网络首发
Research on flow field characteristics of centrifugal half-inch water mist nozzle for explosion suppression
Zhou Wen;Wang Jinxi;Tang Xinyu;Cheng Wenjun;Zhang Kun;Xue Zhongqing;Shi Xueqiang;To investigate the atomization and flow field characteristics of a traditional straight-blade half-inch centrifugal water mist nozzle and a newly designed structurally optimized airfoil-blade counterpart， a comprehensive series of experimental tests and numerical simulations was systematically conducted. The experimental phase utilized a custom-built closed-loop water circulation testing platform integrated with a high-precision Phase Doppler Particle Analyzer (PDPA)， enabling accurate， real-time measurement of various macroscopic and microscopic spray parameters. Specifically， fluid flow rate， spray angle， maximum average axial velocity， and droplet diameter distribution were evaluated under varying inlet pressure conditions ranging from 0.5 MPa to 4.0 MPa. Concurrently， to uncover internal flow mechanisms that are not easily observed in physical experiments， Computational Fluid Dynamics (CFD) simulations were performed using Fluent software. The numerical model incorporated the RNG k–ε turbulence model coupled with the Volume of Fluid (VOF) multiphase framework to capture complex air-water interface dynamics. We simulated internal static pressure variations， velocity distributions of the internal flow field， and outlet cross-sectional velocity profiles for both nozzle geometries under extended inlet pressures from 1.0 MPa to 6.0 MPa. The empirical data demonstrate that the optimized nozzle significantly enhances fluid throughput. Within the tested pressure range， its flow rate increased by 20% to 35% compared to the traditional design， peaking at a maximum flow difference of 1.039 m³/h under the 2.0 MPa working condition. Furthermore， the airfoil-blade structure exhibits a broader operational range for the spray angle， contracting from 78.8° to 46°， which provides a distinct spatial coverage advantage， particularly around the 1.5–2.0 MPa pressure interval. Interestingly， regarding droplet size distribution， a crossover effect was observed: the traditional straight-blade nozzle generates finer droplets at lower pressures (0.5–2.5 MPa)， while the optimized nozzle demonstrates superior atomization performance at higher pressures exceeding 3.0 MPa. Both designs successfully achieved effective droplet velocities surpassing 50 m/s once system pressure reached 3.5 MPa. From a numerical perspective， simulation results illustrate that structural optimization significantly smooths the internal pressure gradient; specifically， at the extreme pressure of 6.0 MPa， the local pressure drop across the blades is reduced by approximately 57%. This research provides a theoretical basis and data accumulation for the selection and structural optimization of water mist nozzles， serving as a valuable reference for dust protection in mining operations.
Risk propagation and facility exposure assessment of urban underground spaces based on cascading failures
Chen Wenqiang;Zang Xiaolei;Shi Juan;Jia Jian;To address the insufficient characterization of cross-layer risk transmission and differential facility exposure in urban underground spaces， this study proposes a three-layer coupled network consisting of risk factors， disaster events， and facility types. The network structure is established by representing the relationships among different risk elements and describing the cascading transmission pathway from initial risk factors to disaster consequences and facility impacts. A cascading failure model is developed to simulate the dynamic propagation process among interconnected nodes. Specifically， risk propagation pressure is introduced to quantify the transmission intensity between nodes， while node tolerance thresholds are defined to represent the resistance capacity of individual nodes against cascading failures. Based on the proposed mechanism， a method for identifying key cascading risk sources is developed， and a facility exposure assessment index is constructed to quantify the heterogeneous exposure characteristics of different underground facility categories. The proposed method is validated using 200 representative accident cases collected in China from 2010 to 2025. The identified key cascading risk sources are compared with frequently reported accident causes， and the calculated facility exposure index is further compared with actual damage frequency. The results show that lax safety management， operational errors， and equipment aging or corrosion play important triggering roles in risk propagation. Among different facility categories， underground pipelines exhibit the highest exposure level， whereas underground passageways show the lowest exposure level. The consistency rate between the identified key cascading risk sources and frequently reported accident causes reaches 66.7%， and the facility exposure index demonstrates a significant correlation with actual damage frequency， with a Pearson correlation coefficient of 0.706. Furthermore， the comparison between cascading influence and topological centrality indicates that structural importance does not necessarily correspond to cascading propagation capability. The proposed method provides an effective approach for disaster chain interruption， critical facility monitoring， and hierarchical risk management in urban underground spaces.
