Selective Laser Melting(SLM),an advanced metal additive manufacturing technology,offers high precision and personalized customization advantages.However,selecting reasonable SLM parameters is challenging due to comple...Selective Laser Melting(SLM),an advanced metal additive manufacturing technology,offers high precision and personalized customization advantages.However,selecting reasonable SLM parameters is challenging due to complex relationships.This study proposes a method for identifying the optimal process window by combining the simulation model with an optimization algorithm.JAYA is guided by the principle of preferential behavior towards best solutions and avoidance of worst ones,but it is prone to premature convergence thus leading to insufficient global search.To overcome limitations,this research proposes a Differential Evolution-framed JAYA algorithm(DEJAYA).DEJAYA incorporates four key enhancements to improve the flexibility of the original algorithm,which include DE framework design,horizontal crossover operator,longitudinal crossover operator,and global greedy strategy.The effectiveness of DEJAYA is rigorously evaluated by a suite of 23 distinct benchmark functions.Furthermore,the numerical simulation establishes AlSi10Mg single-track formation models,and DEJAYA successfully identified the optimal process window for this problem.Experimental results validate that DEJAYA effectively guides SLM parameter selection for AlSi10Mg.展开更多
Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durabili...Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durability,and corrosion resistance.These metals have body-centered cubic crystal structure,characterized by limited slip systems and impeded dislocation motion,resulting in significant low-temperature brittleness,which poses challenges for the conventional processing.Additive manufacturing technique provides an innovative approach,enabling the production of intricate parts without molds,which significantly improves the efficiency of material usage.This review provides a comprehensive overview of the advancements in additive manufacturing techniques for the production of refractory metals,such as W,Ta,Mo,and Nb,particularly the laser powder bed fusion.In this review,the influence mechanisms of key process parameters(laser power,scan strategy,and powder characteristics)on the evolution of material microstructure,the formation of metallurgical defects,and mechanical properties were discussed.Generally,optimizing powder characteristics,such as sphericity,implementing substrate preheating,and formulating alloying strategies can significantly improve the densification and crack resistance of manufactured parts.Meanwhile,strictly controlling the oxygen impurity content and optimizing the energy density input are also the key factors to achieve the simultaneous improvement in strength and ductility of refractory metals.Although additive manufacturing technique provides an innovative solution for processing refractory metals,critical issues,such as residual stress control,microstructure and performance anisotropy,and process stability,still need to be addressed.This review not only provides a theoretical basis for the additive manufacturing of high-performance refractory metals,but also proposes forward-looking directions for their industrial application.展开更多
The challenge of wastewater treatment facilities is growing as they strive to enhance compliance strength and minimize energy consumption,chemical usage,downtime,and labor requirements in the face of increasingly vari...The challenge of wastewater treatment facilities is growing as they strive to enhance compliance strength and minimize energy consumption,chemical usage,downtime,and labor requirements in the face of increasingly variable influent and climate-related disruptions.The use of recent developments in Internet of Things(IoT),artificial intelligence,and robotics enables a transition to a less reactive mode of operation and more closed-loop automation.This review leads to an understanding of the demonstrations of networked sensing and edge data architecture to enhance observability,transform heterogeneous time-series and multimodal data into monitoring,forecasting,and risk intelligent decision knowledge,and extends robotics ability to measure and intervene in hazardous,distributed,or intermittently observed plant environments.We structure the literature on a deployable sense-think-act structure between unit processes,sensing strategies,Artificial Intelligence(AI)tasks,and execution pathways based on supervisory control and robotic operations.The applications of high leverage are evaluated,such as aeration and nutrient removal optimization,chemical dosing and disinfection control,prediction of membrane fouling and cleaning schedules,solids line stabilization,and predictive maintenance of the important assets.In these areas,we highlight aspects of quality of evidence,benchmarking issues,and operational circumstances that will define persistence of reported efficiency improvements after pilots,such as sensor drift and biofouling control,constraint-based control in service of Supervisory Control and Data Acquisition(SCADA)/Programmable Logic Controller(PLC)systems,cybersecurity-by-design,and model life cycle governance.We bring it to the maturity perspective of resilient,interoperable,and conscientiously independent Wastewater Treatment Plants(WWTPs)with a research requirement of standardized datasets,hybrid digital twins,uncertainty intentional optimization,and adaptive sampling and inspection by robotized techniques.展开更多
Ultra-high-strength aluminumalloy profile is an ideal choice for aerospace structuralmaterials due to its excellent specific strength and corrosion resistance.However,issues such as uneven metal flow,stress concentrat...Ultra-high-strength aluminumalloy profile is an ideal choice for aerospace structuralmaterials due to its excellent specific strength and corrosion resistance.However,issues such as uneven metal flow,stress concentration,and forming defects are prone to occur during their extrusion.This study focuses on an Al-Zn-Mg-Cu ultra-high-strength aluminum alloy profile with a double-U,multi-cavity thin-walled structure.Firstly,hot compression experiments were conducted at temperatures of 350○C,400○C,and 450○C,with strain rates of 0.01 and 1.0 s^(−1),to investigate the plastic deformation behavior of the material.Subsequently,a 3D coupled thermo-mechanical extrusion simulation model was established using Deform-3D to systematically analyze the influence of die structure and process parameters on metal flow velocity,effective stress/strain,and temperature distribution.The simulation revealed significant velocity differences,stress concentration,and uneven temperature distribution.Key parameters,including mesh density,extrusion ratio,die fillet,and bearing length,were optimized through full-factorial experiments.This optimization,combined with a stepped flow-guiding die design,effectively improved the metal flow pattern during extrusion.Trial production based on both the initial and optimized parameters were carried out.A comparative analysis demonstrates that the optimized scheme results in a final profile whose cross-section matches the target design closely,with complete filling of complex features and no obvious forming defects.This research provides a valuable reference for the extrusion process optimization and die design of complex-section profiles made from ultra-high-strength aluminum alloys.展开更多
