Air System Research Articles

AeroSense: Sensing Aerosol Emissions from Indoor Human Activities

The types of human activities occupants are engaged in within indoor spaces significantly contribute to the spread of airborne diseases through emitting aerosol particles. Today, ubiquitous computing technologies can inform users of common atmosphere pollutants for indoor air quality. However, they remain uninformed of the rate of aerosol generated directly from human respiratory activities, a fundamental parameter impacting the risk of airborne transmission. In this paper, we present AeroSense, a novel privacy-preserving approach using audio sensing to accurately predict the rate of aerosol generated from detecting the kinds of human respiratory activities and determining the loudness of these activities. Our system adopts a privacy-first as a key design choice; thus, it only extracts audio features that cannot be reconstructed into human audible signals using two omnidirectional microphone arrays. We employ a combination of binary classifiers using the Random Forest algorithm to detect simultaneous occurrences of activities with an average recall of 85%. It determines the level of all detected activities by estimating the distance between the microphone and the activity source. This level estimation technique yields an average of 7.74% error. Additionally, we developed a lightweight mask detection classifier to detect mask-wearing, which yields a recall score of 75%. These intermediary outputs are critical predictors needed for AeroSense to estimate the amounts of aerosol generated from an active human source. Our model to predict aerosol is a Random Forest regression model, which yields 2.34 MSE and 0.73 r2 value. We demonstrate the accuracy of AeroSense by validating our results in a cleanroom setup and using advanced microbiological technology. We present results on the efficacy of AeroSense in natural settings through controlled and in-the-wild experiments. The ability to estimate aerosol emissions from detected human activities is part of a more extensive indoor air system integration, which can capture the rate of aerosol dissipation and inform users of airborne transmission risks in real time.

Effectiveness of natural ventilation through single-sided window opening in air-conditioning rooms

Since many buildings are not equipped with fresh air systems, many people open windows to allow for natural ventilation while the air conditioner is running. However, prolonged window opening may cause unnecessary energy consumption. Additionally, the diverse ways of window opening lead to significant variations in indoor airflow distribution, consequently impacting ventilation efficiency. Therefore, this study used field experiments and computational fluid dynamics (CFD) to determine the air exchange efficiency and air change rate of single-sided natural ventilation in air-conditioning rooms by fitting the decay curves of tracer gas. CFD simulation was performed using the unsteady Reynolds-averaged Navier-Stokes (RANS) model to examine how window openings affect the room’s air distribution, and the computed indoor CO2 concentration was compared to the corresponding field experiment data. The results show that natural ventilation through the window opening induced constant heat and mass exchange between indoor and outdoor air, which caused extra cooling losses but was globally effective in eliminating indoor contaminants. The air exchange efficiency is influenced to varying degrees by factors such as the air supply register’s position, window opening percentage, and window opening position. The air supply register’s position exerted the most significant impact at 46.45%. Efficient indoor-outdoor air exchange can be achieved by opening windows intermittently. When the window is opened from one side and the opening percentage is 100%, the indoor environment can be improved by opening the window for about 10 min every 39 min for X-direction air supply and about 7 min every 39 min for Y-direction.

Particle Bounce Stick Behavior in the Rotating Frame of Reference

Abstract Particle deposition is a major damage mechanism for gas turbine components, especially in the secondary air system. Predicting the transport and deposition of ingested atmospheric contaminants is of great interest in component-level simulations. Bounce stick models predict deposition upon collision with a wall during Lagrangian particle tracking; they consider a range of physical phenomena, including van der Waals forces and plastic deformation. The effect of the rotating frame of reference on particle collision physics has thus far been neglected in the literature despite the significant centrifugal (CF) loads experienced by many components of interest for deposition studies, for example, turbine blades. The collision physics of the rotating frame are discussed here using low-order models and Monte Carlo style simulations. The present work aims to provide a conceptual framework for the inclusion of CF forces in collision physics. No significant effect was found on the rebound velocities of particles experiencing “worst case” CF forces. However, differences were observed in the sticking probability between concave and convex rotating surfaces, where the CF forces act in opposing directions to either push the particle into the surface or detach it. A force-based analogy of the popular critical velocity model was developed to study the phenomenon. It was used in a Monte Carlo style simulation of a rotor disk, finding that the variation of critical velocity due to CF forces was likely to bias deposition toward concave surfaces. The collision physics of the rotating frame were found to be unintuitive, with complex implications for modeling deposition in gas turbine components. However, they were consequential in determining the distribution of deposition through the system, hence should be included in particle deposition simulations in computational fluid dynamics (CFD).

