Tunnel fires pose significant challenges to evacuation and emergency response due to high-temperature environments, rapid smoke spread, and the complex interactions between fire-induced flows and ventilation systems. Mobile fans are increasingly applied in emergency ventilation due to their flexible deployment; however, the complex airflow generated by their operation introduces additional difficulties for accurate temperature prediction inside tunnels. This study proposes a dual-module framework based on a self-attention mechanism, integrating the Transpose Convolutional Neural Network (TCNN) and Long Short-Term Memory (LSTM) network to predict the spatiotemporal evolution of tunnel fire scenarios equipped with mobile fans. A numerical dataset of 128 fire scenarios was constructed by varying fire source intensities, fan configurations, and ventilation conditions. By inputting time-series data and temperature field images, the AI model can accurately predict spatial temperature fields in real-time and the longitudinal temperature variation trends in a period of 30 s. The results indicate that the temporal module achieves an overall mean relative error below 3 % under varying conditions of HRR, fan-fire source distance, and fan airflow volume. Slightly higher errors are observed for the fan inclined angle; yet all predictions remain within acceptable limits. The spatial module accurately predicts the temperature distribution at various fire development stages, demonstrating high consistency with CFD simulation results, especially during the steady-state stage. This study provides valuable support for intelligent tunnel fire prediction and the optimal control of mobile fans, while also demonstrating the feasibility of artificial intelligence in achieving rapid and accurate predictions in dynamic tunnel fire scenarios.

Reconstruction of 3-D roof from airborne light detection and ranging (LiDAR) point clouds is an important task in the field of remote sensing and photogrammetry. Due to the high noise, large volume, and structural complexity inherent in LiDAR point clouds, traditional point cloud processing methods have limited performance in terms of accuracy and robustness. Most existing methods rely on corner point detection and edge prediction to extract and reconstruct roof structures. However, corner points are often sparsely distributed and difficult to locate precisely, resulting in noticeable geometric deviations and incomplete structural reconstruction. Therefore, generating a high-quality 3-D roof from complex LiDAR point clouds is still a challenging problem to be solved. To address these issues, we propose a novel roof reconstruction method RR-Net that combines edge segmentation and wireframe generation. First, an innovative unified point cloud edge segmentation network was developed, achieving integrated edge detection, segmentation, and denoising. Second, based on the segmentation results from this network, an efficient and robust pipeline for wireframe generation and roof reconstruction was designed, enabling automated transformation from airborne LiDAR point clouds to roof models. Extensive experiments on the Building dataset demonstrate that RR-Net can efficiently and accurately reconstruct roofs from airborne LiDAR point clouds. RR-Net achieves 95.7% accuracy in edge detection and reduces the Chamfer distance (CD) error of the wireframe to 0.021. The results of RR-Net are publicly available at https://yecoxu.github.io/publications/RR-Net/

Hazardous clouds and toxic zones resulting from gas leaks from storage tanks in chemical plants present immediate threats to environmental health and industrial process safety. However, the fluctuation characteristics and fluctuation-induced consequence variations received limited attention. This study employed the large-eddy simulation (LES) to address the time-averaged and dynamic characteristics of consequences associated with gas leaks from a tank group, focusing on the impacts of leak locations and wind directions. Four metrics were introduced to quantify consequences: volumes of flammable and toxic gas clouds (VF, VT), toxic zone area (AT) and toxic dose for population (TD). The results indicated that the Reynolds-averaged Navier-Stokes model (RANS) markedly overestimated the mean values of these metrics compared to LES, with the prediction of AT even increased by 147.5%. The leeward leak from the rear-row tank presented the highest mean and peak values. Both the peak and mean values were generally higher when the wind direction (theta) was 0 degrees, except for TD. Moreover, AT and TD were significantly impacted by pulsating flow, with fluctuation-induced components generally reaching 30%-40%. When theta <= 0 degrees, AT was primarily influenced by pulsating flow rather than mean flow. The results provide guidance for the design of chemical industrial parks, ensuring the industrial processes safety and refining emergency response strategies.

