Search Results (24)

Building on our previous 310-h test of a larger MEMS sensor, this study develops and validates a miniaturized, lift-off-fabricated, and FPC-integrated three-in-one microsensor. In addition to extending the operation to 744 h, we introduce a wireless MQTT/Node-RED architecture to enable real-time IoT-level monitoring in factory HVAC ducts. The microsensor was fabricated using Micro-electro-mechanical systems (MEMS) technology and integrated with a flexible printed circuit (FPC) for improved mechanical compliance and ease of installation. To assess its durability and reliability, a 744-h long-term test was conducted in an industrial HVAC environment, where the performance of the microsensor was compared with that of two commercially available velocity sensors. The integrated sensor exhibited stable operation throughout the test and demonstrated effective measurement capabilities in the ranges of 10–40 °C for temperature, 60–90% RH for humidity, and 1.5–5.0 m/s for airflow velocity, with an overall accuracy of approximately ±3%. The results highlight the sensor’s potential for real-time environmental monitoring in factory HVAC systems, offering advantages in integration, adaptability, and cost-effectiveness compared to traditional single-function commercial sensors. Full article

Heating, Ventilation, and Air Conditioning (HVAC) systems primarily consist of pre-cooling air handling units (PAUs), air handling units (AHUs), and air ducts. Existing HVAC control methods, such as Proportional–Integral–Derivative (PID) control or Model Predictive Control (MPC), face limitations in understanding high-level information, handling rare events, and optimizing control decisions. Therefore, to address the various challenges in temperature and humidity control, a more sophisticated control approach is required to make high-level decisions and coordinate the operation of HVAC components. This paper utilizes Large Language Models (LLMs) as a core component for interpreting complex operational scenarios and making high-level decisions. A chain-of-thought mechanism is designed to enable comprehensive reasoning through LLMs, and an algorithm is developed to convert LLM decisions into executable HVAC control commands. This approach leverages adaptive guidance through parameter matrices to seamlessly integrate LLMs with underlying MPC controllers. Simulated experimental results demonstrate that the improved control strategy, optimized through LLM-enhanced Model Predictive Control (MPC), significantly enhances the energy efficiency and stability of HVAC system control. During the summer conditions, energy consumption is reduced by 33.3% compared to the on–off control strategy and by 6.7% relative to the conventional low-level MPC strategy. Additionally, during the system startup phase, energy consumption is slightly reduced by approximately 17.1% compared to the on–off control strategy. Moreover, the proposed method achieves superior temperature stability, with the mean squared error (MSE) reduced by approximately 35% compared to MPC and by 45% relative to on–off control. Full article

Airborne transmission has been implicated as a major route for the spread of microorganisms, causing infectious disease outbreaks worldwide. This has been emphasized by the recent COVID-19 pandemic, caused by the SARS-CoV-2 virus. There is thus an unmet need to develop technologies that arrest the spread of airborne infectious diseases by inactivating viruses in the air. In this study, the efficacy of two commercially available air ionizer systems for inactivating the bacteriophage MS2, which has been utilized as a surrogate of SARS-CoV-2 as well as a surrogate of noroviruses, was assessed. An experimental test apparatus similar to an HVAC duct system was utilized for the efficacy testing. Each of the two ionizer devices was challenged with viral aerosols of the bacteriophage MS2. The results indicate that the two ionizers were able to reduce the concentration of bacteriophage MS2 virus in the air by 82.02% and 81.72%, respectively. These results point to the efficacy of these ionizer devices in inactivating airborne microorganisms and thus making them an important tool in arresting the spread of infectious diseases. More studies are needed to assess their efficacy against other important airborne viruses such as influenza and strains of the SARS-CoV-2 virus. Full article

Climate change and the need to reduce greenhouse gas emissions have made energy efficiency in modern building operations more critical than ever. This study presents an improved damper control strategy for VAV systems, combined with techniques like DCV and duct static pressure adjustments, to optimize fan energy consumption. Using energy simulations and mathematical models, the research evaluates traditional HVAC operating methods against the proposed novel control approach across diverse climates. Findings show that the refined control integrations effectively adjust ventilation air volumes during low occupancy and achieve up to 47% savings in fan energy, cost, and CO₂ savings annually. While DCV alone had minimal impact on fan energy, it significantly reduced the amount of outdoor air that required conditioning, thereby lowering cooling and heating demands. This research highlights the importance of integrating an advanced control strategy in building mechanical systems to reduce operational costs and environmental impact, contributing to sustainability and carbon reduction goals. Full article

