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Study on the explosion characteristics of premixed hydrogen/air mixtures in a wavy confined pipe 波状密闭管道中预混氢/空气的爆炸特性研究
IF 7.8 2区 环境科学与生态学 Q1 ENGINEERING, CHEMICAL Pub Date : 2026-01-31 DOI: 10.1016/j.psep.2026.108538
Qiang Liu, Zhuangzhuang Xu, Guogang Yang, Han Sun, Shuyao Zhang
In the pipeline, ventilation, and storage systems, pipe structures with curved geometries may unexpectedly act as explosion risk amplifiers. Based on large Eddy Simulation (LES), this study conducted a numerical simulation of the explosion characteristics of hydrogen/air mixtures in wavy pipelines, focusing on analyzing the effects of waveform parameters (amplitude A and wavelength B) and hydrogen equivalence ratio on flame propagation dynamics. The results indicate that the wavy structure significantly promotes flame acceleration and instability by enhancing the interaction between pressure waves and the flame front through increased pressure wave reflection frequency, thereby inducing the formation of special structures such as asymmetric tulip flames. Increased amplitude accelerates flame propagation but leads to incomplete combustion; wavelength variations also affect explosion intensity, with the highest explosion hazard occurring at wavelength B= 0.5. An increase in the hydrogen equivalent ratio further intensifies flame velocity and explosion intensity. This study reveals the mechanism by which the coupling of pipeline structure and fuel concentration accelerates flame propagation, providing theoretical support for hydrogen energy safety protection.
在管道、通风和存储系统中,具有弯曲几何形状的管道结构可能出乎意料地充当爆炸风险放大器。基于大涡模拟(large Eddy Simulation, LES),对波浪管道中氢气/空气混合物的爆炸特性进行了数值模拟,重点分析了波形参数(振幅a和波长B)和氢气等效比对火焰传播动力学的影响。结果表明,波纹结构通过增加压力波反射频率,增强压力波与火焰前缘的相互作用,从而形成不对称郁金香火焰等特殊结构,从而显著促进火焰的加速和不稳定。振幅的增加加速了火焰的传播,但导致燃烧不完全;波长变化对爆炸强度也有影响,在波长B= 0.5处爆炸危险性最大。氢当量比的增大进一步增强了火焰速度和爆炸强度。本研究揭示了管道结构与燃料浓度耦合加速火焰传播的机理,为氢能安全防护提供理论支持。
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引用次数: 0
Biological treatment and purification of photofermentation biohydrogen production effluent to achieve high-value conversion of pollutants 光发酵产氢废水的生物处理与净化,实现污染物的高值转化
IF 7.8 2区 环境科学与生态学 Q1 ENGINEERING, CHEMICAL Pub Date : 2026-01-31 DOI: 10.1016/j.psep.2026.108498
Yinggang Jiao , Wen Cao , Haitao Liu , Yameng Li , Hong Liu , Bing Hu , Yang Zhang , Xudong Yang , Xiaohang Guo , Quanguo Zhang , Zhiping Zhang
Relying on their highly efficient photosynthetic capacity, microalgae can achieve the efficient conversion of pollutants in wastewater into high-value-added products. However, during the treatment of photofermentation biohydrogen production effluents (PFEs), their high organic load, high chroma and extreme pH values significantly inhibit the pollutant conversion efficiency of microalgae. Hence, this study investigated the cultivation mechanism of Chlorella pyrenoidosa based on in-situ PFEs, and evaluated the pollutant removal capacity and the output of high-value-added products. The results showed that the optimal tolerant concentration of Chlorella pyrenoidosa to PFEs was approximately 40 %. The inhibitory effect of PFEs on the growth of Chlorella pyrenoidosa was mitigated by optimizing light intensity and initial pH value. The maximum biomass yield of 1480.94 ± 5.13 mg/L was achieved under the conditions of 7000 lux light intensity and initial pH= 8. The removal rate of chemical oxygen demand (COD) in PFEs reached 74.30 %, which exceeded the 60 % removal criterion for municipal wastewater treatment plants. The removal efficiencies of typical pollutants including TN, NH4+ -N and PO43--P were 79.75 %, 90.06 % and 77.51 %, respectively. In terms of the output of high-value-added products, the maximum protein content reached 60.35 %, with the highest protein yield of 887.62 ± 15.11 mg/L, which was increased by 235.72 % compared with the group cultured in the traditional BG-11 medium. Compared with the single photofermentation biohydrogen production process, the integrated process of co-producing biohydrogen and microalgae from corn stover improved the overall carbon conversion efficiency by 56.59 %.