To address the persistent challenge of dynamic mismatch between wellbore lifting capacity and reservoir fluid supply,and to establish a robust optimization framework for drainage operations in high-water-cut tight san...To address the persistent challenge of dynamic mismatch between wellbore lifting capacity and reservoir fluid supply,and to establish a robust optimization framework for drainage operations in high-water-cut tight sandstone gas reservoirs,this study systematically investigates the graded optimization and dynamic adaptation of drainage gas recovery technologies.Production data from a representative tight gas field were first employed to forecast reservoir performance.The predictive reliability was rigorously validated through high-precision history matching,thereby providing a quantitatively consistent foundation for subsequent wellbore optimization.Building on this characterization,a coupled simulation framework was developed that integrates wellbore multiphase flow modeling with nodal analysis based on the Inflow Performance Relationship,IPR,and the Vertical Lift Performance,VLP.This coordinated approach enables comprehensive evaluation of process adaptability and dynamic optimization of foam-assisted drainage,mechanical pumping,and jet pumping systems under evolving water-gas ratio,WGR conditions.The results reveal that a progressively increasing water-gas ratio is the dominant factor driving the transition from chemically assisted drainage methods to mechanically enhanced lifting technologies.A distinct quantitative threshold is identified at WGR≈0.002,beyond which mechanical intervention becomes more effective and economically justified.For mechanical pumping and jet pumping systems,a parameter inversion optimization strategy constrained by the target bottomhole flowing pressure,Pwf,is proposed to ensure stable production while maintaining reservoir drawdown control.In particular,the nozzle-to-throat area ratio of the jet pump is identified as the key governing parameter influencing entrainment capacity and lifting efficiency.Moreover,a configuration characterized by small pump diameter,long stroke length,and low operating speed is demonstrated to satisfy drainage requirements while mitigating torque fluctuations,enhancing volumetric efficiency,and improving pump fillage stability.展开更多
To address the challenges of complexity,power consumption,and cost constraints in traditional display driver integrated circuits(DDICs)caused by external NOR Flash and SRAM,this work proposes an embedded resistive ran...To address the challenges of complexity,power consumption,and cost constraints in traditional display driver integrated circuits(DDICs)caused by external NOR Flash and SRAM,this work proposes an embedded resistive random-access memory(RRAM)integration solution based on a 40 nm high-voltage CMOS logic platform.Targeting the yield fluctuations and stability challenges during RRAM mass production,systematic process optimizations are implemented to achieve synergistic improvements in RRAM performance and yield.Through modifications to the film sputtering and pre-deposition treatment,the withinwafer resistance uniformity(RSU)of the oxygen-deficient layer(ODL)thin film is improved from 11%to 8%,while inter-wafer process stability variation reduces from 23%to below 6%.Consequently,the yield of 8 Mb RRAM embedded mass production products increases from 87%to 98.5%.In terms of device performance,the RRAM demonstrates a fast 4.8 ns read speed,exceptional read disturb immunity of 3×10^(8) cycles at 95℃,10^(3) write/erase endurance cycles for the 1 Mb cells,and data retention of 12.5 years at 125℃.Post high-temperature operating life(HTOL)testing exhibits stable high/low resistance window.This study provides process optimization strategies and a reliability assurance framework for the mass production of highly integrated,low-power embedded RRAM display driver IC.展开更多
Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard ...Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.展开更多
On the principle of non-incremental algorithm, some basic ideas of process optimal control iterative algorithm, based on the Optimal Control Variational Principle in Mechanics, is proposed in this paper. Then the esse...On the principle of non-incremental algorithm, some basic ideas of process optimal control iterative algorithm, based on the Optimal Control Variational Principle in Mechanics, is proposed in this paper. Then the essential governing equations are presented. This work provides a new method to achieve the numerical solutions of the mechanic of finite deformation.展开更多
The optimization system, which was the subject of our study, is an autonomous chain for the automatic management of cyanide consumption. It is in the phase of industrial automation which made it possible to use the ma...The optimization system, which was the subject of our study, is an autonomous chain for the automatic management of cyanide consumption. It is in the phase of industrial automation which made it possible to use the machines in order to reduce the workload of the worker while keeping a high productivity and a quality in great demand. Furthermore, the use of cyanide in leaching tanks is a necessity in the gold recovery process. This consumption of cyanide must be optimal in these tanks in order to have a good recovery while controlling the concentration of cyanide. Cyanide is one of the most expensive products for mining companies. On a completely different note, we see huge variations during the addition of cyanide. Following a recommendation from the metallurgical and operations teams, the control team carried out an analysis of the problem while proposing a solution to reduce the variability around plus or minus 10% of the addition setpoint through automation. It should be noted that this automatic optimization by monitoring the concentration of cyanide, made use of industrial automation which is a technique which ensures the operation of the ore processing chain without human intervention. In other words, it made it possible to substitute a machine for man. So, this leads us to conduct a study on concentration levels in the real world. The results show that the analysis of the modeling of the cyanide consumption optimization system is an appropriate solution to eradicate failures in the mineral processing chain. The trend curves demonstrate this resolution perfectly.展开更多
