Heating, Ventilation, And Air Conditioning Duct Research Articles

Autonomous Control of a Hybrid Rolling and Flying Caged Drone for Leak Detection in HVAC Ducts

In this article, a hybrid, rolling, and flying multirotor caged drone is developed for inspection and leak detection of heating, ventilation, and air conditioning (HVAC) ducts. The developed passive-cage drone is designed, manufactured, and controlled autonomously using direct model reference adaptive control (DMRAC). The platform is equipped with a 2-D LIDAR sensor that provides a scan of the surroundings in a plane. Possible leaks are detected using a thermal camera. DMRAC is used for higher level roll, pitch, and yaw control, while lower level motor speed control is achieved through Proportional-Integral-Derivative (PID) controllers. This article compares, for the first time, PID-based controllers for roll, pitch, and yaw control, with standard DMRAC and DMRAC with gain modifications, in a cascaded setting on a hybrid passive-caged drone. Several hardware tests are used to highlight the differences in the control performance when PID controllers/DMRAC with certain gain modifications are used to control the developed hybrid passive-caged drone.

Comparing and validating air sampling methods for SARS-CoV-2 detection in HVAC ducts of student dorms

The Coronavirus disease 2019 (COVID-19) pandemic demonstrated the threat of airborne pathogenic respiratory viruses such as the airborne Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The ability to detect circulating viruses in a workplace or dormitory setting allows an early warning system that can alert occupants to implement precautions (e.g. masking) and/or trigger individual testing to allow isolation and quarantine measures to halt contagion. This work extends and validates the first successful detection of SARS-CoV-2 virus in dormitory Heating, Ventilation, and Air Conditioning (HVAC) systems and compares different air sampling methods and media types combined with optimized quantitative Reverse-Transcription PCR (qRT-PCR) analysis. The study was performed in two environments; large dormitories of students who underwent periodic testing for COVID-19 (unknown environment) and the HVAC air from a suite with a student who had tested positive for COVID-19 (known dorm). The air sampling methods were performed using Filter Cassettes, BioSampler, AerosolSense Sampler and Button Sampler (with four media types with different pore sizes of 5 μm, 3 μm, 3 μm (gelatin), and 1.2 μm). The SARS-CoV-2 positive air samples were compared with the positive samples collected by individual student campus track tracing methods using PCR testing on saliva and nasopharyngeal samples. The results show a detection rate of 73% in the unknown environment and a 78% detection rate in the known dorm. Our data show that the virus was detectable with all the sampling methods we employed. However, the AerosolSense sampler and BioSampler performed the best at 63% and 61% detection rates, compared to 25% for the Filter Cassettes and 23% for the Button Sampler. Despite the success rate, it is not possible to definitively conclude which method is most sensitive due to the limited number of samples. These results show that with careful sampling and optimized PCR methods, pathogenic respiratory viruses can be detected in large buildings using HVAC return air.

Realization of rule-based automated design for HVAC duct layout

In the traditional process of pipeline design, a designer typically creates a general layout of pipeline based on their experience, and then calculates whether the hydraulic calculation of pipeline meets the requirements. This method of design is both time-consuming and labor-intensive. Furthermore, the results are often suboptimal and prone to errors, which creates a lot of waste of human and material resources. The objective of this paper is to propose a computer-aided method for completely automating the heating, ventilation and air conditioning (HVAC) duct system design process. This method incorporates all the necessary design processes, such as duct selection and hydraulic calculation, and introduces a rule-based divide-and-conquer method to the pipe routing design (PRD). The research assesses the practical effect of this piping design algorithm in a BIM environment using varied building scenarios. The findings show that the proposed method is capable of meeting the design requirements of actual projects. The automatic piping design technique presented in this paper can significantly reduce labor costs associated with HVAC design while eliminating calculation errors and compressing the design timeline for most of the complex projects to within 5 min.

Noise isolation in building HVAC system using recyclable plastic bottles

The paper proposes an improvement of the acoustic environment in a sustainable building by utilizing differently sized discarded bottles. The HVAC (heating, ventilation and air conditioning) ducts in buildings serve as conduits for purified air, but they also generate noise as a result of turbulent flow caused by internal irregularities within the ducts. This study involves the modification in the design of ducts by utilizing the discarded or recyclable bottles. By incorporating recyclable bottles along the periphery of the duct, there is decrease in the generation of flow noise. The work presents a comprehensive investigation that employs numerical, experimental, and theoretical methods to assess the sound transmission loss (STL) within the redesigned air duct. The four-microphone impedance tube technique is utilized to measure the STL. The findings reveal that connecting bottles along the length of the air duct at specific intervals leads to a significant reduction in low-frequency noise. Additionally, increasing the number of bottles arranged radially along the air duct leads to a further enhancement and widening of the bandwidth of sound transmission loss (STL).

