Based on the self-shrinkage effect of liquid metal,liquid-metal energy dissipators(LMEDs)have good applications in the energy absorption branch of a high-voltage DC system.However,LMEDs instantaneously produce large a...Based on the self-shrinkage effect of liquid metal,liquid-metal energy dissipators(LMEDs)have good applications in the energy absorption branch of a high-voltage DC system.However,LMEDs instantaneously produce large amounts of liquid-metal vapor during operation;therefore,the varying characteristics of the pressure in the cavity affect their energy consumption capacity and service life.In this study,the force and motion of liquid metal were analyzed,a mathematical model of shrinkage time before the arc was constructed,the influence of shortcircuit current and pore size on shrinkage time was explored,and the key factors affecting shrinkage time were clarified.Based on the theory of magnetohydrodynamics,the entire process of liquid metal from the beginning of contraction to the truncation of the arc was simulated to obtain the change characteristics of physical parameters,such as pressure and Lorentz force,in the cavity during the shrinkage process and to study the influence on contraction time by adjusting the short-circuit current and aperture size.A GaInSn liquid-metal energy dissipation test platform was built.The pre-arc shrinkage characteristics of the GaInSn liquid metal were studied,the variation in the voltammetry characteristic curve during liquid-metal energy dissipation was detected,and the accuracy of the simulation model was verified using experimental data.This study provides a theoretical reference for the application of LMEDs to power systems of different grades.展开更多
Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental con...Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental concept drift,gradually alter the behavior or structure of processes,making their detection and localization a challenging task.Traditional process mining techniques frequently assume process stationarity and are limited in their ability to detect such drift,particularly from a control-flow perspective.The objective of this research is to develop an interpretable and robust framework capable of detecting and localizing incremental concept drift in event logs,with a specific emphasis on the structural evolution of control-flow semantics in processes.We propose DriftXMiner,a control-flow-aware hybrid framework that combines statistical,machine learning,and process model analysis techniques.The approach comprises three key components:(1)Cumulative Drift Scanner that tracks directional statistical deviations to detect early drift signals;(2)a Temporal Clustering and Drift-Aware Forest Ensemble(DAFE)to capture distributional and classification-level changes in process behavior;and(3)Petri net-based process model reconstruction,which enables the precise localization of structural drift using transition deviation metrics and replay fitness scores.Experimental validation on the BPI Challenge 2017 event log demonstrates that DriftXMiner effectively identifies and localizes gradual and incremental process drift over time.The framework achieves a detection accuracy of 92.5%,a localization precision of 90.3%,and an F1-score of 0.91,outperforming competitive baselines such as CUSUM+Histograms and ADWIN+Alpha Miner.Visual analyses further confirm that identified drift points align with transitions in control-flow models and behavioral cluster structures.DriftXMiner offers a novel and interpretable solution for incremental concept drift detection and localization in dynamic,process-aware systems.By integrating statistical signal accumulation,temporal behavior profiling,and structural process mining,the framework enables finegrained drift explanation and supports adaptive process intelligence in evolving environments.Its modular architecture supports extension to streaming data and real-time monitoring contexts.展开更多
The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurode...The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurodegenerative diseases are characterized by the progressive loss of neuronal structure and function.展开更多
The complexity of the seismicity pattern for the subduction zone along the oceanic plate triggered the outer rise events and revealed cyclic tectonic deformation conditions along the plate subduction zones.The outer r...The complexity of the seismicity pattern for the subduction zone along the oceanic plate triggered the outer rise events and revealed cyclic tectonic deformation conditions along the plate subduction zones.The outer rise earthquakes have been observed along the Sunda arc,following the estimated rupture area of the 2005 M_(W)8.6 Nias earthquakes.Here,we used kinematic waveform inversion(KIWI)to obtain the source parameters of the 14 May 2021 M_(W)6.6 event off the west coast of northern Sumatra and to define the fault plane that triggered this outer rise event.The KIWI algorithm allows two types of seismic source to be configured:the moment tensor model to describe the type of shear with six moment tensor components and the Eikonal model for the rupture of pure double-couple sources.This method was chosen for its flexibility to be applied for different sources of seismicity and also for the automated full-moment tensor solution with real-time monitoring.We used full waveform traces from 8 broadband seismic stations within 1000 km epicentral distances sourced from the Incorporated Research Institutions for Seismology(IRIS-IDA)and Geofon GFZ seismic record databases.The initial origin time and hypocenter values are obtained from the IRIS-IDA.The synthetic seismograms used in the inversion process are based on the existing regional green function database model and were accessed from the KIWI Tools Green's Function Database.The obtained scalar seismic moment value is 1.18×10^(19)N·m,equivalent to a moment magnitude M_(W)6.6.The source parameters are 140°,44°,and−99°for the strike,dip,and rake values at a centroid depth of 10.2 km,indicating that this event is a normal fault earthquake that occurred in the outer rise area.The outer rise events with normal faults typically occur at the shallow part of the plate,with nodal-plane dips predominantly in the range of 30°-60°on the weak oceanic lithosphere due to hydrothermal alteration.The stress regime around the plate subduction zone varies both temporally and spatially due to the cyclic influences of megathrust earthquakes.Tensional outer rise earthquakes tend to occur after the megathrust events.The relative timing of these events is not known due to the viscous relaxation of the down going slab and poroelastic response in the trench slope region.The occurrence of the 14 May 2021 earthquake shows the seismicity in the outer rise region in the strongly coupled Sunda arc subduction zone due to elastic bending stress within the duration of the seismic cycle.展开更多