凭借其高效的光合作用能力,微藻可以将废水中的污染物高效转化为高附加值产品。然而,在光发酵产氢废水处理过程中,其高有机负荷、高色度和极端pH值显著抑制了微藻的污染物转化效率。因此,本研究基于原位pfe研究了核核小球藻的培养机理,并对其污染物去除能力和高附加值产品产量进行了评价。结果表明,pyrenoidosa小球藻对pfe的最佳耐受浓度约为40% %。通过优化光照强度和初始pH值,可减轻pfe对核核小球藻生长的抑制作用。在光照强度为7000 lux,初始pH= 8的条件下,最大生物量产量为1480.94 ± 5.13 mg/L。pfe对化学需氧量(COD)的去除率达到74.30 %,超过了城市污水处理厂60 %的去除率标准。对典型污染物TN、NH4+ -N和PO43—P的去除率分别为79.75 %、90.06 %和77.51 %。在高附加值产品产量方面,蛋白含量最高可达60.35 %,最高蛋白产量为887.62 ± 15.11 mg/L,较传统BG-11培养基培养组提高了235.72 %。与单一光发酵制氢工艺相比,玉米秸秆与微藻共生制氢工艺整体碳转化效率提高了56.59 %。
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引用次数: 0
Amorphous Fe–Al binary hydroxides for enhanced Arsenic removal: Mechanistic role of stoichiometry and synergistic adsorption 非晶铁铝二元氢氧化物对砷的去除:化学计量学和协同吸附的机制作用
IF 7.8 2区 环境科学与生态学 Q1 ENGINEERING, CHEMICAL Pub Date : 2026-01-31 DOI: 10.1016/j.psep.2026.108534
Maulidiah Nani Lailil Islahah , Wei Mo , Yang Yang , Shaojian Ma , Jinlin Yang , Jinpeng Feng , Xiujuan Su
Removing the highly toxic and mobile arsenite (As(III)) from water and wastewater is a persistent challenge. To address this, we designed two novel amorphous Fe–Al binary hydroxides, Fe5Al2(OH)216H2O (Fe5) and Fe7Al3(OH)306H2O (Fe7), using a simple co-precipitation method. The Fe5 adsorbent exhibited outstanding As removal, with record-high capacities of 793.65 mgg1 for As(V) and 220.75 mgg1 for As(III) at 318 K. Characterization showed that its amorphous structure, high surface area (∼204.8 m2g1), and controlled Fe/Al stoichiometry work synergistically to enhance ligand exchange and provide redox-active sites. While adsorption for both species followed chemisorption kinetics, the mechanisms differed: As(V) adsorbed via inner-sphere complexation, whereas As(III) removal involved oxidation to As(V) followed by complexation. The material’s practical potential was confirmed through its robust performance under realistic conditions, including high removal (>98.5 %) in the presence of a 10,000-fold excess of competing anions, consistent efficiency across a broad pH range, and excellent regenerability, retaining over 90 % capacity after five cycles. This study provides a high-performance, sustainable adsorbent and clarifies the critical role of stoichiometric control in tailoring amorphous materials for environmental remediation.