HVAC Noise Prediction Using Lighthill Wave Method

Automotive Heating Ventilation and Air Conditioning (HVAC) system is an essential component in providing thermal comfort to the cabin occupants. The HVAC noise which is typically not the main noise source in ICE vehicles, is considered to be one of the dominant sources in the electric vehicle (EVs) cabin interiors. As air is delivered through ducts and registers into the cabin, it will create an air-rush/broadband noise and in addition to that, any sharp edges or gaps in flow path can generate monotone/tonal noise. Noise emanating from the HVAC system can be reduced by optimizing the airflow path by the use of virtual analysis during the development stage. This paper mainly focuses on predicting the noise from the HVAC ducts and registers. In this study, Noise simulations were carried out with Ducts and Registers. An FVM based 3-Dimensional (3D) CFD solver was used for flow as well as acoustic simulation. Large Eddy Simulation (LES) was used for flow field generation and noise characteristics were studied using Lighthill Wave method which is a hybrid aeroacoustic approach that can provide results with a quick turnaround time and low computational power. The frequency response of the aeroacoustic noise from the ducts and registers were predicted using the simulations and the models were compared in terms of Overall Average Sound Pressure Level (OASPL). The simulated spectra exhibit good correlation with the test data.

Life cycle analysis methodology for heating, ventilation and air conditioning ductwork in healthcare buildings

The design, modelling and construction of heating, ventilation and air conditioning (HVAC) facilities in healthcare buildings must aim for the users’ maximum comfort and meet sanitary criteria for indoor air quality. The environmental impact of 12 HVAC duct types was subjected to life cycle assessment, with a single-score damage category analysis carried out for the midpoint and endpoint levels. The two most favourable duct types for the different impact categories were aluminium with helical steel wire reinforcement and fibreglass insulation, and also copper sheeting with rock wool and polyurethane insulation. However, although the former presented the best environmental impact values, this type is inadvisable for healthcare buildings. This is due to its nature and the subsequent tendency of the system to lose pressure and efficiency, as well as the difficulty of cleaning this type of ductwork and its predisposition to bacterial proliferation. Thus, the copper duct type with rock wool insulation is the most suitable type for healthcare buildings. This came second overall environmentally (1.06 pt/m2), with values 2.83 times more favourable than the polyisocyanurate solution. Finally, the application of the life cycle assessment (LCA) methodology to HVAC ductwork was demonstrated to reduce the impact by up to 39.88%.

A Micro Air Velocity Sensor for Measuring the Internal Environment of the Cold Air Ducts of Heating, Ventilation, and Air Conditioning Systems.

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.

Prediction of automotive HVAC duct acoustic properties via innovative simulation techniques

or the automotive industry, acoustic comfort is of increasing importance. Customer expectations and strong competition in the market play an important role to accelerate vehicle development activities. Although the primary function of HVAC (Heating ventilation and Air-conditioning) is thermal comfort of the occupant during ride; acoustic comfort is also important when it comes to customer satisfaction resulting in overall experience of the vehicle. Hence, prediction of cabin interior noise in the early design stage plays an important role in designing a superior quality product.In this paper, cabin interior noise levels generated by HVAC systems are predicted by using computational 1-D (one dimensional) analysis. 3-D (three dimensional) CAD geometry is designed using SOLIDWORKS and 1-D analysis is done on GT-Suite. Main purpose of this paper is to demonstrate how 1-D simulation can be an aid for a duct designer by predicting the NVH characteristic of HVAC Ducts and continuing the research to shorten the product development timelines.

Optimization of the Electric Vehicle HVAC Duct System Based on Gradient Method

Our study describes the optimization of the part of heating, ventilation and air conditioning (HVAC) system of an electric car. The geometry of the air duct connected to the heater unit on one side and the dashboard on the other. From the point of view of aerodynamics, it is necessary to change the geometry of the air duct so as to minimize the loss of air pressure and ensure a more uniform flow from the exit holes to improve the efficiency of windshield heating. In order to optimize the initial geometry of the air duct, approach of using gradient methods was applied. According to the results of the study, detailed concept of optimizing the air duct of an electric car is presented. The optimized geometry was tested with the use of methods of computational aerodynamics. Calculations were made as part of the interior model of electric car with the output of temperature fields on the windshield. The results can be applied to the design of heating, ventilation and air conditioning systems of vehicles in a short time.

