Ventilating Air Conditioning Research Articles

Energy-saving Design of Heating Ventilating Air Conditioning for Tall Space Structures

Energy-saving Design of Heating Ventilating Air Conditioning for Tall Space Structures

Optimal ventilation strategies for balancing carbon dioxide and suspended particulate matter concentrations in vehicle cabins

Maintaining safe levels of carbon dioxide (CO2) and particulate matter (PM) in vehicle cabins during driving is essential to ensure driver safety and minimize health risks. However, while the fresh-air ventilation mode reduces the CO2 level, it also allows the ingress of PM pollutants from the external environment and hence increases the PM concentration in the cabin. Thus, effective ventilation strategies are required to optimize the air quality by balancing the average levels of CO2 and suspended PM within the cabin. Accordingly, this study performed computational fluid dynamics simulations to explore the effects of different air-conditioning ventilation modes on the indoor air quality in the cabin of a commercial sports utility vehicle. The simulations commenced by examining the optimal switching times between the recirculation and fresh-air modes that yielded an average CO2 concentration of less than 1000 ppm for various numbers of occupants in the cabin. Further simulations were then performed to investigate the effect of the air filtration efficiency of the in-cabin filter on the PM concentration in the cabin under the optimal ventilation strategies determined for 1–5 occupants. The results indicated that, as the number of occupants increased, the required fresh-air mode usage time also increased. Furthermore, to mitigate the corresponding increase in the PM concentration, a higher filtration efficiency was required. Overall, the results showed that the optimal switching cycles achieved the required indoor air quality within the cabin by successfully balancing the CO2 and suspended PM concentrations.

Self-powered electrochromic smart window helps net-zero energy buildings

Net-zero energy buildings are becoming an important energy-saving and low-carbon technology for global environmental protection and resource conservation. As the least energy-efficient building components, windows have promoted the development of electrochemically light/thermal management, where smart windows without external electrical supplies are highly desired for net-zero energy buildings. Here, we develop a self-powered electrochromic smart window system to regulate solar radiation transmittance, constructed by a triboelectric nanogenerator (TENG) and a high-performance electrochromic device. The visible–near-infrared (VIS-NIR) dual-band electrochromic device is well-designed based on an eco-friendly low-energy demand phenothiazine redox ionic liquid, demonstrating a fast switching response of ﹤1.9 s, a large transmittance modulation of >51.8 %, and outstanding electrochemical durability (5.5 % attenuation after 4000 cycles). Upon continuous pressing/releasing motions, the integrated TENG-powered electrochromic smart window (TECSW) displays a prompt light/thermal management behavior with desirable privacy preservation performance (transmittance modulation of 51 % in the visible region) and excellent thermal management property (12.3 °C reducti°n). The whole-building energy simulations show that TECSW can save 347.79 MJ/m2yr (amounting to 96.60 kWh/m2yr) of operational Heating Ventilation Air Conditioning (HVAC) warming/cooling energy consumption among 34 cities in China, accounting for 17.25 % of the total energy consumption. This research provides new insight into designing green and energy-efficient smart windows for net-zero energy buildings.

Study on the deposition characteristics of fine particles at local components in air conditioning ventilation ducts

Air conditioning ventilation ducts are widely used in contemporary buildings. The change of airflow direction in the ducts local components can easily lead to the deposition of particles, which can easily form a secondary source of indoor air pollution and have an adverse effect on human health. Based on this, this paper utilizes the existing experimental data to validate the numerical simulation. The Reynolds stress turbulence model combined with the method of enhanced wall function was used to investigate the deposition characteristics of fine particles in different local components. For the first time, local deposition rates and deposition hotspots were proposed to analyze the simulation results. The results show that the local deposition rate of the particles with a particle size of 1μm do not differ much on each wall surface, and the particles are deposited more uniformly on each wall at the local components, with a difference of less than 10 %, and the maximum local deposition rate is on the outer wall of the local components. When the particle size is larger than 10μm, the local deposition rate on the outer wall of the local component increases significantly, with a maximum increase of 23.3 % (compared to 5μm particles), and the maximum local deposition rate increases slowly with increasing air velocity, with a maximum increase of less than 8 %. The effect of increasing particle size on the maximum local deposition rate is much greater than the increase in air velocity. With the increase of air velocity and particle size, the deposition hotspots of both the 90° bend and the T-type tee duct migrate to the middle of the wall, and the deposition hotspots of the 4-way duct migrate to the inside of the wall.