In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in...In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them.These bounding boxes are subsequently passed to a YOLOv11 classification model,which analyzes cropped images and assigns class labels.An additional counting module automatically tallies the detected fruits,offering a near-instantaneous estimation of quantity.The experimental results suggest high precision and recall for detection,high classification accuracy(across 15 classes),and near-perfect counting in real time.This paper presents a multi-stage pipeline for date fruit detection,classification,and automated counting,employing YOLOv11-based models to achieve high accuracy while maintaining real-time throughput.The results demonstrated that the detection precision exceeded 90%,the classification accuracy approached 92%,and the counting module correlated closely with the manual tallies.These findings confirm the potential of reducing manual labour and enhancing operational efficiency in post-harvesting processes.Future studies will include dataset expansion,user-centric interfaces,and integration with harvesting robotics.展开更多
Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remain...Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remains one of the security challenges. is paper proposes LinguTimeX,a new framework that combines natural language processing with arti cial intelligence,along with explainable Arti cial Intelligence(AI)not only to detect CTC but also to provide insights into the decision process.LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely.LinguTimeX demonstrates strong e ectiveness in detecting CTC across multiple languages;namely English,Arabic,and Chinese.Speci cally,the LSTM and RNN models achieved F1 scores of 90%on the English dataset,89%on the Arabic dataset,and 88%on the Chinese dataset,showcasing their superior performance and ability to generalize across multiple languages. is highlights their robustness in detecting CTCs within security systems,regardless of the language or cultural context of the data.In contrast,the DeepForest model produced F1-scores ranging from 86%to 87%across the same datasets,further con rming its e ectiveness in CTC detection.Although other algorithms also showed reasonable accuracy,the LSTM and RNN models consistently outperformed them in multilingual settings,suggesting that deep learning models might be better suited for this particular problem.展开更多
With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance s...With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.展开更多
Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a w...Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a wide range of factors, spanning from genetic to environmental factors, and even includes the gut microbiome(GM)(Mayer et al., 2022). All these processes coincide at some point in the inflammatory process, oxidative stress, and apoptosis, at different degrees in various organs and systems that constitute a living organism(Mayer et al., 2022;AguilarHernández et al., 2023).展开更多
Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley a...Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.展开更多
Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the p...Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.展开更多
Recently published in Joule,Feng Liu and colleagues from Shanghai Jiaotong University reported a record-breaking 20.8%power conversion efficiency in organic solar cells(OSCs)with an interpenetrating fibril network act...Recently published in Joule,Feng Liu and colleagues from Shanghai Jiaotong University reported a record-breaking 20.8%power conversion efficiency in organic solar cells(OSCs)with an interpenetrating fibril network active layer morphology,featuring a bulk p-in structure and proper vertical segregation achieved through additive-assisted layer-by-layer deposition.This optimized hierarchical gradient fibrillar morphology and optical management synergistically facilitates exciton diffusion,reduces recombination losses,and enhances light capture capability.This approach not only offers a solution to achieving high-efficiency devices but also demonstrates the potential for commercial applications of OSCs.展开更多
Fenton and Fenton-like processes,which could produce highly reactive species to degrade organic contaminants,have been widely used in the field of wastewater treatment.Therein,the chemistry of Fenton process including...Fenton and Fenton-like processes,which could produce highly reactive species to degrade organic contaminants,have been widely used in the field of wastewater treatment.Therein,the chemistry of Fenton process including the nature of active oxidants,the complicated reactions involved,and the behind reason for its strongly pH-dependent performance,is the basis for the application of Fenton and Fenton-like processes in wastewater treatment.Nevertheless,the conflicting views still exist about the mechanism of the Fenton process.For instance,reaching a unanimous consensus on the nature of active oxidants(hydroxyl radical or tetravalent iron)in this process remains challenging.This review comprehensively examined the mechanism of the Fenton process including the debate on the nature of active oxidants,reactions involved in the Fenton process,and the behind reason for the pH-dependent degradation of contaminants in the Fenton process.Then,we summarized several strategies that promote the Fe(Ⅱ)/Fe(Ⅲ)cycle,reduce the competitive consumption of active oxidants by side reactions,and replace the Fenton reagent,thus improving the performance of the Fenton process.Furthermore,advances for the future were proposed including the demand for the high-accuracy identification of active oxidants and taking advantages of the characteristic of target contaminants during the degradation of contaminants by the Fenton process.展开更多