ECONOMIC AND ENVIRONMENTAL IMPACTS OF THERMAL INSULATION USED IN DIFFERENT DUCT SIZES

In this study, the economic and environmental impacts of insulation material are determined for different sizes of heating, ventilation and air conditioning (HVAC) duct. The optimum insulation thickness (OIT), energy-saving (ES) and payback period (PP) for HVAC duct are estimated using Life cycle cost (LCC) analysis. The analysis considers coal, natural gas (NG), liquefied petroleum gas (LPG), fuel oil (FO), bagasse, rice husk (RH) and geothermal as an energy source and the fiberglass as an insulation material. The results indicate the OIT and PP for an HVAC duct increase with the size of the duct while ES decreases. The maximum value of OIT, ES and minimum value of PP for different sizes and energy sources are determined as 48.27 mm in size A (300 mm) and NG, 84.91% in size E (500 mm) and LPG, and 0.2035 years in size A and NG, respectively. Additionally, the environmental analysis results indicate emission of CO2, CO and SO2 decreases with insulation thickness. The maximum value of CO2 and CO emission is determined for size E and NG i.e. 81.8% and SO2 emission for size E and FO i.e. 76.66%, respectively.

An experiment and numerical study of resuspension of fungal spore particles from HVAC ducts

Fungal spore resuspension on the surfaces of the heating, ventilation and air-conditioning (HVAC) ducts have been verified as one of the most important factors causing indoor biological pollution. To effectively control indoor bioaerosols pollution, it is essential to understand the resuspension characteristics of fungal spores in HVAC ducts. Therefore, this study aims to investigate the movement behavior of particles and further the variation of particle resuspension with HVAC operation mode. Based on the experimental and numerical study, this study specifically investigated the micro-movement behavior of particles and impact of particle size (1, 4, 7 and 10 μm), air temperature (9, 15 and 30 °C), relative humidity (20, 50 and 80%), duct surface roughness (0.5 and 50 μm) and air velocity (0.3, 0.9, 1.5 and 2.5 m/s) on the short-term resuspension of particle in horizontal HVAC ducts. Results indicate that spore particles were dominantly rolling off rather than sliding or being lifted into the air. Compared with larger particles, smaller ones were more sensitive to the wall roughness. The resuspension rate of spores was mainly affected by airflow velocity and particle size, where the resuspension rate of particles increased by up to six times with the increase of airflow velocity from 0.9 to 2.5 m/s. In comparison, either air temperature or relative humidity made negligible difference to particle resuspension rate. Overall, this study provides the knowledge of fungal spore resuspension in HVAC ducts, laying the foundation for effectively controlling the indoor biological pollution.

Prediction of HAVC Cool-Down Performance inside a Minibus Passenger Cabin Using CFD and Its Experimental Validation.

Now with more time spent by people while travelling and increasing mobility, providing passengers with a thermally comfortable experience are one of the important targets of any bus manufacturer. Conversely, comprehensive assessment through Climatic Wind Tunnel testing is costly and not possible during early stages of vehicle design. The aim of this work has been to develop a simplified simulation methodology to model the Minibus passenger cabin for cool down test. This study presents a methodology for predicting Heating, Ventilation and Air Conditioning (HVAC) cool-down performance inside Minibus cabin using Computational Fluid Dynamics (CFD) simulation to revise the HVAC duct design and parametric optimization in order to ensure thermal comfort of occupant. Heat Load is calculated analytically and has been considered in the CFD model and occupant heat load is considered as per ASHRAE standard. CFD simulation predicted the temperature and velocity distribution inside passenger cabin. Simulated cool-down results were found to be in good agreement with the experimental results. CFD cool-down prediction is useful in order to reduce time and costs related to climatic wind tunnel and road tests. Validated CFD model is used to study the effect of air flow on cool-down performance.

Experimental Study on the Demand Shifting Effects of PCM Integrated Air-Conditioning Duct

The proportion of electricity used for civil buildings is increasing, which intensifies the imbalance between the demand side and supply side of the grids and leads to a large decrement in grid efficiency and large energy losses. The phase change material (PCM) can be used to store numerous heat or cold for heating, ventilation, and air-conditioning (HVAC) systems for its phase change temperature range suitable for maintaining comfortable building thermal environment. Utilizing PCM for HVAC is an important way to mitigate fluctuations in the power consumption of buildings. This paper proposes a new type of air-conditioning duct combined with PCM. The demand shift effects of the PCM integrated air-conditioning duct is studied through experiments. The PCM material ingredients are designed according to the required phase change temperature range. The feasibility of PCM application in HVAC ducts is verified. The results show that air-conditioning duct combined with PCM can keep the indoor temperature in a comfortable range during the power peak load after shutting down chiller.

