Detection of Oscillations in Process Control Loops From Visual Image Space Using Deep Convolutional Networks

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant profitability.Although numerous automatic detection techniques have been proposed,most of them can only address part of the practical difficulties.An oscillation is heuristically defined as a visually apparent periodic variation.However,manual visual inspection is labor-intensive and prone to missed detection.Convolutional neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction capabilities.In this work,an exploration of the typical CNN models for visual oscillation detection is performed.Specifically,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation detection.The feasibility and validity of this framework are verified utilizing extensive numerical and industrial cases.Compared with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and mean-nonstationarity.In addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

Causal temporal graph attention network for fault diagnosis of chemical processes

Fault detection and diagnosis(FDD)plays a significant role in ensuring the safety and stability of chemical processes.With the development of artificial intelligence(AI)and big data technologies,data-driven approaches with excellent performance are widely used for FDD in chemical processes.However,improved predictive accuracy has often been achieved through increased model complexity,which turns models into black-box methods and causes uncertainty regarding their decisions.In this study,a causal temporal graph attention network(CTGAN)is proposed for fault diagnosis of chemical processes.A chemical causal graph is built by causal inference to represent the propagation path of faults.The attention mechanism and chemical causal graph were combined to help us notice the key variables relating to fault fluctuations.Experiments in the Tennessee Eastman(TE)process and the green ammonia(GA)process showed that CTGAN achieved high performance and good explainability.

Big Data Application Simulation Platform Design for Onboard Distributed Processing of LEO Mega-Constellation Networks

Due to the restricted satellite payloads in LEO mega-constellation networks(LMCNs),remote sensing image analysis,online learning and other big data services desirably need onboard distributed processing(OBDP).In existing technologies,the efficiency of big data applications(BDAs)in distributed systems hinges on the stable-state and low-latency links between worker nodes.However,LMCNs with high-dynamic nodes and long-distance links can not provide the above conditions,which makes the performance of OBDP hard to be intuitively measured.To bridge this gap,a multidimensional simulation platform is indispensable that can simulate the network environment of LMCNs and put BDAs in it for performance testing.Using STK's APIs and parallel computing framework,we achieve real-time simulation for thousands of satellite nodes,which are mapped as application nodes through software defined network(SDN)and container technologies.We elaborate the architecture and mechanism of the simulation platform,and take the Starlink and Hadoop as realistic examples for simulations.The results indicate that LMCNs have dynamic end-to-end latency which fluctuates periodically with the constellation movement.Compared to ground data center networks(GDCNs),LMCNs deteriorate the computing and storage job throughput,which can be alleviated by the utilization of erasure codes and data flow scheduling of worker nodes.

Mechanism of Rosae Rugosae Flos flavonoids in the treatment of hyperlipidemia and optimization of extraction process based on network pharmacology

This study aims to identify a natural plant chemical with hypolipidemic effects that can be used to treat high cholesterol without adverse reactions.Through network pharmacology screening,it was found that Rosae Rugosae Flos(RF)flavonoids had potential therapeutic effects on hyperlipidemia and its mechanism of action was discussed.TCMSP and GeneCards databases were used to obtain active ingredients and disease targets.Venn diagrams were drawn to illustrate the findings.The interaction network diagram was created using Cytoscape 3.8.0 software.The PPI protein network was constructed using String.GO and KEGG enrichment analysis was performed using Metascape.The results revealed 2 active flavonoid ingredients and 60 potential targets in RF.The key targets,including CCL2,PPARG,and PPARA,were found to play a role in multiple pathways such as the AGE-RAGE signaling pathway,lipid and atherosclerosis,and cancer pathway in diabetic complications.The solvent extraction method was optimized for efficient flavonoid extraction based on network pharmacology prediction results.This was achieved through a single factor and orthogonal test,resulting in an optimum process with a reflux time of 1.5 h,a solid-liquid ratio of 1:13 g/mL,and an ethanol concentration of 50%.

