Air Volume Research Articles

Application of graph neural networks to predict explosion-induced transient flow

We illustrate an application of graph neural networks (GNNs) to predict the pressure, temperature and velocity fields induced by a sudden explosion. The aim of the work is to enable accurate simulation of explosion events in large and geometrically complex domains. Such simulations are currently out of the reach of existing CFD solvers, which represents an opportunity to apply machine learning. The training dataset is obtained from the results of URANS analyses in OpenFOAM. We simulate the transient flow following impulsive events in air in atmospheric conditions. The time history of the fields of pressure, temperature and velocity obtained from a set of such simulations is then recorded to serve as a training database. In the training simulations we model a cubic volume of air enclosed within rigid walls, which also encompass rigid obstacles of random shape, position and orientation. A subset of the cubic volume is initialized to have a higher pressure than the rest of the domain. The ensuing shock initiates the propagation of pressure waves and their reflection and diffraction at the obstacles and walls. A recently proposed GNN framework is extended and adapted to this problem. During the training, the model learns the evolution of thermodynamic quantities in time and space, as well as the effect of the boundary conditions. After training, the model can quickly compute such evolution for unseen geometries and arbitrary initial and boundary conditions, exhibiting good generalization capabilities for domains up to 125 times larger than those used in the training simulations.

A novel dual-wheel air-conditioning system operating strategy in different seasons

The application of solid desiccant air-conditioning systems can significantly reduce building energy consumption. Previous studies have focused on innovating the integration of solid desiccant air-conditioning systems (DACS) to improve dehumidification performance in summer. In this paper, a novel DACS is proposed, which can humidify the supply air in winter based on satisfying the dehumidification demands in summer. It can satisfy the year-round humidity requirements of domestic housing with significant savings in humidification costs. Furthermore, the operating strategy of the novel DACS is proposed, particularly for winter humidification conditions. It is adaptable as well as cost-effective compared to traditional operating strategies. The dehumidification/humidification capacity of the core component, polymer desiccant wheel, and the variation of temperature rise/temperature drop are investigated under different variations of parameters, including air temperature, air humidity, air volume flow rate, and wheel speed. The results show that with the increase of supply air mass flow from 0.6 kg/s to 1.9 kg/s, the power consumption of the system only increases by 9.5 kW. In winter, when the supply air temperature decreases from 8 °C to 1 °C, the power consumption increases by 7.2 kW, but in summer, when the temperature of the supply air increases by 7 °C, the power consumption of the system decreases by 7.0 kW. The power consumption of the system varies greatly when the humidity of the supply air is less than 17 g/kg, conversely, the power consumption of the system showed a negative trend. The analysis demonstrates the effective performance of the proposed system under varying climatic conditions.

Study on CO dispersion characteristics and isolation door control technology of refuge chamber in coal mine

To investigate the dispersion process of the underground toxic gas carbon monoxide (CO) into the refuge chamber during a mine disaster and enhance the survival rate of trapped miners, a simplified model of an underground refuge chamber and the main roadway was constructed. The impact of temperature and pressurized air volume on CO dispersion into the refuge chamber has been examined through both analog experiments and numerical simulations, and the reliability of the simulation results was verified. The results indicate that CO dispersion into the refuge chamber through the top of the protective isolation door occurs when the temperature in the refuge chamber is lower than that of the toxic gas. When the temperature of the toxic gas is higher, it tends to enter the refuge chamber through the bottom of the protective isolation door. The evolution of CO concentration in the transition chamber can be divided toxic survival chamber can be categorized into a sudden decline stage and a stable stage. And a flexible isolation door designed to control the entry of toxic gases into the refuge chamber was implemented, and its impact on CO dispersion has been compared and analyzed. When the temperature of the main roadway is 50 °C and the temperature of the refuge chamber is 20 °C, the required pressurized air volume to maintain the CO concentration within the safe threshold (24 ppm) is reduced to 69.6% of that needed without the isolation door, thereby significantly reducing the infiltration of harmful gases from the main roadway into the refuge chamber.

