Air Volume Research Articles

AI-driven ventilation control policy proximal optimization coupled with dynamic-informed real-time model calibration for healthy and sustainable indoor PM2.5 management

Indoor air quality (IAQ) is an important factor for determining quality of life and urban sustainability. In underground subway stations, improving IAQ through ventilation systems remains challenging due to the complexity and nonstationary nature of IAQ resulting from diverse influential factors such as subway schedules, passenger volume, and outdoor air quality (OAQ). Therefore, this study aimed to develop a novel artificial intelligence (AI)-driven ventilation system for healthy and sustainable IAQ management in subway stations. First, an IAQ mechanistic model coupled with genetic algorithm (GA)-driven rolling-horizon calibration was developed from the collected IAQ big dataset, and global sensitivity analysis was then employed to identify the dominant variables in IAQ dynamics. Subsequently, proximal policy optimization (PPO), one of the reinforcement learning (RL) algorithms, was employed to control the ventilation system in both the lobby and platform areas of a subway station. The results demonstrated that the IAQ mechanistic model can capture IAQ dynamics with acceptable modeling performance, achieving around 19 % of mean absolute percentage error (MAPE). Furthermore, the PPO-driven ventilation control system can reduce energy consumption by around 22 % while maintaining IAQ at an acceptable level.

Stable Air Retention under Water on Artificial Salvinia Surfaces Enabled by the Air Spring Effect: The Importance of Geometrical and Surface‐Energy Barriers, and of the Air Spring Height

AbstractSuperhydrophobic surfaces that can remain dry under water have a high potential as nontoxic antifouling coatings or for drag‐reducing ship coatings. The Salvinia effect leads to impressive stable air layers on underwater submerged floating plants Salvinia, decisively determined by the hydrophilic tips of the otherwise hydrophobic Salvinia hairs (Salvinia paradox). The water adheres to these hydrophilic tips, stabilizing the water–air interface. An even more important contribution to the stability of the air layer is provided by the air spring, which is formed by the air volume bound by the hydrophilic leaf edge and the leaf base. Using an artificial Salvinia model with hydrophobic pillars (syn‐trichomes), how the stability against pressure changes in water depends on the height of the artificial hair is systematically shown: a reduction of the air spring height from 3 mm to 300 µm increases the stability against negative pressure by 500% from 72 to 380 mbar. Thicker air layers react much more strongly when subjected to overpressure (1000 mbar). It is also shown that the presence of a boundary is essential for the function of the air spring: removing the limiting hydrophilic edge around the hydrophobic air spring reduces the stability against negative pressure by 300%.

Influence of Long Pressure and Short Suction Ventilation Parameters on Air Flow Field and Dust Migration in Driving Face

A combination of similar tests and numerical simulation was used to study the distribution of the air flow field and the dust field in the driving face under the conditions of long pressure and short suction ventilation. The results show that the air flow field is divided into return, jet, and vortex zones. When the distance (L) is 1.6 m, the wind speed (Va) is 8 m/s, and the ratio of pumped air volume to pressure air volume (Q) is 0.8, the total and exhaled dust concentration (Td, Rd, Tp, and Rp) at the driver’s and pedestrian’s position were the lowest. According to the grey correlation analysis, the importance of factors affecting Td and Tp is ranked as L > Va > Q, Rd is ranked as Va > L > Q, and Rp is as follows: Va > Q > L. The increase in Va and the decrease in L have a significant effect on the expulsion of exhaled dust.