Aluminum alloys manufactured using traditional processes are increasingly unable to meet the high flexibility and performance requirements of modern engineering.In this study,Al-Mg-Sc-Zr alloys were manufactured via l...Aluminum alloys manufactured using traditional processes are increasingly unable to meet the high flexibility and performance requirements of modern engineering.In this study,Al-Mg-Sc-Zr alloys were manufactured via laser powder bed fusion(LPBF)to obtain high-performance aluminum alloys.To this end,process parameter optimization and heat treatment were adopted.The optimal process parameters were determined by initially analyzing the relative density and defect distribution under varying energy densities.The sample obtained under the optimal process parameters exhibited a relative density of 99.84%.Subsequently,the corresponding phase compositions,microstructures,and mechanical performance of the as-fabricated specimens were determined using the optimal process parameters before and after heat treatment.The microstructures of the samples showed typical equiaxed columnar bimodal grain structures,with Al_(3)(Sc,Zr)precipitates detected.The samples exhibited no significant anisotropy before and after heat treatment,while the grain orientation differences were dominated by high-angle grain boundaries.The mechanical properties of all the samples were characterized using tensile and hardness tests.The yield strength,ultimate tensile strength,and elongation of the sample were 475.0 MPa,508.2 MPa,and 8.3%,respectively.Overall,samples with high density,low porosity,high strength,and high plasticity were obtained by process parameter optimization and appropriate heat treatment.展开更多
Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biolo...Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array＇s energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection.展开更多
Fiber quality measurement in spinning preparation is crucial for optimizing waste and meeting yarn quality specifications.The brand-new Uster AFIS 6–the next-generation laboratory instrument from Uster Technologies–...Fiber quality measurement in spinning preparation is crucial for optimizing waste and meeting yarn quality specifications.The brand-new Uster AFIS 6–the next-generation laboratory instrument from Uster Technologies–uniquely tests man-made fiber properties in addition to cotton.It provides critical data to optimize fiber process control for cotton,man-made fibers,and blended yarns.展开更多
Objective:To investigate the application effects of intelligent guidance systems in optimizing health check-up process management.Methods:A total of 400 examinees who underwent physical examinations at the hospital’s...Objective:To investigate the application effects of intelligent guidance systems in optimizing health check-up process management.Methods:A total of 400 examinees who underwent physical examinations at the hospital’s Health Management Center from January to December 2024 were randomly divided into a control group(200 cases)and an observation group(200 cases).The control group used traditional manual guidance methods,while the observation group employed the intelligent guidance system.The study compared two groups in terms of completion time,waiting time for each procedure,check-up efficiency scores,examinee satisfaction,and report issuance time.Results:The overall examination time in the observation group(85.3±12.7 minutes)was significantly shorter than that in the control group(142.6±18.5 minutes)(P<0.01);average waiting time per procedure decreased by 62.4%;check-up efficiency scores(8.9±0.8 points)were significantly higher than those in the control group(5.2±1.1 points)(P<0.01);satisfaction reached 96.5%,significantly higher than the control group’s 78.0%(P<0.01);and report issuance time was advanced by 1.5 days.Conclusion:Intelligent guidance systems can significantly optimize check-up processes,improve work efficiency,and examinee satisfaction,demonstrating significant clinical application value.展开更多
The latest progress in the process optimization and stability improvement of third-generation cephalosporins in recent years was reviewed.The introduction of green chemistry,enzyme catalysis,nanotechnology,lyophilizat...The latest progress in the process optimization and stability improvement of third-generation cephalosporins in recent years was reviewed.The introduction of green chemistry,enzyme catalysis,nanotechnology,lyophilization,and nitrogen-filled packaging technologies can only improve production efficiency and reduce the generation of by-products,but also significantly extend the shelf life of drugs.In the future,process automation and intelligent technology will further optimize the large-scale production process,and the combination of nanotechnology and precision drug delivery will promote the improvement of effect in clinical applications.展开更多
High ammonia-nitrogen digestate has become a key bottleneck limiting the anaerobic digestion of organic solid waste.Vacuum ammonia stripping can simultaneously remove and recover ammonia nitrogen,which has attracted a...High ammonia-nitrogen digestate has become a key bottleneck limiting the anaerobic digestion of organic solid waste.Vacuum ammonia stripping can simultaneously remove and recover ammonia nitrogen,which has attracted a lot of attention in recent years.To investigate the parameter effects on the efficiency and mass transfer,five combination conditions(53℃ 15 kPa,60°C 20 kPa,65°C 25 kPa,72°C 35 kPa,and 81°C 50 kPa)were conducted for ammonia stripping of sludge digestate.The results showed that 80%of ammonia nitrogen was stripped in 45 min for all experimental groups,but the ammonia transfer coefficient varied under different conditions,which increased with the rising of boiling point temperature,and reached the maximum value(39.0 mm/hr)at 81°C 50 kPa.The ammonia nitrogen removal efficiency was more than 80%for 30 min vacuum stripping after adjusting the initial pH to above 9.5,and adjustment of the initial alkalinity also affects the pH value of liquid digestate.It was found that pH and alkalinity are the key factors influencing the ammonia nitrogen dissociation and removal efficiency,while temperature and vacuum mainly affect the ammonia nitrogen mass transfer and removal velocity.In terms of the mechanism of vacuum ammonia stripping,it underwent alkalinity destruction,pH enhancement,ammonia nitrogen dissociation,and free ammonia removal.In this study,two-stage experiments of alkalinity destruction and ammonia removal were also carried out,which showed that the two-stage configuration was beneficial for ammonia removal.It provides a theoretical basis and practical technology for the vacuum ammonia stripping from liquid digestate of organic solid waste.展开更多
A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are ...A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are modeled by level set functions.Secondly,the mathematical model of the additive direction optimization problem is established,and an improved particle swarm optimization algorithm is designed to decide the best additive direction.Then,the two-step strategy is used to plan the hybrid manufacturing alternating sequence.The target parts are directly divided into various processing regions;each processing region is optimized based on manufacturability and manufacturing efficiency,and the optimal hybrid manufacturing alternating sequence is obtained by merging some processing regions.Finally,the method is used to outline the process plan of the designed example model and applied to the actual hybrid manufacturing process of the model.The manufacturing result shows that the method can meet the main considerations in hybrid manufacturing.In addition,the degree of automation of process planning is high,and the dependence on manual intervention is low.展开更多