The Hualien M 7.3 earthquake on April 3,2024,was a significant and strong earthquake in Taiwan,China in the past two decades.The rupture process of the main shock and strong aftershocks is of great significance to the...The Hualien M 7.3 earthquake on April 3,2024,was a significant and strong earthquake in Taiwan,China in the past two decades.The rupture process of the main shock and strong aftershocks is of great significance to the subsequent seismic activity and seismogenic tectonic research.Based on local strong-motion data,we used the IDS(Iterative Deconvolution and Stacking)method to obtain the rupture process of the mainshock and two strong aftershocks on the 23rd.The rupture of the mainshock was mainly unilateral,lasting 31 s,with a maximum slip of 2m,and the depth of the large slip zone is about 41–49 km.There is a clear difference between the rupture depth of the main shock and the two strong aftershocks.The depths of the large slip zones of the latter two are 3–9 km and 8–10 km,respectively.There is also a significant difference in the seismogenic fault between the mainshock and the aftershocks,and we believe that there are two seismogenic fault zones in the study area,the deep and the shallow fault zone.The slip of the deep faults activates the shallow faults.展开更多
In general,the rapid growth of α-Fe clusters is a challenge in high Fe-content Fe-based amorphous alloys,negatively affecting their physical properties.Herein,we introduce an efficient and rapid post-treatment techni...In general,the rapid growth of α-Fe clusters is a challenge in high Fe-content Fe-based amorphous alloys,negatively affecting their physical properties.Herein,we introduce an efficient and rapid post-treatment technique known as ultrasonic vibration rapid processing(UVRP),which enables the formation of high-density strong magnetic α-Fe clusters,thereby enhancing the soft magnetic properties of Fe_(78)Si(13)B_(9) amorphous alloy ribbon.展开更多
Purpose–The precast concrete slab track(PST)has advantages of fewer maintenance frequencies,better smooth rides and structural stability,which has been widely applied in urban rail transit.Precise positioning of prec...Purpose–The precast concrete slab track(PST)has advantages of fewer maintenance frequencies,better smooth rides and structural stability,which has been widely applied in urban rail transit.Precise positioning of precast concrete slab(PCS)is vital for keeping the initial track regularity.However,the cast-in-place process of the self-compacting concrete(SCC)filling layer generally causes a large deformation of PCS due to the water-hammer effect of flowing SCC,even cracking of PCS.Currently,the buoyancy characteristic and influencing factors of PCS during the SCC casting process have not been thoroughly studied in urban rail transit.Design/methodology/approach–In this work,a Computational Fluid Dynamics(CFD)model is established to calculate the buoyancy of PCS caused by the flowing SCC.The main influencing factors,including the inlet speed and flowability of SCC,have been analyzed and discussed.A new structural optimization scheme has been proposed for PST to reduce the buoyancy caused by the flowing SCC.Findings–The simulation and field test results showed that the buoyancy and deformation of PCS decreased obviously after adopting the new scheme.Originality/value–The findings of this study can provide guidance for the control of the deformation of PCS during the SCC construction process.展开更多
Current research on heterogeneous advanced oxidation processes(HAOPs)predominantly emphasizes catalyst iteration and innovation.Significant efforts have been made to regulate the electron structure and optimize the el...Current research on heterogeneous advanced oxidation processes(HAOPs)predominantly emphasizes catalyst iteration and innovation.Significant efforts have been made to regulate the electron structure and optimize the electron distribution,thereby increasing the catalytic activity.However,this focus often overshadows an equally essential aspect of HAOPs:the adsorption effect.Adsorption is a critical initiator for triggering the interaction of oxidants and contaminants with heterogeneous catalysts.The efficacy of these interactions is influenced by a variety of physicochemical properties,including surface chemistry and pore sizes,which determine the affinities between contaminants and material surfaces.This dispar ity in affinity is pivotal because it underpins the selective removal of contaminants,especially in complex waste streams containing diverse contaminants and competing matrices.Consequently,understanding and mastering these interfacial interactions is fundamentally indispensable not only for improving pro cess efficiency but also for enhancing the selectivity of contaminant removal.Herein,we highlight the importance of adsorption-driven interfacial interactions for fundamentally elucidating the catalytic mechanisms of HAOPs.Such interactions dictate the overall performance of the treatment processes by balancing the adsorption,reaction,and desorption rates on the catalyst surfaces.Elucidating the adsorption effect not only shifts the paradigm in understanding HAOPs but also improves their practical ity in water treatment and wastewater decontamination.Overall,we propose that revisiting adsorption driven interfacial interactions holds great promise for optimizing catalytic processes to develop effective HAOP strategies.展开更多
With the emergence of general foundational models,such as Chat Generative Pre-trained Transformer(ChatGPT),researchers have shown considerable interest in the potential applications of foundation models in the process...With the emergence of general foundational models,such as Chat Generative Pre-trained Transformer(ChatGPT),researchers have shown considerable interest in the potential applications of foundation models in the process industry.This paper provides a comprehensive overview of the challenges and opportunities presented by the use of foundation models in the process industry,including the frameworks,core applications,and future prospects.First,this paper proposes a framework for foundation models for the process industry.Second,it summarizes the key capabilities of industrial foundation models and their practical applications.Finally,it highlights future research directions and identifies unresolved open issues related to the use of foundation models in the process industry.展开更多
