Pub Date : 2026-01-31DOI: 10.1016/j.psep.2026.108524
Junlei Li , Jinpeng Zhao , Chenglong Zhang , Yonghai Zhang , Haixiao Liu , Shuaiwei Gu , Fengqi Li , Pengfei Duan , Jinjia Wei
Hydrogen‑enriched methane (HEM) is a promising bridge fuel for hydrogen‑ready gas networks, yet rapid, accurate prediction of its high‑hydrogen combustion behavior remains challenging. We present a multitask‑learning (MTL) framework that simultaneously predicts laminar burning velocity (LBV) and ignition delay time (IDT) for HEM with 60–100 % hydrogen volume fraction (HVF). The network is trained on data produced with a new 39‑steps skeletal mechanism—extracted from GRI‑Mech 3.0 via DRGEP and sensitivity analysis—and validated against computational‑fluid‑dynamics jet‑flame simulations covering HVF, equivalence ratio (Φ) and nozzle radius. The MTL model yields R² = 0.99 for LBV and perfect ignition‑state classification while preserving the physical coupling between the two tasks. Coupling the MTL outputs with a Damköhler‑number turbulent‑flame‑speed correction enables fast mapping of flame fronts and explosion‑hazard zones in pipeline‑leak scenarios. By integrating reduced chemistry, high‑fidelity computational fluid dynamics (CFD) and data‑driven inference, the workflow offers an efficient, physically consistent tool for Quantitative Risk Assessment of hydrogen‑rich combustion systems.
{"title":"Reduced-mechanism supported multitask learning model for fast flame hazard mapping in hydrogen-enriched methane jets","authors":"Junlei Li , Jinpeng Zhao , Chenglong Zhang , Yonghai Zhang , Haixiao Liu , Shuaiwei Gu , Fengqi Li , Pengfei Duan , Jinjia Wei","doi":"10.1016/j.psep.2026.108524","DOIUrl":"10.1016/j.psep.2026.108524","url":null,"abstract":"<div><div>Hydrogen‑enriched methane (HEM) is a promising bridge fuel for hydrogen‑ready gas networks, yet rapid, accurate prediction of its high‑hydrogen combustion behavior remains challenging. We present a multitask‑learning (MTL) framework that simultaneously predicts laminar burning velocity (LBV) and ignition delay time (IDT) for HEM with 60–100 % hydrogen volume fraction (HVF). The network is trained on data produced with a new 39‑steps skeletal mechanism—extracted from GRI‑Mech 3.0 via DRGEP and sensitivity analysis—and validated against computational‑fluid‑dynamics jet‑flame simulations covering HVF, equivalence ratio (<em>Φ</em>) and nozzle radius. The MTL model yields <em>R</em>² = 0.99 for LBV and perfect ignition‑state classification while preserving the physical coupling between the two tasks. Coupling the MTL outputs with a Damköhler‑number turbulent‑flame‑speed correction enables fast mapping of flame fronts and explosion‑hazard zones in pipeline‑leak scenarios. By integrating reduced chemistry, high‑fidelity computational fluid dynamics (CFD) and data‑driven inference, the workflow offers an efficient, physically consistent tool for Quantitative Risk Assessment of hydrogen‑rich combustion systems.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"208 ","pages":"Article 108524"},"PeriodicalIF":7.8,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146095882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-31DOI: 10.1016/j.psep.2026.108531
Changhe Wu , Ridong Zhang , Furong Gao
To address the impact of strong coupling in chemical processes fault diagnosis, this paper proposes a novel fault diagnosis network called EOI: Encoder for "One-dimensional Image." By modifying the Transformer Encoder-only architecture to construct the EOI network, we enable the computer to understand this "image" through supervised learning. The architecture proposed in this paper mainly contains three improvements to the Encoder. Firstly, it removes the position encoding to prevent the introduction of noise signals. Secondly, it employs the Squeeze-and-Excitation (SE) attention module from the field of image processing and adapts it to a one-dimensional version. Finally, it improves the traditional Feed-Forward Network (FFN) module based on the idea of Convolutional Neural Network (CNN). The designed EOI network integrates traditional CNN and Long Short-Term Memory (LSTM) networks, significantly enhancing feature extraction efficiency for chemical time-series data and improving fault diagnosis accuracy. Experiments on the Tennessee Eastman (TE) process and industrial coke furnace have demonstrated that the proposed network exhibits high performance.