Optimization of extraction process for total fl avonoids of Sophorae Flos for the treatment of hyperlipidemia based on network pharmacology and molecular docking

This study aimed to investigate the mechanism of action of Sophora Flos(SF)in the treatment of hyperlipidemia(HLP)using network pharmacology and molecular docking methods,and to optimize the extraction process of the predicted active components.The STRING database was used for protein interaction analysis and PPI network construction via Cytoscape 3.9.1.Pymol was employed for docking and visualization.An extensive review of SF identifi ed 6 active ingredients,297 related objectives,84 disease objectives,and 57 total objectives.After protein interaction and topology analysis,18 core targets were identifi ed.These included 146 gene function entries(P<0.05).Active compounds,mainly fl avonoids,can modulate the expression of various proteins such as TNF,IL-6,IL-1β,PPARG,and TGFB1 to achieve therapeutic eff ects on HLP.The network pharmacology and molecular docking results suggested that the active fl avonoids component in SF may be related to the treatment of hyperlipidemia.Therefore,the orthogonal experiment method was used to optimize the extraction process of total fl avonoid from SF using ethanol refl ux extraction,based on a single factor experiment.The eff ects of refl ux time,solid-liquid ratio,ethanol concentration,and other factors on the extraction of total fl avonoid from SF were investigated.The optimum process conditions were refl ux time of 1.25 h,solid-liquid ratio of 1:15 g/mL and ethanol concentration of 60%.Using these conditions,the purity of total fl avonoid extracted from SF was 70.33±0.22%.

A new insight into LPSO phase transformation and mechanical properties uniformity of large-scale Mg-Gd-Y-Zn-Zr alloy prepared by multi-pass friction stir processing

A large-scale fine-grained Mg-Gd-Y-Zn-Zr alloy plate with high strength and ductility was successfully prepared by multi-pass friction stir processing(MFSP)technology in this work.The structure of grains and long period stacking ordered(LPSO)phase were characterized,and the mechanical properties uniformity was investigated.Moreover,a quantitative relationship between the microstructure and tensile yield strength was established.The results showed that the grains in the processed zone(PZ)and interfacial zone(IZ)were refined from 50μm to 3μm and 4μm,respectively,and numerous original LPSO phases were broken.In IZ,some block-shaped 18R LPSO phases were transformed into needle-like 14H LPSO phases due to stacking faults and the short-range diffusion of solute atoms.The severe shear deformation in the form of kinetic energy caused profuse stacking fault to be generated and move rapidly,greatly increasing the transformation rate of LPSO phase.After MFSP,the ultimate tensile strength,yield strength and elongation to failure of the large-scale plate were 367 MPa,305 MPa and 18.0% respectively.Grain refinement and LPSO phase strengthening were the major strengthening mechanisms for the MFSP sample.In particularly,the strength of IZ was comparable to that of PZ because the strength contribution of the 14H LPSO phase offsets the lack of grain refinement strengthening in IZ.This result opposes the widely accepted notion that IZ is a weak region in MFSP-prepared large-scale fine-grained plate.

Effect of bubble morphology and behavior on power consumption in non-Newtonian fluids’aeration process

Due to a prolonged operation time and low mass transfer efficiency, the primary challenge in the aeration process of non-Newtonian fluids is the high energy consumption, which is closely related to the form and rate of impeller, ventilation, rheological properties and bubble morphology in the reactor. In this perspective, through optimal computational fluid dynamics models and experiments, the relationship between power consumption, volumetric mass transfer rate(kLa) and initial bubble size(d0) was constructed to establish an efficient operation mode for the aeration process of non-Newtonian fluids. It was found that reducing the d0could significantly increase the oxygen mass transfer rate, resulting in an obvious decrease in the ventilation volume and impeller speed. When d0was regulated within 2-5 mm,an optimal kLa could be achieved, and 21% of power consumption could be saved, compared to the case of bubbles with a diameter of 10 mm.

Process design and intensification of multicomponent azeotropes special distillation separation via molecular simulation and system optimization

This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.

A review on plasma-based CO_(2) utilization:process considerations in the development of sustainable chemical production

Plasma-based processes,particularly in carbon capture and utilization,hold great potential for addressing environmental challenges and advancing a circular carbon economy.While significant progress has been made in understanding plasma-induced reactions,plasma-catalyst interactions,and reactor development to enhance energy efficiency and conversion,there remains a notable gap in research concerning overall process development.This review emphasizes the critical need for considerations at the process level,including integration and intensification,to facilitate the industrialization of plasma technology for chemical production.Discussions centered on the development of plasma-based processes are made with a primary focus on CO_(2) conversion,offering insights to guide future work for the transition of the technology from laboratory scale to industrial applications.Identification of current research gaps,especially in upscaling and integrating plasma reactors with other process units,is the key to addressing critical issues.The review further delves into relevant research in process evaluation and assessment,providing methodological insights and highlighting key factors for comprehensive economic and sustainability analyses.Additionally,recent advancements in novel plasma systems are reviewed,presenting unique advantages and innovative concepts that could reshape the future of process development.This review provides essential information for navigating the path forward,ensuring a comprehensive understanding of challenges and opportunities in the development of plasma-based CCU process.