Magnesium and magnesium alloys,serving as crucial lightweight structural materials and hydrogen storage elements,find extensive applications in space technology,aviation,automotive,and magnesium-based hydrogen industr...Magnesium and magnesium alloys,serving as crucial lightweight structural materials and hydrogen storage elements,find extensive applications in space technology,aviation,automotive,and magnesium-based hydrogen industries.The global production of primary magnesium has reached approximately 1.2 million tons per year,with anticipated diversification in future applications and significant market demand.Nevertheless,approximately 80%of the world’s primary magnesium is still manufactured through the Pidgeon process,grappling with formidable issues including high energy consumption,massive carbon emission,significant resource depletion,and environmental pollution.The implementation of the relative vacuum method shows potential in breaking through technological challenges in the Pidgeon process,facilitating clean,low-carbon continuous magnesium smelting.This paper begins by introducing the principles of the relative vacuum method.Subsequently,it elucidates various innovative process routes,including relative vacuum ferrosilicon reduction,aluminum thermal reduction co-production of spinel,and aluminum thermal reduction co-production of calcium aluminate.Finally,and thermodynamic foundations of the relative vacuum,a quantitative analysis of the material,energy flows,carbon emission,and production cost for several new processes is conducted,comparing and analyzing them against the Pidgeon process.The study findings reveal that,with identical raw materials,the relative vacuum silicon thermal reduction process significantly decreases raw material consumption,energy consumption,and carbon dioxide emissions by 15.86%,30.89%,and 26.27%,respectively,compared to the Pidgeon process.The relative vacuum process,using magnesite as the raw material and aluminum as the reducing agent,has the lowest magnesium-to-feed ratio,at only 3.385.Additionally,its energy consumption and carbon dioxide emissions are the lowest,at 1.817 tce/t Mg and 7.782 t CO_(2)/t Mg,respectively.The energy consumption and carbon emissions of the relative vacuum magnesium smelting process co-producing calcium aluminate(12CaO·7Al_(2)O_(3),3CaO·Al_(2)O_(3),and CaO·Al_(2)O_(3))are highly correlated with the consumption of dolomite in the raw materials.When the reduction temperature is around 1473.15 K,the critical volume fraction of magnesium vapor for different processes varies within the range of 5%–40%.Production cost analysis shows that the relative vacuum primary magnesium smelting process has significant economic benefits.This paper offers essential data support and theoretical guidance for achieving energy efficiency,carbon reduction in magnesium smelting,and the industrial adoption of innovative processes.展开更多
Spiral bevel gears are critical transmission components,and are widely used in the aerospace field.This paper proposes a new multi-DOF envelope forming process for fabricating spiral bevel gears.Firstly,the multi-DOF ...Spiral bevel gears are critical transmission components,and are widely used in the aerospace field.This paper proposes a new multi-DOF envelope forming process for fabricating spiral bevel gears.Firstly,the multi-DOF envelope forming principle of spiral bevel gears is proposed.Secondly,the design methods for the envelope tool geometry and movement are proposed based on the envelope geometry and movement relationships.Thirdly,the metal flow and tooth filling laws are revealed through 3D FE simulation of the multi-DOF envelope forming process of a typical spiral bevel gear.Fourthly,a new method for separating the envelope tool and the formed spiral bevel gear with back taper tooth is proposed to avoid their interference.Finally,experiments on multi-DOF envelope forming of this typical spiral bevel gear are conducted using new heavy load multi-DOF envelope forming equipment.The simulation and experimental results show the feasibility of the proposed multi-DOF envelope forming process for fabricating spiral bevel gears with back taper tooth and the corresponding process design methods.展开更多
The big-tapered profiled ring disk is a key component of engines for rockets and missiles.A new forming technology,as called spinning-rolling process,has been proposed previously for the high performance,high efficien...The big-tapered profiled ring disk is a key component of engines for rockets and missiles.A new forming technology,as called spinning-rolling process,has been proposed previously for the high performance,high efficiency and low-cost manufacturing of the component.Blank design is the key part of plastic forming process design.For spinning-rolling process,the shape and size of the blank play a crucial role in process stability,deformation behavior and dimensional accuracy.So this work proposes a blank design method to determine the geometry structure and sizes of the blank.The mathematical model for calculating the blank size has been deduced based on volume conservation and neutral layer length invariance principle.The FE simulation and corresponding trial production of an actual big-tapered profiled ring disk show that the proposed blank design method is applicative.In order to obtain a preferred blank,the influence rules of blank size determined by different deformation degrees(rolling ratio k)on the spinning-rolling process are revealed by comprehensive FE simulations.Overall considering the process stability,circularity of the deformed ring disk and forming forces,a reasonable range of deformation degree(rolling ratio k)is recommended for the blank design of the new spinning-rolling process.展开更多
基金supported by the Excellent Young Scientists Fund of China(No.51922090)National Natural Science Foundation of China(Nos.U19A20105,U1966602,and 51837009)。
文摘Based on the self-shrinkage effect of liquid metal,liquid-metal energy dissipators(LMEDs)have good applications in the energy absorption branch of a high-voltage DC system.However,LMEDs instantaneously produce large amounts of liquid-metal vapor during operation;therefore,the varying characteristics of the pressure in the cavity affect their energy consumption capacity and service life.In this study,the force and motion of liquid metal were analyzed,a mathematical model of shrinkage time before the arc was constructed,the influence of shortcircuit current and pore size on shrinkage time was explored,and the key factors affecting shrinkage time were clarified.Based on the theory of magnetohydrodynamics,the entire process of liquid metal from the beginning of contraction to the truncation of the arc was simulated to obtain the change characteristics of physical parameters,such as pressure and Lorentz force,in the cavity during the shrinkage process and to study the influence on contraction time by adjusting the short-circuit current and aperture size.A GaInSn liquid-metal energy dissipation test platform was built.The pre-arc shrinkage characteristics of the GaInSn liquid metal were studied,the variation in the voltammetry characteristic curve during liquid-metal energy dissipation was detected,and the accuracy of the simulation model was verified using experimental data.This study provides a theoretical reference for the application of LMEDs to power systems of different grades.