Simulation study of mine gas laser remote sensing technology based on dual optical paths
Zhang Andong;Hu Min;Zhao Dongyue;He Qing;Nie Shibin;Xue Shuo;To enable non-contact remote estimation of the absolute methane volume fraction at non-fixed measurement points in mines， a dual-optical-path differential absorption laser method is proposed. The method is based on the principle of methane path-integrated volume fraction measurement using a single optical path. Two adjacent parallel optical paths are arranged in the measurement area to obtain path-integrated methane volume fraction information at different spatial positions. By using the difference between the two path-integrated volume fractions， an approximate relationship is established between this difference and the local methane volume fraction near the target measurement point. In this way， the conventional path-integrated measurement result is transformed into an estimate of the local methane volume fraction at a non-fixed measurement point. This conversion helps alleviate the inherent limitation of single-path measurements， which provide only cumulative information along the optical path. To evaluate the feasibility of the proposed method and the effects of key parameters， a simulation model of the local methane volume fraction field near a coal wall is developed. The effects of the vertical distance Δn between the reference reflective surface and the target measurement point， together with the optical-path spacing d， on the estimation error are analyzed. The results show that， under a given Δn， the estimation error first decreases and then increases with increasing d， indicating that an appropriate matching relationship exists between d and Δn. When Δn is 0.02， 0.04， and 0.06 m， the corresponding preferred d values are approximately 0.05， 0.17， and 0.35 m， respectively. The minimum absolute error reaches 0.000 9%. As Δn increases， the preferred d generally increases， reflecting a balance between the difference in path-integrated information and the local representativeness of the measurement. When the absolute error is no greater than 0.01%， d can be adjusted within an allowable range. The results provide a theoretical basis and a methodological reference for remote estimation of the absolute methane volume fraction at non-fixed measurement points in mines.
Dynamic risk assessment of underground heating pipe galleries based on game theory-based combined weighting
Liu Yufeng;Zhang Xiaojian;Xie Wei;Li He;Zhu Haiyue;Feng Deng;Zhu Dong;Wang Chenglong;Addressing the conflict between subjective and objective weights in the risk assessment of underground heating pipe galleries， as well as the lack of dynamics in traditional models， this study proposes a dynamic assessment method that integrates game theory-based combined weighting with residual-driven feedback correction. This integrated framework explicitly acknowledges the evolving nature of infrastructure risks by establishing a closed-loop， self-optimizing evaluation system. First， initial subjective and objective weight sets are constructed using three methods: the G1 method (Order Relationship Analysis Method) determines subjective weights based on expert insights to identify implicit risks such as weld defects; the improved entropy weight method captures data discreteness; and the CRITIC (Criteria Importance Through Intercriteria Correlation) method integrates data variability and inter-indicator correlation to form complementary objective weights， mitigating the limitations of single-method approaches. Subsequently， game theory combined weighting achieves collaborative optimization by minimizing the Euclidean distance between the combined weight vector and the three initial sets， resulting in the Nash equilibrium between subjective experience and objective data. To enhance dynamics， a residual-driven multi-stage feedback correction mechanism is designed: each phase calculates the relative residual between predicted and actual risk levels， which dynamically adjusts the subjective weight coefficient via an exponential decay function and updates cloud model parameters (Ex， En， He). This continuous adaptation mechanism ensures that the assessment model remains synchronized with the real-time degradation process and environmental variations of the pipe gallery system throughout its operational lifecycle. Using a case study of a 12.3 km DN1200 heating pipe gallery in Hebei Province， results indicate that Section 2 in the old urban silty clay layer is the highest-risk priority， with a risk score of 52.5. Operation and maintenance indicators exhibit the highest sensitivity， contributing 35% to total risk. The subjective weight coefficient decays from 0.5 to 0.001， thereby reducing reliance on expert experience. The comprehensive score achieved by the proposed method (0.975 9) outperforms the G1 method (0.874 3)， improved entropy weight method (0.703 1)， and CRITIC method (0.892 4) by 12.3%， 8.7%， and 10.1%， respectively. This method effectively identifies high-risk sections and dominant factors， providing scientific support for full-life-cycle safety management of underground heating pipe galleries.