The Advection Boundary Law in absence of mean flow: Passivity, nonreciprocity and enhanced noise transmission attenuation

Sound attenuation along a waveguide is intensively studied for applications ranging from heating and air-conditioning ventilation systems, to aircraft turbofan engines. In particular, the new generation of Ultra-High-By-Pass-Ratio turbofan requires higher attenuation at low frequencies, in less space for liner treatment. This demands to go beyond the classical acoustic liner concepts and overcome their limitations. In this paper, we discuss an unconventional boundary operator, called Advection Boundary Law, which can be artificially synthesized by electroactive means, such as Electroacoustic Resonators. This boundary condition entails nonreciprocal propagation, meanwhile enhancing noise transmission attenuation with respect to purely locally-reacting boundaries, along one sense of propagation. Because of its artificial nature though, its acoustical passivity limits are yet to be defined. A thorough numerical study is provided to assess the performances of the Advection Boundary Law, in absence of mean flow. An experimental test-bench validates the numerical outcomes in terms of passivity limits, non-reciprocal propagation and enhanced isolation with respect to local impedance operators. Guidelines are outlined to properly implement the Advection Boundary Law for optimal noise transmission attenuation. Moreover, the tools and criteria provided here can also be employed for the design and characterization of other innovative liners.

The Effect of Suggested Ventilation Approaches After Covid-19 on The Probability of Infection, Number of Cases and Ventilation Rates in University Classrooms

After COVID-19, two ventilation approaches have been adopted for infection control. The first is the EN 16798-1 ventilation standard recommended by international organizations. The second is ventilation design, determined according to the risk of infection. This study investigated the effects of various post-COVID-19 ventilation scenarios on the probability of COVID-19 infection, the number of cases, and ventilation rates in four separate university classrooms. Ventilation rates based on infection risk and infection risk were determined by the Wells-Riley mathematical model calibrated to the SARS-CoV-2 virus. The findings showed that the EN 16798-1 ventilation standard may be inadequate in terms of infection risk in classrooms. It showed that ventilation rates determined based on infection risk may not be met by existing HVAC system capacities, even in LEED-certified schools. In possible future pandemics, current ventilation standards and air conditioning system designs in schools should be reviewed in order to control the outbreak.

Chiller fault diagnosis based on improved variational autoencoder and co-training framework: A case study of insufficient samples

Implementing efficient automatic fault diagnosis is critical for saving energy and minimizing financial losses in the heating ventilation air-conditioning (HVAC) systems of commercial buildings. However, the limited quantity and weak features of fault samples acquired during HVAC operations hinder the effectiveness of conventional machine learning-based fault diagnosis methodologies. This paper proposes a method based on an improved conditional variational autoencoder (MCVAE) and co-training (CT) ideology to address the issue of insufficient training samples. Initially, we employ MCVAE to synthesize an extensive dataset of chiller fault samples from the original training dataset. Subsequently, the beneficial samples for training our fault diagnostic classifier, namely high-quality samples, are selected from the generated dataset using the CT-based framework. Finally, the selected high-quality samples are merged into the original training dataset to train the ultimate fault classifiers. Experimental results demonstrate that our proposed method outperforms in effectiveness and efficiency compared to recently published methods. For instance, in the case of fault level 1 compared to the suboptimal model, our approach exhibits improvements of 2.41% when each type has 5 fault samples.