Comprehensive performance evaluation of HVAC systems integrated with direct air capture of CO2 in various climate zones

Direct Air Capture (DAC) is a rapidly evolving technology that extracts CO2 directly from ambient air. This study presents a comprehensive performance evaluation of integrating DAC in HVAC systems, which can reduce indoor CO2 concentration and improve energy efficiency of HVAC systems. The DAC equipment is modeled in Modelica based on isotherm and thermodynamic equations, and pressure drop curves of the CO2 sorbent described in literature. The model is validated with data from the literature, and then integrated into a typical HVAC system available in Modelica Buildings library. The HVAC system is a Variable Air Volume (VAV) with reheater system for a one-floor office building with standard ASHRAE 2006 control sequences. Demand control ventilation strategies are designed to reduce the outdoor air flowrates when indoor CO2 concentrations are lower than the threshold, which is to maximize the benefits of integrating DAC. Four cases are proposed to assess the impacts of integrating DAC and DCV in HVAC systems in 8 different ASHRAE climate zones in the USA. The results show that by integrating DAC unit into the HVAC system, the average indoor CO2 concentration can be significantly reduced by over 45 % against the baseline without a DAC unit. By integrating DCV, 0.39–21.66 % of annual energy savings and 226–9539 kg carbon emissions reduction are observed across different climate zones. The highest energy savings are found to be achieved with cold climatic conditions while the lowest energy savings occur with favorable weather.

Development of a methodology for studying microbiological contamination of office indoor air by analyzing air handling unit filters - Application to a low-energy building

Bioaerosols can alter the air quality, affecting differently people depending on their health status. Methods to sample bioaerosols are limited in terms of sampling time and air volumes. This study evaluated a new methodology to sample airborne microorganisms in buildings, using the air handling unit (AHU) filters and filtration media sampling discs (FMSD). Filtration media with FMSD of different natures were tested at the laboratory, and characterized by their air permeability, particle collection efficiency and the airflow distribution on their surface. Filtration media with FMSD of the same nature had best properties with a sampling particle efficiency of the FMSD of 50 %. This sampling methodology was applied on a building AHU, and FMSD were collected each month during one year. Airborne microorganisms collected by the FMSD were analyzed by culture and nucleic acids based methods (qPCR and Next-Generation sequencing). FMSD methodology gave results for all of those identification methods. Most of the bacteria orders identified by 16 S sequencing were Rhodobacterales (Paracoccus), Pseudomonadales and Cyanobacteria. For fungi, the most represented orders were Agaricales, Polyporales and Hymenochaetales. This sampling methodology has also made it possible to detect small size airborne microorganisms like viruses including two Coronaviruses. This study has shown the potential of using AHU filters to sample the airborne microorganisms in buildings.

Investigation and optimization heat and humidity environmental control model in construction tunnels: A multifactorial approach incorporating ventilation parameters and hot water quantity

The high rock temperature and hot water influx in the surrounding area of the tunnel construction cause an excessively humid and environment high temperature inside the excavated area of the tunnel, necessitating urgent investigations into the environmental characteristics coupled with these factors and optimizing the control scheme of the construction environment. The on-site data of the tunnel temperature, humidity fields, and external environmental parameters have been collected, along with statistical analysis of the amount of the heat in the resource at the excavation face during the construction period. Subsequently, a three-dimensional numerical model coupling with high rock temperature, hot water, and ventilation was established. Based on the site monitoring data comparison, it was found that the average errors of temperature and humidity field values in the numerical simulation were 4.7 % and 7.1 %, respectively. By introducing the Heat Index (HI), the tunnel environmental characteristics under different conditions were analyzed, showing a linear relationship between the maximum HI at the excavation face and the two following features which are: the temperature-humidity of the input wind, and the hot water quantity. At the same time the air volume exhibited a quadratic relationship. Furthermore, by utilizing multivariate functions to fit the research results, the results show that the maximum HI under various conditions can be predicted. In addition, ultimately establishing an environmental safety assessment model was effective in incorporating multiple factors like input wind temperature, humidity, air volume, and hot water quantity for construction tunnels.

Research and design of low-noise cooling fan for fuel cell vehicle

Abstract The main noise source of fuel cell vehicles comes from the cooling vehicle, which has the characteristics of high voltage and large air volume. However, the large air volume makes the fan noise level significantly increase, reaching about 70dB. Even if the car adopts a variety of physical noise reduction methods, the noise level inside the car is still high, seriously affecting the passenger ride experience. In recent years, related research combined with bionic technology to improve the fan blade by designing a new shape structure, so that it has similar characteristics to some organisms to achieve the purpose of noise reduction. In this paper, ANSYS-CFX software is used to simulate the fan efficiency and noise level under different blade numbers, predict its performance, and optimize its structure.