Barrier effect of intumescent flame-retardant composites on thermal runaway propagation in lithium-ion batteries
Yang Yun;Song Ran;Xi Yuqiong;Ju Zetao;Ren Yanan;Wang Zhirong;To enhance the ability to block thermal runaway propagation in lithium-ion battery modules， an intumescent flame-retardant composite material was designed and fabricated. Using Silicone Resin Modified by Epoxy (SE) as the matrix， flame-retardant composites were prepared by blending phosphorus-nitrogen Intumescent Flame Retardant (IFR)， Cellulose (C)， Sepiolite (Sep)， and Aluminum Hydroxide (AH). Four material systems were constructed: pure SE， SE–C， SE–IFR， and SE–IFR/C/Sep/AH. Module-scale thermal runaway propagation tests were conducted to systematically investigate their performance in blocking thermal runaway. The thermal runaway suppression capabilities of the SE–IFR/C/Sep/AH intumescent flame-retardant composite were comprehensively evaluated through Thermogravimetric Analysis (TGA)， Raman spectroscopy， Scanning Electron Microscope (SEM)， and Limiting Oxygen Index (LOI) tests. The experimental results are as follows: (1) Sustained thermal runaway propagation occurred in both the SE and SE–C groups， while no continuous thermal runaway spread was observed in the SE–IFR and SE–IFR/C/Sep/AH groups. Notably， the SE–IFR/C/Sep/AH composite exhibited a significantly stronger inhibitory effect on cascading thermal runaway compared to the SE–IFR sample. When the SE–IFR/C/Sep/AH composite was used as a barrier， only cell 1 underwent thermal runaway， while the maximum temperatures of cell 2 and cell 3 were merely 93.3℃ and 50.1 ℃， respectively. (2) Material characterization results indicate that the SE–IFR/C/Sep/AH composite achieves a char residue rate of 42.38% at 800 ℃ under a nitrogen atmosphere， facilitating the formation of a relatively stable inorganic skeleton structure. Raman spectroscopy reveals that the ID/IG ratio of the residual char after combustion is 0.53， indicating that the produced char layer possesses higher ordering and superior structural stability. SEM observations show that this composite forms a rough， porous structure with layered stacking characteristics. Additionally， its LOI increases to 32.4%， confirming that composite modification effectively enhances the material's flame retardancy. The SE–IFR/C/Sep/AH intumescent flame-retardant composite serves as a valuable reference for the design of thermal safety protective materials applied in lithium-ion battery modules.
Application Research of Thermal Breathing Mannequins on Inhalation Exposure of Susceptible Persons in Hospital Diagnosis and Treatment Environments
Fu Linzhi;Bao Xiaoni;Meng Xiaojing;Liu Yalin;Hospital diagnosis and treatment scenarios feature dense personnel and frequent close contact. Airborne transmission is the primary cause of cross-infection of respiratory infectious diseases between doctors and patients as well as among patients， posing major hidden dangers to in-hospital treatment safety and public health prevention and control. To reduce the infection risk between medical staff and patients and clarify the core prevention and control key points of indoor respiratory exposure， this study built a full-scale standardized experimental platform for hospital scenarios and carried out multi-condition simulation tests on particulate inhalation exposure. Equipped with thermal breathing mannequins， the experiment simulated the physiological characteristics and breathing states of infected and susceptible individuals， faithfully restoring the processes of respiratory plume diffusion， airflow disturbance， and particle transport in real hospital environments.Inhalation ratio and respiratory deposition fraction were selected as two core evaluation indicators to quantitatively characterize the particulate inhalation exposure level and actual respiratory deposition of susceptible populations. With the controlled variable method， this study systematically explored the influence laws of interpersonal distance， body posture， and relative orientation on inhalation exposure.The experimental results show that both inhalation ratio and deposition fraction decrease with the increase of interpersonal distance under both standing and sitting postures. At the spacings of 0.85 m and 1.0 m， the inhalation ratio of standing individuals ranks side-facing， face-to-face， and back-facing in sequence， while the deposition fraction follows the order of back-facing， side-facing， and face-to-face. For sitting posture， the inhalation ratio at both distances consistently presents the order of back-facing， side-facing， and face-to-face. However， the deposition fraction varies significantly with spacing: the order is side-facing， back-facing， and face-to-face at 0.85 m， and changes to back-facing， face-to-face， and side-facing at 1.0 m. Under the same spacing and relative orientation， standing posture produces higher inhalation exposure and respiratory deposition levels than sitting posture， indicating that sitting posture can effectively reduce the risk of droplet nucleus infection. This study clarifies the core variation laws of respiratory exposure in hospital scenarios and provides a quantitative reference for the prevention and control of airborne nosocomial infections.