Modeling and optimization of a passive building HVAC system based on improved PSO and H-J Algorithm

Passive buildings employ the principles of active optimization and passive priority to demonstrate their energy-saving, comfortable, and cost-effective qualities, thereby addressing energy consumption in an efficient manner. However, it cannot be ignored that the Heating Ventilation Air Conditioning (HVAC) system is still the largest energy consumer, especially when it is necessary to maintain the comfort of the indoor environment. Consequently, the control and optimization of the HVAC system is a research hotspot and a challenge in the field of building energy conservation, as it is the key to achieving ultra-low energy consumption operation in passive buildings while ensuring the thermal comfort of the indoor environment. This paper presents a comprehensive modeling, control, and optimization framework for the efficient operation of HVAC systems in a passive building located in Jinan, China. Firstly, the HVAC system is modeled using the transient system simulation tool (TRNSYS), GenOpt, Java, and other software. Secondly, the HVAC system’s year-round operation is simulated using specific configurations. In order to enhance the energy-saving effect, a strategy of increasing heat storage and return air ducts was proposed, and a significant energy-saving effect (approximately 17.31%) was realized. Lastly, the data communication interface with GenOpt is established utilizing the TRNOPT module, a method for actively optimizing the refrigerant temperature is proposed, and recalculation and optimization are carried out utilizing the swarm intelligence algorithm and the pattern search algorithm (Hooker-Jeeves algorithm, H-J algorithm). The final optimization results demonstrate a 19% reduction in energy consumption relative to the baseline heat recovery model, validating the applicability of the optimization method under this strategy. The control and optimization method of the HVAC system proposed in this paper can further exploit the energy-saving potential of the passive building HVAC system and will contribute to the advancement of building energy conservation.

Improving the Indoor Air Quality of Office Buildings in the Post-Pandemic Era—Impact on Energy Consumption and Costs

Before the COVID-19 pandemic, ventilation in buildings was not always given its due importance. The World Health Organization has highlighted the important role of air exchange with the outdoors in improving the air quality in buildings; buildings should, therefore, be equipped with mechanical ventilation or adequate air conditioning systems. This paper aims to investigate different retrofit solutions for air conditioning, evaluating them in terms of energy consumption and cost and the impact of increased outdoor air exchange rates on countering the propagation of COVID-19; the latter is the main novelty of the paper. As a case study, we take an existing office building located in Central Italy that was previously not equipped with a mechanical ventilation system (a system with primary air was introduced during the study). The energy analysis was conducted using dynamic simulation software after validation through energy bills; energy and economic analyses were conducted considering different external-air exchange rates. An optimal number of outdoor air changes was found to mitigate the risk of COVID-19 infection, a finding in line with the international literature. The increase in air changes with outdoor air leads to a rise in energy consumption and costs. These values were evaluated for different air conditioning systems and operational schedules. These drawbacks can be made less significant by combining interventions in the system with energy-efficiency measures applied to the building envelope.

Distributed Control of HVAC-BESS under Solar Power Forecasts in Microgrid System

This paper investigates an energy management problem in the microgrid by scheduling heating ventilation air conditioning (HVAC) and battery energy storage system (BESS) with a distributed algorithm. A multi-layer energy management architecture is presented at a system-level to co-optimize the HVAC-BESS by taking into account solar energy forecasts. A surplus-based consensus algorithm is proposed to solve the optimization problem, where the local power mismatch is introduced as a surplus term, and the HVAC-BESS can thus be co-scheduled to maximize renewable energy efficiency at the peak generation time. A set of the convex cost functions are formulated to minimize the HVAC's user dissatisfaction degree and alleviate power loss during the BESS operation. The goal is to collectively minimize the total energy cost in a distributed manner, subject to individual load constraints and power balance constraints. It is theoretically proved that a global convergence of the proposed algorithm is achieved provided that the directed network is strongly connected. The results from a number of case studies are promising, demonstrating the effectiveness and robustness of the algorithm under practical scenarios.

