

Membrane energy exchanger (MEE) for a new generation of energy efficient heating, ventilation and air conditioning (HVAC) systems has attracted wide attention. As MEE has been increasingly employed, extensive studies of heat and moisture transfer features have been carried out. Nevertheless, odour transfer through MEE, which may cause odour nuisance and complaints regarding indoor environment, is seldom studied. For most applications of MEE in ventilation, MEE is presumed to be able to prevent the pollutants transfer including volatile organic compounds (VOCs) and odours, despite a lack of clear scientific evidence. This study measured the potential odour transport through an MEE by using an odour sensation panel. The sensory measurement shows the percentage of dissatisfied could reach 84% for the odour source of waffle mix powder in extract air. In comparison, the percentage of dissatisfied is 5% when there is no odour source. The sensory air acceptability, odour intensity and hedonic tone for the supply air using MEE are assessed by a panel for different odour sources in the extract air. The findings of this study indicate that the odours generated from, such as cooking and cleaning in kitchens and in bathrooms, are likely to be undesirably transferred to the supply air through the tested polypropylene membrane exchanger, which may lead to a poor perception of the indoor environment. It may be particularly important to pay attention to the odour transfer through MEE when the odours originate from a kitchen. More studies for different membranes are recommended in the future.

Experimental investigation of an integrated absorption- solid desiccant air conditioning system

Separate handling of sensible and latent components of building loads can be an energy efficient approach compared to simultaneous management of both. This paper presents a detailed experimental analysis of an energy efficient air conditioning system using solid desiccant integrated with absorption system for separate building thermal load handling. The experimental system consists of silica-gel based solid desiccant for latent load handling, whereas the gas fired air-cooled NH3-H2O absorption chiller is used to handle sensible load of the space. A chilled water-cooling coil heat exchanger is installed on the process side of desiccant cooling system to integrate it with the absorption chiller. The performance of integrated absorption- solid desiccant system is compared with a standalone conventional desiccant air conditioning system with a direct evaporative cooler considering it as baseline system under wide range of operating conditions including air temperature, air humidity, and regeneration temperature. The comparative analysis is performed in terms of supply air temperature, cooling capacity, and coefficient of performance. The experimental results exhibit that supply air temperature of the integrated system is 15.2 °C compared to 24.6 °C achieved by conventional desiccant system. Moreover, COPth of the integrated system is also 50–55% higher than its counterpart and it is almost comparable with double-effect absorption chiller. It is concluded that the integrated system using separate load management approach is more efficient for HVAC applications.

Load forecasting and operation optimization of residential fresh air system based on artificial neural network

Radiant cooling and heating and fresh air system is more and more widely used in residential buildings as a high-comfort, energy-saving and efficient air-conditioning system. The fresh air system handles all the moisture load and part of the cooling load of the building. In actual operation, there are some problems, such as high proportion of energy consumption and mismatch between load and operation characteristics. In this paper, a zone-level artificial neural network (ANN) model is established to predict the moisture load of residential building fresh air system. Compared with the measured data, the zonelevel ANN model is established and verified. The total data used for training and testing are 13260 and 864 respectively. This paper also introduces a system control optimization model, and optimizes the operation of the fresh air system combined with the load forecasting results of the zone-level ANN model. Under the scenario of potential energy storage and time of use price, the optimization control strategy is formulated to improve the flexibility of the system. The results show that the zone-level ANN model has high prediction accuracy. The root mean square error variation coefficients corresponding to the prediction results of moisture load is 8.72%. The optimization results can reduce the operation energy consumption and cost of the system by 27.2% and 29.2% respectively in the whole air conditioning season.