Operational optimization of copper flotation process based on the weighted Gaussian process regression and index-oriented adaptive differential evolution algorithm

Concentrate copper grade(CCG)is one of the important production indicators of copper flotation processes,and keeping the CCG at the set value is of great significance to the economic benefit of copper flotation industrial processes.This paper addresses the fluctuation problem of CCG through an operational optimization method.Firstly,a density-based affinity propagationalgorithm is proposed so that more ideal working condition categories can be obtained for the complex raw ore properties.Next,a Bayesian network(BN)is applied to explore the relationship between the operational variables and the CCG.Based on the analysis results of BN,a weighted Gaussian process regression model is constructed to predict the CCG that a higher prediction accuracy can be obtained.To ensure the predicted CCG is close to the set value with a smaller magnitude of the operation adjustments and a smaller uncertainty of the prediction results,an index-oriented adaptive differential evolution(IOADE)algorithm is proposed,and the convergence performance of IOADE is superior to the traditional differential evolution and adaptive differential evolution methods.Finally,the effectiveness and feasibility of the proposed methods are verified by the experiments on a copper flotation industrial process.

Modeling and analysis of air combustion and steam regeneration in methanol to olefins processes

Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However,the catalyst deactivation is an inevitable feature in MTO processes,and regeneration,therefore,is one of the key steps in industrial MTO processes.Traditionally the MTO catalyst is regenerated by removing the deposited coke via air combustion,which unavoidably transforms coke into carbon dioxide and reduces the carbon utilization efficiency.Recent study shows that the coke species over MTO catalyst can be regenerated via steam,which can promote the light olefins yield as the deactivated coke species can be essentially transferred to industrially useful synthesis gas,is a promising pathway for further MTO processes development.In this work,we modelled and analyzed these two MTO regeneration methods in terms of carbon utilization efficiency and technology economics.As shown,the steam regeneration could achieve a carbon utilization efficiency of 84.31%,compared to 74.74%for air combustion regeneration.The MTO processes using steam regeneration can essentially achieve the near-zero carbon emission.In addition,light olefins production of the MTO processes using steam regeneration is 12.81%higher than that using air combustion regeneration.In this regard,steam regeneration could be considered as a potential yet promising regeneration method for further MTO processes,showing not only great environmental benefits but also competitive economic performance.

Transferable adversarial slow feature extraction network for few-shot quality prediction in coal-to-ethylene glycol process

In the coal-to-ethylene glycol(CTEG)process,precisely estimating quality variables is crucial for process monitoring,optimization,and control.A significant challenge in this regard is relying on offline laboratory analysis to obtain these variables,which often incurs substantial monetary costs and significant time delays.The resulting few-shot learning scenarios present a hurdle to the efficient development of predictive models.To address this issue,our study introduces the transferable adversarial slow feature extraction network(TASF-Net),an innovative approach designed specifically for few-shot quality prediction in the CTEG process.TASF-Net uniquely integrates the slowness principle with a deep Bayesian framework,effectively capturing the nonlinear and inertial characteristics of the CTEG process.Additionally,the model employs a variable attention mechanism to identify quality-related input variables adaptively at each time step.A key strength of TASF-Net lies in its ability to navigate the complex measurement noise,outliers,and system interference typical in CTEG data.Adversarial learning strategy using a min-max game is adopted to improve its robustness and ability to model irregular industrial data accurately and significantly.Furthermore,an incremental refining transfer learning framework is designed to further improve few-shot prediction performance achieved by transferring knowledge from the pretrained model on the source domain to the target domain.The effectiveness and superiority of TASF-Net have been empirically validated using a real-world CTEG dataset.Compared with some state-of-the-art methods,TASF-Net demonstrates exceptional capability in addressing the intricate challenges for few-shot quality prediction in the CTEG process.

Coupled bio-chemo-hydro-mechanical modeling of microbially induced calcite precipitation process considering biomass encapsulation using a micro-scale relationship