Low-temperature plasma is recognized as a CO2 decomposition technology with substantial sustainable potential. Enhancing energy efficiency remains a critical challenge for plasma technology to achieve broader industrial adoption. This study developed two water electrode reactors-one with a stationary water electrode and the other with a flowing water electrode-designed to enhance energy efficiency in the CO2 decomposition process. A systematic performance comparison was subsequently made with a conventional aluminum mesh electrode reactor. The findings revealed that water electrode reactors significantly enhanced both heat transfer efficiency and power factor, thereby improving CO2 conversion performance. The stationary water reactor achieved a peak energy efficiency of 20.64%. The effects of input power, feed flow rate, and N2 content on dielectric barrier discharge plasma performance under high flow rate conditions were also explored in this study. The results indicated that as the input power increased, discharge intensity in all three reactors were intensified, leading to higher CO2 conversion. However, a portion of the energy was dissipated as heat, which gradually diminished overall energy efficiency. When the feed flow rate increased from 150 sccm to 600 sccm, the shorter residence time resulted in decreased CO2 conversion, while overall energy efficiency improved significantly. Increasing the N2 content caused an exponential rise in CO2 conversion, while the effective conversion rate and energy efficiency did not improve accordingly. Compared to previous studies, this research demonstrates a clear advantage in energy efficiency, offering useful insights for the industrial application of plasma technology in CO2 decomposition.

When a fire occurs, fast recognition on key information of the fire based on limited data available and predict fire smoke motion trends from limited fire information is desirable to develop effective emergency strategies. The proposed models include fire intensity traceability model and fire position traceability model based on Back Propagation Neural Network (BPNN). Smoke prediction model is proposed based on Transpose Convolutional Neural Network (TCNN). The numerical model is first validated by the single-room fire test, and then a numerical database of 165 transient room-fire scenarios is established under various fire locations, fire sizes, and vent sizes. The model test is conducted in new fire intensity and vent size scenarios, with R2 coefficients of 0.965 and 0.95, respectively. The experimental data validation shows that relative errors were less than 10%. The position traceability model has Kappa values of 0.758 and 0.75. The average visibility error values of the smoke prediction model's output images in the validation of the test set generally fall within the range of +/- 1.5 m. The results indicate that the models have good accuracy and strong adaptability to different compartment fire scenarios which can provides effective support for fire rescue and emergency strategy development in fire scenes.

Mobile fans, as flexible and convenient new longitudinal ventilation and smoke extraction equipment for tunnels, demonstrate more significant effectiveness in an emergency response to tunnel fires compared to traditional smoke extraction methods. This study employs computational fluid dynamics simulation methods, selecting two fire scenarios to investigate the effects of fan inclined angles and fan airflow volumes on the longitudinal temperature distribution and smoke back-layering length in tunnels. The results indicate that when using mobile fans for longitudinal ventilation in tunnels, at a lower fan airflow volume, the temperature distribution along the longitudinal axis is nearly symmetrical. The fire source and the fan installed in the upstream are within a certain range, and it is more effective to use the horizontal angle for longitudinal ventilation. As the fan airflow volume increases, the back-layering length significantly decreases (210,000 m3/h < V < 270,000 m3/h). However, as the fan flow volume continues to increase (270,000 m3/h < V < 300,000 m3/h), the reduction in the back-layering length becomes less pronounced, the smoke spread distance of the latter is only 11% of that of the former. Therefore, selecting appropriate fan airflow volumes and fan inclined angles them can effectively enhance the performance of tunnel smoke extraction systems. Moreover, by comparing with traditional fans, we find that mobile fans provide an alternative effective strategy during firefighting by allowing adjustments in distance from the fire source and fan inclination angles, enhancing fire suppression effectiveness while reducing energy losses. The research findings can serve as a reference for tunnel fire prevention design.

In recent years, atmospheric-pressure plasma jets have emerged as valuable tools in many application areas, including material modification, environmental remediation and biomedicine. Understanding the discharge characteristics of these plasma jets under various operating conditions is crucial for optimizing process outcomes. This paper presents a two-dimensional fluid model for numerical simulation to study the variation in electron density within an atmospheric-pressure helium plasma jet under different operating conditions. The investigated parameters include helium gas flow rate, voltage amplitude, needle-to-ring discharge gap, and relative permittivity of the dielectric tube. The results reveal that the peak electric field and electron density initially occur at the wall of the dielectric tube and subsequently shift towards the head of the propagating jet. Gas flow rate has minimal impact on the electron density throughout the plasma jet, whereas increasing the needle-to-ring discharge gap significantly decreases the average electron density within the jet. In addition, an increase in the voltage amplitude and the relative permittivity of the dielectric tube enhances the electric field within the discharge space, thereby increasing the electron density in the plasma jet. These findings underscore the importance of understanding the correlation between electron density and operating conditions to precisely control plasma jets and enhance material treatment effectiveness for specific applications.

