Analysis of spontaneous ignition of hydrogen-enriched methane in a rectangular tube

This study investigates the spontaneous ignition of high-pressure hydrogen-enriched methane in air within a rectangular tube. A computationally efficient approach has been adopted, utilizing a reduced reaction mechanism and ignition delay model within a 3D Large Eddy Simulation (LES) framework. This approach overcomes the limitations of traditional 1D and 2D simulations with detailed chemistry models, which are unable to accurately reproduce the complex 3D shock wave structures within the tube. The simulated shock wave behavior during 9 MPa hydrogen leakage (case 1) and 11 MPa 90 vol% hydrogen/10 vol% methane mixture leakage (case 2) are found to agree well with experimental observations. In case 2, the hot spots generated by reflected shock waves and Mach reflections ignite the hydrogen/methane-air mixture, resulting in three sequential spontaneous ignitions. The flame is observed to primarily propagate along the tube corners and wall centers, with the central ignition spreading across the entire cross-section. For the 25 MPa 24 vol% hydrogen/76 vol% methane mixture leakage (case 6), the shock intensity is significantly reduced due to the increased methane proportion, leading to spontaneous ignition only at the tube corners when the hemispherical shock wave reflects from the wall. The flame predominantly forms downstream along the tube corner, gradually spreading along the tube wall. It is indicated that while the probability of spontaneous ignition decreases with increasing methane content, the risk remains significant under sufficiently high pressures. To the best our knowledge, this study represents the first 3D large eddy simulation of spontaneous ignition for high-pressure hydrogen-enriched methane leakage into air, providing valuable insights into the underlying physical phenomena

Molecular subgroups of adult medulloblastoma: a long-term single-institution study

Background Recent transcriptomic approaches have demonstrated that there are at least 4 distinct subgroups in medulloblastoma (MB); however, survival studies of molecular subgroups in adult MB have been inconclusive because of small sample sizes. The aim of this study is to investigate the molecular subgroups in adult MB and identify their clinical and prognostic implications in a large, single-institution cohort. Methods We determined gene expression profiles for 13 primary adult MBs. Bioinformatics tools were used to establish distinct molecular subgroups based on the most informative genes in the dataset. Immunohistochemistry with subgroup-specific antibodies was then used for validation within an independent cohort of 201 formalin-fixed MB tumors, in conjunction with a systematic analysis of clinical and histological characteristics. Results Three distinct molecular variants of adult MB were identified: the SHH, WNT, and group 4 subgroups. Validation of these subgroups in the 201-tumor cohort by immunohistochemistry identified significant differences in subgroup-specific demographics, histology, and metastatic status. The SHH subgroup accounted for the majority of the tumors (62%), followed by the group 4 subgroup (28%) and the WNT subgroup (10%). Group 4 tumors had significantly worse progression-free and overall survival compared with tumors of the other molecular subtypes. Conclusions We have identified 3 subgroups of adult MB, characterized by distinct expression profiles, clinical features, pathological features, and prognosis. Clinical variables incorporated with molecular subgroup are more significantly informative for predicting adult patient outcome

Experiment on the promoting-inhibiting effects on methane explosion by using haloalkanes