从水和废水中去除剧毒和可移动的亚砷酸盐(As(III))是一项持久的挑战。为了解决这个问题,我们使用简单的共沉淀法设计了两种新型无定形Fe-Al二元氢氧化物Fe5Al2(OH)21∙6H2O (Fe5)和Fe7Al3(OH)30∙6H2O (Fe7)。Fe5吸附剂表现出出色的As去除能力,在318 K下,对As(V)和As(III)的去除能力分别达到793.65 mg∙g−1和220.75 mg∙g−1。表征表明,其无定形结构、高表面积(~ 204.8 m2∙g−1)和可控的Fe/Al化学计量协同作用,促进配体交换并提供氧化还原活性位点。虽然两种物质的吸附都遵循化学吸附动力学,但机理不同:As(V)通过球内络合吸附,而As(III)的去除则通过氧化成As(V),然后进行络合。该材料的实用潜力通过其在现实条件下的强大性能得到了证实,包括在超过10,000倍的竞争阴离子存在下的高去除率(98.5%),在广泛的pH范围内保持一致的效率,以及出色的可再生性,在五次循环后保持超过90%的容量。该研究提供了一种高性能、可持续的吸附剂,并阐明了化学计量控制在定制非晶材料用于环境修复中的关键作用。
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引用次数: 0
Performance and low-carbon assessment of polymer modification processes for emulsified asphalt based on grey rational analysis 基于灰色理性分析的乳化沥青聚合物改性工艺性能及低碳评价
IF 7.8 2区 环境科学与生态学 Q1 ENGINEERING, CHEMICAL Pub Date : 2026-01-31 DOI: 10.1016/j.psep.2026.108439
Ling Xu , Shuyi Wang , Giuseppe Loprencipe , Feipeng Xiao , Yuanwen Lai
The preparation of emulsified asphalt is often challenged by initial aging and high energy consumption, particularly during high-temperature modification and inefficient emulsification. This study evaluates the performance and environmental impacts of emulsified asphalt modified with innovative waterborne polymers, featuring self-crosslinking properties. Four modifiers-epoxy resin, acrylate, nitrile rubber, and polyurethane-were incorporated at 3 %, 6 %, and 9 % dosages. Adhesion tests revealed that all self-crosslinking polymers significantly improved bonding strength, with polyurethane achieving the highest increase (over 30 % compared to the control). Rheological analyses explored using Multiple Stress Creep and Recovery tests showed that acrylate, epoxy resin, and polyurethane enhanced rutting resistance by increasing zero Viscosity and ηM values, while nitrile rubber had a softening effect. Fatigue resistance, assessed through dissipated energy calculations, also improved with crosslinking polymers but declined with nitrile rubber. Conversely, Glover–Rowe parameters at 180 kPa and 450 kPa indicated a moderate increase in low-temperature cracking susceptibility for crosslinking polymers, whereas nitrile rubber reduced cracking potential. Life-cycle assessment demonstrated that the use of waterborne polymers reduced total energy consumption by 16.55 %-17.94 % and carbon emissions by 15.64 %-16.88 % compared to traditional hot-mix processes. Finally, Grey Relational Analysis ranked 9 % polyurethane-modified asphalt as the optimal formulation considering the high-temperature environment, balancing mechanical performance and environmental benefits. Waterborne nitrile rubber showed deteriorated high-temperature rutting resistance but excellent fatigue resistance, which were suitable for anti-cracking at low temperature. These findings confirm that self-crossilinking waterborne polymers can enhance asphalt emulsion performance while reducing lifecycle energy use and emissions.