{"title":"A novel design of Transformer Encoder-only network model for fault diagnosis in strongly coupled industrial processes","authors":"Changhe Wu , Ridong Zhang , Furong Gao","doi":"10.1016/j.psep.2026.108531","DOIUrl":"10.1016/j.psep.2026.108531","url":null,"abstract":"<div><div>To address the impact of strong coupling in chemical processes fault diagnosis, this paper proposes a novel fault diagnosis network called EOI: Encoder for \"One-dimensional Image.\" By modifying the Transformer Encoder-only architecture to construct the EOI network, we enable the computer to understand this \"image\" through supervised learning. The architecture proposed in this paper mainly contains three improvements to the Encoder. Firstly, it removes the position encoding to prevent the introduction of noise signals. Secondly, it employs the Squeeze-and-Excitation (SE) attention module from the field of image processing and adapts it to a one-dimensional version. Finally, it improves the traditional Feed-Forward Network (FFN) module based on the idea of Convolutional Neural Network (CNN). The designed EOI network integrates traditional CNN and Long Short-Term Memory (LSTM) networks, significantly enhancing feature extraction efficiency for chemical time-series data and improving fault diagnosis accuracy. Experiments on the Tennessee Eastman (TE) process and industrial coke furnace have demonstrated that the proposed network exhibits high performance.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"208 ","pages":"Article 108531"},"PeriodicalIF":7.8,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-31DOI: 10.1016/j.psep.2026.108536
Jingling Zhao , Xingqing Yan , Shuai Yu , Lei Chen , Jianliang Yu
Nano-aluminum/n-heptane fluid fuels hold broad application prospects in military and aerospace industries; however, their explosion hazards remain poorly understood. This study employs a cubic confined chamber with optical access to investigate the impact of aluminum particle loading (0.5 wt%–6 wt%) on explosion pressure and flame propagation characteristics of fluid fuels within a concentration range of 64.33 g/m³ to 175.74 g/m³ . With increasing aluminum mass fraction, both the peak explosion pressure (Pmax) and the peak pressure rise rate ((dP/dt)max) of aluminum/n-heptane fluid fuels first increase and then decrease. At a concentration of 112.92 g/m³ and a mass fraction of1wt% aluminum, Pmax and (dP/dt)max peak at 1.31 MPa and 66.1 MPa/s, respectively, representing increases of 14.08 % and 22.86 % compared to pure n-heptane. Aluminum particle addition intensifies flame brightness and accelerates flame propagation. Combined with an analysis of the explosion residues, the reaction mechanism of the fluid fuel explosion is elucidated. Chemical kinetics calculations show that aluminum particle addition promotes the consumption of key radicals (H, O, and OH), increases the adiabatic flame temperature, and thereby enhances the overall explosion reaction. These findings provide important guidance for the promotion and safe application of aluminum/n-heptane nanofluid fuels in engineering fields.
{"title":"Study on the explosion characteristics and reaction mechanisms of Aluminum/n-heptane nanofluid fuel in a confined chamber","authors":"Jingling Zhao , Xingqing Yan , Shuai Yu , Lei Chen , Jianliang Yu","doi":"10.1016/j.psep.2026.108536","DOIUrl":"10.1016/j.psep.2026.108536","url":null,"abstract":"<div><div>Nano-aluminum/n-heptane fluid fuels hold broad application prospects in military and aerospace industries; however, their explosion hazards remain poorly understood. This study employs a cubic confined chamber with optical access to investigate the impact of aluminum particle loading (0.5 wt%–6 wt%) on explosion pressure and flame propagation characteristics of fluid fuels within a concentration range of 64.33 g/m³ to 175.74 g/m³ . With increasing aluminum mass fraction, both the peak explosion pressure (P<sub>max</sub>) and the peak pressure rise rate ((dP/dt)<sub>max</sub>) of aluminum/n-heptane fluid fuels first increase and then decrease. At a concentration of 112.92 g/m³ and a mass fraction of1wt% aluminum, P<sub>max</sub> and (dP/dt)<sub>max</sub> peak at 1.31 MPa and 66.1 MPa/s, respectively, representing increases of 14.08 % and 22.86 % compared to pure n-heptane. Aluminum particle addition intensifies flame brightness and accelerates flame propagation. Combined with an analysis of the explosion residues, the reaction mechanism of the fluid fuel explosion is elucidated. Chemical kinetics calculations show that aluminum particle addition promotes the consumption of key radicals (H, O, and OH), increases the adiabatic flame temperature, and thereby enhances the overall explosion reaction. These findings provide important guidance for the promotion and safe application of aluminum/n-heptane nanofluid fuels in engineering fields.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"209 ","pages":"Article 108536"},"PeriodicalIF":7.8,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146095893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-30DOI: 10.1016/j.psep.2026.108528