Novel occupancy detection method based on convolutional neural network model using PIR sensor and smart meter data

Occupancy information, especially the number of occupants, can effectively guide the operation of building systems. Capturing real-time and accurate occupancy information is critical. Passive infrared (PIR) sensors and smart meters have been deployed extensively. To improve the occupancy detection accuracy, this study proposes an innovative occupant number detection approach involving a temporal sequential analysis of occupancy-related data using data fusion from PIR sensors and smart meters with a convolutional neural network (CNN) model. A university office was investigated as a case study. PIR sensors and smart meters were adopted to collect data. And CNN model was established with both various data types and historical data as multi-dimensional model inputs. The model outperformed than traditional ANN models with an improved accuracy by 26.8%. The proposed occupancy detection model was applied to optimize the control strategy of an outdoor air system, which helped to provide comfortable built environment and realize energy savings.

Characteristics and Application Analysis of a Novel Full Fresh Air System Using Only Geothermal Energy for Space Cooling and Dehumidification

To effectively reduce building energy consumption, a novel full fresh air system with a heat source tower (HST) and a borehole heat exchanger (BHE) was proposed for space cooling and dehumidification in this paper. The cooling system only adopts geothermal energy to produce dry and cold fresh air for space cooling and dehumidification through the BHE and HST, which has the advantage of non-condensate water compared to BHE systems integrated with a fan coil or chilled beam. Based on the established mathematical model of the cooling system, this paper analyzed the system characteristics, feasibility, operation strategy, energy performance, and cost-effectiveness of the proposed model in detail. The results show that the mathematical model has less than 10% error in estimating the system performance compared to the practical HST–BHE experimental set up. Under the specific boundary conditions, the cooling and dehumidification capacity of this system increases with the decrease in the air temperature, air moisture content, and inlet water temperature of the HST. The optimal cooling capacity and the system COP can be achieved when the air–water flow ratio is at 4:3. A case study was conducted in a residential building in Shenyang with an area of about 1800 m2. It was found that this system can fully meet the cooling and dehumidification demand in such a residential building. The operation strategy of the cooling system can be optimized by adjusting the air–water flow ratio from 4:3 to 3:2 during the early cooling season (7 June–1 July) and end cooling season (3 August–1 September). As a result, the average COP of the cooling system during the whole cooling season can be improved from 6.1 to 8.7. Compared with the air source heat pump (ASHP) and the ground source heat pump (GSHP) for space cooling, the proposed cooling system can achieve an energy saving rate of 123% and 26%, respectively. Considering that the BHE of the GSHP can be part of the proposed HST–BHE cooling system, the integration of the HST and GHSP for space cooling (and heating) is strongly recommended in actual applications.

Research on the coordinated control of oxygen excess ratio and air pressure for PEMFC's air supply system

The proton exchange membrane fuel cell (PEMFC) air supply system is a complex nonlinear system with strong coupling of air flow and pressure. To avoid oxygen starvation and unstable output performance during rapid load changes, the oxygen excess ratio (OER) and air pressure need to be controlled effectively. To cope with the nonlinearity, coupling and uncertainty of the PEMFC air system, this paper puts forward a coordinated controller regulating OER and air pressure based on the input-output linearization and sliding mode methods. Firstly, a control-oriented third-order model is proposed to describe the dynamic behavior of the air supply system. Secondly, this paper decouples the flow and pressure of the PEMFC air system by using an input-output linearization method to obtain two independent linear subsystems. Moreover, a sliding mode method, effectively coping with the uncertainty of the system model, is designed to regulate the OER and air pressure of the PEMFC, which enhances the robustness of the control system. The overall simulation outcomes show that the proposed controller regulates OER and cathode pressure with smaller root mean square error (RMSE) and mean absolute percentage error (MAPE) compared with the combined proportional integral (PI) and feedforward controller.