文摘Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental concept drift,gradually alter the behavior or structure of processes,making their detection and localization a challenging task.Traditional process mining techniques frequently assume process stationarity and are limited in their ability to detect such drift,particularly from a control-flow perspective.The objective of this research is to develop an interpretable and robust framework capable of detecting and localizing incremental concept drift in event logs,with a specific emphasis on the structural evolution of control-flow semantics in processes.We propose DriftXMiner,a control-flow-aware hybrid framework that combines statistical,machine learning,and process model analysis techniques.The approach comprises three key components:(1)Cumulative Drift Scanner that tracks directional statistical deviations to detect early drift signals;(2)a Temporal Clustering and Drift-Aware Forest Ensemble(DAFE)to capture distributional and classification-level changes in process behavior;and(3)Petri net-based process model reconstruction,which enables the precise localization of structural drift using transition deviation metrics and replay fitness scores.Experimental validation on the BPI Challenge 2017 event log demonstrates that DriftXMiner effectively identifies and localizes gradual and incremental process drift over time.The framework achieves a detection accuracy of 92.5%,a localization precision of 90.3%,and an F1-score of 0.91,outperforming competitive baselines such as CUSUM+Histograms and ADWIN+Alpha Miner.Visual analyses further confirm that identified drift points align with transitions in control-flow models and behavioral cluster structures.DriftXMiner offers a novel and interpretable solution for incremental concept drift detection and localization in dynamic,process-aware systems.By integrating statistical signal accumulation,temporal behavior profiling,and structural process mining,the framework enables finegrained drift explanation and supports adaptive process intelligence in evolving environments.Its modular architecture supports extension to streaming data and real-time monitoring contexts.
文摘The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurodegenerative diseases are characterized by the progressive loss of neuronal structure and function.
基金supported by the National Natural Science Foundation of China(Grant No.42130312)。
文摘The complexity of the seismicity pattern for the subduction zone along the oceanic plate triggered the outer rise events and revealed cyclic tectonic deformation conditions along the plate subduction zones.The outer rise earthquakes have been observed along the Sunda arc,following the estimated rupture area of the 2005 M_(W)8.6 Nias earthquakes.Here,we used kinematic waveform inversion(KIWI)to obtain the source parameters of the 14 May 2021 M_(W)6.6 event off the west coast of northern Sumatra and to define the fault plane that triggered this outer rise event.The KIWI algorithm allows two types of seismic source to be configured:the moment tensor model to describe the type of shear with six moment tensor components and the Eikonal model for the rupture of pure double-couple sources.This method was chosen for its flexibility to be applied for different sources of seismicity and also for the automated full-moment tensor solution with real-time monitoring.We used full waveform traces from 8 broadband seismic stations within 1000 km epicentral distances sourced from the Incorporated Research Institutions for Seismology(IRIS-IDA)and Geofon GFZ seismic record databases.The initial origin time and hypocenter values are obtained from the IRIS-IDA.The synthetic seismograms used in the inversion process are based on the existing regional green function database model and were accessed from the KIWI Tools Green's Function Database.The obtained scalar seismic moment value is 1.18×10^(19)N·m,equivalent to a moment magnitude M_(W)6.6.The source parameters are 140°,44°,and−99°for the strike,dip,and rake values at a centroid depth of 10.2 km,indicating that this event is a normal fault earthquake that occurred in the outer rise area.The outer rise events with normal faults typically occur at the shallow part of the plate,with nodal-plane dips predominantly in the range of 30°-60°on the weak oceanic lithosphere due to hydrothermal alteration.The stress regime around the plate subduction zone varies both temporally and spatially due to the cyclic influences of megathrust earthquakes.Tensional outer rise earthquakes tend to occur after the megathrust events.The relative timing of these events is not known due to the viscous relaxation of the down going slab and poroelastic response in the trench slope region.The occurrence of the 14 May 2021 earthquake shows the seismicity in the outer rise region in the strongly coupled Sunda arc subduction zone due to elastic bending stress within the duration of the seismic cycle.