Active Noise Control of Air Conditioning System Noise

A HVAC (Heat Ventilation Air Condition) system of the passenger seat in the autonomous bus is used for heating and cooling of the seat. The compressor of the HVAC system generates the operating noise, and the noise makes passengers annoyance. The frequency spectrum of the compressor noise composes of operating frequency and its harmonics components. The frequency band of operating frequencies is low, and that of harmonic frequencies is high. Active noise control (ANC) has been used for the reduction of low-frequency noise while a passive method using absorption material has been used for the attenuation of high-frequency harmonic noise. However, some part of harmonic components at low-frequency band among harmonic components is not able to reduce by using absorption materials. In this paper, a new ANC method is proposed for the reduction of the noise level of low-frequency harmonic components based on the harmonic filtered x- LMS (HFX-LMS) algorithm. The novel method is successfully applied to the noise control of the compressor of the HVAC system of the passenger seat in the autonomous bus.

Intelligent fault diagnosis for air handing units based on improved generative adversarial network and deep reinforcement learning

Data-driven Automatic fault detection and diagnosis (AFDD) for air handling units (AHUs) is crucial for ensuring the stable operation and energy consumption of the heating ventilation air-conditioning (HVAC) system. However, traditional machine learning methods often underperform when confronted with insufficient training sample data, especially when lacking samples from the fault types. Based on the issues of insufficient samples from the fault types and imbalanced training dataset, this study proposes a novel AFDD approach using transformer integrated conditional Wasserstein generative adversarial network and deep reinforcement learning (TCWGAN-DRL) to synthesize the fault data and select high quality synthetic data samples. Firstly, we utilize the proposed TransCWGAN to synthesize fault samples. Then, reinforcement learning is utilized to select high quality synthetic samples. Finally, the filtered samples and the real fault samples are merged to form the training dataset for conventional supervised learning classifiers. Experimental results demonstrate that the enriched training dataset can effectively improve the AFDD results and outperforms recently published existing methods, for instance, compared to the suboptimal model, our method exhibits an increase in fault recognition accuracy of 4.9%, 3.66%, and 4.02% when the number of real fault samples is 15, 20, and 30, respectively.

A Comparative Analysis of a Radiation-Cooling-Plate-Coupled Adhesion-Jet Air Conditioning System in Different Positions

Compared with the traditional radiant cooling combined with a displacement ventilation air conditioning system, an air conditioning system of radiant cooling combined with an attached jet can not only effectively prevent dew on the surface of the radiant cooling plate, but also further improve the cooling capacity of the radiant air conditioning system; however, most scholars have installed the radiant cooling plate on the radiant roof and the ground, and there are fewer studies on installing the radiant cooling plate on the two sides of the wall. Based on this, this paper builds an experimental system of radiant air conditioning and conducts experiments on summer working conditions in June–October to experimentally study the indoor thermal and humid environments and thermal comfort under different water supply temperatures when radiant cold panels are installed in single-side-wall, symmetrical-wall, and top-panel positions. The experimental results show that the optimal water supply temperatures of single-side-wall radiation combined with an attached-jet air conditioning system, symmetrical-wall radiation combined with an attached-jet air conditioning system, and roof radiation combined with an attached-jet air conditioning system are 18 °C, 22 °C, and 16 °C, respectively, and at the same time, the temperatures of the human body’s working area under the above water supply temperatures are 26 °C, 26.3 °C, and 26.4 °C, respectively. The average humidities in the working area are 58%, 53%, and 57%, which can meet the requirements of our country’s level II comfort when the indoor heat and humidity environment is stable, the energy consumption amounts of the radiant end are 5.71 kW·h, 3.99 kW·h, and 10.81 kW·h, respectively, and the highest efficiency of cooling and dehumidification is achieved with the symmetric-wall radiation combined with the adherent-jet air conditioning system.