LCC Optimization of Different Insulation Materials and Energy Sources Used in HVAC Duct Applications

The heating, ventilation and air conditioning (HVAC) ducts distribute the conditioned air to different zones. They are installed outside in a harsh environment which escalates the energy loss due to heat transfer. This study aims to estimate the economically feasible and environmental amiable insulation thickness for HVAC duct using life cycle cost (LCC) and environmental assessment method. It deems five insulation materials for the duct and eight energy sources for chiller operation in selected countries. It uses the design and operating parameters of the duct installed in a renowned pharmaceutical company at Jamshoro/Pakistan. An apropos mathematical model is developed using the collected parameters to calculate optimum insulation thickness (OIT), LCC, maximum energy savings (ES) at minimum payback period (PP) and emission reduction in the insulated duct. It examines the effect of insulation thickness on economic and environmental outcomes using the linear slope line regression method. The results revealed that the use of EP and natural gas has minimum LCC of 13.66 $/m-year (− 0.484), 95% ES (0.248) corresponding to OIT (64.64 mm) with minimum PP of 1.2 years (decreasing at a rate of − 3.69 with insulation thickness). Fuel consumption reduces dramatically (− 0.79) and once OIT is achieved, further increasing insulation thickness has a negligible impact on fuel savings (− 0.041). Higher fuel cost produces maximum ES in the duct and reduces PP of insulation cost in selected countries but they do not affect the variation in fuel consumption and CO, $$\hbox {CO}_{2}$$ and $$\hbox {SO}_{2}$$ emission. Additionally, OIT of EP for duct reduces CO and $$\hbox {CO}_{2}$$ emission at a maximum rate of -0.134 in case LPG (96%) and − 0.484 (95%) in the case of natural gas, respectively.

Piezoelectric energy harvesting from vortex shedding and galloping induced vibrations inside HVAC ducts

This study focuses on the conceptual development, analytical modeling and experimental wind tunnel testing of a high efficiency energy harvesting (EH) device, based on piezoelectric materials, with an application for the sustainability of smart buildings. The device, harvests the airflow inside Heating, Ventilation and Air Conditioning (HVAC) systems, using a piezoelectric component and an appropriate customizable aerodynamic appendix (“fin”) that takes advantage of specific airflow phenomena (vortex shedding and galloping), and can be implemented for optimizing the energy consumption inside buildings. Different relevant aspects are explored in wind tunnel testing, after a thoughtful investigation using analytical methods. Two different configurations for the fin (circular and T-section) are compared. Aspects of the electrical modeling for the EH circuit are provided (including issues on the EH induced damping), and the effective energy harvesting potential of the working prototype device in close-to-real conditions is assessed.

Design and Implementation of a Cloud Enabled Random Neural Network-Based Decentralized Smart Controller With Intelligent Sensor Nodes for HVAC

Building energy management systems (BEMSs) monitor and control the heating ventilation and air conditioning (HVAC) of buildings in addition to many other building systems and utilities. Wireless sensor networks (WSNs) have become the integral part of BEMS at the initial implementation phase or latter when retro fitting is required to upgrade older buildings. WSN enabled BEMS, however, have several challenges which are managing data, controllers, actuators, intelligence, and power usage of wireless components (which might be battery powered). The wireless sensor nodes have limited processing power and memory for embedding intelligence in the sensor nodes. In this paper, we present a random neural network (RNN)-based smart controller on a Internet of Things (IoT) platform integrated with cloud processing for training the RNN which has been implemented and tested in an environment chamber. The IoT platform is modular and not limited to but has several sensors for measuring temperature, humidity, inlet air coming from the HVAC duct and PIR. The smart RNN controller has three main components: 1) base station; 2) sensor nodes; and 3) the cloud with embedded intelligence on each component for different tasks. This IoT platform is integrated with cloud processing for training the RNN. The RNN-based occupancy estimator is embedded in sensor node which estimates the number of occupants inside the room and sends this information to the base station. The base station is embedded with RNN models to control the HVAC on the basis of setpoints for heating and cooling. The HVAC of the environment chamber consumes 27.12% less energy with smart controller as compared to simple rule-based controllers. The occupancy estimation time is reduced by our proposed hybrid algorithm for occupancy estimation that combines RNN-based occupancy estimator with door sensor node (equipped with PIR and magnetic reed switch). The results show that accuracy of hybrid RNN occupancy estimator is 88%.