Li Lin , Lei Dong , Haibo Zhang , Guochuan Yin , Zhuqi Chen , Haiyang Jin , Xingrui Qi , Xiong Pan , Yu Gao
This study presents the first comprehensive investigation of hydrological rhythm–driven patterns of polycyclic aromatic hydrocarbons (PAHs) and phthalate esters (PAEs) in sediments from Danjiangkou Reservoir (the core water source of the South-to-North Water Diversion Project’s central route). Results demonstrate that hydrological rhythms dominate the pollution differentiation of PAHs and PAEs: PAHs peak during the dry season with a mean concentration of 139.7 ng/g (66.6 % contributed by mixed combustion sources), while PAEs peak in the flood season (mean: 286.5 ng/g, with 59.5 % originating from the use and discharge of solvents used in personal care products). These seasonal peaking phenomena systematically reveal hydrology-driven differences in pollutant peak timing and challenges the conventional attribution of PAEs primarily to plasticizer sources. These findings challenge the conventional perception of PAEs as plasticizers. Integrating a multitechnical chain comprising positive matrix factorization for source apportionment, partial least squares structural equation modeling for factor analysis, and machine learning predictive models, the contribution rates from different sources are quantified, providing the first evidence that total phosphorus negatively regulates ΣPAHs/DEHP (DEHP = di-(2-ethylhexyl)phthalate). The innovation of this study lies in the establishment of an integrated “entire–local” predictive framework for PAE prediction; this framework integrates the Stacking model (which best predicts the PAE concentration over entire the Danjiangkou Reservoir) and the XGBoost model (which can be locally optimized in sub-regions of the reservoir). Considering the risk heterogeneity driven by hydrological periodicity, this study proposes prioritized control of mixed combustion sources for PAHs during the dry season, and the continuous regulation of solvent usage and emissions (e.g., personal care products) for PAEs across three hydrological periods. These findings provide theoretical paradigms and intelligent technological support for sediment risk management in large-scale water diversion projects.
{"title":"Spatiotemporal variability of PAHs and PAEs in sediments driven by hydrological rhythms in Danjiangkou Reservoir, China: Multisource analysis to machine-learning prediction","authors":"Li Lin , Lei Dong , Haibo Zhang , Guochuan Yin , Zhuqi Chen , Haiyang Jin , Xingrui Qi , Xiong Pan , Yu Gao","doi":"10.1016/j.psep.2026.108528","DOIUrl":"10.1016/j.psep.2026.108528","url":null,"abstract":"<div><div>This study presents the first comprehensive investigation of hydrological rhythm–driven patterns of polycyclic aromatic hydrocarbons (PAHs) and phthalate esters (PAEs) in sediments from Danjiangkou Reservoir (the core water source of the South-to-North Water Diversion Project’s central route). Results demonstrate that hydrological rhythms dominate the pollution differentiation of PAHs and PAEs: PAHs peak during the dry season with a mean concentration of 139.7 ng/g (66.6 % contributed by mixed combustion sources), while PAEs peak in the flood season (mean: 286.5 ng/g, with 59.5 % originating from the use and discharge of solvents used in personal care products). These seasonal peaking phenomena systematically reveal hydrology-driven differences in pollutant peak timing and challenges the conventional attribution of PAEs primarily to plasticizer sources. These findings challenge the conventional perception of PAEs as plasticizers. Integrating a multitechnical chain comprising positive matrix factorization for source apportionment, partial least squares structural equation modeling for factor analysis, and machine learning predictive models, the contribution rates from different sources are quantified, providing the first evidence that total phosphorus negatively regulates ΣPAHs/DEHP (DEHP = di-(2-ethylhexyl)phthalate). The innovation of this study lies in the establishment of an integrated “entire–local” predictive framework for PAE prediction; this framework integrates the Stacking model (which best predicts the PAE concentration over entire the Danjiangkou Reservoir) and the XGBoost model (which can be locally optimized in sub-regions of the reservoir). Considering the risk heterogeneity driven by hydrological periodicity, this study proposes prioritized control of mixed combustion sources for PAHs during the dry season, and the continuous regulation of solvent usage and emissions (e.g., personal care products) for PAEs across three hydrological periods. These findings provide theoretical paradigms and intelligent technological support for sediment risk management in large-scale water diversion projects.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"208 ","pages":"Article 108528"},"PeriodicalIF":7.8,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-30DOI: 10.1016/j.psep.2026.108523