Explainable few-shot prediction of accident injury risk in autonomous driving safety based on TabPFN
Lai Zhijian;Dong Chunjiao;Yan Song;Huang Boyang;Xiao Shengjie;This study addresses the challenges of small sample sizes， class imbalance， and limited model interpretability in predicting injury risk from autonomous vehicle traffic accidents by proposing a prediction framework that integrates TabPFN (Tabular Prior-data Fitted Network) with eXplainable Artificial Intelligence (XAI). The research is based on 1 725 real-world autonomous vehicle accident records from the National Highway Traffic Safety Administration (NHTSA)， where injury cases account for 20% of the dataset. Through recursive feature elimination and XGBoost-based feature importance assessment， nine key predictive features—including collision type， ego-vehicle driving behavior， perception system type， and collision object—were identified from an initial set of 49 variables. To evaluate the performance of TabPFN in small-sample scenarios， we constructed comparative experiments involving eight baseline machine learning models， including Decision Tree (DT)， Random Forest (RT)， eXtreme Gradient Boosting (XGBoost)， and Artificial Neural Network (ANN). The results demonstrate that TabPFN achieves a recall of 0.855 and an Area Under the Curve (AUC) of 0.923 on the test set， outperforming the best baseline model by 11.6percentage points in recall while significantly reducing the risk of missed detections. This indicates superior classification performance and generalization capability. Further analysis using enhanced confusion matrices and Receiver Operating Characteristic (ROC) curves confirms TabPFN’s suitability for safety-critical applications. In terms of interpretability， the study combines SHapley Additive exPlanations (SHAP) global analysis and Local Interpretable Model-agnostic Explanations (LIME) local explanations to systematically reveal key risk factors and their underlying mechanisms. SHAP analysis identifies collision type， driving behavior， perception system configuration， and collision object as the most influential features， while LIME provides sample-level validation of the model’s decision logic， ensuring consistency and transparency. Visualization through PCA reduction further supports the model’s discriminative reliability by demonstrating clear class separation in small and imbalanced datasets. This research represents the first application of the TabPFN model to the prediction of injury risks in autonomous vehicle accidents. It establishes a comprehensive workflow encompassing feature selection， model construction， and interpretability verification. The study not only validates the superior performance of TabPFN in small-sample and imbalanced classification tasks but also provides a high-accuracy， interpretable risk assessment paradigm for pre-collision safety warning systems. This contributes meaningfully to enhancing the safety and transparency of autonomous driving systems.
Evolution and dynamic assessment of disaster risks in urban transportation infrastructure from an energy perspective
Zhang Yongcheng;Wang Jianwei;Li Chengqian;Liu Yang;Xu Wenxin;Understanding the evolution characteristics and risk states of urban transportation infrastructure during heavy rainstorms and flood disasters is crucial for effective disaster prevention and risk management. Using the Zhengzhou “7.20” extreme rainstorm event as a case study， this research develops a multidimensional dynamic risk evolution assessment framework for urban transportation infrastructure from an energy perspective. The proposed framework systematically analyzes the disaster evolution process and quantifies the associated risk levels. First， the mechanisms of risk energy accumulation， transfer， and transformation during heavy rainstorms and floods are analyzed through the lens of energy flow. A coupling relationship model is constructed to describe the interactions between rainfall intensity， surface runoff， and transportation infrastructure systems， revealing a three-stage disaster evolution pattern characterized by energy accumulation， threshold breakthrough， and system failure. Second， based on the energy transfer mechanism， a dynamic risk assessment model is developed that incorporates key elements of risk energy， including energy type， intensity， and transmission pathways. This model captures the processes of energy release， propagation， and dissipation throughout the disaster chain evolution. To quantify the overall disaster risk level， the Ordinal Priority Approach (OPA) is employed to determine the weights of evaluation indicators， while interval type-1 fuzzy logic is introduced to address uncertainties and ambiguities in the evaluation process. The results indicate that the evolution of the “7.20” heavy rainstorm and flood disaster chain exhibits strong dynamic and nonlinear characteristics. The integrated risk level of the urban transportation infrastructure system in Zhengzhou is assessed as high risk， which aligns closely with field investigation reports and post-disaster assessments. Furthermore， incorporating the evolution of risk energy into the evaluation framework facilitates the identification of critical early-warning signals during the initial stages of disaster development. This study provides a theoretical basis and methodological reference for dynamic risk assessment and early warning of urban transportation systems under extreme rainstorm and flooding scenarios， offering valuable support for enhancing urban disaster prevention and resilience.