基金supported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia,Grant No.KFU250098.
文摘In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them.These bounding boxes are subsequently passed to a YOLOv11 classification model,which analyzes cropped images and assigns class labels.An additional counting module automatically tallies the detected fruits,offering a near-instantaneous estimation of quantity.The experimental results suggest high precision and recall for detection,high classification accuracy(across 15 classes),and near-perfect counting in real time.This paper presents a multi-stage pipeline for date fruit detection,classification,and automated counting,employing YOLOv11-based models to achieve high accuracy while maintaining real-time throughput.The results demonstrated that the detection precision exceeded 90%,the classification accuracy approached 92%,and the counting module correlated closely with the manual tallies.These findings confirm the potential of reducing manual labour and enhancing operational efficiency in post-harvesting processes.Future studies will include dataset expansion,user-centric interfaces,and integration with harvesting robotics.
基金This study is financed by the European Union-NextGenerationEU,through the National Recovery and Resilience Plan of the Republic of Bulgaria,Project No.BG-RRP-2.013-0001.
文摘Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remains one of the security challenges. is paper proposes LinguTimeX,a new framework that combines natural language processing with arti cial intelligence,along with explainable Arti cial Intelligence(AI)not only to detect CTC but also to provide insights into the decision process.LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely.LinguTimeX demonstrates strong e ectiveness in detecting CTC across multiple languages;namely English,Arabic,and Chinese.Speci cally,the LSTM and RNN models achieved F1 scores of 90%on the English dataset,89%on the Arabic dataset,and 88%on the Chinese dataset,showcasing their superior performance and ability to generalize across multiple languages. is highlights their robustness in detecting CTCs within security systems,regardless of the language or cultural context of the data.In contrast,the DeepForest model produced F1-scores ranging from 86%to 87%across the same datasets,further con rming its e ectiveness in CTC detection.Although other algorithms also showed reasonable accuracy,the LSTM and RNN models consistently outperformed them in multilingual settings,suggesting that deep learning models might be better suited for this particular problem.
基金funded by scientific research projects under Grant JY2024B011.
文摘With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.
基金funded by CONAHCYT grant(252808)to GFCONAHCYT’s“Estancias Posdoctorales por México”program(662350)to HTB。
文摘Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a wide range of factors, spanning from genetic to environmental factors, and even includes the gut microbiome(GM)(Mayer et al., 2022). All these processes coincide at some point in the inflammatory process, oxidative stress, and apoptosis, at different degrees in various organs and systems that constitute a living organism(Mayer et al., 2022;AguilarHernández et al., 2023).
基金supported by the General Program of the National Natural Science Foundation of China(No.52274326)the China Baowu Low Carbon Metallurgy Innovation Foundation(No.BWLCF202109)the Seventh Batch of Ten Thousand Talents Plan of China(No.ZX20220553).
文摘Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.
基金Technology Development Program of Jilin Province(YDZJ202201ZYTS640)the National Key Research and Development Program of China(2022YFB4200400)funded by MOST+4 种基金the National Natural Science Foundation of China(52172048 and 52103221)Shandong Provincial Natural Science Foundation(ZR2021QB024 and ZR2021ZD06)Guangdong Basic and Applied Basic Research Foundation(2023A1515012323,2023A1515010943,and 2024A1515010023)the Qingdao New Energy Shandong Laboratory open Project(QNESL OP 202309)the Fundamental Research Funds of Shandong University.
文摘Recently published in Joule,Feng Liu and colleagues from Shanghai Jiaotong University reported a record-breaking 20.8%power conversion efficiency in organic solar cells(OSCs)with an interpenetrating fibril network active layer morphology,featuring a bulk p-in structure and proper vertical segregation achieved through additive-assisted layer-by-layer deposition.This optimized hierarchical gradient fibrillar morphology and optical management synergistically facilitates exciton diffusion,reduces recombination losses,and enhances light capture capability.This approach not only offers a solution to achieving high-efficiency devices but also demonstrates the potential for commercial applications of OSCs.
基金supported by the National Natural Science Foundation of China(Nos.22206050 and 52270047).
文摘Fenton and Fenton-like processes,which could produce highly reactive species to degrade organic contaminants,have been widely used in the field of wastewater treatment.Therein,the chemistry of Fenton process including the nature of active oxidants,the complicated reactions involved,and the behind reason for its strongly pH-dependent performance,is the basis for the application of Fenton and Fenton-like processes in wastewater treatment.Nevertheless,the conflicting views still exist about the mechanism of the Fenton process.For instance,reaching a unanimous consensus on the nature of active oxidants(hydroxyl radical or tetravalent iron)in this process remains challenging.This review comprehensively examined the mechanism of the Fenton process including the debate on the nature of active oxidants,reactions involved in the Fenton process,and the behind reason for the pH-dependent degradation of contaminants in the Fenton process.Then,we summarized several strategies that promote the Fe(Ⅱ)/Fe(Ⅲ)cycle,reduce the competitive consumption of active oxidants by side reactions,and replace the Fenton reagent,thus improving the performance of the Fenton process.Furthermore,advances for the future were proposed including the demand for the high-accuracy identification of active oxidants and taking advantages of the characteristic of target contaminants during the degradation of contaminants by the Fenton process.