Yuxin Huang , Zhenmin Luo , Shugang Li , Jingdao Fan , Zhenguo Yan
This study examines damage to solid structures from gas explosions to improve hazard prevention. A numerical model of dynamic damage under fluid-thermal-structural coupling was developed. Factors including load, pipeline geometry, gas concentration, and distance from ignition were analyzed to compare stress and strain distributions. The coupling mechanism of shock waves and thermal effects was investigated, revealing the structural dynamic damage process. It was found that stress and strain concentrations were first observed near fixed boundaries, then propagated inward, with peak stress near boundaries and the center. Below the stoichiometric concentration, each 1 % gas increase raised stress by about 5 %; above it, each 1 % decrease raised stress by about 3 %. Pipeline geometry showed limited effect on stress mitigation. During shock wave decay, the central region was sensitive to distance attenuation, while boundary areas were not. Shock waves were identified as the main driver of stress evolution. A quantitative relation between equivalent stress and combined mechanical-thermal stress was derived. These findings support damage assessment in gas explosion events and aid in preventing hazard escalation.
{"title":"Numerical study on the damage characteristics of solid facilities due to coal mine gas explosion under fluid-thermal-structural coupling conditions","authors":"Yuxin Huang , Zhenmin Luo , Shugang Li , Jingdao Fan , Zhenguo Yan","doi":"10.1016/j.psep.2026.108523","DOIUrl":"10.1016/j.psep.2026.108523","url":null,"abstract":"<div><div>This study examines damage to solid structures from gas explosions to improve hazard prevention. A numerical model of dynamic damage under fluid-thermal-structural coupling was developed. Factors including load, pipeline geometry, gas concentration, and distance from ignition were analyzed to compare stress and strain distributions. The coupling mechanism of shock waves and thermal effects was investigated, revealing the structural dynamic damage process. It was found that stress and strain concentrations were first observed near fixed boundaries, then propagated inward, with peak stress near boundaries and the center. Below the stoichiometric concentration, each 1 % gas increase raised stress by about 5 %; above it, each 1 % decrease raised stress by about 3 %. Pipeline geometry showed limited effect on stress mitigation. During shock wave decay, the central region was sensitive to distance attenuation, while boundary areas were not. Shock waves were identified as the main driver of stress evolution. A quantitative relation between equivalent stress and combined mechanical-thermal stress was derived. These findings support damage assessment in gas explosion events and aid in preventing hazard escalation.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"208 ","pages":"Article 108523"},"PeriodicalIF":7.8,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Among the microplastics (MPs) detected in wastewater treatment plants (WWTPs), polypropylene microplastics (PP-MPs) contributed the most to the mass. However, research on their impacts on anaerobic ammonium oxidation (anammox) processes remained scarce. This research investigated the influence of PP-MPs on anammox from both the macroscopic (performance efficiency and microbial community changes) and microscopic (cellular activities, metabolic mechanisms, and spread of antibiotic resistance genes (ARGs)) perspectives. Also, the recovery potential of biochar on PP-MPs-stressed anammox systems was explored. The effect of PP-MPs on the anammox process exhibited a characteristic pattern of initial inhibition followed by recovery. Analysis of microbial communities revealed that Ca. Brocadia exhibited superior adaptability to PP-MPs compared to other anaerobic ammonium-oxidizing bacteria. Ignavibacterium demonstrated better adaptation to both PP-MPs and biochar, and exhibited cross-feeding with Ca. Brocadia, thereby promoting the total nitrogen removal efficiency (TNRE). However, this process also elevated the risk of ARGs proliferating within the anammox system. This study elucidated the combined effects and potential risks of PP-MPs on the anammox system, providing theoretical support for optimizing the anammox process to treat wastewater containing PP-MPs.