Supervised learning based iterative learning control platform for optimal HVAC start-stop in a real building context

In comparison to commonly employed iterative learning controls and reinforced learning techniques in model predictive controls for buildings, a supervised learning based iterative learning control platform that is more suitable and computationally efficient for real-world applications is proposed. The proposed control system relies on a data-driven model and utilizes the Random Forest algorithm to develop an HVAC start-stop model; this model considers only a limited system history period that can influence the current state, thus avoiding prolonged learning periods and time-consuming exploration. Specifically, within the current timeframe, the HVAC start-stop model learns from daily errors, and start and stop times “labeled as adjusted” accordingly.The proposed platform was validated against the TRNSYS baseline of a research facility, which was meticulously calibrated with actual measurements. In comparison with the convention, the proposed approach yielded significant energy savings of 6.5–7.6 % in HVAC annual energy consumption, while maintaining temperature comfort for approximately 97–98 % of the annual operating days. Notably, by implementing supply air volume ramp-up in conjunction with HVAC optimal start control, temperature comfort for up to 99 % of the annual operating days was achieved, along with a notable 9.7 % reduction in HVAC annual energy consumption.

A comparative study on the combustion of lean NH3/H2/air ignited by pre-chamber turbulent jet ignition modes

Internal combustion engines fueled with mixtures of hydrogen (H2) and ammonia (NH3) are potential power devices for reducing carbon emissions. To improve the ignition and combustion performance of NH3/H2, turbulent jet ignition (TJI) can be used. This study aims to investigate NH3/H2/air combustion under TJI modes at low equivalence ratios. Considering that the adoption of the scavenging system is beneficial for improving the reactivity of the pre-chamber, the effect of active TJI with scavenging is also explored. The results show that injecting 1.2 times the initial mixture volume of air is optimal for scavenging, and the scavenging effect becomes significant as the NH3 fraction increases. Using conventional active TJI and active TJI with scavenging effectively improves ignition performance and flame propagation, reducing sensitivity to the equivalence ratio compared to passive TJI mode. Although the adoption of active TJI modes improves the lean flammability limit of NH3/H2, weak flame propagation may occur in the early stage of combustion under ultra-lean conditions. Appropriately increasing the injection of auxiliary H2 can effectively improve this phenomenon.

Precision Control for Room Temperature of Variable Air Volume Air-Conditioning Systems with Large Input Delay

A large input delay, parametric uncertainties, matched disturbances and mismatched disturbances exist extensively in variable air volume air-conditioning systems, which can deteriorate the control performance of the room temperature and even destabilize the system. To address this problem, an adaptive-gain command filter control framework for the room temperature of variable air volume air-conditioning systems is exploited. Through skillfully designing an auxiliary system, both the filtered error and the input delay can be compensated concurrently, which can attenuate the effect of the filtered error and the input delay on the control performance of the room temperature. Then, a smooth nonlinear term with an adjusted gain is introduced into the control framework to compensate for parametric uncertainties, matched disturbances and mismatched disturbances, which relieves the conservatism of the controller gain selection. With the help of the Lyapunov theory, both the boundedness of all the system signals and the asymptotic tracking performance for the room temperature can be assured with the presented controller. Finally, the contrastive simulation results demonstrate the validity of the developed method.

Experimental and numerical studies on hydrogen leakage and dispersion in underground parking garages: Impact of leakage direction on safety considerations