Objective To optimize the ultrasonic extraction process for benzoic acid as a harmful substance in Paeonia lactiflora Pall.(P.lactiflora Pall.).Methods Methanol and ethanol solutions at different concentration gradien...Objective To optimize the ultrasonic extraction process for benzoic acid as a harmful substance in Paeonia lactiflora Pall.(P.lactiflora Pall.).Methods Methanol and ethanol solutions at different concentration gradients(25,50,75%)were prepared to investigate the effects of extraction solvents on the extraction efficiency of benzoic acid.The influences of ultrasonic frequency(35,50 Hz),ultrasonic power(40,60,80,100 W),ultrasonic time(10,20,30,40,50,60 minutes),and ultrasonic temperature(20,30,40,50℃)on the extraction efficiency were examined.Orthogonal experiments were conducted to analyze the effects of temperature,time,and ultrasonic power on the extraction efficiency and to screen the optimal ultrasonic extraction process.Results Various influencing factors had certain effects on the extraction efficiency of benzoic acid from P.lactiflora Pall.Single-factor analysis revealed that 25%methanol,ultrasonic frequency of 50 Hz,ultrasonic power of 40 W,ultrasonic time of 10minutes,and ultrasonic temperature of 30℃yielded the highest extraction efficiency for benzoic acid.The order of influence of different factors on the extraction efficiency was temperature>time>power.The optimal conditions obtained from orthogonal experiments were:extraction solvent of 25%methanol,ultrasonic frequency of 50 Hz,ultrasonic time of 20 minutes,ultrasonic power of 40 W,and ultrasonic temperature of 30℃.Conclusion Under the conditions of 25%methanol as the extraction solvent,ultrasonic frequency of 50 Hz,ultrasonic time of 20 minutes,ultrasonic power of 40 W,and ultrasonic temperature of 30℃,the extraction efficiency of benzoic acid from P.lactiflora Pall.was the highest.This method offers advantages such as simple operation,small sample size requirement,and low solvent consumption,providing a reliable analytical approach for quality control and safety evaluation of P.lactiflora Pall.展开更多
This paper examines the challenges in the technical briefing process for construction projects,including a three-level system and issues related to formalization.An optimization approaches was introduced based on the ...This paper examines the challenges in the technical briefing process for construction projects,including a three-level system and issues related to formalization.An optimization approaches was introduced based on the PDCA cycle,alongside the application of BIM and AR technologies.The key preparatory measures were outlined in this study and the functions of the management system was mentioned.Through case comparisons,this paper demonstrated that these optimizations can significantly improve efficiency and quality,support the development of an evaluation system to verify results,and highlight the critical role of organizational support.展开更多
Notable advancements have been made in the additive manufacturing(AM)of aerospace materials,driven by the needs for integrated components with intricate geometries and small-lot production of high-value components.Nic...Notable advancements have been made in the additive manufacturing(AM)of aerospace materials,driven by the needs for integrated components with intricate geometries and small-lot production of high-value components.Nickel-based superalloys,pivotal materials for high-temperature bearing components in aeroengines,present significant challenges in the fabrication of complex parts due to their great hardness.Huge attention and rapid progress have been garnered in AM processing of nicklebased superalloys,largely owing to its distinct benefits in the freedom of fabrication and reduced manufacturing lifecycle.Despite extensive research into AM in nickel-based superalloys,the corresponding results and conclusions are scattered attributed to the variety of nickel-based superalloys and complex AM processing parameters.Therefore,there is still a pressing need for a comprehensive and deep understanding of the relationship between the AM processing and microstructures and mechanical performance of nickel-based superalloys.This review introduces the processing characteristics of four primary AM technologies utilized for superalloys and summarizes the microstructures and mechanical properties prior to and post-heat treatments.Additionally,this review presents innovative superalloys specifically accommodated to AM processing and offers insights into the material development and performance improvement,aiming to provide a valuable assessment on AM processing of nickel-based superalloys and an effective guidance for the future research.展开更多
The optimization of reaction processes is crucial for the green, efficient, and sustainable development of the chemical industry. However, how to address the problems posed by multiple variables, nonlinearities, and u...The optimization of reaction processes is crucial for the green, efficient, and sustainable development of the chemical industry. However, how to address the problems posed by multiple variables, nonlinearities, and uncertainties during optimization remains a formidable challenge. In this study, a strategy combining interpretable machine learning with metaheuristic optimization algorithms is employed to optimize the reaction process. First, experimental data from a biodiesel production process are collected to establish a database. These data are then used to construct a predictive model based on artificial neural network (ANN) models. Subsequently, interpretable machine learning techniques are applied for quantitative analysis and verification of the model. Finally, four metaheuristic optimization algorithms are coupled with the ANN model to achieve the desired optimization. The research results show that the methanol: palm fatty acid distillate (PFAD) molar ratio contributes the most to the reaction outcome, accounting for 41%. The ANN-simulated annealing (SA) hybrid method is more suitable for this optimization, and the optimal process parameters are a catalyst concentration of 3.00% (mass), a methanol: PFAD molar ratio of 8.67, and a reaction time of 30 min. This study provides deeper insights into reaction process optimization, which will facilitate future applications in various reaction optimization processes.展开更多
文摘Selective Laser Melting(SLM),an advanced metal additive manufacturing technology,offers high precision and personalized customization advantages.However,selecting reasonable SLM parameters is challenging due to complex relationships.This study proposes a method for identifying the optimal process window by combining the simulation model with an optimization algorithm.JAYA is guided by the principle of preferential behavior towards best solutions and avoidance of worst ones,but it is prone to premature convergence thus leading to insufficient global search.To overcome limitations,this research proposes a Differential Evolution-framed JAYA algorithm(DEJAYA).DEJAYA incorporates four key enhancements to improve the flexibility of the original algorithm,which include DE framework design,horizontal crossover operator,longitudinal crossover operator,and global greedy strategy.The effectiveness of DEJAYA is rigorously evaluated by a suite of 23 distinct benchmark functions.Furthermore,the numerical simulation establishes AlSi10Mg single-track formation models,and DEJAYA successfully identified the optimal process window for this problem.Experimental results validate that DEJAYA effectively guides SLM parameter selection for AlSi10Mg.