Geomaterials with inferior hydraulic and strength characteristics often need improvement to enhance their engineering behaviors.Traditional ground improvement techniques require enormous mechanical effort or synthetic chemicals.Sustainable stabilization technique such as microbially induced calcite precipitation(MICP)utilizes bacterial metabolic processes to precipitate cementitious calcium carbonate.The reactive transport of biochemical species in the soil mass initiates the precipitation of biocement during the MICP process.The precipitated biocement alters the hydro-mechanical performance of the soil mass.Usually,the flow,deformation,and transport phenomena regulate the biocementation technique via coupled bio-chemo-hydro-mechanical(BCHM)processes.Among all,one crucial phenomenon controlling the precipitation mechanism is the encapsulation of biomass by calcium carbonate.Biomass encapsulation can potentially reduce the biochemical reaction rate and decelerate biocementation.Laboratory examination of the encapsulation process demands a thorough analysis of associated coupled effects.Despite this,a numerical model can assist in capturing the coupled processes influencing encapsulation during the MICP treatment.However,most numerical models did not consider biochemical reaction rate kinetics accounting for the influence of bacterial encapsulation.Given this,the current study developed a coupled BCHM model to evaluate the effect of encapsulation on the precipitated calcite content using a micro-scale semiempirical relationship.Firstly,the developed BCHM model was verified and validated using numerical and experimental observations of soil column tests.Later,the encapsulation phenomenon was investigated in the soil columns of variable maximum calcite crystal sizes.The results depict altered reaction rates due to the encapsulation phenomenon and an observable change in the precipitated calcite content for each maximum crystal size.Furthermore,the permeability and deformation of the soil mass were affected by the simultaneous precipitation of calcium carbonate.Overall,the present study comprehended the influence of the encapsulation of bacteria on cement morphology-induced permeability,biocement-induced stresses and displacements.

Process synthesis for the separation of coal-to-ethanol products

The coal-to-ethanol process,as the clean coal utilization,faces challenges from the energy-intensive distillation that separates multi-component effluents for pure ethanol.Referring to at least eight columns,the synthesis of the ethanol distillation system is impracticable for exhaustive comparison and difficult for conventional superstructure-based optimization as rigorous models are used.This work adopts a superstructure-based framework,which combines the strategy that adaptively selects branches of the state-equipment network and the parallel stochastic algorithm for process synthesis.High-performance computing significantly reduces time consumption,and the adaptive strategy substantially lowers the complexity of the superstructure model.Moreover,parallel computing,elite search,population redistribution,and retention strategies for irrelevant parameters are used to improve the optimization efficiency further.The optimization terminates after 3000 generations,providing a flowsheet solution that applies two non-sharp splitting options in its distillation sequence.As a result,the 59-dimension superstructure-based optimization was solved efficiently via a differential evolution algorithm,and a high-quality solution with a 28.34%lower total annual cost than the benchmark was obtained.Meanwhile,the solution of the superstructure-based optimization is comparable to that obtained by optimizing a single specific configuration one by one.It indicates that the superstructure-based optimization that combines the adaptive strategy can be a promising approach to handling the process synthesis of large-scale and complex chemical processes.

Molecular investigation into the transformation of recalcitrant dissolved organic sulfur in refinery sour water during stripping process

Refinery sour water primarily originates from the tops of towers in various units and coker condensate,and cannot be discharged directly to a wastewater treatment plant due to high levels of chemical oxygen demand(COD)and organic sulfur contents.Even after the recovery of H_(2)S from the sour water by the stripping process,the effluent still contains a high concentration of dissolved organic sulfur(DOS),which can have a huge bad influence.While chemical composition of dissolved organic matter(DOM)in refinery wastewater has been extensively studied,the investigation of recalcitrant DOS from sour waters remains unclear.In the present study,chemical composition of sour water DOMs(especially DOS)was investigated using fluorescence spectroscopy(excitation-emission matrix,EEM)and mass spectrometry,including gas chromatography-mass spectrometry(GC-MS)and high-resolution Orbitrap MS.The GC-MS and EEM results showed that volatile and low-aromaticity compounds were effectively removed during the stripping process,while compounds with high hydrophilicity and humification degree were found to be more recalcitrant.The Orbitrap MS results showed that weak-polar oxygenated sulfur compounds were easier to be removed than oxygenated compounds.However,the effluent still contained significant amounts of sulfur-containing compounds with multiple sulfur atoms,particularly in the form of highly unsaturated and aromatic compounds.The Orbitrap MS/MS results of CHOS-containing compounds from the effluent indicate that the sulfur atoms may exist as sulfonates,disulfide bonds,thioethers.Understanding the composition and structure of sour water DOS is crucial for the development of effective treatment processes that can target polysulfide compounds and minimize their impact on the environment.

Study on trifluoromethanesulfonic acid-promoted synthesis of daidzein: Process optimization and reaction mechanism

Daidzein has been widely used in pharmaceuticals,nutraceuticals,cosmetics,feed additives,etc.Its preparation process and related reaction mechanism need to be further investigated.A cost-effective process for synthesizing daidzein was developed in this work.In this article,a two-step synthesis of daidzein(Friedel–Crafts acylation and[5+1]cyclization)was developed via the employment of trifluoromethanesulfonic acid(TfOH)as an effective promoting reagent.The effect of reaction conditions such as solvent,the amount of TfOH,reaction temperature,and reactant ratio on the conversion rate and the yield of the reaction,respectively,was systematically investigated,and daidzein was obtained in 74.0%isolated yield under optimal conditions.Due to the facilitating effect of TfOH,the Friedel–Crafts acylation was completed within 10 min at 90℃ and the[5+1]cyclization was completed within 180 min at 25℃.In addition,a possible reaction mechanism for this process was proposed.The results of the study may provide useful guidance for industrial production of daidzein on a large scale.