基金sponsored by the Earthquake Spark Technology Project(XH23051B)。
文摘The Hualien M 7.3 earthquake on April 3,2024,was a significant and strong earthquake in Taiwan,China in the past two decades.The rupture process of the main shock and strong aftershocks is of great significance to the subsequent seismic activity and seismogenic tectonic research.Based on local strong-motion data,we used the IDS(Iterative Deconvolution and Stacking)method to obtain the rupture process of the mainshock and two strong aftershocks on the 23rd.The rupture of the mainshock was mainly unilateral,lasting 31 s,with a maximum slip of 2m,and the depth of the large slip zone is about 41–49 km.There is a clear difference between the rupture depth of the main shock and the two strong aftershocks.The depths of the large slip zones of the latter two are 3–9 km and 8–10 km,respectively.There is also a significant difference in the seismogenic fault between the mainshock and the aftershocks,and we believe that there are two seismogenic fault zones in the study area,the deep and the shallow fault zone.The slip of the deep faults activates the shallow faults.
基金supported by the Major Science and Technology Project of Zhongshan City(No.2022AJ004)the Key Basic and Applied Research Program of Guangdong Province(Nos.2019B030302010 and 2022B1515120082)Guangdong Science and Technology Innovation Project(No.2021TX06C111).
文摘In general,the rapid growth of α-Fe clusters is a challenge in high Fe-content Fe-based amorphous alloys,negatively affecting their physical properties.Herein,we introduce an efficient and rapid post-treatment technique known as ultrasonic vibration rapid processing(UVRP),which enables the formation of high-density strong magnetic α-Fe clusters,thereby enhancing the soft magnetic properties of Fe_(78)Si(13)B_(9) amorphous alloy ribbon.
文摘Purpose–The precast concrete slab track(PST)has advantages of fewer maintenance frequencies,better smooth rides and structural stability,which has been widely applied in urban rail transit.Precise positioning of precast concrete slab(PCS)is vital for keeping the initial track regularity.However,the cast-in-place process of the self-compacting concrete(SCC)filling layer generally causes a large deformation of PCS due to the water-hammer effect of flowing SCC,even cracking of PCS.Currently,the buoyancy characteristic and influencing factors of PCS during the SCC casting process have not been thoroughly studied in urban rail transit.Design/methodology/approach–In this work,a Computational Fluid Dynamics(CFD)model is established to calculate the buoyancy of PCS caused by the flowing SCC.The main influencing factors,including the inlet speed and flowability of SCC,have been analyzed and discussed.A new structural optimization scheme has been proposed for PST to reduce the buoyancy caused by the flowing SCC.Findings–The simulation and field test results showed that the buoyancy and deformation of PCS decreased obviously after adopting the new scheme.Originality/value–The findings of this study can provide guidance for the control of the deformation of PCS during the SCC construction process.
基金supported by the National Key Research and Development Program of China(2022YFC3205300)the National Natural Science Foundation of China(22176124).
文摘Current research on heterogeneous advanced oxidation processes(HAOPs)predominantly emphasizes catalyst iteration and innovation.Significant efforts have been made to regulate the electron structure and optimize the electron distribution,thereby increasing the catalytic activity.However,this focus often overshadows an equally essential aspect of HAOPs:the adsorption effect.Adsorption is a critical initiator for triggering the interaction of oxidants and contaminants with heterogeneous catalysts.The efficacy of these interactions is influenced by a variety of physicochemical properties,including surface chemistry and pore sizes,which determine the affinities between contaminants and material surfaces.This dispar ity in affinity is pivotal because it underpins the selective removal of contaminants,especially in complex waste streams containing diverse contaminants and competing matrices.Consequently,understanding and mastering these interfacial interactions is fundamentally indispensable not only for improving pro cess efficiency but also for enhancing the selectivity of contaminant removal.Herein,we highlight the importance of adsorption-driven interfacial interactions for fundamentally elucidating the catalytic mechanisms of HAOPs.Such interactions dictate the overall performance of the treatment processes by balancing the adsorption,reaction,and desorption rates on the catalyst surfaces.Elucidating the adsorption effect not only shifts the paradigm in understanding HAOPs but also improves their practical ity in water treatment and wastewater decontamination.Overall,we propose that revisiting adsorption driven interfacial interactions holds great promise for optimizing catalytic processes to develop effective HAOP strategies.
基金supported by the National Natural Science Foundation of China(62225302,623B2014,and 62173023).
文摘With the emergence of general foundational models,such as Chat Generative Pre-trained Transformer(ChatGPT),researchers have shown considerable interest in the potential applications of foundation models in the process industry.This paper provides a comprehensive overview of the challenges and opportunities presented by the use of foundation models in the process industry,including the frameworks,core applications,and future prospects.First,this paper proposes a framework for foundation models for the process industry.Second,it summarizes the key capabilities of industrial foundation models and their practical applications.Finally,it highlights future research directions and identifies unresolved open issues related to the use of foundation models in the process industry.