Evolution mechanisms of “small-fire fatalities” accident under coupled multiple causations
Tian Fengshi;Zhao Xiaolong;Chen Chong;Feng Tao;Ding Feng;An analytical model is established based on an improved Technology-Organization-Environment (TOE) framework. This model incorporates five antecedent conditions: Electrical Hazard Index (EHI)， Behavioral Risk (BR)， Mitigation Facilities (MF)， Fire Load Density (FLD)， and Time Risk Factor (TRF). It aims to decode the nonlinear causative mechanisms of “small-fire fatalities” in residential premises， which refer to fires with limited burned areas and low economic loss but disproportionately high fatality rates. Forty-five typical cases that occurred in China from 2020 to 2025 are selected for analysis. These cases encompass urban residences， old communities， rural self-built houses， and “three-in-one” premises (integrating production， storage， and accommodation). All cases are strictly screened based on criteria of authority， information integrity， and maximum heterogeneity， exclusively sourced from official fire accident bulletins or regulatory warning records. Qualitative Comparative Analysis (QCA) is employed as the core research method. This set-theoretic approach is suitable for medium-sized samples and can identify nonlinear risk couplings that traditional linear regression cannot capture. Dichotomous calibration is performed for all variables (1 indicating risk presence and 0 indicating absence). Necessity analysis is conducted with a consistency threshold of 0.9 for identifying necessary conditions. A truth table is constructed with a frequency threshold of 1 and a consistency threshold of 0.8， and the intermediate solution is selected for core analysis. Results from the necessity analysis show that the consistency scores of all single factors and their negations fall below 0.9， indicating that no single factor serves as a necessary condition for such accidents and undermining the validity of single-factor linear attribution. Four equivalent causative paths are identified and summarized into three dominant modes， with the intermediate solution achieving an overall coverage of 73.3%: the behavior-load driven mode， the equipment-behavior paradox mode， and the electrical-temporal coupling mode. This study confirms that these accidents exhibit significant multiple concurrent causation and equifinality. Consequently， fire governance strategies should transition from single-point inspections to configuration-oriented systematic prevention and control.
Influencing factors and condition optimization of catalytic degradation of sulfamerazine using bismuth ferrite
Cong Xin;Wang Xiaobo;Guo Hongwei;This study investigates the preparation of cobalt-doped bismuth ferrite catalysts (Cox-Bi25FeO40) using hydrothermal synthesis and explores the degradation of the pollutant Sulfamerazine (SMR) in aqueous environments through the activation of Persulfate (PS) by Cox-Bi25FeO40. The successful synthesis of the Cox-Bi25FeO40 catalyst was confirmed by comprehensive material characterization， specifically utilizing Scanning Electron Microscopy (SEM) and X-ray Diffraction (XRD) analysis. A series of single-factor experiments were systematically conducted to evaluate the effects of key operational parameters on SMR degradation performance. These parameters included the molar ratio of cobalt dopant， catalyst dosage， and reaction temperature. The experimental results demonstrated that a Co2⁺ to Fe³⁺ molar ratio of 2:1 provided optimal degradation efficiency for SMR within the Co2-Bi25FeO40/PS system. Building on the findings from the single-factor experiments， the Box-Behnken design within response surface methodology was employed to further optimize the reaction conditions. A robust quadratic polynomial regression model was established， incorporating PS concentration， temperature， and initial pH as the primary independent variables. The predictive model identified the optimal conditions for SMR degradation in the Co2-Bi25FeO40/PS system， with the best performance achieved at an initial pH of 8.0， a reaction temperature of 45 °C， and a persulfate concentration of 4 mmol/L. Furthermore， experiments investigating the influence of inorganic anions revealed that the Co2-Bi25FeO40/PS system exhibits notable tolerance to ionic interference， suggesting its potential applicability in complex water matrices. To elucidate the underlying degradation mechanism， radical quenching experiments were performed， indicating that sulfate radicals (SO₄⁻·) and singlet oxygen are the dominant reactive oxygen species responsible for the oxidative breakdown of SMR. In summary， this research provides a substantial experimental foundation and valuable data to support the future development and application of advanced oxidation processes for the effective remediation of SMR contamination in aquatic environments.