Prediction of psychological impacts of noise from ventilation systems

Air-conditioning ventilation systems are essential for maintaining good indoor environmental quality. However, the noise generated by these systems can have negative psychological impacts on occupants, such as dissatisfaction, discomfort, disturbance, and unacceptability. This problem cannot be solved simply by reducing the noise level. With the help of a valid, reliable, and applicable psychometric tool called the psychoacoustics perception scale (PPS), the psychological impacts of the noise on human general judgment (Evaluation, E), sensitivity to the magnitude (Potency, P), and sensation of the temporal and spectral compositions (Activity, A) of sounds can be quantified. A holistic sound quality assessment was proposed to cover the objective assessments of traditional indoor criteria and acoustic metrics, as well as subjective assessment using the PPS. The correlations found between the objective characteristics of the noise from ventilation systems, the PPS scores, and the occupants’ cognitive performance can extend traditional noise level prediction to the prediction of psychological impacts of air-conditioned environments. This advanced knowledge of noise prediction will help acoustic professionals in the design of teaching courses in acoustics, noise, and vibration control, as well as in building services engineering, and throughout the built environment.

Acoustic resonances in an automotive HVAC outlet

In order to better understand the noise generation mechanism of air outlets in an HVAC (Heating Ventilation Air Conditioning) system of a car, investigations were performed in a generic geometry representing a typical air outlet of an automotive car. A hybrid aeroacoustic simulation based on a Large-Eddy Simulation of the incompressible flow coupled with a solver for the acoustic perturbation equations is backed up by an experiment to study the interaction between a throttle valve (used to control the flow rate) and fins (used to guide the flow). Several sound generation mechanisms are identified, of which the so-called Parker-β mode is the most prominent in the sensible frequency range. Both the experimental and simulation results indicate a whistling noise at certain gap lengths between the throttle valve and fins at the frequency of the Parker-β mode. Two different levels of resonance are identified of which one leads to feedback from the acoustic mode to the flow field and one works without feedback. We demonstrate that the latter is established by an efficient excitation of the Parker-β mode by the vortex shedding from the throttle valve if the vortex shedding frequency is close enough to the acoustic frequency.

Utilization of Distinct HVAC Operation Modes to Improve Demand Response Flexibility in the Pharmaceutical Industry and Economic Analysis for Optimization by HOMER Software

Abstract In the pharmaceutical industry (PMI), the major portion of energy is consumed in heat ventilation air conditioning (HVAC) system; therefore, building energy management systems (BEMS) primarily focus on optimizing the energy consumption in HVAC systems. The two operation modes of HVAC, function mode (FM) and non-function mode (NFM), are descriptively explained with their role in improving the flexibility of demanded energy. Both modes are also exposed to hybrid optimization of multiple electric renewables (HOMER) software analysis from an economic perspective. Concerning net present cost (NPC) and cost of energy (COE) constraints, the FM/NFM of HVAC is preferable to the FM. This paper recognizes a comparative evaluation of several demand response (DR) alliances to deliver a comprehensive image of the suitability of DR alliances for different PMIs. Further, the paper also explores an innovative concept in the form of a control algorithm and discusses the relevant challenges and future opportunities. Moreover, the use of renewable energy systems (RESs) for enhancing energy management (EM) flexibility with the economy in the PMI or other industries is emphasized through DR alliances. This review study could be helpful to the PMI in terms of managing energy demand and also incorporating DR as an essential aspect of EM.

Model-Based Reinforcement Learning Method for Microgrid Optimization Scheduling

Due to the uncertainty and randomness of clean energy, microgrid operation is often prone to instability, which requires the implementation of a robust and adaptive optimization scheduling method. In this paper, a model-based reinforcement learning algorithm is applied to the optimal scheduling problem of microgrids. During the training process, the current learned networks are used to assist Monte Carlo Tree Search (MCTS) in completing game history accumulation, and updating the learning network parameters to obtain optimal microgrid scheduling strategies and a simulated environmental dynamics model. We establish a microgrid environment simulator that includes Heating Ventilation Air Conditioning (HVAC) systems, Photovoltaic (PV) systems, and Energy Storage (ES) systems for simulation. The simulation results show that the operation of microgrids in both islanded and connected modes does not affect the training effectiveness of the algorithm. After 200 training steps, the algorithm can avoid the punishment of exceeding the red line of the bus voltage, and after 800 training steps, the training result converges and the loss values of the value and reward network converge to 0, showing good effectiveness. This proves that the algorithm proposed in this paper can be applied to the optimization scheduling problem of microgrids.