基金supported by the China Postdoctoral Science Foundation(No.2023T160088)the Youth Fund of the National Natural Science Foundation of China(No.52304324).
文摘Magnesium and magnesium alloys,serving as crucial lightweight structural materials and hydrogen storage elements,find extensive applications in space technology,aviation,automotive,and magnesium-based hydrogen industries.The global production of primary magnesium has reached approximately 1.2 million tons per year,with anticipated diversification in future applications and significant market demand.Nevertheless,approximately 80%of the world’s primary magnesium is still manufactured through the Pidgeon process,grappling with formidable issues including high energy consumption,massive carbon emission,significant resource depletion,and environmental pollution.The implementation of the relative vacuum method shows potential in breaking through technological challenges in the Pidgeon process,facilitating clean,low-carbon continuous magnesium smelting.This paper begins by introducing the principles of the relative vacuum method.Subsequently,it elucidates various innovative process routes,including relative vacuum ferrosilicon reduction,aluminum thermal reduction co-production of spinel,and aluminum thermal reduction co-production of calcium aluminate.Finally,and thermodynamic foundations of the relative vacuum,a quantitative analysis of the material,energy flows,carbon emission,and production cost for several new processes is conducted,comparing and analyzing them against the Pidgeon process.The study findings reveal that,with identical raw materials,the relative vacuum silicon thermal reduction process significantly decreases raw material consumption,energy consumption,and carbon dioxide emissions by 15.86%,30.89%,and 26.27%,respectively,compared to the Pidgeon process.The relative vacuum process,using magnesite as the raw material and aluminum as the reducing agent,has the lowest magnesium-to-feed ratio,at only 3.385.Additionally,its energy consumption and carbon dioxide emissions are the lowest,at 1.817 tce/t Mg and 7.782 t CO_(2)/t Mg,respectively.The energy consumption and carbon emissions of the relative vacuum magnesium smelting process co-producing calcium aluminate(12CaO·7Al_(2)O_(3),3CaO·Al_(2)O_(3),and CaO·Al_(2)O_(3))are highly correlated with the consumption of dolomite in the raw materials.When the reduction temperature is around 1473.15 K,the critical volume fraction of magnesium vapor for different processes varies within the range of 5%–40%.Production cost analysis shows that the relative vacuum primary magnesium smelting process has significant economic benefits.This paper offers essential data support and theoretical guidance for achieving energy efficiency,carbon reduction in magnesium smelting,and the industrial adoption of innovative processes.
基金the National Science and Technology Major Project of China(No.2019-VII0017e0158)the National Natural Science Foundation of China(No.U21A20131)+1 种基金the Industry-University Research Cooperation Project,China(No.HFZL2020CXY025)the National Key Laboratory of Science and Technology on Helicopter Transmission,China(No.HTL-O-21G05).
文摘Spiral bevel gears are critical transmission components,and are widely used in the aerospace field.This paper proposes a new multi-DOF envelope forming process for fabricating spiral bevel gears.Firstly,the multi-DOF envelope forming principle of spiral bevel gears is proposed.Secondly,the design methods for the envelope tool geometry and movement are proposed based on the envelope geometry and movement relationships.Thirdly,the metal flow and tooth filling laws are revealed through 3D FE simulation of the multi-DOF envelope forming process of a typical spiral bevel gear.Fourthly,a new method for separating the envelope tool and the formed spiral bevel gear with back taper tooth is proposed to avoid their interference.Finally,experiments on multi-DOF envelope forming of this typical spiral bevel gear are conducted using new heavy load multi-DOF envelope forming equipment.The simulation and experimental results show the feasibility of the proposed multi-DOF envelope forming process for fabricating spiral bevel gears with back taper tooth and the corresponding process design methods.
基金the National Natural Science Foundation of China(No.52275378)the National Key Laboratory for Precision Hot Processing of Metals(6142909200208)。
文摘The big-tapered profiled ring disk is a key component of engines for rockets and missiles.A new forming technology,as called spinning-rolling process,has been proposed previously for the high performance,high efficiency and low-cost manufacturing of the component.Blank design is the key part of plastic forming process design.For spinning-rolling process,the shape and size of the blank play a crucial role in process stability,deformation behavior and dimensional accuracy.So this work proposes a blank design method to determine the geometry structure and sizes of the blank.The mathematical model for calculating the blank size has been deduced based on volume conservation and neutral layer length invariance principle.The FE simulation and corresponding trial production of an actual big-tapered profiled ring disk show that the proposed blank design method is applicative.In order to obtain a preferred blank,the influence rules of blank size determined by different deformation degrees(rolling ratio k)on the spinning-rolling process are revealed by comprehensive FE simulations.Overall considering the process stability,circularity of the deformed ring disk and forming forces,a reasonable range of deformation degree(rolling ratio k)is recommended for the blank design of the new spinning-rolling process.