Faults of heating, ventilation, and air-conditioning (HVAC) systems can cause significant consequences, such as negatively affecting thermal comfort of occupants, energy demand, indoor air quality, etc. Several methods of fault detection and diagnosis (FDD) in building energy systems have been proposed since the late 1980s in order to reduce the consequences of faults in heating, ventilation, and air-conditioning (HVAC) systems. All the proposed FDD methods require laboratory data, or simulated data, or field data. Furthermore, the majority of the recently proposed FDD methods require labelled faulty and normal data to be developed. Thus, providing reliable ground truth data of HVAC systems with different technical characteristics is of great importance for advances in FDD methods for HVAC units. The primary objective of this study is to examine the operational behaviour of a typical single-duct dual-fan constant air volume air-handling unit (AHU) in both faulty and fault-free conditions. The investigation encompasses a series of experiments conducted under Mediterranean climatic conditions in southern Italy during summer and winter. This study investigates the performance of the AHU by artificially introducing seven distinct typical faults: (1) return air damper kept always closed (stuck at 0%); (2) fresh air damper kept always closed (stuck at 0%); (3) fresh air damper kept always opened (stuck at 100%); (4) exhaust air damper kept always closed (stuck at 0%); (5) supply air filter partially clogged at 50%; (6) fresh air filter partially clogged at 50%; and (7) return air filter partially clogged at 50%. The collected data from the faulty scenarios are compared to the corresponding data obtained from fault-free performance measurements conducted under similar boundary conditions. Indoor thermo-hygrometric conditions, electrical power and energy consumption, operation time of AHU components, and all key operating parameters are measured for all the aforementioned faulty tests and their corresponding normal tests. In particular, the experimental results demonstrated that the exhaust air damper stuck at 0% significantly reduces the percentage of time with indoor air relative humidity kept within the defined deadbands by about 29% (together with a reduction in the percentage of time with indoor air temperature kept within the defined deadbands by 7.2%) and increases electric energy consumption by about 13% during winter. Moreover, the measured data underlined that the effects on electrical energy demand and indoor thermo-hygrometric conditions are minimal (with deviations not exceeding 5.6% during both summer and winter) in the cases of 50% clogging of supply air filter, fresh air filter, and return air filter. The results of this study can be exploited by researchers, facility managers, and building operators to better recognize root causes of faulty evidences in AHUs and also to develop and test new FDD tools. Full article

EU legislation requires introducing a variety of measures to reduce energy consumption. Energy use decrease should be achieved through thermal retrofitting of the least energy-efficient buildings. In the case of cities like Kraków, this means the need to modernize (retrofitting as well as the incorporation of modern HVAC systems) historical buildings. Furthermore, urban morphology is an influencing factor with regards to the energy performance of buildings and therefore of cities (since the influence of shading from nearby buildings cannot be ignored). The paper presents the results of a study on the impact of shading on energy demand for heating and cooling in the historic centre of Krakow. A comparative analysis of the simulation calculation results was performed using the statistical climate as a boundary condition. In the case of a typical five-floor residential tenement house from the turn of the 20th century, an 8% increase in energy demand for heating and a 50% reduction in energy demand for cooling were estimated. As the analysis of the results shows, taking into account the shading from nearby buildings may be crucial for optimizing the volume (power of devices, diameters of ducts and pipes) of the HVAC installation. Full article

The purpose of this study was to determine the annual energy consumption that can be attributed to heating, ventilation, and air conditioning (HVAC) systems’ mixing temperature error. To develop a mixing temperature prediction model for a single-duct variable air volume (VAV) system, the mixing temperature was measured using 15 temperature sensors installed in an HVAC mixing chamber as well as the existing air handling unit’s (AHU) mixing temperature sensor. The mixing chamber was modeled using computational fluid dynamics (CFD), and a coefficient of variation of the root-mean-square error of 7.927% indicated that the model was reliable. Next, CFD simulation cases were formulated, and the temperature distribution of the mixing chamber was analyzed. This revealed that the amount of outdoor airflow input and the change in the temperature distribution of the mixing chamber were directly proportional to each other and that the mixing temperature measurements for the mixing chamber were not accurate. The mixing temperature prediction model was developed through multiple regression analysis and was successfully applied and verified. Compared with the measurements provided by existing mixing temperature sensors, the mixing temperature prediction model indicated an absolute error of 0.008–0.42 °C, confirming the model’s prediction performance. Full article