Improving the Behavior of Indirect Evaporative Cooler*


 
 
 
 ndirect evaporative cooling is one of the technologies currently used to build highly efficient air conditioning systems and low power consumption. A computer program was created to predict the effectiveness of an indirect-evaporation cooling system which operates based on Maisotsenko cycle (M-cycle) to determine the environmental conditions and proper system design. Several variables that affect the performance of the system have been studied; the amount of volumetric flow of air ranged from (1050 cfm) to (1550 cfm) for the dry side, and changing from 700 cfm to 1200 cfm from the wet side. With respect to design variables, the length of the channel changed from 50 cm to 100 cm. For environmental variables, the effect of changes in dry and wet temperature on system performance had been studied. The experiment was conducted in mid-June over 24 hours. The results showed that the best air supply provided for the best performance of the system is (1050cfm) for the dry side, while the wet side was (900 cfm), when the length of the channel is 80 cm. The results showed the possibility of applying this system in (Tikrit) because it is characterized by its hot and dry climate in the summer, as evaporative cooling efficiency increases in hot, dry climates
 © 2018 JASET, International Scholars and Researchers Association
 
 
 

CNN-LSTM architecture for predictive indoor temperature modeling

Indoor temperature modeling is a crucial part towards efficient Heating, Ventilation and Air Conditioning (HVAC) systems. Data-driven black-box approaches have been an attractive way to develop such models due to their unique feature of not requiring detailed knowledge about the target zone. However, the noisy and non-linear nature of the problem remains a bottleneck especially for long prediction horizons. In this paper, we introduce a Convolutional Neural Networks-Long Short Term Memory (CNN-LSTM) architecture to combine the exceptional feature extraction of convolutional layers with the Long Short Term Memory (LSTM)’s capability of learning sequential dependencies. We experimentally collected a dataset and compared three approaches: Multi-Layer Perceptron (MLP), LSTM and CNN-LSTM. Models are evaluated and compared with 1-30-60-120 min horizons with a closed-loop prediction scheme. The CNN-LSTM outperformed all other models for all prediction horizons and showed a better robustness against error accumulation. It managed to predict room temperature with R2>0.9 in a 120-min prediction horizon.

Design, simulation, and construction an air-conditioning system to eliminate any pathogenic microorganisms in the air

In this paper, for the first time, we have designed, simulated, and constructed an efficient air-conditioning system via a microwave plasma source to eliminate pathogens in the air, which can be found in crowded places such as hospitals and subways, and prevent the diseases' outbreak. The plasma air-conditioning system designed in this paper, besides having a high plasma density (increasing the probability of electrons collision with contaminants), uses a very high-temperature plasma (gas), which is an effective factor to eliminate any contamination. Also, to design and simulate the introduced system, COMSOL software, and its Electromagnetic Waves, Plasma, Laminar Flow, Heat Transfer in Fluids, and Bioheat Transfer modules were used; and the performance of the system has been entirely investigated. Finally, we have shown that the designed system, via an output power of 1000 W, a frequency of 2.45 GHz, and a standard airflow of 170 l/min, can destroy any microorganisms and pathogenic respiratory droplets in the air.

Efficient Off Grid Solar Powered DC Air Conditioning System

Wydawnictwo SIGMA-NOT wydaje czasopisma fachowe informujące swoich czytelników o najnowszych osiągnięciach naukowych i nowoczesnych rozwiązaniach technicznych w Polsce i na świecie, popularyzuje problemy techniczne oraz poszerza wiedzę i kulturę techniczną.

Implementing the Integrated Design Process (IDP) to design, construct and monitor an eco-house in hot climate

ABSTRACT Eco-houses play a pivotal role in reducing greenhouse gas emissions. To implement such a concept, the current Conventional Design Process (CDP) needs to be improved. Thus, Integrated Design Process (IDP) was recently introduced to the buildings sector. IDP involves early stakeholders in a systematic approach to achieve performance targets. In this study, IDP was implemented in a single-family house, targeting efficient houses with minimum/no cost. Many energy efficiency strategies (EESs), such as envelop insulation, orientation, window properties, and efficient air-conditioning system, have been applied. These energy strategies predicted a substantial energy reduction where the energy use intensity (EUI) would fall from 182 to 72 kWh/m2.year. In addition, solar renewable energy, domestic solar hot water (DSHW), and photovoltaic (PV) panels (10 kW) saved 18.78 MWh/year. Besides, water efficiency strategies (WESs) are anticipated to save 217,581 gallons/year due to the use of a water recycling unit, low flowrate faucets, and efficient shower systems, all of which have been proposed. All the recommended energy efficiency strategies (EESs) and water efficiency strategies (WESs) had a simple payback period of fewer than 10 years and proved their cost feasibility over their life-cycle. Moreover, a considerable CO₂ emission avoidance (117 tons/year) was attained.