Design and Development of Pneumatic Sheet Metal Cutting Machine

It is important to note that in today's industrial era, sheet metal is cut and bent into a variety of shapes to obtain better surface finish and flexibility in manufacturing processes. The use of modern techniques, such as pneumatic sheet cutting machines, has greatly improved the efficiency of sheet metal cutting and bending processes. This review focuses on the reliability, performance, and design simplification of pneumatic sheet cutting machines. Additionally, it examines the energy lost in the pneumatic cylinder while it imparts force on the cutting blade. The energy efficiency of pneumatic and compressed air systems is a critical aspect in the development of sustainable production. The objective of this cross-discipline review is to provide production and life cycle engineering researchers with an update on the state of the art in energy efficiency for pneumatic production and associated compressed air infrastructure.

Influential factors on the energy efficiency of fresh air systems in nearly zero energy buildings

Ensuring precise control of fresh air volume is crucial for minimizing energy usage in nearly zero energy buildings. Research shows that automatic pressure-independent dampers offer a promising solution for maintaining the desired fresh air volume. However, the energy performance of damper-controlled fresh air systems is influenced by multiple factors that have not been thoroughly investigated. This study focuses on examining the impact of influencing factors on the energy efficiency of fresh air systems. Laboratory experiments and field testing were conducted on a typical fresh air system. Subsequently, based on the experimental data, an energy saving model of the damper-controlled fresh air system was developed and validated. The main influencing factors were comprehensively investigated according to the energy-saving model. Results show that damper resistance is one of the main influencing factors on energy efficiency. Pressure-independent damper with a low resistance ratio of less than 48 % are recommended; When the average PM2.5 concentration increases by 1 µg/m3, the energy saving rate decreases by approximately 0.3 %, indicating that pressure-independent dampers are more suitable for use in regions with cleaner air; In the heating season, the energy saving rate increases by approximately 0.075 % when the dry bulb temperature decreases by 1 °C; In the cooling season, the energy saving rate increases by 1.19 % when the wet bulb temperature rises by 1 °C. This study contributes to the development of sustainable building practices by identifying key factors that influencing the energy usage of damper-controlled fresh air systems and further guiding the selection and utilization of pressure-independent dampers in nearly zero energy buildings.

Air leaks fault detection in maintenance using machine learning

PurposeThe objective of this paper is to develop a condition-based maintenance (CBM) scheme for pneumatic cylinders. The CBM scheme will detect two common types of air leaking failure modes and identify the leaky/faulty cylinder. The successful implementation of the proposed scheme will reduce energy consumption, scrap and rework, and time to repair.Design/methodology/approachEffective implementation of maintenance is important to reduce operation cost, improve productivity and enhance quality performance at the same time. Condition-based monitoring is an effective maintenance scheme where maintenance is triggered based on the condition of the equipment monitored either real time or at certain intervals. Pneumatic air systems are commonly used in many industries for packaging, sorting and powering air tools among others. A common failure mode of pneumatic cylinders is air leaks which is difficult to detect for complex systems with many connections. The proposed method consists of monitoring the stroke speed profile of the piston inside the pneumatic cylinder using hall effect sensors. Statistical features are extracted from the speed profiles and used to develop a fault detection machine learning model. The proposed method is demonstrated using a real-life case of tea packaging machines.FindingsBased on the limited data collected, the ensemble machine learning algorithm resulted in 88.4% accuracy. The algorithm can detect failures as soon as they occur based on majority vote rule of three machine learning models.Practical implicationsEarly air leak detection will improve quality of packaged tea bags and provide annual savings due to time to repair and energy waste reduction. The average annual estimated savings due to the implementation of the new CBM method is $229,200 with a payback period of less than two years.Originality/valueTo the best of the authors’ knowledge, this paper is the first in terms of proposing a CBM for pneumatic systems air leaks using piston speed. Majority, if not all, current detection methods rely on expensive equipment such as infrared or ultrasonic sensors. This paper also contributes to the research gap of economic justification of using CBM.