전동차용 Blow-Down HVAC 덕트 시스템의 유동 균일도 향상을 위한 수치적 연구

A HVAC(Heating Ventilation and Air Conditioning) is adapted to increase the comfort of the cabin environment for train. The train HVAC duct system has very long duct and many outlets due to the shape of a train set. the duct cross section shape is limited by a roof structure and equipments. Therefore, the pressure distribution and flow uniformity is an important performance indicator for the duct system. In this study, the existing blow down type HVAC duct system for a train was supplemented to improve the flow uniformity by applying a design method combining design of experiment (DOE) with numerical analysis. The design variables and the test sets were selected and the performance for each test set was evaluated using CFD(Computational Fluid Dynamics). The influence of each design variable on the system performance was analysed based on the results of the performance evaluation on the test sets. Furthermore, the optimized model, whose the flow uniformity was improved was produced using the direct optimization(gradient-based method). Finally, the performance of the optimized model was evaluated using numerical analysis, and it was confirmed that its flow uniformity has indeed improved.

Automated defect and contaminant inspection of HVAC duct

To sustain acceptable indoor air quality in a building, it is essential to frequently inspect and clean the Heating, Ventilation and Air-Conditioning (HVAC) ductwork. Nowadays the condition inspection is mostly conducted manually according to the video acquired by a pipeline robot. This situation has been significantly resulting in subjectivity, high-cost and inefficiency for HVAC ductwork cleaning and maintenance. In this paper an automatic defect and contaminant inspection system of HVAC duct is developed. The system consists of an infrared-CCD diagnosis device and a novel supervised method for duct inspection by cascading seeded k-means and C4.5 decision tree. The seeded k-means feature-clustering method first partitions the features of training instances into k clusters using Euclidean distance similarity. C4.5 decision tree is then used to refine the decision boundaries by learning the subgroups within the cluster. Finally the decisions of the k-means and C4.5 methods are combined to achieve the inspection results. To improve the classification performance on the minority classes as well as reduce the computation load during the process, Tabu search is employed for the feature selection and the cost-sensitive function is introduced into Tabu search. Experimental results on real-world data sets demonstrate that the proposed system is effective and efficient in inspecting the condition of HVAC ductwork.

Fumigation of a laboratory-scale HVAC system with hydrogen peroxide for decontamination following a biological contamination incident

To evaluate hydrogen peroxide vapour (H2 O2 ) for its ability to inactivate Bacillus spores within a laboratory-scale heating, ventilation and air-conditioning (HVAC) duct system. Experiments were conducted in a closed-loop duct system, constructed of either internally lined or unlined galvanized metal. Bacterial spores were aerosol-deposited onto 18-mm-diameter test material coupons and strategically placed at several locations within the duct environment. Various concentrations of H2 O2 and exposure times were evaluated to determine the sporicidal efficacy and minimum exposure needed for decontamination. For the unlined duct, high variability was observed in the recovery of spores between sample locations, likely due to complex, unpredictable flow patterns within the ducts. In comparison, the lined duct exhibited a significant desorption of the H2 O2 following the fumigant dwell period and thus resulted in complete decontamination at all sampling locations. These findings suggest that decontamination of Bacillus spore-contaminated unlined HVAC ducts by hydrogen peroxide fumigation may require more stringent conditions (higher concentrations, longer dwell duration) than internally insulated ductwork. These data may help emergency responders when developing remediation plans during building decontamination.

빌딩 내 공조 닥트의 무선망 활용을 위한 전파 특성 측정

본 논문에서는 빌딩 내부의 공조 닥트를 이용한 무선 통신망의 전파 특성을 측정하고 분석한다. 공조 피더 구조를 분석하고 전송 모드를 여기할 수 있는 피더 장치를 제작하여 시뮬레이션을 통하여 여기 특성을 분석한다. 2.45 GHz 와이파이 대역에서 실제 건물 내부의 공조 닥트를 통해 송수신되는 전파의 세기를 측정하고, LOS 환경 및 격벽이 있는 사무실 그리고 복도 등 여러 실내 환경 조건에서 전파를 측정하여 닥트 피더 방식과 비교한다. 측정 및 분석 결과를 활용하여 닥트를 이용한 무선망 설계 방법을 제안한다. In this paper, we measure and analyze propagation characteristic of heating, ventilation, and air conditioning(HVAC) ducts within buildings for wireless networks. We analyze the duct structures, implement the feeders exciting propagating modes, and simulate the excitation characteristic. We measure the propagation characteristic of HAVC ducts at 2.45 GHz WiFi band and compare it with that of LOS and partitioned office environments. We propose the design method of wireless network using HVAC ducts based on our results.