Deep structure of the Southeast Asian curved subduction system and its dynamic process

The deep structure,material circulation,and dynamic processes in the Southeast Asia have long been an elusive scientific puzzle due to the lack of systematic scientific observations and recognized theoretical models.Based on the deep seismic tomography using long-period natural earthquake data,in this study,the deep structure and material circulation of the curved subduction system in Southeast Asia was studied,and the dynamic processes since 100 million years ago was reconstructed.It is pointed out that challenges still exist in the precise reconstruction of deep mantle structures of the study area,the influence of multi-stage subduction on deep material exchange and shallow magma activity,as well as the spatiotemporal evolution and coupling mechanism of multi-plate convergence.Future work should focus on high-resolution land-sea joint 3-D seismic tomography imaging of the curved subduction system in the Southeast Asia,combined with geochemical analysis and geodynamic modelling works.

Observation of Giant Topological Hall Effect in Room-Temperature Ferromagnet Cr_(0.82)Te

Novel magnetic materials with non-trivial magnetic structures have led to exotic magnetic transport properties and significantly promoted the development of spintronics in recent years.Among them is the Crx Tey family,the magnetism of which can persist above room temperature,thus providing an ideal system for potential spintronic applications.Here we report the synthesis of a new compound,Cr_(0.82)Te,which demonstrates a record-high topological Hall effect at room temperature in this family.Cr_(0.82)Te displays soft ferromagnetism below the Curie temperature of 340 K.The magnetic measurement shows an obvious magneto-crystalline anisotropy with the easy axis located in the ab plane.The anomalous Hall effect can be well explained by a dominating skew scattering mechanism.Intriguing,after removing the normal Hall effect and anomalous Hall effect,a topological Hall effect can be observed up to 300 K and reaches up to 1.14μΩ·cm at 10 K,which is superior to most topological magnetic structural materials.This giant topological Hall effect possibly originates from the noncoplanar spin configuration during the spin flop process.Our work extends a new Cr_(x)Te_(y) system with topological non-trivial magnetic structure and broad prospects for spintronics applications in the future.

Pressure stimulated current in progressive failure process of combined coal-rock under uniaxial compression:Response and mechanism

Effective monitoring of the structural health of combined coal-rock under complex geological conditions by pressure stimulated currents(PSCs)has great potential for the understanding of dynamic disasters in underground engineering.To reveal the effect of this way,the uniaxial compression experiments with PSC monitoring were conducted on three types of coal-rock combination samples with different strength combinations.The mechanism explanation of PSCs are investigated by resistivity test,atomic force microscopy(AFM)and computed tomography(CT)methods,and a PSC flow model based on progressive failure process is proposed.The influence of strength combinations on PSCs in the progressive failure process are emphasized.The results show the PSC responses between rock part,coal part and the two components are different,which are affected by multi-scale fracture characteristics and electrical properties.As the rock strength decreases,the progressive failure process changes obviously with the influence range of interface constraint effect decreasing,resulting in the different responses of PSC strength and direction in different parts to fracture behaviors.The PSC flow model is initially validated by the relationship between the accumulated charges of different parts.The results are expected to provide a new reference and method for mining design and roadway quality assessment.

Exploring Nutritional Compositions,Volatile Compounds,Health Benefits,Emerging Processing Technologies,and Potential Food Products of Glutinous Rice:A Review

Glutinous rice(Oryza sativa var.glutinosa)stands out as one of the most popular rice varieties globally,amidst thousands of rice cultivars.Its increasing popularity is attributed to its rich nutritional compositions and health benefits.This review aims to summarize the nutritional compositions,volatile compounds,and health benefits of glutinous rice.Further,in-depth studies are necessary to explore the utilization of glutinous rice in enhancing processing technologies and developing new food products.Glutinous rice has been shown to possess numerous health benefits,including antioxidant activity,bioactive compounds,anti-cancer properties,anti-inflammatory effects,anti-diabetic potential,and cholesterol-lowering effects.Besides its nutritional compositions,the major volatile compounds identified in glutinous rice could serve as a functional food for human consumption.Emerging processing technologies related to glutinous rice are elaborated to improve the latest developments for incorporating them into various food products.