An Engine-Level Safety Assessment Approach of Sustainable Aviation Fuel Based on a Multi-Fidelity Aerodynamic Model

Safety is essential for sustainable aviation fuels (SAFs). However, evaluating SAFs’ impacts on aero-engine safety is challenging because it involves multiple space scales and the strongly coupled relationships of aero-engine components. Aiming at addressing this problem, a model-based approach is proposed to establish the relationship between the fuel-level physical properties and engine-level safety parameters. Firstly, a unified modeling criterion is proposed to consider the interrelations of aero-engine components. Under this criterion, aero-engine secondary air system (SAS) components are included in SAF safety assessment, since they have non-neglectable influences on aero-engine safety. Secondly, this paper proposes a surrogate-based iteration strategy to embed the combustor’s high-dimensional computational fluid dynamics (CFD) model into the aero-engine flow network model. Then, the proposed model-based safety assessment approach is applied to a Fischer–Tropsch hydro-processed synthesized paraffinic kerosine (F-T SPK) safety assessment case. The effects of fuel flow and blending ratio are considered. The results indicate the necessity to evaluate SAFs’ safety at the aero-engine level and consider the influences of SAS components. The proposed model-based approach may provide a preliminary screening before SAFs’ certification tests. This convenience may be beneficial for reducing the cost and accelerating SAFs’ application.

Randomized comparison between a forced air system and warm water bath for resuscitation of neonatal hypothermic calves with or without oral administration of caffeine.

Hypothermia is a cause of neonatal calf death in cold climates. Practical and effective rewarming methods are important for bovine health within affected regions. To compare the rewarming rate and blood analytes (glucose, lactate, and cortisol) of calves resuscitated with forced air with warm water bath, with or without oral administration of caffeine. Twenty healthy neonatal Holstein bull calves. In this randomized, prospective study, calves born healthy and without history of dystocia were cooled to 32°C rectal temperature then thermally resuscitated using either forced air rewarming or warm water bath (40°C) with or without oral administration of caffeine. Rectal temperatures were used to quantify recovery rate. Measurements of glucose, lactate, and cortisol were recorded for every 2°C change in rectal temperature. Rectal temperature decline (0.03°C per minute) and total cooling time (191.0 ± 33.3 minutes) did not significantly differ among treatment groups. Calves were successfully resuscitated to 38°C by either method. Time required to euthermia using warm water was significantly faster (0.1°C per minute; 64.3 ± 17.8 minute; P < .05) than forced air (0.05°C per minute; 123.1 ± 20.0 minutes). Caffeine had no significant effect on resuscitation rate (P = .14; 95% CI, -0.002 to 0.024) in either treatment; however, caffeine was associated with reduced time to euthermia by 8.3 and 10.8 minutes, respectively. Changes in metabolic variables (glucose, lactate, and cortisol), were inversely related to rectal temperature with no statistical significance among rewarming methods. Although warm water submersion is faster, forced air rewarming is an effective alternative for restoration of euthermia.

Aircraft bleed air system fault detection based on MSE of LSTM and informer

Aircraft bleed air system fault detection based on MSE of LSTM and informer

Optimizing the characteristic cooling curves of PCM-integrated thermally active buildings: Experimental and numerical investigations

Phase change materials (PCMs) exploit their cyclic phase change (solidification and melting) to enable latent heat storage. While incorporating them in thermally activated building systems can potentially enhance energy savings and thermal comfort, they can introduce significant challenges to the building energy management system. This work first reports the result of small-scale side-by-side experiments on two thermally active cuboids with and without BioPCMs at different supply water and PCM melting temperatures, as well as irradiance levels. Next, a dynamic model is developed in TRNSYS v18.05 for a typical design of an office space under hot desert climate conditions. The model is then integrated into a multi-objective optimization routine using NSGA-II algorithms to identify the optimal characteristic cooling curves, melting temperatures, and PCM thicknesses that simultaneously minimize energy consumption and maximize the percentage of comfortable hours. The experimental observations of the PCM-integrated cuboid highlighted energy savings between 80.45 and 84.56 %, compared to the reference cuboid, at nearly the same levels of indoor temperatures. The PCM panels reduced the cooling capacity of the radiant floor but also dampened air temperature variations by up to 83.17 %. Besides, higher solar irradiance levels, encountered in desert areas, were found to enhance the cooling capacity by up to 46.8 %. The Pareto solutions highlighted the possibility of achieving acceptable unmet hours of 3.16 % using PCMs and without the need for an assisting air system, compared to 14.1 % without PCMs. Besides, at the same unmet hours of the reference system, the PCMs reduced the total energy consumption and the peak cooling power by 9.75 and 41.2 %, which translates into substantial operation and capital investments, respectively. Moreover, the study demonstrated by example the importance of calibrating the commonly used cooling curves of thermally active buildings when planning for PCM integration.