Methane explosion is one of the major disasters that seriously threaten the safety of coal mine production, the development of efficient methane explosion suppression technology can effectively improve the prevention and control level of methane explosion accidents, and its focus is on the function of explosion suppression materials. In order to systematically study the effect of typical haloalkanes extinguishing agents on methane explosion, the effects of typical haloalkanes such as heptafluoropropane (C3HF7), hexafluoropropane (C3H2F6) and trifluoromethane (CHF3) on the ignition and explosion characteristics of methane were systematically studied by combining experimental tests and theoretical analysis. The effects of haloalkanes on methane explosion pressure parameters and laminar burning velocity were tested by a 20 L spherical explosive vessel and a self-developed Bunsen burner laminar flame propagation velocity system. The variation laws of peak explosion pressure, maximum pressure rise rate, laminar burning velocity, and laminar flame morphology evolution were obtained. The results show that with the increase of the added volume fraction, the haloalkanes had a double effect of promoting and inhibiting the methane explosion process. Under the chemical equivalent condition, only C3HF7 can first promote and then inhibit the peak explosion pressure and maximum pressure rise rate of methane, while CHF3 and C3H2F6 can inhibit the effect. The three haloalkanes all showed inhibition on the combustion rate of methane laminar flow. In the oxygen-poor condition, the three haloalkanes inhibited the peak explosion pressure, the maximum pressure boost rate, and the laminar burning velocity of methane. In general, C3H2F6 and C3HF7 have better inhibition effects on methane explosion pressure characteristic parameters and laminar burning velocity than CHF3. The theoretical analysis results show that the double effect of promoting and inhibiting the haloalkanes with the increase of the mixture volume fraction can be attributed to the competition between the improvement of the heat release characteristics of the system reaction and the inhibition of the key free radicals such as H, O, and OH by the main intermediates containing F. The results of this paper provide a theoretical basis for the theoretical research and technical development of methane explosion prevention and control

The influence of methane blending ratio on the spontaneous combustion characteristics of high-pressure hydrogen leakage

Adding CH4 to high-pressure H2 is considered one of the effective and convenient measures to reduce high-pressure H2 leakage and spontaneous combustion, which is conducive to improving the safety of H2 energy storage. Based on the independently built high-pressure hydrogen leakage and self ignition experimental platform, the influence of CH4 on the critical self ignition pressure and flame of high-pressure H2 leakage and self ignition was tested. The results indicate that the addition of methane can effectively increase the critical spontaneous combustion pressure. When 20% CH4 is added, the critical self ignition pressure can be increased by 151.58%. Under similar discharge pressure conditions, the flame velocity in the pipeline decreases from 1224.64m/s for pure H2 to 1024.07m/s for 10% CH4. In addition, after mixing CH4, the dispersion time of the jet flame is advanced, the flame duration is shortened, and the flame brightness is reduced. There are two main reasons for the mixed inhibition of spontaneous combustion by CH4. On the one hand, it reduces the Mach number of shock wave propagation, thereby lowering the ignition temperature. On the other hand, the activity of the fuel system decreases, and the heat required for self ignition increases

An Experiment Study on the Dynamic Behavior of Concrete Used in a Mine Sealing Wall under a High Temperature

Micro-cracks and material deterioration occur in concrete under high-temperature conditions. To reveal the impact resistance of concrete at a high temperature, a dynamic splitting test and dynamic compression test were carried out using a split Hopkinson pressure bar (SHPB). The failure process and dynamic stress–strain curve of the concrete specimens were obtained, investigating the failure mode and dynamic tensile and compressive strength of the concrete. The test results showed that the surface cracks appeared along the loading direction and extended to the core area under the impact load. With an increase in the temperature, different degrees of damage would be caused, the dynamic strength and toughness of the concrete would decrease, showing brittle failure, and the energy absorbed in the failure process would also decrease correspondingly

Characterization of Red Sand Dust Pollution Control Performance via Static and Dynamic Laboratorial Experiments when Applying Polymer Stabilizers

Red sand dust pollution is of great concern for its occupational and environmental detriments. The current remediation technique includes water spray and non-traditional stabilization via the application of polymer stabilizers. The dust erosion resistance plays a significant role in quantifying the effectiveness of red sand dust suppression. The aim of this paper is to evaluate the reliability and accuracy of five static and dynamic laboratorial methods that are commonly utilized to quantify the dust erosion resistance in the presence of polymers in previous studies, which are wind tunnel simulation, dynamic viscosity test, crust thickness test, penetration resistance test, and unconfined compressive strength test. The advantages and shortcomings of these methods were comprehensively demonstrated. The results illustrated that the penetration resistance test is the most reliable method in terms of the highest accuracy and relatively simpler operation. It also reveals excellent universality for effectively quantifying the dust erosion resistance of red sand with different particle sizes and for different polymers with various concentrations, while the rest of the methods failed to identify. The application of polymers contributes to improved dust erosion resistance for longer crust failure time, higher solution dynamic viscosity and crust penetration resistance, and higher unconfined compressive strength of rending sand samples. PAM outperformed guar gum and xanthan gum on the base of polymer ionicity and molecular weight. This study offers a better understanding in guiding the selection of optimum evaluation methods and polymers for the study of bauxite residue dust control