乳化沥青的制备经常面临初始老化和高能耗的挑战,特别是在高温改性和低效乳化过程中。本研究评估了具有自交联特性的创新型水性聚合物改性乳化沥青的性能和环境影响。四种改性剂——环氧树脂、丙烯酸酯、丁腈橡胶和聚氨酯——分别以3 %、6 %和9 %的剂量掺入。粘合测试显示,所有自交联聚合物都显著提高了粘合强度,其中聚氨酯的增幅最大(与对照组相比,增幅超过30% %)。通过多重应力蠕变和恢复试验进行的流变学分析表明,丙烯酸酯、环氧树脂和聚氨酯通过提高零粘度和ηM值来增强抗车辙性,而丁腈橡胶具有软化作用。通过耗散能量计算评估的抗疲劳性,使用交联聚合物也有所提高,但使用丁腈橡胶则有所下降。相反,在180 kPa和450 kPa下,Glover-Rowe参数表明交联聚合物的低温开裂敏感性适度增加,而丁腈橡胶则降低了开裂潜力。生命周期评估表明,与传统的热混合工艺相比,水性聚合物的使用减少了总能耗16.55 %-17.94 %,碳排放量15.64 %-16.88 %。最后,灰色关联分析将9 %聚氨酯改性沥青作为考虑高温环境、平衡机械性能和环境效益的最佳配方。水性丁腈橡胶耐高温车辙性能变差,但耐疲劳性能优良,适合低温抗裂。这些研究结果证实,自交联水性聚合物可以提高沥青乳液的性能,同时减少生命周期的能源消耗和排放。
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引用次数: 0
Mitigation of propylene oxide/air vapor cloud explosion shockwave hazards using protective forest belts: Experimental and numerical insights 使用防护林带减轻环氧丙烷/空气蒸气云爆炸冲击波危害:实验和数值见解
IF 7.8 2区 环境科学与生态学 Q1 ENGINEERING, CHEMICAL Pub Date : 2026-01-31 DOI: 10.1016/j.psep.2026.108539
Han Li , Linghui Zeng , Zhongqi Wang , Shenghua Fu
A propylene oxide (PO) release may lead to a vapor cloud explosion (VCE), and the resulting shockwave can still cause significant damage in the far field. Motivated by the need to control shockwave consequences for sensitive receptors such as residential areas surrounding chemical parks, this study examines the mitigation effects of protective forest belts located around the park perimeter under an already occurred VCE scenario, and provides a quantitative evaluation based on combined experiments and numerical simulations. A PO/air VCE test was conducted, and a scaled hedgerow blast experiment was employed as a surrogate validation to examine the reasonableness of vegetation-obstacle-induced shockwave attenuation trends. On this basis, an Euler-Lagrange numerical framework was established and validated against measured peak overpressures, with an average relative error of less than 10 %. Using the validated simulations, we systematically evaluated the influence of canopy coverage and tree height on hazard extents: when coverage increased from 0 % to 65 %, the equivalent safe distance decreased from 62.2 m to 54.32 m, and the fatal and severe injury areas were reduced by 55.92 % and 56.97 %, respectively; when tree height increased from 5 m to 35 m, the safe distance decreased from 61.04 m to 58.13 m, and the total hazardous area decreased by 20.54 %. To support rapid engineering assessment, semi-empirical prediction models were further developed for the total hazardous area and three injury-level zones, and the total-area model achieved an R² of 0.992 within the parameter ranges considered in this study. These results indicate that protective forest belts around chemical parks can effectively mitigate far-field shockwave consequences following a VCE, providing quantitative support for safety-distance evaluation and green buffer design.