Plate heat exchangers are widely used in the Heating, Ventilation, and Air Conditioning (HVAC) field. Cross-corrugated triangular ducts are commonly employed in plate heat exchangers. Inserting baffles into the cross-corrugated triangular ducts can improve the heat transfer performance of the plate heat exchangers. This study focuses on intricate interdependencies among the flow channel apex angle, the trapezoidal baffle inclination angle, baffle position, and Reynolds number (Re) on heat transfer and pressure drop using response surface methodology (RSM) and computational fluid dynamic (CFD). To identify the factors that maximize the Nusselt number (Nu) and minimize friction factor (f), the RSM is used to design factors, conduct numerical studies, and establish regression equations. The results show that the apex angle, baffle angle, X-direction position, and Re have significantly affected Nu and f. Compared to a non-baffled channel with the same apex angle and Re conditions, the optimized channel enhances heat transfer by 1.54 times and has an almost identical pressure drop. The inclined baffle significantly enhances comprehensive performance at low Re. The synergistic effect of the heat transfer and pressure drop is most optimal when the apex angle of the flow channel is 90°, the trapezoidal baffle inclination angle is 52.5°, and the Re is 1000, with the baffle position at 0.625H in the X-direction. Full article

With the renewed focus on indoor air quality (IAQ) due to “Sick building syndrome” and the recent COVID-19 pandemic, the availability of innovative components and innovative guidance for maintenance and systemic safety design will play an important role, with HVAC systems as protagonists. UV-C irradiation has been investigated for a long time, and some system solutions are known. The aim of this work is to provide an overview of the latest outcomes related to the innovative components of HVAC systems using UV-C irradiation and investigate the current state of the art. A procedure based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was adopted, and the Scopus database was used to query the relevant literature. A total of 66 publications qualified for inclusion in the survey: 29 articles report experimental investigations, 24 articles are related to numerical or theoretical analysis, and both approaches were used in 13 articles. Many papers deal with upper-room UVGI, AHUs, and ducts. A few papers analyse mobile devices. The evaluation of the dose, as in the case of the definition of irradiance, is reported in a small number of articles. This lack of information makes the scenario imprecise and non-quantitative. Full article

Buildings’ heating, ventilation, and air-conditioning (HVAC) systems account for significant global energy use. Proper maintenance can minimize their environmental footprint and enhance the quality of the indoor environment. The adoption of Internet of Things (IoT) sensors integrated into HVAC systems has paved the way for predictive maintenance (PdM) grounded in real-time operational metrics. However, HVAC systems without such sensors cannot leverage the advantages of current data-driven PdM techniques. This work introduces a novel data-driven framework, the health prognostics classification with autoencoders (HPC-AE), designed specifically for PdM. It utilizes solely HVAC power consumption and outside temperature readings for its operations, both of which are readily obtainable. The primary objective of the HPC-AE framework is to facilitate PdM through a health prognostic approach. The HPC-AE framework utilizes an autoencoder for feature enrichment and then applies an artificial neural network to classify the daily health condition of an HVAC system. A multi-objective evaluation metric is employed to ensure optimal performance of the autoencoder within this framework. This metric evaluates the autoencoder’s proficiency in reducing reconstruction discrepancies in standard data conditions and its capability to differentiate between standard and degraded data scenarios. The HPC-AE framework is validated in two HVAC fault scenarios, including a clogged air filter and air duct leakage. The experimental results show that compared to methods used in similar studies, HPC-AE exhibits a 5.7% and 2.1% increase in the F1 score for the clogged air filter and duct leakage scenarios. Full article

The energy consumption of a heating, ventilation, and air conditioning (HVAC) system represents a large amount of the total for a commercial or civic building. In order to optimize the system performance and to increase the comfort of people living or working in a building, it is necessary to monitor the relevant parameters of the circulating air flux. To this end, an array of sensors (i.e., temperature, humidity, and CO₂ percentage sensors) is usually deployed along the aeraulic ducts and/or in various rooms. Generally, these sensors are powered by wires or batteries, but both methods have some drawbacks. In this paper, a possible solution to these drawbacks is proposed. It presents a wireless sensor node powered by an Energy Harvesting (EH) device acted on by the air flux itself. The collected data are transmitted to a central unit via a LoRa radio channel. The EH device can be placed in air ducts or close to air outlets. Full article