基金National MCF Energy R&D Program(2024YFE03260300)。
文摘Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durability,and corrosion resistance.These metals have body-centered cubic crystal structure,characterized by limited slip systems and impeded dislocation motion,resulting in significant low-temperature brittleness,which poses challenges for the conventional processing.Additive manufacturing technique provides an innovative approach,enabling the production of intricate parts without molds,which significantly improves the efficiency of material usage.This review provides a comprehensive overview of the advancements in additive manufacturing techniques for the production of refractory metals,such as W,Ta,Mo,and Nb,particularly the laser powder bed fusion.In this review,the influence mechanisms of key process parameters(laser power,scan strategy,and powder characteristics)on the evolution of material microstructure,the formation of metallurgical defects,and mechanical properties were discussed.Generally,optimizing powder characteristics,such as sphericity,implementing substrate preheating,and formulating alloying strategies can significantly improve the densification and crack resistance of manufactured parts.Meanwhile,strictly controlling the oxygen impurity content and optimizing the energy density input are also the key factors to achieve the simultaneous improvement in strength and ductility of refractory metals.Although additive manufacturing technique provides an innovative solution for processing refractory metals,critical issues,such as residual stress control,microstructure and performance anisotropy,and process stability,still need to be addressed.This review not only provides a theoretical basis for the additive manufacturing of high-performance refractory metals,but also proposes forward-looking directions for their industrial application.
文摘The challenge of wastewater treatment facilities is growing as they strive to enhance compliance strength and minimize energy consumption,chemical usage,downtime,and labor requirements in the face of increasingly variable influent and climate-related disruptions.The use of recent developments in Internet of Things(IoT),artificial intelligence,and robotics enables a transition to a less reactive mode of operation and more closed-loop automation.This review leads to an understanding of the demonstrations of networked sensing and edge data architecture to enhance observability,transform heterogeneous time-series and multimodal data into monitoring,forecasting,and risk intelligent decision knowledge,and extends robotics ability to measure and intervene in hazardous,distributed,or intermittently observed plant environments.We structure the literature on a deployable sense-think-act structure between unit processes,sensing strategies,Artificial Intelligence(AI)tasks,and execution pathways based on supervisory control and robotic operations.The applications of high leverage are evaluated,such as aeration and nutrient removal optimization,chemical dosing and disinfection control,prediction of membrane fouling and cleaning schedules,solids line stabilization,and predictive maintenance of the important assets.In these areas,we highlight aspects of quality of evidence,benchmarking issues,and operational circumstances that will define persistence of reported efficiency improvements after pilots,such as sensor drift and biofouling control,constraint-based control in service of Supervisory Control and Data Acquisition(SCADA)/Programmable Logic Controller(PLC)systems,cybersecurity-by-design,and model life cycle governance.We bring it to the maturity perspective of resilient,interoperable,and conscientiously independent Wastewater Treatment Plants(WWTPs)with a research requirement of standardized datasets,hybrid digital twins,uncertainty intentional optimization,and adaptive sampling and inspection by robotized techniques.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFB3710805).
文摘Ultra-high-strength aluminumalloy profile is an ideal choice for aerospace structuralmaterials due to its excellent specific strength and corrosion resistance.However,issues such as uneven metal flow,stress concentration,and forming defects are prone to occur during their extrusion.This study focuses on an Al-Zn-Mg-Cu ultra-high-strength aluminum alloy profile with a double-U,multi-cavity thin-walled structure.Firstly,hot compression experiments were conducted at temperatures of 350○C,400○C,and 450○C,with strain rates of 0.01 and 1.0 s^(−1),to investigate the plastic deformation behavior of the material.Subsequently,a 3D coupled thermo-mechanical extrusion simulation model was established using Deform-3D to systematically analyze the influence of die structure and process parameters on metal flow velocity,effective stress/strain,and temperature distribution.The simulation revealed significant velocity differences,stress concentration,and uneven temperature distribution.Key parameters,including mesh density,extrusion ratio,die fillet,and bearing length,were optimized through full-factorial experiments.This optimization,combined with a stepped flow-guiding die design,effectively improved the metal flow pattern during extrusion.Trial production based on both the initial and optimized parameters were carried out.A comparative analysis demonstrates that the optimized scheme results in a final profile whose cross-section matches the target design closely,with complete filling of complex features and no obvious forming defects.This research provides a valuable reference for the extrusion process optimization and die design of complex-section profiles made from ultra-high-strength aluminum alloys.