{"title":"Microplastics reshape anammox microbial consortia: Insights into stress adaptation, metabolic interplay, and antibiotic resistance trade-offs in wastewater treatment","authors":"Long Wu , Xiaonong Zhang , Xingxing Zhang , Peng Wu","doi":"10.1016/j.psep.2026.108521","DOIUrl":"10.1016/j.psep.2026.108521","url":null,"abstract":"<div><div>Among the microplastics (MPs) detected in wastewater treatment plants (WWTPs), polypropylene microplastics (PP-MPs) contributed the most to the mass. However, research on their impacts on anaerobic ammonium oxidation (anammox) processes remained scarce. This research investigated the influence of PP-MPs on anammox from both the macroscopic (performance efficiency and microbial community changes) and microscopic (cellular activities, metabolic mechanisms, and spread of antibiotic resistance genes (ARGs)) perspectives. Also, the recovery potential of biochar on PP-MPs-stressed anammox systems was explored. The effect of PP-MPs on the anammox process exhibited a characteristic pattern of initial inhibition followed by recovery. Analysis of microbial communities revealed that <em>Ca. Brocadia</em> exhibited superior adaptability to PP-MPs compared to other anaerobic ammonium-oxidizing bacteria. <em>Ignavibacterium</em> demonstrated better adaptation to both PP-MPs and biochar, and exhibited cross-feeding with <em>Ca. Brocadia</em>, thereby promoting the total nitrogen removal efficiency (TNRE). However, this process also elevated the risk of ARGs proliferating within the anammox system. This study elucidated the combined effects and potential risks of PP-MPs on the anammox system, providing theoretical support for optimizing the anammox process to treat wastewater containing PP-MPs.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"208 ","pages":"Article 108521"},"PeriodicalIF":7.8,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-30DOI: 10.1016/j.psep.2026.108520
Qunfang Hu , Zongyuan Zhang , Fei Wang , Zhan Su , Qiang Zhang , Jiahua Zhou
Corrosion poses a critical challenge to the integrity of urban pipeline infrastructure systems. In buried metallic pipelines, long-term exposure to aggressive soils often causes pitting corrosion with irregular defect shapes and variable depths, driven by multiple interacting environmental and operational factors. Traditional data-driven models for predicting pitting corrosion depth in buried metallic pipelines exhibit significant limitations, particularly in terms of physical consistency and interpretability. This study presents a novel methodology that incorporates Physics-Informed Neural Networks (PINNs) with domain-specific physical knowledge. By embedding fundamental physical laws governing the relationship between corrosion depth and time into the neural network training process, the PINN model effectively combines physical constraints with data-driven techniques, enabling precise predictions of complex nonlinear corrosion behaviors. The model is trained and validated on a dataset comprising 259 coated steel pipe samples, which reflect diverse corrosion scenarios and varying defect severity. Results demonstrate that the PINN model significantly outperforms conventional approaches, including Artificial Neural Networks (ANN), achieving superior metrics on the test dataset (R² = 0.93, MAE = 0.34, RMSE = 0.42). Moreover, the model exhibits remarkable robustness and generalization capability under extreme corrosion conditions. SHAP analysis further validated the model's high sensitivity to key features, including pH value, chloride content, and pipeline age, revealing that acidic conditions and high chloride levels significantly accelerate corrosion progression through enhanced electrochemical degradation mechanisms, while effectively capturing complex feature interactions. By incorporating physics-based constraints into the learning framework, this approach enhances both prediction reliability and model interpretability, particularly in scenarios characterized by limited data availability and high measurement noise. The developed methodology provides valuable technical support for pipeline integrity management and offers practical applications in corrosion assessment, risk monitoring, and maintenance optimization, thereby contributing to enhanced operational safety and reliability of pipeline systems.