Hydrogen leakage in confined spaces poses significant safety risks in hydrogen energy applications, potentially leading to fires and explosions. This paper focuses on the accident scene of hydrogen leakage and dispersion in underground parking garages. A medium-scale model (1/10) of an underground parking garage is designed and built to study the characteristics of the dispersion of hydrogen leaked from hydrogen fuel cell vehicles (HFCVs) in underground garages using experimental and numerical simulation methods. This paper focused on analyzing the dispersion characteristics of hydrogen leaked from hydrogen fuel cell vehicles (HFCVs) within these environments, with particular attention given to the influence of leakage direction—upward, horizontal, and downward—on hydrogen concentration distribution over space and time. For instance, it was observed that under equivalent flow rates, upward leakage tends to result in higher hydrogen concentrations at the leakage site. Conversely, downward leakage promotes wider hydrogen diffusion around the source, particularly evident at higher flow rates. Horizontal leakage, comparatively, exhibits lower risk due to greater air volume absorption. Complementing the experimental data, numerical simulations revealed consistent patterns in hydrogen diffusion. Specifically, the simulations illustrated a cyclic accumulation-diffusion-accumulation process. Notably, vertical upward leakage demonstrated the largest volume of regions exceeding a 4 % hydrogen volume fraction, whereas vertical downward leakage resulted in the greatest volume of regions surpassing an 18.3 % hydrogen volume fraction. This disparity arises from hydrogen accumulation beneath the vehicle in cases of vertical downward leakage. Conversely, regions of high concentration induced by horizontal leakage were the smallest. The study offers valuable insights for the design and construction of HFCVs and parking facilities, providing a theoretical framework for enhancing safety measures.

Air pollutant removal performance using a BiLSTM-based demand-controlled ventilation method after tunnel blasting

Efficient tunnel ventilation is essential for ensuring construction safety and protecting personnel health during tunnel construction. This study proposes a demand-controlled ventilation (DCV) method on the basis of deep learning algorithm to both improve pollutant removal efficiency and reduce energy consumption. The DCV method utilizes a two-layer bidirectional long short-term memory algorithm (BiLSTM) to predict pollutant concentrations. The air volume is dynamically adjusted based on the gaseous pollutant removal requirements. The coefficient of ventilation performance (COVP) is proposed to evaluate the performance of two ventilation methods (DCV and constant air-volume ventilation (CAV)) through computational fluid dynamics (CFD) simulations. The results show that the DCV results in a lower maximum average CO concentration and higher removal efficiency in the heading area (372.3 mg/m3) than the CAV does (404.1 mg/m3). The fan's energy consumption of DCV is 64.6% lower than that of CAV during a 1000 s ventilation period. The COVPs for both methods exhibit temporal variation and achieves their maximums (2.25 for DCV and 0.741 for CAV) after reaching the constraint conditions (air volume threshold). The DCV method expedites pollutant elimination, reduces construction waiting period, and minimizes energy consumption, providing a novel application of a deep learning algorithm in construction engineering.

Evaluating edge joint preparation impact on penetration depth in laser-arc hybrid welding

Nowadays, conventional welding technologies such as submerged arc welding (SAW) are still used in most heavy-steel industries. This type of traditional technology means that welding takes up a large part of the productive time. As a solution to this problem, there are welding methods, such as Laser-Arc Hybrid Welding (LAHW), that have the potential to reduce the cost of manufacturing large steel structures. This is possible due to the reduced number of weld passes required to join thicker steel sections, as large thicknesses can be welded in one or a few passes.A problem with LAHW is achieving satisfactory quality. For this reason, it is essential to study the starting conditions, e.g. edge joint preparation. The target of this research work is to find out the relationship between the penetration value of the weld bead obtained and the edge joint preparation. The evolution of the molten pool and the behavior of the molten material in the joint is discussed for the different edge joint preparation configurations. The effect of the roughness is that it affects the wetting of the molten material in the joint, which would affect the penetration result, together with the gap and air volume gap used in the joint. Cut-wire is also used in the research, in samples that presented a larger air volume gap. The behavior of the molten metal inside the joint in this case is also discussed. In addition, the quality of the weld beads has also been determined by making macrographs, microstructural analysis, X-ray, microhardness profiles, tensile test and Charpy test. Some pores and cracks have been found, although destructive tests show adequate behavior of the weld bead. It is possible to elucidate from the findings that as the roughness, gap and/or air volume gap of the edge joint increases, the penetration value obtained increases. Cut-wire samples obtained full penetration.