Development and Evaluation of an Optimized Energy Recovery System from Excess Heat of a Compressed Air System

The aim of this study is to build a bounded optimized energy recovery system from the compressed air system’s excess heat. It is important to concentrate on the use of products that satisfy the requirements for performance and sustainability, as well as the need for energy that will be optimized. Purposive sampling is used to select the respondents, using quantitative research, specifically both descriptive and developmental methods. The researcher utilized a decision support tool developed by Kolaitis et al., (2020) as the primary research instrument of the study. The adopted tool was slightly modified to suit the assessment needs of the developed energy utilization system. All the main criteria components are interpreted as highly sustainable. The researcher utilized log sheets to determine the performance of the study. Finally, paired t-test was used to determine whether there was a significant difference in the performance of the study. The performance of the optimized energy after the implementation of the project was statistically higher than the performance of the optimized energy before the implementation of the project. The researcher concluded that the performance of the optimized energy recovery system from excess heat of a compressed air system after the installation and operation was effective and efficient based on the ratings of respondents and descriptive measures on the log sheet. For this kind of innovation, the manufacturing company with the same equipment should adopt and sustain it for potential energy savings and protect mother nature.

Development of an Automatic Control System for Individual Air Conditioning Equipment Using Machine Learning

Development of an Automatic Control System for Individual Air Conditioning Equipment Using Machine Learning

Performance study of a heat pump fresh air unit based on desiccant coated heat exchangers under different operation strategies

Fresh air system is getting more and more important nowadays. The heat pump fresh air system based on the desiccant coated heat exchanger (DCHE) that can handle the latent and sensible load of fresh air efficiently has a large energy saving potential. To improve the performance of the heat pump fresh air system based on DCHE, in this paper, a control system based on PLC is established and the operation strategies of the system are investigated. An operation strategy including automatic control of the opening of the electronic expansion valve based on the suction superheat of the compressor, control of the switchover period based on the relative humidity of supply air, and control of compressor frequency based on evaporation and condensation temperature is established. By using the optimal operation strategies, the dehumidification rate and COP of the system can reach 4.42 kg/h and 6.2 in summer, compared with the unoptimized strategy it increased 8% and 25%, respectively. The two performance indices can reach to 3.04 kg/h and 6.98, with an increase of 89% and 78%.

Transient simulation and experimental analysis for the response of dual-cycle air-carrying energy radiant diffuse terminal

A novel air-carrying energy radiant diffuse terminal is proposed, and the response of the terminal is investigated by field experiment and numerical simulation. This paper explores the dynamic operation characteristics of the new system to guide the optimal operation of the system. A transient simulation method of three factors (conduction, convection, and radiation) with dual-circulation (air-carrying energy zone and occupied zone) is put forward for the radiant diffuse terminal with a fresh air system. This transient simulation sets up the porous baffle model coupling radiation model concurrently, revealing the dynamic thermal performance for the system's response accurately, quickly, and comprehensively. This method avoids the limits for the complexity of mini porous (Pore size of 1 mm–3mm) geometric models and the transient uncertainty in multiple combination models. The results show that the average error between the convective-conductive model and the convective-conductive-radiative model is about 8% at five different heights. This system has high response performance, which can quickly heat the room while maintaining the comfort requirements of vertical temperature. The radiated heat transfer between the radiant diffuse terminal and the occupied zone is greater than the convective heat transfer (Radiation accounts for 74%). This system has a short response time, high energy efficiency, uniform airflow, and eliminates draught rating. Moreover, the indoor non-uniform transient thermal and humid environments, the thermal comfort, and air quality for the response of the terminal with fresh air system under four different diffuser placements are compared using computational fluid dynamic simulation. The results indicate that introducing heating strategies featuring higher-positioned fresh air inlet and lower-positioned recirculation return air outlet for this system leads to a temperature efficiency increase by 5%, velocity uniformity by 8%, and age of air reduction by 16–50% in human-breathed zone and the response time by 25%, which shows substantial potential for energy savings. The transient simulation and experiments in the paper are beneficial to optimize design parameters and carry out energy-saving applications of operation energy consumption for the response of this terminal with a fresh air system in the future.