环氧丙烷(PO)的释放可能导致蒸汽云爆炸(VCE),由此产生的冲击波仍然可以在远场造成重大损害。由于需要控制对敏感受体(如化学园区周围的居民区)的冲击波后果,本研究考察了在已经发生的VCE情景下,位于园区周边的防护林带的缓解效果,并基于联合实验和数值模拟提供了定量评估。进行了PO/air VCE试验,并采用树篱爆炸实验作为替代验证,验证了植被-障碍物诱导冲击波衰减趋势的合理性。在此基础上,建立了欧拉-拉格朗日数值框架,并根据实测的峰值超压进行了验证,平均相对误差小于10 %。系统评价了林冠盖度和树高对危险程度的影响:当林冠盖度从0 %增加到65 %时,等效安全距离从62.2 m减少到54.32 m,致命和严重伤害面积分别减少55.92 %和56.97 %;当树高从5 m增加到35 m时,安全距离从61.04 m减少到58.13 m,总危险面积减少20.54 %。为支持快速工程评价,进一步建立了总危险区和3个危险区的半经验预测模型,在本文考虑的参数范围内,总危险区模型的R²为0.992。上述结果表明,化工园区周边防护林带能够有效缓解VCE后的远场冲击波后果,为安全距离评价和绿色缓冲设计提供定量支持。
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引用次数: 0
A novel attention-enhanced deep learning framework for intelligent fault detection and diagnosis in dynamic chemical processes 一种新的基于注意力增强的深度学习框架,用于动态化工过程中的智能故障检测与诊断
IF 7.8 2区 环境科学与生态学 Q1 ENGINEERING, CHEMICAL Pub Date : 2026-01-31 DOI: 10.1016/j.psep.2026.108517
Remigius Nnadozie Ewuzie , Shivaneswar Gunasekaran , Zainal Ahmad , Norazwan Md Nor
Ensuring operational safety and reliability in chemical industries requires accurate and timely fault detection and diagnosis (FDD). Conventional machine learning and deep learning approaches often struggle to fully exploit temporal–spatial dependencies, provide interpretability, and adapt to nonlinear, time-varying process behaviors. To overcome these limitations, this study presents a novel attention-enhanced deep learning framework that integrates attention mechanisms into LSTM, GRU, and CNN architectures for intelligent FDD in dynamic chemical processes. The framework was validated using the continuous stirred-tank reactor (CSTR) benchmark involving twelve fault classes representing sensor bias, catalyst decay, and process disturbances, and benchmarked against conventional (KNN, ANN, RF) and advanced hybrid models (RATransformer, SST+CNN, KSCW-VAE). The Attention-LSTM achieved superior diagnostic performance with 98.0 % accuracy, 98.3 % F1-score, 98.2 % precision, and an inference latency of 0.493 ms. Its mean detection delay of 1.20 min confirmed rapid fault response, while a G-mean of 0.98 reflected balanced classification. Attention visualization through temporal and feature–time heatmaps enhanced interpretability. The effects of hyperparameters and activation functions were also analyzed, with Tanh and LeakyReLU yielding the best trade-off between accuracy and stability. The proposed framework offers a scalable, interpretable, and computationally efficient solution for real-time fault diagnosis in chemical processes.
为了保证化工行业运行的安全性和可靠性,需要准确、及时的故障检测和诊断(FDD)。传统的机器学习和深度学习方法往往难以充分利用时空依赖性,提供可解释性,并适应非线性、时变的过程行为。为了克服这些限制,本研究提出了一种新的注意力增强深度学习框架,该框架将注意力机制集成到LSTM、GRU和CNN架构中,用于动态化学过程中的智能FDD。该框架使用连续搅拌槽反应器(CSTR)基准进行了验证,该基准包括12个故障类别,分别代表传感器偏置、催化剂衰变和过程干扰,并针对传统(KNN、ANN、RF)和先进的混合模型(rattransformer、SST+CNN、KSCW-VAE)进行了基准测试。Attention-LSTM的诊断准确率为98.0 %,f1评分为98.3% %,准确率为98.2% %,推断延迟为0.493 ms。其平均检测延迟为1.20 min,表明故障响应迅速,g均值为0.98,表明分类均衡。通过时间和特征时间热图的注意力可视化增强了可解释性。还分析了超参数和激活函数的影响,Tanh和LeakyReLU在准确性和稳定性之间取得了最佳平衡。该框架为化工过程的实时故障诊断提供了一种可扩展、可解释、计算效率高的解决方案。
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引用次数: 0
From CFD to real-time deployment: Operator learning for instantaneous longwall mine hazard prediction 从CFD到实时部署:长壁矿井灾害瞬时预测的操作员学习
IF 7.8 2区 环境科学与生态学 Q1 ENGINEERING, CHEMICAL Pub Date : 2026-01-31 DOI: 10.1016/j.psep.2026.108537
Runzhe Hu , Yudi Tang , Boxue Pang , Shunzheng Jia , Xuebin Wu , Ismet Canbulat , Guangyao Si
Longwall mining faces persistent hazards from spontaneous combustion, methane explosion, and their coupled occurrence. Day-to-day hazard management practice relies on field monitoring, indicators, and empirical rules, while high-fidelity CFD is typically reserved for studies due to its high computational cost and specialist configuration. This study develops an operator-learning surrogate that maps three site parameters, ventilation flux, gas-emission rate, and drainage pressure, to continuous O₂ and CH₄ fields and to oxidation, explosive, and synergistic hazard masks. Trained on 2000 CFD-generated cases and