Energy saving of vacuum-based membrane dehumidification with indirect evaporative cooling in a low sensible-heat-ratio building

In hot and humid climates, dehumidification generally consumes more energy than cooling, and conventional mechanical vapor compression system is not efficient for dehumidification. Vacuum-based membrane dehumidification system have been developed as a more environmentally friendly alternative for dehumidification due to non-refrigerant system and isothermal dehumidification process. In this study, a novel hybrid air conditioning system that combines vacuum-based membrane dehumidification with an indirect evaporative cooler for pre-cooling is proposed to achieve efficient air conditioning in building with low sensible heat ratio. The energy performance of the proposed system is investigated by detailed thermodynamic simulations and compared with conventional variable air volume (VAV) system and indirect evaporative pre-coolers combined VAV system. The simulation results show that when the average sensible heat ratio of the space is 0.73 and the COP of the vacuum-based membrane dehumidifier is 1.0, the proposed system can reduce energy consumption by 16.1 % compared to conventional VAV system and by 6.4 % compared to indirect evaporative pre-cooler combined VAV system during the cooling season. The energy performance of the proposed system is significantly affected by the sensible heat ratio of the building and the energy efficiency of the vacuum-based membrane dehumidifier. When the COP of the vacuum-based membrane dehumidifier reaches 2.0, the proposed system can achieve an energy savings of 48.2 % compared to conventional VAV system.

Development and application of closed-loop-oriented intelligent control system for blast furnace air volume addition or reduction

Adjusting the upper and lower parts is an important means to ensure stable operation of blast furnaces. It is a common operation method to adjust the smelting state of the blast furnace by adjusting the air volume. Most of the domestic blast furnace air volume increase and decrease operations are confirmed by manual experience, and it is difficult to realize intelligent automatic control. This paper presents an intelligent control system for regulating air volume in blast furnaces, based on operational logic, expert knowledge, fundamental theories, and other relevant information. The system enables automatic analysis of the blast furnace's state and intelligent reasoning of the foreman's operational methods, laying the foundation for achieving closed-loop control. The system unifies the control philosophy and stabilizes the control methods for regulating air volume in blast furnaces. This achieves standardization of operation and proceduralization of cause analysis. The system enhances adaptability by creating an information feedback mechanism, increasing acceptance among blast furnace operators, and continuously resolving various anomalies in practical applications. The system currently maintains a true hit rate of over 95%, enabling effective reduction of operational misjudgments, intelligent control of airflow adjustment, and promotion of stable and smooth blast furnace operation.

Effects of Hollowed Neck Designs on Sound Radiation and Loudness of Baglama

This study investigated the effects of two experimental (patented) neck designs on sound radiation and the perceived loudness of the baglama, a stringed instrument. The primary hypothesis of this research is that compared to traditional neck, the experimental neck designs increase the stringed instrument's air volume and vibrating surface area, thereby contributing to radiation efficiency and perceived loudness. Sound radiation analysis based on acoustic modal analysis and psychoacoustic analysis were conducted. First, sound radiation measurements were made in an experimental setup. The data were then examined using the Frequency Response Function (FRF). The results revealed that the experimental necked baglamas’ sound radiated better than the traditional one. Second, listening (N=38) and playability (N=26) tests were conducted in focus group interviews. The participants listened to or played traditional and experimental necked baglamas and rated their loudness. The Friedman and Wilcoxon signed-rank test on the scores indicated that the participants perceived the experimental necked baglamas as significantly louder than the traditional one. Most participants stated that the experimental necked baglamas sounded higher and had better quality than the traditional one. Psychoacoustic findings corroborated the results of sound radiation analysis.