基金supported by the Major Science and Technology Project of PetroChina Company Limited“Research on Key Technologies for Enhancing Recovery in Tight Sandstone Gas Reservoirs”,specifically under its third sub-project:“Research on Integrated Fracturing,Drainage,and Production Technology to Enhance Single-Well Production in Water-Bearing Gas Reservoirs”(Grant number:2023ZZ25YJ03).
文摘To address the persistent challenge of dynamic mismatch between wellbore lifting capacity and reservoir fluid supply,and to establish a robust optimization framework for drainage operations in high-water-cut tight sandstone gas reservoirs,this study systematically investigates the graded optimization and dynamic adaptation of drainage gas recovery technologies.Production data from a representative tight gas field were first employed to forecast reservoir performance.The predictive reliability was rigorously validated through high-precision history matching,thereby providing a quantitatively consistent foundation for subsequent wellbore optimization.Building on this characterization,a coupled simulation framework was developed that integrates wellbore multiphase flow modeling with nodal analysis based on the Inflow Performance Relationship,IPR,and the Vertical Lift Performance,VLP.This coordinated approach enables comprehensive evaluation of process adaptability and dynamic optimization of foam-assisted drainage,mechanical pumping,and jet pumping systems under evolving water-gas ratio,WGR conditions.The results reveal that a progressively increasing water-gas ratio is the dominant factor driving the transition from chemically assisted drainage methods to mechanically enhanced lifting technologies.A distinct quantitative threshold is identified at WGR≈0.002,beyond which mechanical intervention becomes more effective and economically justified.For mechanical pumping and jet pumping systems,a parameter inversion optimization strategy constrained by the target bottomhole flowing pressure,Pwf,is proposed to ensure stable production while maintaining reservoir drawdown control.In particular,the nozzle-to-throat area ratio of the jet pump is identified as the key governing parameter influencing entrainment capacity and lifting efficiency.Moreover,a configuration characterized by small pump diameter,long stroke length,and low operating speed is demonstrated to satisfy drainage requirements while mitigating torque fluctuations,enhancing volumetric efficiency,and improving pump fillage stability.
文摘To address the challenges of complexity,power consumption,and cost constraints in traditional display driver integrated circuits(DDICs)caused by external NOR Flash and SRAM,this work proposes an embedded resistive random-access memory(RRAM)integration solution based on a 40 nm high-voltage CMOS logic platform.Targeting the yield fluctuations and stability challenges during RRAM mass production,systematic process optimizations are implemented to achieve synergistic improvements in RRAM performance and yield.Through modifications to the film sputtering and pre-deposition treatment,the withinwafer resistance uniformity(RSU)of the oxygen-deficient layer(ODL)thin film is improved from 11%to 8%,while inter-wafer process stability variation reduces from 23%to below 6%.Consequently,the yield of 8 Mb RRAM embedded mass production products increases from 87%to 98.5%.In terms of device performance,the RRAM demonstrates a fast 4.8 ns read speed,exceptional read disturb immunity of 3×10^(8) cycles at 95℃,10^(3) write/erase endurance cycles for the 1 Mb cells,and data retention of 12.5 years at 125℃.Post high-temperature operating life(HTOL)testing exhibits stable high/low resistance window.This study provides process optimization strategies and a reliability assurance framework for the mass production of highly integrated,low-power embedded RRAM display driver IC.
基金Supported by the National High Technology Research and Development Program of China(2014AA041803)the National Natural Science Foundation of China(61320106009)
文摘Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.
基金the National Natural Science Foundation of China(Grant No.594305050).
文摘On the principle of non-incremental algorithm, some basic ideas of process optimal control iterative algorithm, based on the Optimal Control Variational Principle in Mechanics, is proposed in this paper. Then the essential governing equations are presented. This work provides a new method to achieve the numerical solutions of the mechanic of finite deformation.
文摘The optimization system, which was the subject of our study, is an autonomous chain for the automatic management of cyanide consumption. It is in the phase of industrial automation which made it possible to use the machines in order to reduce the workload of the worker while keeping a high productivity and a quality in great demand. Furthermore, the use of cyanide in leaching tanks is a necessity in the gold recovery process. This consumption of cyanide must be optimal in these tanks in order to have a good recovery while controlling the concentration of cyanide. Cyanide is one of the most expensive products for mining companies. On a completely different note, we see huge variations during the addition of cyanide. Following a recommendation from the metallurgical and operations teams, the control team carried out an analysis of the problem while proposing a solution to reduce the variability around plus or minus 10% of the addition setpoint through automation. It should be noted that this automatic optimization by monitoring the concentration of cyanide, made use of industrial automation which is a technique which ensures the operation of the ore processing chain without human intervention. In other words, it made it possible to substitute a machine for man. So, this leads us to conduct a study on concentration levels in the real world. The results show that the analysis of the modeling of the cyanide consumption optimization system is an appropriate solution to eradicate failures in the mineral processing chain. The trend curves demonstrate this resolution perfectly.
基金supported by National Natural Science Foundation of China(Grant Nos.5233500651975073)State Key Laboratory of Mechanical Transmission for Advanced Equipment(Grant No.SKLMT-MSKFKT-202104).