{"title":"A physics-informed neural network method for predicting maximum pitting corrosion depth in pipelines","authors":"Qunfang Hu , Zongyuan Zhang , Fei Wang , Zhan Su , Qiang Zhang , Jiahua Zhou","doi":"10.1016/j.psep.2026.108520","DOIUrl":"10.1016/j.psep.2026.108520","url":null,"abstract":"<div><div>Corrosion poses a critical challenge to the integrity of urban pipeline infrastructure systems. In buried metallic pipelines, long-term exposure to aggressive soils often causes pitting corrosion with irregular defect shapes and variable depths, driven by multiple interacting environmental and operational factors. Traditional data-driven models for predicting pitting corrosion depth in buried metallic pipelines exhibit significant limitations, particularly in terms of physical consistency and interpretability. This study presents a novel methodology that incorporates Physics-Informed Neural Networks (PINNs) with domain-specific physical knowledge. By embedding fundamental physical laws governing the relationship between corrosion depth and time into the neural network training process, the PINN model effectively combines physical constraints with data-driven techniques, enabling precise predictions of complex nonlinear corrosion behaviors. The model is trained and validated on a dataset comprising 259 coated steel pipe samples, which reflect diverse corrosion scenarios and varying defect severity. Results demonstrate that the PINN model significantly outperforms conventional approaches, including Artificial Neural Networks (ANN), achieving superior metrics on the test dataset (R² = 0.93, MAE = 0.34, RMSE = 0.42). Moreover, the model exhibits remarkable robustness and generalization capability under extreme corrosion conditions. SHAP analysis further validated the model's high sensitivity to key features, including pH value, chloride content, and pipeline age, revealing that acidic conditions and high chloride levels significantly accelerate corrosion progression through enhanced electrochemical degradation mechanisms, while effectively capturing complex feature interactions. By incorporating physics-based constraints into the learning framework, this approach enhances both prediction reliability and model interpretability, particularly in scenarios characterized by limited data availability and high measurement noise. The developed methodology provides valuable technical support for pipeline integrity management and offers practical applications in corrosion assessment, risk monitoring, and maintenance optimization, thereby contributing to enhanced operational safety and reliability of pipeline systems.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"208 ","pages":"Article 108520"},"PeriodicalIF":7.8,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-30DOI: 10.1016/j.psep.2026.108515
Xiang Wang , Yuxin He , Ke Wang , Lijun Yang , Yuan Yuan , Yikun Zhao , Zongliang Zhang , Jiaxi Li , Chen Chen
To enhance the explosion-proof performance of power transformers and support structural assessment of transformer tanks, a bidirectional fluid-structure interaction numerical method is proposed. This approach predicts gas generation from oil pyrolysis, pressure wave propagation, and the dynamic response of the tank structure induced by internal arcing faults. By incorporating the pyrolysis kinetics of insulating oil, two-phase multi-component continuity equations are established based on the conservation of mass to capture the complete evolution of the insulating oil, ranging from heterogeneous pyrolysis, defined as the evaporative phase transition and initial pyrolysis, to gas-phase homogeneous deep pyrolysis. Based on charge conservation, arc energy is incorporated into the energy equation as a volumetric heat source that drives oil pyrolysis. Furthermore, the dynamic behavior of the pressure relief valve is modeled using a porous media approach by adding a resistance source term to the momentum equation. Model accuracy is verified on a split-type tank arc platform by two tests with energies of 0.65 MJ and 1.28 MJ in the tap-changer oil compartment. The simulation results agree well with the test data in the pressure and stress time histories and accurately reproduce the pressure impact, bubble pulsation and venting. The maximum relative errors for peak pressure and stress were 9.65 % and 26.97 %, respectively, with a mass conservation error within 1.14 %. This work offers an effective tool for elucidating gas generation and pressure propagation mechanisms, providing a quantitative basis for the explosion-resistant design and safety assessment of transformer tanks.