Heating ventilation and air conditioning (HVAC) systems represent one of the main noise sources inside classrooms. This explain why HVAC systems require careful design, competent installation and balancing, and regular maintenance. Many factors influence the classroom acoustical design, such as air handlers or fans, the velocity of air inside the classroom, as well as the size and acoustical treatment of ducts, returns, and diffusers. Acoustic parameters, including background-noise levels, reverberation time, and intelligibility, were analyzed in 17 classrooms at the Università Politecnica in the Marche region. The study of intelligibility was performed by measuring the objective parameters in situ and using prediction methods to determine the intelligibility score. The relationship between speech intelligibility measurements and speech intelligibility calculation has been studied. The relationship between the STI values with the background-noise levels and the reverberation time was also studied. This research shows that a comparison between predictive methods and measurement methods results in speech intelligibility for classrooms of different sizes with and without HVAC systems. The current method of calculating the voice transmission index (STI), proposed by national and international standards, has been used to determine speech intelligibility scores in classrooms. The results show that the calculation tool has computational robustness allowing its use in preliminary evaluations of speech intelligibility, design of the optimal type of school buildings, and sound amplification systems in classrooms that comply with Italian regulations. Full article

Aerosols carrying the virus inside enclosed spaces is an important mode of transmission for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as supported by growing evidence. Urban subways are one of the most frequented enclosed spaces. The subway is a utilitarian and low-cost transit system in modern society. However, studies are yet to demonstrate patterns of viral transmission in subway heating, ventilation, and air conditioning (HVAC) systems. To fill this gap, we performed a computational investigation of the airflow (and associated aerosol transmission) in an urban subway cabin equipped with an HVAC system. We employed a transport equation for aerosol concentration, which was added to the basic buoyant solver to resolve the aerosol transmission inside the subway cabin. This was achieved by considering the thermal, turbulent, and induced ventilation flow effects. Using the probability of encountering aerosols on sampling surfaces crossing the passenger breathing zones, we detected the highest infection risk zones inside the urban subway under different settings. We proposed a novel HVAC system that can impede aerosol spread, both vertically and horizontally, inside the cabin. In the conventional model, the maximum probability of encountering aerosols from the breathing of infected individuals near the fresh-air ducts was equal to 51.2%. This decreased to 3.5% in the proposed HVAC model. Overall, using the proposed HVAC system for urban subways led to a decrease in the mean value of the probability of encountering the aerosol by approximately 84% compared with that of the conventional system. Full article

A wireless flexible air velocity microsensor was developed by using micro-electro-mechanical systems (MEMS) technology. Polyimide (PI) material was selected for the waterproof and oilproof requirements of the cold air duct environment of heating, ventilation, and air conditioning (HVAC) systems, and then a wireless flexible micro air velocity sensor was completed. To obtain real-time wireless measurements of the air velocity inside the cold air ducts of an HVAC system, and to create a measurements database, the deployment locations and quantity of micro air velocity sensors for the internal environment of the cold air ducts were planned. A field domain verification was performed to optimize the internal environment control of the cold air ducts of ventilation and air conditioning systems and to enhance the quality and reliability of process materials. This study realized real-time monitoring of velocity in the HVAC ducts of a chemical-fiber plant. A commercial velocity sensor (FS7.0.1L.195) was purchased and a micro-electro-mechanical systems (MEMS) approach was also used to develop a home-built micro air velocity sensor, to optimize the provision of the commercial sensors and our home-built micro air velocity sensor. Comparing the specifications of the two commercially available sensors with our home-built micro air velocity sensor, the results show that the home-built micro air velocity sensor has the advantages of fast response time, simultaneous sensing of three important physical quantities, and low cost. Full article

As global warming accelerates due to greenhouse gas emissions, more efforts are required to reduce greenhouse gas emissions. One of the methods used to save building energy is the efficient management of building mechanical systems. The economizer control of HVAC systems is an energy-efficient measure that improves operating methods by introducing outdoor air to save cooling energy when the outdoor-air temperature is sufficiently low. When the HVAC system is operated using economizer control, cooling energy can be saved, and the set-point of the mixed-air temperature is kept constant. Several studies are being conducted on the saving of energy using economizers. Although various studies have been conducted on the control of economizers, there is insufficient research dealing with the optimal control of mixed-air temperature in economizers that consider real-time changes. Therefore, in this study, predictive model-based mixed-air temperature optimization for a single-duct VAV system was constructed. For this, an ANN (Artificial Neural Network) that could be analyzed regardless of the variables was applied to predict the load and energy consumption and a simulator was constructed for the optimized mixed air temperature of the system. The predictive model-based control was evaluated in terms of its thermal comfort and energy, along with the existing economizer control. According to the application of the optimal economizer control, the energy consumption of the building was reduced by 28.9% compared to the existing dry-bulb temperature control, and was within ±1 °C of the indoor-air temperature set point. Full article