文摘Aluminum alloys manufactured using traditional processes are increasingly unable to meet the high flexibility and performance requirements of modern engineering.In this study,Al-Mg-Sc-Zr alloys were manufactured via laser powder bed fusion(LPBF)to obtain high-performance aluminum alloys.To this end,process parameter optimization and heat treatment were adopted.The optimal process parameters were determined by initially analyzing the relative density and defect distribution under varying energy densities.The sample obtained under the optimal process parameters exhibited a relative density of 99.84%.Subsequently,the corresponding phase compositions,microstructures,and mechanical performance of the as-fabricated specimens were determined using the optimal process parameters before and after heat treatment.The microstructures of the samples showed typical equiaxed columnar bimodal grain structures,with Al_(3)(Sc,Zr)precipitates detected.The samples exhibited no significant anisotropy before and after heat treatment,while the grain orientation differences were dominated by high-angle grain boundaries.The mechanical properties of all the samples were characterized using tensile and hardness tests.The yield strength,ultimate tensile strength,and elongation of the sample were 475.0 MPa,508.2 MPa,and 8.3%,respectively.Overall,samples with high density,low porosity,high strength,and high plasticity were obtained by process parameter optimization and appropriate heat treatment.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11105062 and 11265014the Fundamental Research Funds for the Central Universities under Grant Nos LZUJBKY-2011-57 and LZUJBKY-2015-119
文摘Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array＇s energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection.
文摘Fiber quality measurement in spinning preparation is crucial for optimizing waste and meeting yarn quality specifications.The brand-new Uster AFIS 6–the next-generation laboratory instrument from Uster Technologies–uniquely tests man-made fiber properties in addition to cotton.It provides critical data to optimize fiber process control for cotton,man-made fibers,and blended yarns.
文摘Objective:To investigate the application effects of intelligent guidance systems in optimizing health check-up process management.Methods:A total of 400 examinees who underwent physical examinations at the hospital’s Health Management Center from January to December 2024 were randomly divided into a control group(200 cases)and an observation group(200 cases).The control group used traditional manual guidance methods,while the observation group employed the intelligent guidance system.The study compared two groups in terms of completion time,waiting time for each procedure,check-up efficiency scores,examinee satisfaction,and report issuance time.Results:The overall examination time in the observation group(85.3±12.7 minutes)was significantly shorter than that in the control group(142.6±18.5 minutes)(P<0.01);average waiting time per procedure decreased by 62.4%;check-up efficiency scores(8.9±0.8 points)were significantly higher than those in the control group(5.2±1.1 points)(P<0.01);satisfaction reached 96.5%,significantly higher than the control group’s 78.0%(P<0.01);and report issuance time was advanced by 1.5 days.Conclusion:Intelligent guidance systems can significantly optimize check-up processes,improve work efficiency,and examinee satisfaction,demonstrating significant clinical application value.
基金Supported by the Funds from Central Government for Guiding Local Science and Technology Development(ZY20230102)Planning Project of Scientific Research and Technology Development in Guilin(20220104-4,20210202-1)Science and Technology Planing Project of Guangxi(Guike AB24010263).
文摘The latest progress in the process optimization and stability improvement of third-generation cephalosporins in recent years was reviewed.The introduction of green chemistry,enzyme catalysis,nanotechnology,lyophilization,and nitrogen-filled packaging technologies can only improve production efficiency and reduce the generation of by-products,but also significantly extend the shelf life of drugs.In the future,process automation and intelligent technology will further optimize the large-scale production process,and the combination of nanotechnology and precision drug delivery will promote the improvement of effect in clinical applications.
基金supported by the National Key Research and Development Program of China(No.2020YFC1908702)the National Natural Science Foundation of China(No.52131002)+1 种基金the Science and Technology Commission of Shanghai Municipality(No.22dz1209200)China Three Gorges Corporation(No.202403018).
文摘High ammonia-nitrogen digestate has become a key bottleneck limiting the anaerobic digestion of organic solid waste.Vacuum ammonia stripping can simultaneously remove and recover ammonia nitrogen,which has attracted a lot of attention in recent years.To investigate the parameter effects on the efficiency and mass transfer,five combination conditions(53℃ 15 kPa,60°C 20 kPa,65°C 25 kPa,72°C 35 kPa,and 81°C 50 kPa)were conducted for ammonia stripping of sludge digestate.The results showed that 80%of ammonia nitrogen was stripped in 45 min for all experimental groups,but the ammonia transfer coefficient varied under different conditions,which increased with the rising of boiling point temperature,and reached the maximum value(39.0 mm/hr)at 81°C 50 kPa.The ammonia nitrogen removal efficiency was more than 80%for 30 min vacuum stripping after adjusting the initial pH to above 9.5,and adjustment of the initial alkalinity also affects the pH value of liquid digestate.It was found that pH and alkalinity are the key factors influencing the ammonia nitrogen dissociation and removal efficiency,while temperature and vacuum mainly affect the ammonia nitrogen mass transfer and removal velocity.In terms of the mechanism of vacuum ammonia stripping,it underwent alkalinity destruction,pH enhancement,ammonia nitrogen dissociation,and free ammonia removal.In this study,two-stage experiments of alkalinity destruction and ammonia removal were also carried out,which showed that the two-stage configuration was beneficial for ammonia removal.It provides a theoretical basis and practical technology for the vacuum ammonia stripping from liquid digestate of organic solid waste.
基金The National Natural Science Foundation of China(No.52305381)the Natural Science Foundation of Jiangsu Province(No.BK20210351)the Fundamental Research Funds for the Central Universities(No.30923011008).