{"title":"Evaluation method for explosion resistance of oil-immersed power equipment tanks under internal arcing faults","authors":"Xiang Wang , Yuxin He , Ke Wang , Lijun Yang , Yuan Yuan , Yikun Zhao , Zongliang Zhang , Jiaxi Li , Chen Chen","doi":"10.1016/j.psep.2026.108515","DOIUrl":"10.1016/j.psep.2026.108515","url":null,"abstract":"<div><div>To enhance the explosion-proof performance of power transformers and support structural assessment of transformer tanks, a bidirectional fluid-structure interaction numerical method is proposed. This approach predicts gas generation from oil pyrolysis, pressure wave propagation, and the dynamic response of the tank structure induced by internal arcing faults. By incorporating the pyrolysis kinetics of insulating oil, two-phase multi-component continuity equations are established based on the conservation of mass to capture the complete evolution of the insulating oil, ranging from heterogeneous pyrolysis, defined as the evaporative phase transition and initial pyrolysis, to gas-phase homogeneous deep pyrolysis. Based on charge conservation, arc energy is incorporated into the energy equation as a volumetric heat source that drives oil pyrolysis. Furthermore, the dynamic behavior of the pressure relief valve is modeled using a porous media approach by adding a resistance source term to the momentum equation. Model accuracy is verified on a split-type tank arc platform by two tests with energies of 0.65 MJ and 1.28 MJ in the tap-changer oil compartment. The simulation results agree well with the test data in the pressure and stress time histories and accurately reproduce the pressure impact, bubble pulsation and venting. The maximum relative errors for peak pressure and stress were 9.65 % and 26.97 %, respectively, with a mass conservation error within 1.14 %. This work offers an effective tool for elucidating gas generation and pressure propagation mechanisms, providing a quantitative basis for the explosion-resistant design and safety assessment of transformer tanks.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"209 ","pages":"Article 108515"},"PeriodicalIF":7.8,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-30DOI: 10.1016/j.psep.2026.108522
Dongdong Zhu , Li Zhou , Qiuying Lai , Ziyu Gong , Yan Wang , Xiaoshuai Hang
The accumulation of methylmercury (MeHg) poses risks to both ecosystems and human health. It is well established that the methylation of mercury (Hg) in sediments, facilitated by microbial activity, is influenced by the cycles of carbon (C) and nitrogen (N), although the specific mechanisms are not fully understood. This study investigates the effects of carbon and nitrogen on Hg methylation in the sediments of Xuanwu Lake, a typical urban shallow lake. The findings revealed significant spatial variability in the concentrations of Hg and MeHg across different areas of the water and sediment. A positive correlation was found between total organic carbon (TOC), total nitrogen (TN), and ammonia nitrogen (NH4+-N) in sediments with MeHg, while a notable negative correlation was observed with nitrate nitrogen (NO3--N) (p ≤ 0.05). In anaerobic incubation experiments, the addition of carbon (in the form of glucose) significantly enhanced both denitrification and Hg methylation, resulting in the highest MeHg concentration (2.01 μg/kg) and methylation rate (1.00 %), along with an increase in the bacterial phylum Firmicutes and genera such as Clostridium sensu stricto. Conversely, the introduction of nitrogen (sodium nitrate) hindered this process, with the MeHg concentration dropping to 0.77 μg/kg and a methylation rate of 0.34 %. It was demonstrated that high carbon concentration was found to expedite Hg methylation, while elevated nitrogen levels hindered MeHg production, with the underlying mechanisms being influenced by the interplay of carbon and nitrogen in denitrification and the associated microbial community. The study revealed the carbon and nitrogen effects on Hg methylation in sediments, providing insights for ecological restoration engineering applications of Hg pollution in eutrophic lakes.
{"title":"Carbon and Nitrogen mediated denitrification modulates the methylation process of mercury in lake sediments","authors":"Dongdong Zhu , Li Zhou , Qiuying Lai , Ziyu Gong , Yan Wang , Xiaoshuai Hang","doi":"10.1016/j.psep.2026.108522","DOIUrl":"10.1016/j.psep.2026.108522","url":null,"abstract":"<div><div>The accumulation of methylmercury (MeHg) poses risks to both ecosystems and human health. It is well established that the methylation of mercury (Hg) in sediments, facilitated by microbial activity, is influenced by the cycles of carbon (C) and nitrogen (N), although the specific mechanisms are not fully understood. This study investigates the effects of carbon and nitrogen on Hg methylation in the sediments of Xuanwu Lake, a typical urban shallow lake. The findings revealed significant spatial variability in the concentrations of Hg and MeHg across different areas of the water and sediment. A positive correlation was found between total organic carbon (TOC), total nitrogen (TN), and ammonia nitrogen (NH<sub>4</sub><sup>+</sup>-N) in sediments with MeHg, while a notable negative correlation was observed with nitrate nitrogen (NO<sub>3</sub><sup>-</sup>-N) (<em>p</em> ≤ 0.05). In anaerobic incubation experiments, the addition of carbon (in the form of glucose) significantly enhanced both denitrification and Hg methylation, resulting in the highest MeHg concentration (2.01 μg/kg) and methylation rate (1.00 %), along with an increase in the bacterial phylum <em>Firmicutes</em> and genera such as <em>Clostridium sensu stricto</em>. Conversely, the introduction of nitrogen (sodium nitrate) hindered this process, with the MeHg concentration dropping to 0.77 μg/kg and a methylation rate of 0.34 %. It was demonstrated that high carbon concentration was found to expedite Hg methylation, while elevated nitrogen levels hindered MeHg production, with the underlying mechanisms being influenced by the interplay of carbon and nitrogen in denitrification and the associated microbial community. The study revealed the carbon and nitrogen effects on Hg methylation in sediments, providing insights for ecological restoration engineering applications of Hg pollution in eutrophic lakes.