We propose a novel method that aims to automatically generate outdoor building layouts based on given boundary constraints. It effectively solves the problem of irregular shapes that occur in practical application scenarios, where boundary and building outlines are not only composed of horizontal and vertical lines but also include oblique lines. The proposed method is a two-stage process that uses a Graph Neural Network (GNN) to generate the location of each building and the minimum external polygon. The GNN utilizes a pre-defined relative location diagram and the given boundary. Afterwards, the Generative Adversarial Network (GAN) is utilized to generate building outlines that fit the boundary within the minimum external polygon area. Our method has demonstrated the ability to effectively handle diverse and complex outdoor building layouts, as evidenced by its superior performance on the Huizhou traditional village dataset. Both qualitative and quantitative evaluations demonstrate that our method outperforms current GNN-based layout methods in terms of realism and diversity.

Leakage of hazardous chemical gases during storage or transport via roadways is a common type of accident that threatens human life. This study built a typical residential building model in rural areas of southern China based on Building Information Model technology. The model was then simplified and employed as a target building to simulate the hazardous gas dispersion around it after a leak accident by means of Computational Fluid Dynamic methods. A dose-response model was combined with a probit function analysis to quantitatively identify the exposure risks for different scenarios. The impacts of source location and ventilation path on the dispersion characteristics were analyzed through comparisons of indoor concentration distributions. In addition, the study also quantified the relationship between individual mortality risk and the source intensity by employing H 2 S as a source of toxic substances. If the source strength was increased by 2.5 times for the same ventilation path, the corresponding mortality rates can improve from 0.1 to 99%. The findings provide effective information about rapid consequence evaluation after accidental leakage of hazardous chemical gas and could be helpful in proposing effective emergency measures to minimize the exposure risk in roadside buildings.

The emergence of viral variants has driven a continuous pandemic with a higher possibility of airborne transmission and a larger scale of infective cases, posing greater demands on indoor risk control. However, the role of room-level air recirculation systems (RRSs) in infection control remains unclear due to insufficient detailed research. There are also fewer analyses of the filtering rating of recirculation filters from the perspective of multi-scale particle size. Thus, a simulation procedure to assess the performance of RRSs on infection control that accounts the transient recirculation of real virus-laden particles in multi-scale sizes was proposed, and focusing on recirculation filter strategies to balance the risk limitation and energy cost. A poorly ventilated winter classroom was selected as a typical environment equipped with RRSs to operate this procedure. Different RRS strategies (i.e., wall-mounted air conditioners (WMAC), floor-standing air conditioners (FSAC) and 4-way cassette air conditioners (WCAC)) were compared. The results show the important contribution of recirculated particles to accumulating the overall infection risk of susceptible occupants towards a high basic reproduction number (Ro > 1). Then, there is a strong correlation of the spatial distributions between high-risk zones and large vortexes at the breathing height of susceptible occupants. Considering rating suitability and filtration effectiveness, the optimization of recirculation filters on energy and cost can be suggested with comparable benefits of infection control.

Efforts to develop efficient methods for converting carbon dioxide (CO2) have drawn mounting interest due to incremental concerns over carbon emissions. Non-thermal plasma (NTP) technology has shown promise in this regard by producing numerous reactive substances at relatively low temperatures. However, an analysis of relevant literature reveals an underwhelming level of overall energy efficiency for this technology and an insufficient level of attention being paid to it. It is crucial to put forward more effective energy-saving schemes based on a comprehensive analysis of past research results to promote sustained development. This review highlights the latest advances in pertinent energy efficiency optimization studies and outlines state-of-the-art methods. In terms of energy efficiency optimization for plasma CO2 conversion, a comparison is made among different research results in four aspects as follows. Specifically, this study analyzes reactor structure optimization in terms of discharge characteristic, flow field, and plasma contact area; discusses pathways of heat transfer optimization to suppress the competing reaction; and explores catalyst optimization in terms of active sites, calcination temperature, and product selectivity; examines the potential of utilizing solar energy for clean energy applications. The analysis of energy efficiency data indicates an overall improvement when the aforementioned optimization measures are applied, which is essential to validate the effectiveness of each method. Finally, this paper discusses the potential difficulties and future research areas of NTP technology. Urgent further research is imperative on energy efficiency optimization methods for potential large-scale industrial applications in the future.