evaluated on 400-case held-out test sets, the surrogate attains an R² of 0.992 for O₂ and 0.998 for CH₄, and achieves precision of 98.6 and 86.5 % for oxidation, 80.9 and 98.8 % for explosive, and 83.8 and 99.0 % for synergistic, reported for the positive and negative classes, respectively. The prediction of a single case completes within 0.015 s, which corresponds to an effective speedup of roughly 1.4 × 10⁶ relative to a six-hour CFD run. Increasing training-case cardinality yields rapid gains for the continuous fields from a few dozen to a few hundred cases, with diminishing returns beyond 200 cases, while positive-class precision for explosive and synergistic rises steadily and stabilises at 200 cases. Varying intra-case sampling density shows a marked deficit at 100–250 points per case and near-ceiling accuracy by 500–1000. The work turns CFD from a specialist, time-consuming research workflow into a practical decision-support tool for rapid scenario evaluation. This enables instantaneous prediction of goaf concentration fields and hazard maps under prescribed operating conditions, supporting shift-time planning and rapid comparison of ventilation and drainage designs with immediate visualisation.
长壁开采面临自燃、甲烷爆炸及其耦合发生的持续危害。日常的灾害管理实践依赖于现场监测、指标和经验规则,而高保真CFD由于其高计算成本和专业配置,通常只用于研究。该研究开发了一种操作员学习替代方法,将三个现场参数(通风通量、气体排放率和排水压力)映射到连续的O₂和CH₄油田,以及氧化、爆炸和协同危险面罩。在2000个cfd生成的案例上进行训练,并在400个案例的测试集上进行评估,该代理对O₂和CH₄的R²分别为0.992和0.998,对氧化的精度分别为98.6和86.5%,对爆炸的精度分别为80.9和98.8%,对协同的精度分别为83.8和99.0%。单个案例的预测在0.015 秒内完成,相对于6小时的CFD运行,这相当于大约1.4 × 10 26的有效加速。增加训练案例基数可以使连续领域从几十个案例快速增长到几百个案例,超过200个案例后收益递减,而爆炸性和协同性的正类精度稳步上升并稳定在200个案例。不同的病例内采样密度显示每个病例100-250个点的明显缺陷和500-1000个接近上限的准确性。这项工作将CFD从一个专业的、耗时的研究工作流程转变为一个用于快速情景评估的实用决策支持工具。这可以在规定的操作条件下即时预测采空区浓度场和危险图,支持轮班时间规划和快速比较通风和排水设计,并具有即时可视化。
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引用次数: 0
A dynamic Bayesian network-based probabilistic analysis method for urban gas pipelines from the perspective of “Accident-Barrier-Resilience” 基于动态贝叶斯网络的城市燃气管道“事故-屏障-恢复”概率分析方法
IF 7.8 2区 环境科学与生态学 Q1 ENGINEERING, CHEMICAL Pub Date : 2026-01-31 DOI: 10.1016/j.psep.2026.108533
Fu-qiang Yang , Hai-feng Liu , Shi-yi Li , Xing-lin Chen , Zong-hou Huang
In order to enhance the reliability of urban gas pipeline networks (UGPNs), this paper proposed a resilience assessment model based on dynamic Bayesian network (DBN). The model is constructed following a novel three-tiered “Accident-Barrier-Resilience” framework. Firstly, a Scenario Evolution and Barrier Deduction Analysis (SEBDA) method is proposed to systematically identify critical risk nodes and construct safety barrier systems based on the physical evolution paths of complete accident scenarios. Subsequently, accident evolution paths are generated via Event Tree Analysis (ETA). Finally, a DBN-based resilience assessment layer quantifies the system's time-varying performance. A computational resilience model was developed to simulate and quantify the resilience characteristics of UGPNs under disruption scenarios. The impact of different accident scenarios on the reliability of resilience nodes was then analyzed. The results show that the three resilience capacities (absorption, adaptation, and restorative) play corresponding functions to drive the overall resilience of the pipeline network system. Criticality analysis of resilience nodes identifies that pipeline diameter and wall thickness are the two most critical factors affecting the resilience of gas pipeline networks. Furthermore, the study incorporates learning ability as a key factor, demonstrating that it effectively influences the resilience attributes of the UGPN system. The dynamic model extends the static model through the incorporation of a resilience network. This enhancement improves operational reliability by explicitly accounting for resilience impacts on UGPNs. The gas network can ultimately have the potential to adequately handle disturbances by consistently implementing the improvement plan.