Prediction of the Temperature Field in a Tunnel during Construction Based on Airflow–Surrounding Rock Heat Transfer

It is important to determine the ventilation required in the construction of deep and long tunnels and the variation law of tunnel temperature fields to reduce the numbers of high-temperature disasters and serious accidents. Based on a tunnel project with a high ground temperature, with the help of convection heat transfer theory and the theoretical analysis and calculation method, this paper clarifies the contribution of various heat sources to the air demand during tunnel construction, and reveals the important environmental parameters that determine the ventilation value by changing the construction conditions. The results show that increasing the fresh air temperature greatly increases the required air volume, and the closer the supply air temperature is to 28 °C, the more the air volume needs to be increased. The air temperature away from the palm face is not significantly affected by changes in the supply air temperature. Adjusting the wall temperature greatly accelerates the rate of temperature growth. The supply air temperature rose from 15 to 25 °C, while the tunnel temperature at 800 m only increased by 1.5 °C. Over a 50 m range, the wall temperature rose from 35 to 60 degrees Celsius at a rate of 0.0842 to 0.219 degrees Celsius per meter. The total air volume rises and the surface heat transfer coefficient decreases as the tunnel’s cross-section increases. For every 10 m increase in the tunnel diameter, the temperature at 800 m from the tunnel face drops by about 0.5 °C. Changing the distance between the air duct and the tunnel face has little influence on the temperature distribution law. The general trend is that the farther the air duct outlet is from the tunnel face, the higher the temperature is, and the maximum difference is within the range of 50 m~250 m from the tunnel face. The maximum difference between the air temperatures at 12 m and 27 m is 0.79 °C. The geological structure and geothermal background have the greatest influence on the temperature prediction of high geothermal tunnels. The prediction results are of great significance for guiding tunnel construction, formulating cooling measures, and ensuring construction safety.

Thermal performance of counterflow wet cooling tower filled with inclined folding wave packing: An experimental and numerical investigation

Improve the heat transfer performance of cooling tower packing in the field of energy saving and environmental protection is of great significance, this study proposes a kind of inclined folding wave packing, using experimental research and numerical calculations combined method to study the heat and mass transfer characteristics of inclined folding wave packing, the results show that: inlet wind speed rises, the cooling tower approximation reduced from 4.38 °C to 2.78 °C; when the gas to water mass ratio increases from 0.322 to 1.019, the cooling number from 1.115 to 1.754; when the gas to water mass ratio of 0.54, the height of the packing from 0.915 m to 1.830 m, the cooling number from 1.15 to 1.64, the height of the packing to enhance the channel of the gas-liquid heat transfer effect. Compared with the traditional ramp packing, the cooling efficiency of the developed inclined folded wave packing is improved by 15.32 %. Combined with the actual engineering test found that the packing height can be increased to reduce gas to water mass ratio and air volume requirements, up to 28 % of the air volume can be saved. The motor output power of 1.830 m high inclined folding wave packing in actual operation is 0.268 kW, compared with 0.915 m high inclined folding wave packing, the difference in energy consumption is 0.246 kW. Inclined folding wave packing can not only improve the overall performance of the cooling tower, but also significantly reduce energy consumption, which can guide the engineering practice.

Cooling effect and parameter analysis of applying heat insulation layer to tunnel regionalization in construction period based on geothermal level

The construction of high geothermal tunnels presents significant difficulties due to the abnormal rock temperature gradients, including designing a reasonable and cost-effective insulation layer as well as effective cooling measures. In this study, the rock temperature distribution, environmental temperature, and lining surface temperature of the tunnel during the construction period were analyzed through field surveys. A numerical simulation model considering ventilation and heat transfer dynamics was established based on the geothermal measurements and construction characteristics of this tunnel. After validating the 3D numerical model, the effects of installing heat insulation layers according to geothermal levels on the tunnel temperature field control were investigated. Additionally, the impacts of different insulation layer thermal conductivities (λi), ventilation air volume (Wa), and duct thermal conductivities (λd) were analyzed. The results indicate: (1) The comparison of temperature fields in tunnels with insulation layers, which is applied in the range of the rock temperature above 50 °C and without insulation layers was made. The temperature near the excavation face (TAm-1) decreases by up to 0.3% (0.5 °C), tunnel environment temperature with insulation layer applied (TAm-2) decreases by up to 4.2% (2.1 °C), the secondary lining temperature (TSec-lining) decreases by up to 10.5% (4.6 °C), and the wind temperature of air duct outlet (TAir-duct) decreases by up to 0.7% (0.5 °C). (2) The length of the insulation layer increases to the full length of the tunnel, TAm-1 continues to decline by only 0.4°C, TAm-2 by 0.5 °C, TSec-lining by 0.9 °C, and TAir-duct by 0.1 °C, which shows that it is the most economical and reasonable to apply the insulation layer only in the tunnel area where the rock temperature is higher than 50 °C. (3) As λi increases, both the tunnel environment and secondary lining temperatures exhibit linear increases, while increasing Wa and λi cause quadratic decreases and increases in tunnel temperature field parameters, respectively. (4) Range analysis of orthogonal experiments reveals that for tunnel temperature field impact level. For TAm-1, the significance order is Wa >λd >λi. And for TAm-2 and TSec-lining, the significance order is Wa >λi >λd, which can provide the more economical scheme for the insulation layer design and cooling schemes in the high ground temperature tunnel.

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.