The causes of Huizhou traditional villages are complex. This paper gives a parameter description covering the whole village and generates a hierarchical Bayesian network. By learning the parameters, this network extracts the layout pattern of the villages. Sampling results from hierarchical Bayesian networks guide road generation, house generation and placement. It can generate specific layout results according to different geographical environments, and the validity of the layout results is proved by experiments.

In conventional multi-zone control mode, either temperature control or contaminant control, there is usually a clear boundary division or partition wall between subzones. However, regarding large-scale indoor space without physical partitions, the airflow coupling effect between adjacent subzones should be considered while implementing a zonal demand control strategy. Otherwise, the simulation results are unreliable and prone to disparity with real scenarios. Therefore, this paper proposed a control modeling method, particularly applicable to large-scale indoor spaces. The impact of airflow coupling between adjacent subzones in the target open space on CO2 transportation has been addressed. The methodology was developed with the TRNSYS-CONTAM-MATLAB co-simulation platform, of which different control strategies for outdoor airflow were investigated. Results show the controlled CO2 concentration in the space is much closer to the on-site measurements after accounting for the airflow coupling effect, which alleviates the issues of over-ventilation or under-ventilation owing to the traditional global control mode. The overall effectiveness of the different outdoor ventilation control strategies was evaluated in terms of indoor air quality (IAQ), anti-infection, energy consumption, complexity of the control strategy and practical implementation, which offers an alternative option for engineers and managers from the HVAC field to choose suitable control strategies tailored for large-scale indoor spaces.

An indoor high and open space is characterized by high mobility of people and uneven temperature distribution, so the conventional design and operation of air conditioning systems makes it difficult to regulate the air conditioning system precisely and efficiently. Thus, a Wireless Sensor Network was constructed in an indoor space located in Hong Kong to monitor the indoor environmental parameters of the space and improve the temperature control effectively. To ensure the continuity of the measurement data, three algorithms for reconstructing temperature, relative humidity and carbon dioxide data were implemented and compared. The results demonstrate the accuracy of support vector regression model and multiple linear regression model is higher than Back Propagation neural network model for reconstructing temperature data. Multiple linear regression is the most convenient from the perspective of program complexity, computing speed and difficulty in obtaining input conditions. Based on the data we collected, the traditional single-input-single-output control, zonal temperature control and the proposed zonal demand control methods were modeled on a Transient System Simulation Program (TRNSYS) control platform, the thermal coupling between the subzones without physical partition was taken into account, and the mass transfer between the virtual boundaries was calculated by an external CONTAM program. The simulation results showed the proposed zonal demand control can alleviate the over-cooling or over-heating phenomenon in conventional temperature control, thermal comfort and energy reduction is enhanced as well.

In this paper, the characteristics of air cross-contamination around a high-rise building under the combined effect of wind and buoyancy are numerically studied. A 1:1 typical multi-unit building model is constructed and the risks of air contaminant building ingress under various environmental conditions are quantitatively evaluated. Firstly, the reentry ratios are quantified to evaluate the possible cross-unit dispersion without considering thermal effects. Then, the flow field and dispersion behavior are further analyzed considering the effect of wall surface temperature rise. The simulated concentration fields in three intervals of generally recognizes Richardson number (Ri) are investigated from the combined effect of wind and buoyancy. It is found that reentry ratios in multiple cases can reach 10.0%, which indicates that the air cross-contamination is an important route that cannot be neglected when a highly infectious airborne disease outbreak in high-densely residential environment. And the largest reentry ratio is detected when the windward surface temperature difference is 15 K above the ambient air at the wind speed of 1.0 m/s, with Ri=14. This study helps deepen our understanding of the mechanisms of cross-contamination under the influence of solar radiation, and will be useful for the prevention and control of accidental infectious diseases outbreaks.