Performance analysis of a fresh air and indoor air co-treatment parallel-loop exhaust air heat pump for buildings

To reduce building energy consumption and solve the problem that the power of traditional exhaust air heat pump is limited by exhaust air volume, an innovative fresh air and indoor air co-treatment parallel-loop exhaust air heat pump (CPEAHP) was proposed, and three operating modes of the CPEAHP were studied. The results showed that the co-treatment mode not only increased the flexibility of system regulation, but also improved the heating performance of the system at low temperature in winter. When the winter outdoor temperature was higher than 0 °C, the temperature efficiency of the co-treatment mode was higher than 100 %, and that efficiency was higher than 100 % under all outdoor temperature conditions in summer. At a winter outdoor temperature of −15 °C, the co-treatment mode could increase the temperature of fresh air by 20.4 °C and increase the temperature of indoor air by 3.1 °C, the heating capacity of the system was 6.3 kW and the COP was 8.7 at this time. At an outdoor temperature of 42 °C in summer, the co-treatment mode could decrease the temperature of fresh air by 22.8 °C and decrease the temperature of indoor air by 3.1 °C, the cooling capacity of the system was 7.3 kW and the COP was 4.5 at this time. These results demonstrated the excellent performance of CPEAHP system, and the application of CPEAHP system was expected to reduce building energy consumption and promote carbon neutrality in the construction industry.

Centrifuge modeling-of-models investigation on earthquake-induced excess pore pressure behavior of silty sand

Two centrifuge experiments conducted at Rensselaer Polytechnic Institute (RPI) aimed to evaluate the effectiveness of the used centrifuge scaling laws and validate results obtained within the project, related to the liquefaction behavior of silty sand soils under simulated field drainage conditions. These experiments, replicating a 5-m thick silty sand layer under 1 atm overburden pressure and featuring a double drainage condition, were performed at two different centrifugal accelerations. Due to the difficulties encountered in saturating silty sand, this paper presents a bottom-up saturation method, verified through assessments of remaining air volume after saturation. Despite differing g-levels, the tests consistently demonstrated similar behaviors in terms of acceleration, pore pressure buildup and dissipation, and stress-strain responses, validating the saturation and modeling technique for silty sand.

Numerical and experimental investigation of a single-body PVT using a variable air volume control algorithm

Photovoltaic thermal (PVT) collectors that can achieve maximum efficiency from solar irradiation can be critical concepts for meeting energy demand in residential applications. Even though there is much research on increasing heat transfer, multifunctional designs that provide homogeneous results are limited. This study explores the production of electricity and hot air from a novel design of a PVT. A new perforated copper plate design has been proposed to achieve maximum efficiency by providing homogeneous cooling in the PVT. Firstly, numerical analysis of this design was performed using Ansys Fluent software, then tested experimentally. The highest and average electrical and thermal efficiency of PVT are obtained as 17.62 %, 15.63 %, and 76.75 %, 43.68 %. In experiments conducted under winter conditions, the maximum temperature value in the PVT was measured as 41.54 °C. Moreover, the payback period of the PVT system was calculated as 6.1 years. The proposed PVT collector can be used as a new model for integrating solar energy in buildings with almost zero energy. Considering the eco-design, this PVT design can contribute net positive carbon, ecological footprint, and green manufacturing.

Dynamic behaviour and energy dissipation of offline air pockets in transient pipe flows

ABSTRACT The traditional one-dimensional (1D) model often fails to accurately predict the dynamic pressure response of large offline air pockets during transients, due to a lack of comprehensive understanding of the underlying mechanisms of transient interaction with offline air pockets. This study investigated dynamic behavior and energy dissipation of offline air pockets through experiments and numerical models. Experimental pressure responses were predicted using a 1D-3D coupling model, which presented superior performance compared to traditional 1D model. The 1D-3D coupling model was further utilized to investigate the air-water interface, internal energy and turbulence distribution of offline air pockets. The results reveal that the stability of the air-water interface depends on the decelerating distance of the jet in offline tube, explaining the instability phenomenon with lower water levels observed in experimental snapshots. The internal energy pattern suggests different energy dissipation mechanisms compared to the inline air pockets. The distribution of turbulence intensity and effective thermal conductivity indicates significant additional energy dissipation at the inlet and outlet of offline neck. By incorporating a minor head loss term for offline neck into traditional 1D model, the pressure response aligns well with the results obtained from 1D-3D coupling model under different flow rates and air volumes.