단체급식서비스 공간 계획 요소에 대한 건축가와 급식 관리자의 중요도 인식 비교 : 학교와 산업체 급식소를 중심으로

Purpose: The purpose of this study is to derive important space planning elements through a comparison of perceptions of importance between foodservice facility managers and architects, and to present a design guideline that architects can use in remodeling or new construction. Method: For the research, the questionnaire was made based on the feedback from precedent research and preliminary surveys, and consisted of 4 major categories (architecture, indoor environment, sensibility, and convenience factors) and 23 sub-elements. A survey was conducted via e-mail to architects working in Korea and managers at schools and institutional foodservice facilities in the Yeongnam region. A total of 180 questionnaires were distributed, and 155 questionnaires out of 160 collected were used for analysis. Result: As a result of analysis, all three groups considered three elements of architectural factors (circulation, location and layout) and two elements of indoor environmental factors (Ventilation &Humidity control and Air conditioning & Heating system) as the most important ones. In particular, school foodservice managers recognized that two elements of indoor environmental factors (‘noise prevention and ‘size/ place/design of window’) and one of convenience factor (‘reasonable table configuration’) were relatively important to improve comfort in high-density school foodservice spaces. On the other hand, Institutional foodservice managers recognized that elements(‘Accessibility to the subsidiary space’ and ‘Inducing natural access from the outside to the inside through various entry types’) are relatively important to improve customer accessibility and convenience. Based on the research results, basic design guidelines that architects can use are proposed.

Harmonic Distortion Characteristics Generated by Heating Ventilation Air Conditioning System Case Study in PCR Laboratory

Good power quality is required in health facilities since the increasing use of microprocessor-based equipment. Poor power quality in the electric power system can cause medical equipment in health care centers to malfunction and give incorrect medical diagnoses. Since 2020 we are facing a new type of Virus (Covid-19), this virus requires special laboratory construction with specific air conditioning systems (temperature, humidity, and pressure) to process specimens. This paper presents measurement results of harmonic distortion characteristic by Variable Frequency Drive (VFD) of Heating Ventilation Air Conditioning (HVAC) system in PCR Laboratory at Clinic A. The VFD in this system is used to adjust the rotation of the exhaust fan and outdoor unit. The measured voltage, current and power are used to assess power quality. The main power quality problems found in medical facilities are voltage flicker, neutral currents, and total harmonic distortion (THD) values. The measurement of total harmonic distortion (THD) is used to find the source of the harmonics. Potential problems can be identified within the facility. The results of this study can be used to develop, test, and validate the system that has been used.

Effect of a Parked Car Orientation on a Temperature Distribution and Cooling Load Calculation: Experimental Study

When a vehicle is left parked in the sun for an extended period, the gathered heat causes damage to several interiors within the cabin and causes discomfort for people and animals left inside the car. In the present work, the effect of the orientation of a parked white minibus on temperature distribution and cooling load calculation is studied experimentally in an open environment. Two different cases were studied facing south and facing east. For several hours, the temperature inside the car cabin had been monitored and measured at five separate locations. The cooling load calculations are carried out based on the experimental measurements. The results show that the overheating of parked cars always happens as a result of the radiation load especially when a car has a large surface glass area. Also, the ambient load is directly proportional to the ambient temperature, and the total load related directly to radiation load reaches the maximum value of 2358.1 W at 3:00 pm for 1st case and 2118.3 W at 11:00 am for 2nd case which shows an increase of 11.32 %. Thus, these results emphasized the fact that the orientation of the parked car may considerably affect the temperature distribution and the cooling load of the car cabin. Also, the study may be considered an essential step in designing any assisted ventilation or auxiliary air conditioning system that may enhance the car cabin conditions even while the car’s engine was off (parked automobile).