Rapid Switching of a C-Series Linear Accelerator Between Conventional and Ultrahigh-Dose-Rate Research Mode With Beamline Modifications and Output Stabilization

PurposeIn this study, a decommissioned C-series linear accelerator (linac) was configured to enable rapid and reliable conversion between the production of conventional electron beams and an Ultrahigh-dose-rate (UHDR) electron beamline to the treatment room isocenter for FLASH radiation therapy. Efforts to tune the beam resulted in a consistent, stable UHDR beamline. Methods and MaterialsThe linac was configured to allow for efficient switching between conventional and modified electron output modes within two minutes. Additions to the air system allow for retraction of the X-ray target from the beamline when the 10MV photon mode is selected. With the carousel set to an empty port, this grants access to the higher current pristine electron beam normally used to produce clinical photon fields. Monitoring signals related to the automatic frequency control (AFC) system allows for tuning of the waveguide while the machine is in a hold state so a stable beam is produced from the initial pulse. A pulse counting system implemented on a FPGA-based controller platform controls the delivery to a desired number of pulses. Beam profiles were measured with Gafchromic film. Pulse-by-pulse dosimetry was measured using a custom electrometer designed around the EdgeTM diode. ResultsThis method reliably produces a stable UHDR electron beam. Open field measurements of the 16cm (FWHM) gaussian beam saw average dose rates of 432Gy/s at treatment isocenter. Pulse overshoots were limited and ramp up was eliminated. Over the last year, there have been no recorded incidents that resulted in machine downtime due to the UHDR conversions. ConclusionStable 10MeV UHDR beams were generated to produce an average dose rate of 432Gy/s at the treatment room isocenter. With a reliable pulse-counting beam control system, consistent doses can be delivered for FLASH experiments with the ability to accommodate a wide range of field sizes, source-to-surface distances, and other experimental apparatus that may be relevant for future clinical translation.

Comparison of surface tension, density, viscosity and contact angle of ethyl oleate to those of ethanol and oleic acid

Taking into account extensive practical application of ethyl oleate (EO) some of its physicochemical properties were determined and compared to those of ethanol (ET) and oleic acid (OA). For this purpose the surface tension, density, viscosity and contact angle of EO, ET and OA were measured. The contact angle was measured on the polytetrafluoroethylene (PTFE), poly(methyl methacrylate) (PMMA), steel and glass in the solid–liquid–air system. Based on the results of the surface tension and contact angle of ET, EO and OA on PTFE and PMMA the Lifshitz-van der Waals component as well as electron-acceptor and electron-donor parameters of the acid-base component of surface tension of these liquids were determined. For this determination the van Oss et al. method was applied. This method was carefully analyzed in terms of its usefulness for the systems studied by us. The components and parameters of the ET, EO and OA surface tension were analyzed with regard to their molecular structure. Based on the molecular structure and on the length of bonds and contact angle between them the size of the molecules and their contactable area were determined.

A Review of Energy Overconsumption Reduction Methods in the Utilization Stage in Compressed Air Systems

Pneumatic systems use the energy of compressed air to carry out manufacturing automation processes through the implementation of complex handling and motion tasks. However, these systems are energy intensive: it is estimated that pneumatic systems in manufacturing plants consume approximately 10% of all electricity consumed in the industrial sector. At the same time, the energy efficiency of the whole pneumatic system is observed to be 6–10%, due to the compression process, oversizing, and overconsumption. There are numerous solutions in the literature focusing on improving efficiency at the compression stage of utilization; however, for the utilization stage, there is a lack of systematization and grouping of these solutions. The following review will summarize current knowledge about the utilization stage and methods for improving oversizing and energy overconsumption. In addition, a method of exergy analysis for pneumatic systems will be presented, which is a very useful tool to assess the efficiency of these systems.