为了提高城市燃气管网的可靠性,提出了一种基于动态贝叶斯网络(DBN)的弹性评估模型。该模型是根据一个新颖的三层“事故-障碍-弹性”框架构建的。首先,提出了基于完整事故场景物理演化路径的场景演化与屏障演绎分析(SEBDA)方法,系统识别关键风险节点,构建安全屏障系统;随后,通过事件树分析(ETA)生成事故演化路径。最后,基于dbn的弹性评估层量化了系统的时变性能。建立了一个计算弹性模型来模拟和量化ugpn在中断情景下的弹性特性。分析了不同事故场景对弹性节点可靠性的影响。结果表明,吸收、适应和恢复三种弹性能力对管网系统的整体弹性起着相应的驱动作用。弹性节点的临界性分析表明,管径和管壁厚度是影响天然气管网弹性的两个最关键因素。此外,研究将学习能力作为一个关键因素,表明它有效地影响了UGPN系统的弹性属性。动态模型通过纳入弹性网络来扩展静态模型。这种增强通过明确地考虑对ugpn的弹性影响来提高操作可靠性。通过持续实施改进计划,天然气网络最终有可能充分处理干扰。
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引用次数: 0
Atomic-scale insights into solidification behaviors of nitrogen-oxygen mixture: A molecular dynamics study 氮氧混合物凝固行为的原子尺度洞察:分子动力学研究
IF 7.8 2区 环境科学与生态学 Q1 ENGINEERING, CHEMICAL Pub Date : 2026-01-31 DOI: 10.1016/j.psep.2026.108543
Shi Shangguan , Lei Wang , Yanzhong Li , Gang Lei
The intrusion of atmospheric components into liquid hydrogen (LH2) system may pose significant safety hazards to the hydrogen storage and application, especially when solidified air with an oxygen-enriched surface occurs in the LH2 that could amplify the explosion risk. In this paper, Lennard-Jones (LJ) potential parameters for nitrogen and oxygen were optimized, and the maximum deviation of 7 % in predicting the key molecular system properties within the solidification temperature ranges was achieved. Based on the modified potential model, the solidification behaviors of the nitrogen-oxygen mixture under different cryogenic conditions were investigated using molecular dynamics (MD) simulation method. For the molecular system consisting of nitrogen and oxygen molecules, the results showed that the phenomenon of aggregation of nitrogen molecules or oxygen molecules did not occur during the cooling process. For the solidification of nitrogen and oxygen on a cold boundary constructed with copper atoms, comparatively, nitrogen molecules were more prone to concentrating near the cold boundary due to the difference in solidification temperatures of nitrogen and oxygen. For nitrogen and oxygen solidifying in a cold hydrogen atmosphere, it was found the proportion of oxygen molecules on the outer layer of the formed solid-air molecular cluster increased by 5.5 %, while that in the middle layer rose by 17.7 % and that in the inner layer decreased by 72.4 %. This phenomenon indicates that oxygen would gradually diffuse from the interior to the exterior during the cooling process in a hydrogen environment, resulting in an oxygen-rich outer layer in the solidified air. This work reveals the formation characteristics of oxygen-rich surfaces in solidified air deposits, providing critical theoretical support for improving safety assessment and hazard prevention strategies in LH2 system.