In this study, we reported the supersonic combustion wave behaviors as it propagated through a perforated plate in stoichiometric mixtures of H2-CH4-2.5O2, H2-CH4-4O2 and 2H2-O2. The perforated plate maintained an identical thickness of 10 mm with different hole diameters of 4 mm, 8 mm and 10 mm, respectively. Explosion pressures were recorded using pressure transducers flushed-mounted on the top wall, based on which the average velocity was calculated. Meanwhile, the cellular structures of the supersonic combustion waves were recorded by soot foils. According to the average velocity and soot foils, the propagation modes were classified into four regimes including Fast-flame to fast-flame, Fast-flame to detonation, Detonation to fast-flame, Detonation to re-initiation and Overdriven detonation to detonation. The perforated plate exerts a positive effort on fast-flame by disturbing the flow flied, therefore the fast-flame does not decelerate downstream of the perforated plate. However, the effect of the perforated plate is opposite for detonation, and it weakens the detonation and even causes detonation failure. And this effect is weakened with the hole diameter increasing, which is proven by the limit of reinitiation decreases from d/lambda = 0.98(d = 4 mm) to d/lambda = 0.71(d = 10 mm). However, the re-initiation mechanisms are different at various initial pressures. At higher initial pressure, the detonation front is elongated dramatically but not failed and it recovers downstream. However, the failed detonation needs the aid of the shock refection off the tube wall to re-initiate at lower initial pressure. With increasing the sensitivity of the mixture, the overdriven detonation characterized by d/lambda > 1 was found to transmit the holes with no failure. By comparing with the failing cases owning small cells, d/lambda > 1 is not the sole condition to ensure a detonation traveling through with no failure.

SummaryIn order to reduce the undesirable effect of boundary layer separation and plug‐holing in a naturally ventilated tunnel with shaft for smoke extraction, a new design of baffle has been proposed in this paper. Large eddy simulation (LES) was performed with fire dynamics simulator (FDS), the influence of the angle formed by the boards () and the distance between the baffle top and the shaft bottom () has been investigated. The simulation results show that the smoke extraction efficiency is not simply a monotonic function of the distance or the angle , the influence of and has been discussed, and the mechanism has been investigated. With proper configuration of the inverted V‐shaped baffle, the negative effect of plug‐holing can be eliminated, and the boundary layer separation can also be alleviated; the maximal smoke extraction efficiency is 2.04 times of that in the traditional shaft.

The temperature distribution is always assumed to be homogeneous in a traditional single-input-single-output (SISO) air conditioning control strategy. However, the airflow inside is more complicated and unpredictable. This study proposes a zonal temperature control strategy with a thermal coupling effect integrated for air-conditioned large-scale open spaces. The target space was split into several subzones based on the minimum controllable air terminal units in the proposed method, and each zone can be controlled to its own set-point while considering the thermal coupling effect from its adjacent zones. A numerical method resorting to computational fluid dynamics was presented to obtain the heat transfer coefficients (HTCs) under different air supply scenarios. The relationship between heat transfer coefficient and zonal temperature difference was linearized. Thus, currently available zonal models in popular software can be used to simulate the dynamic response of temperatures in large-scale indoor open spaces. Case studies showed that the introduction of HTCs across the adjacent zones was capable of enhancing the precision of temperature control of large-scale open spaces. It could satisfy the temperature requirements of different zones, improve thermal comfort and at least 11% of energy saving can be achieved by comparing with the conventional control strategy.

In this study, a full-scale storage tank was established to investigate the potential risks of leakage accident. We have developed a series of leak scenarios that close to real accidents and have divided the ambient areas according to relevant regulations. Considering the variety and complexity of real-life accident scenarios, the presented work revealed the combined effect of source release intensity and ambient wind speed on dispersion features by classifying leakage scenarios into active or passive release. The environmental hazards in each area is evaluated under various leak scenarios. The results show that when the approaching wind speed is low, the leakage on the windward side is the most dangerous release pattern. With the increase of the wind speed, the case with jet angle perpendicular to the incoming wind produces the largest cloud volume. Top release is the least dangerous way among the studied leak scenarios. However, the results illustrate that under some release angles, the cloud volume near the tank is not sensitive to wind speed. In leak accidents, quantitatively analysis reveals that the commonly used dimensionless concentrations (K-c) cannot be used as a suitable parameter to discuss the concentration field except under top/leeward passive release conditions. This study will be beneficial to on-site rescue and decision-making when leakage accidents occur and provide reasonable suggestions for subsequent research on the environmental impact of container leakage and the diffusion of pollutants.

The flow field structure, pollutant concentration distribution and dimensionless concentration evolution of uplifted street canyon has been analyzed in this study. Different from the ideal street canyon, the pollutant concentration distribution of the uplifting street canyon is higher at the bottom, lower at the top, higher at the windward side and lower at the leeward side. The total pollutant concentration (TPC) generally decreases with the increase of leeward building lifting height while the lift height increases with the same total building height or the total building height increases with increase in the lifting height. It is beneficial to the pollutant emission of in street canyon. On the contrary, the TPC increases when the total building height increases with the same lift height. The main reason is that the vertical length of the vortex increases, which is more difficult for pollutants to be discharged from the street canyon.