Ultra-early prediction of the process parameters of coal chemical production

Most accidents in a chemical process are caused by abnormal or deviations of the process parameters, and the existing research is focused on short-term prediction. When the early warning time is advanced, many false and missing alarms will occur in the system, which will cause certain problems for on-site personnel; how to ensure the accuracy of early warning as much as possible while the early warning time is a technical problem requiring an urgent solution. In the present work, a bidirectional long short-term memory network (BiLSTM) model was established according to the temporal variation characteristics of process parameters, and the Whale optimization algorithm (WOA) was used to optimize the model's hyperparameters automatically. The predicted value was further constructed as a Modified Inverted Normal Loss Function (MINLF), and the probability of abnormal fluctuations of process parameters was calculated using the residual time theory. Finally, the WOA-BiLSTM-MINLF process parameter prediction model with inherent risk and trend risk was established, and the fluctuation process of the process parameters was transformed into dynamic risk values. The results show that the prediction model alarms 16 min ahead of distributed control systems (DCS), which can reserve enough time for operators to take safety protection measures in advance and prevent accidents

Effect of Synergistic Aging on Bauxite Residue Dust Reduction Performance via the Application of Colloids, an Orthogonal Design-Based Study

The application of polymer colloids is a promising approach for bauxite residue dust pollution control. However, due to the existence of synergistic aging, the efficiency of colloid dynamic viscosity to predict the dust control performance of bauxite residue is unclear. Previous studies were also rarely performed under synergistic aging conditions. Thus, this paper investigates the relationship between colloids’ viscosity and dust control performance under synergistic aging modes. Results illustrated that the binary colloid achieved better dust control performance than unitary colloid for their higher viscosity and penetration resistance. For both unitary and binary colloid, higher viscosity results in better crust strength. A logarithmic relationship was found for viscosity and dust erosion resistance under unitary aging. However, Only the dynamic viscosity of colloids in solid-liquid two-phase conditions, rather than dissolved in deionized water, can effectively predict the dust control performance under synergistic aging conditions

Dynamic Re-Weighting and Cross-Camera Learning for Unsupervised Person Re-Identification

Person Re-Identification (ReID) has witnessed tremendous improvements with the help of deep convolutional neural networks (CNN). Nevertheless, because different fields have their characteristics, most existing methods encounter the problem of poor generalization ability to invisible people. To address this problem, based on the relationship between the temporal and camera position, we propose a robust and effective training strategy named temporal smoothing dynamic re-weighting and cross-camera learning (TSDRC). It uses robust and effective algorithms to transfer valuable knowledge of existing labeled source domains to unlabeled target domains. In the target domain training stage, TSDRC iteratively clusters the samples into several centers and dynamically re-weights unlabeled samples from each center with a temporal smoothing score. Then, cross-camera triplet loss is proposed to fine-tune the source domain model. Particularly, to improve the discernibility of CNN models in the source domain, generally shared person attributes and margin-based softmax loss are adapted to train the source model. In terms of the unlabeled target domain, the samples are clustered into several centers iteratively and the unlabeled samples are dynamically re-weighted from each center. Then, cross-camera triplet loss is proposed to fine-tune the source domain model. Comprehensive experiments on the Market-1501 and DukeMTMC-reID datasets demonstrate that the proposed method vastly improves the performance of unsupervised domain adaptability