大气成分侵入液氢系统会给液氢系统的储氢和应用带来重大安全隐患,特别是液氢系统中出现表面富氧的凝固空气时,爆炸危险性会增大。本文对氮气和氧气的Lennard-Jones (LJ)电位参数进行了优化,在凝固温度范围内预测关键分子体系性能的最大偏差为7 %。基于修正电位模型,采用分子动力学(MD)模拟方法研究了不同低温条件下氮氧混合物的凝固行为。对于由氮分子和氧分子组成的分子体系,结果表明,在冷却过程中没有发生氮分子或氧分子聚集的现象。对于氮和氧在铜原子构成的冷边界上的凝固,由于氮和氧的凝固温度不同,氮分子在冷边界附近更容易集中。氮氧在冷氢气氛下凝固,形成的固体-空气分子团外层氧分子的比例增加了5.5 %,中间层氧分子的比例增加了17.7 %,内层氧分子的比例减少了72.4 %。这一现象说明在氢气环境中,氧气在冷却过程中会逐渐从内部向外部扩散,导致凝固空气中形成富氧的外层。该研究揭示了凝固空气沉积物中富氧表面的形成特征,为改进LH2系统的安全评价和危害预防策略提供了重要的理论支持。
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引用次数: 0
Explosion characteristics and kinetic mechanism of oxygen-enriched ultra-lean coal mine methane blended with propane 富氧超贫煤矿瓦斯与丙烷混合的爆炸特性及动力学机理
IF 7.8 2区 环境科学与生态学 Q1 ENGINEERING, CHEMICAL Pub Date : 2026-01-31 DOI: 10.1016/j.psep.2026.108540
Xiaotong Wang , Baisheng Nie , Weili Wang , Yushu Zhang , Bei Hu , Xinyu Ma , Feifei Yin
Ultra-lean coal mine methane is often directly vented due to utilization difficulties, resulting in significant energy waste and carbon emissions. To achieve its resource utilization, this study systematically investigated the explosion characteristics and kinetic mechanisms of oxygen-enriched ultra-lean methane blended with propane via experiments and chemical kinetic simulations. Experimental results indicated that increasing the oxygen enrichment coefficient and equivalence ratio significantly elevated the maximum explosion pressure, maximum pressure rise rate, and explosion energy, thereby defining the optimal operating parameters. Kinetic simulations revealed that oxygen enrichment and propane addition enhanced the overall reaction rate of OH radicals. Key elementary reactions promoting OH generation were identified as R3, R38, R46, and R86, while R84, R99, and R101 dominated OH consumption. Furthermore, reaction path analysis demonstrated that propane undergoes chain reactions before methane during the initial ignition stage, acting as an effective promoter. These findings provide a theoretical basis for the safe development of oxygen-enriched ultra-lean methane power generation technology, contributing to near-zero methane emissions and carbon neutrality goals.
超贫煤矿瓦斯由于利用困难,往往直接排放,造成严重的能源浪费和碳排放。为实现其资源化利用,本研究通过实验和化学动力学模拟,系统研究了富氧超贫甲烷与丙烷混合的爆炸特性和动力学机理。实验结果表明,增大氧富集系数和当量比可显著提高最大爆炸压力、最大升压速率和爆炸能量,从而确定最佳运行参数。动力学模拟表明,氧富集和丙烷的加入提高了OH自由基的总反应速率。促进OH生成的关键元素反应为R3、R38、R46和R86,而OH消耗主要为R84、R99和R101。此外,反应路径分析表明,丙烷在初始点火阶段先于甲烷发生链式反应,起到了有效的促进剂作用。这些发现为富氧超贫甲烷发电技术的安全开发提供了理论基础,有助于实现甲烷近零排放和碳中和目标。
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引用次数: 0
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Process Safety and Environmental Protection
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