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"209 ","pages":"Article 108522"},"PeriodicalIF":7.8,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-30DOI: 10.1016/j.psep.2026.108514
K. Harby , Mohammed El Hadi Attia , El-Sadek H. Nour El-deen , Hisham Maher , Mohamad Ramadan , Yaser H. Alahmadi , Hassan M. Hussein Farh , Abdullrahman A. Al-Shamma’a
Various enhancement technologies have been proposed recently to enhance the productivity and efficiency of solar sills. Among these, water surface disturbance, where the surface of saltwater is disturbed using external means, has emerged as one of the most significant, efficient, and cost-effective methods. This approach aims to disrupt the surface tension of the salt water, facilitate the separation of salt ions from water molecules, and reduce the thickness of the water surface, thereby accelerating and increasing the evaporation rates and overall yield. This review work presents a detailed evaluation of recent studies that investigate various water surface disturbance techniques to achieve the highest performance for solar stills. A comprehensive assessment and comparison of their economic visibility, operating principles, classification, performance parameters, and practical applicability have also been conducted. Furthermore, the latest advancements, limitations, and future research directions are highlighted. Providing an evaluative review of these effective techniques represents a very important and new step towards charting the future direction for increasing the performance of solar distillers and overcoming its specific challenges. Among the reviewed technologies, magnetic field methods enhanced water production by 19.6–218 %, while ultrasonic vaporizers achieved increases between 9.3 % and 415 %. Rotary systems showed greater improvements in productivity, increasing by 200–350 % with rotating drums, by 124–660.5 % with rotating discs, and by 51–300 % with rotating wick belts. The maximum production rate among these is obtained in the case of a rotary disc method. Overall, considering both performance improvement and production cost, water surface perturbation is one of the most promising methods to improve the efficiency of solar stills.
{"title":"A comprehensive and updated overview of water surface disturbance techniques for enhancing the efficiency of solar distillation systems and achieving sustainability","authors":"K. Harby , Mohammed El Hadi Attia , El-Sadek H. Nour El-deen , Hisham Maher , Mohamad Ramadan , Yaser H. Alahmadi , Hassan M. Hussein Farh , Abdullrahman A. Al-Shamma’a","doi":"10.1016/j.psep.2026.108514","DOIUrl":"10.1016/j.psep.2026.108514","url":null,"abstract":"<div><div>Various enhancement technologies have been proposed recently to enhance the productivity and efficiency of solar sills. Among these, water surface disturbance, where the surface of saltwater is disturbed using external means, has emerged as one of the most significant, efficient, and cost-effective methods. This approach aims to disrupt the surface tension of the salt water, facilitate the separation of salt ions from water molecules, and reduce the thickness of the water surface, thereby accelerating and increasing the evaporation rates and overall yield. This review work presents a detailed evaluation of recent studies that investigate various water surface disturbance techniques to achieve the highest performance for solar stills. A comprehensive assessment and comparison of their economic visibility, operating principles, classification, performance parameters, and practical applicability have also been conducted. Furthermore, the latest advancements, limitations, and future research directions are highlighted. Providing an evaluative review of these effective techniques represents a very important and new step towards charting the future direction for increasing the performance of solar distillers and overcoming its specific challenges. Among the reviewed technologies, magnetic field methods enhanced water production by 19.6–218 %, while ultrasonic vaporizers achieved increases between 9.3 % and 415 %. Rotary systems showed greater improvements in productivity, increasing by 200–350 % with rotating drums, by 124–660.5 % with rotating discs, and by 51–300 % with rotating wick belts. The maximum production rate among these is obtained in the case of a rotary disc method. Overall, considering both performance improvement and production cost, water surface perturbation is one of the most promising methods to improve the efficiency of solar stills.</div></div>","PeriodicalId":20743,"journal":{"name":"Process Safety and Environmental Protection","volume":"208 ","pages":"Article 108514"},"PeriodicalIF":7.8,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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