文摘A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are modeled by level set functions.Secondly,the mathematical model of the additive direction optimization problem is established,and an improved particle swarm optimization algorithm is designed to decide the best additive direction.Then,the two-step strategy is used to plan the hybrid manufacturing alternating sequence.The target parts are directly divided into various processing regions;each processing region is optimized based on manufacturability and manufacturing efficiency,and the optimal hybrid manufacturing alternating sequence is obtained by merging some processing regions.Finally,the method is used to outline the process plan of the designed example model and applied to the actual hybrid manufacturing process of the model.The manufacturing result shows that the method can meet the main considerations in hybrid manufacturing.In addition,the degree of automation of process planning is high,and the dependence on manual intervention is low.
基金supported by the Heilongjiang Provincial Administration of Traditional Chinese Medicine Project(ZHY18-153).
文摘Objective To optimize the ultrasonic extraction process for benzoic acid as a harmful substance in Paeonia lactiflora Pall.(P.lactiflora Pall.).Methods Methanol and ethanol solutions at different concentration gradients(25,50,75%)were prepared to investigate the effects of extraction solvents on the extraction efficiency of benzoic acid.The influences of ultrasonic frequency(35,50 Hz),ultrasonic power(40,60,80,100 W),ultrasonic time(10,20,30,40,50,60 minutes),and ultrasonic temperature(20,30,40,50℃)on the extraction efficiency were examined.Orthogonal experiments were conducted to analyze the effects of temperature,time,and ultrasonic power on the extraction efficiency and to screen the optimal ultrasonic extraction process.Results Various influencing factors had certain effects on the extraction efficiency of benzoic acid from P.lactiflora Pall.Single-factor analysis revealed that 25%methanol,ultrasonic frequency of 50 Hz,ultrasonic power of 40 W,ultrasonic time of 10minutes,and ultrasonic temperature of 30℃yielded the highest extraction efficiency for benzoic acid.The order of influence of different factors on the extraction efficiency was temperature>time>power.The optimal conditions obtained from orthogonal experiments were:extraction solvent of 25%methanol,ultrasonic frequency of 50 Hz,ultrasonic time of 20 minutes,ultrasonic power of 40 W,and ultrasonic temperature of 30℃.Conclusion Under the conditions of 25%methanol as the extraction solvent,ultrasonic frequency of 50 Hz,ultrasonic time of 20 minutes,ultrasonic power of 40 W,and ultrasonic temperature of 30℃,the extraction efficiency of benzoic acid from P.lactiflora Pall.was the highest.This method offers advantages such as simple operation,small sample size requirement,and low solvent consumption,providing a reliable analytical approach for quality control and safety evaluation of P.lactiflora Pall.
文摘This paper examines the challenges in the technical briefing process for construction projects,including a three-level system and issues related to formalization.An optimization approaches was introduced based on the PDCA cycle,alongside the application of BIM and AR technologies.The key preparatory measures were outlined in this study and the functions of the management system was mentioned.Through case comparisons,this paper demonstrated that these optimizations can significantly improve efficiency and quality,support the development of an evaluation system to verify results,and highlight the critical role of organizational support.
基金financially supported by the National Key R&D Program of China(No.2021YFB3702301)the National Natural Science Foundation of China(No.52101068]+2 种基金the China Postdoctoral Science Foundation[No.2022T150342]the Postdoctoral International Exchange Program[No.YJ20210129]the Shuimu Tsinghua Scholar Program(No.2020SM100)
文摘Notable advancements have been made in the additive manufacturing(AM)of aerospace materials,driven by the needs for integrated components with intricate geometries and small-lot production of high-value components.Nickel-based superalloys,pivotal materials for high-temperature bearing components in aeroengines,present significant challenges in the fabrication of complex parts due to their great hardness.Huge attention and rapid progress have been garnered in AM processing of nicklebased superalloys,largely owing to its distinct benefits in the freedom of fabrication and reduced manufacturing lifecycle.Despite extensive research into AM in nickel-based superalloys,the corresponding results and conclusions are scattered attributed to the variety of nickel-based superalloys and complex AM processing parameters.Therefore,there is still a pressing need for a comprehensive and deep understanding of the relationship between the AM processing and microstructures and mechanical performance of nickel-based superalloys.This review introduces the processing characteristics of four primary AM technologies utilized for superalloys and summarizes the microstructures and mechanical properties prior to and post-heat treatments.Additionally,this review presents innovative superalloys specifically accommodated to AM processing and offers insights into the material development and performance improvement,aiming to provide a valuable assessment on AM processing of nickel-based superalloys and an effective guidance for the future research.
基金supported by the National Natural Science Foundation of China(22408227,22238005)the Postdoctoral Research Foundation of China(GZC20231576).
文摘The optimization of reaction processes is crucial for the green, efficient, and sustainable development of the chemical industry. However, how to address the problems posed by multiple variables, nonlinearities, and uncertainties during optimization remains a formidable challenge. In this study, a strategy combining interpretable machine learning with metaheuristic optimization algorithms is employed to optimize the reaction process. First, experimental data from a biodiesel production process are collected to establish a database. These data are then used to construct a predictive model based on artificial neural network (ANN) models. Subsequently, interpretable machine learning techniques are applied for quantitative analysis and verification of the model. Finally, four metaheuristic optimization algorithms are coupled with the ANN model to achieve the desired optimization. The research results show that the methanol: palm fatty acid distillate (PFAD) molar ratio contributes the most to the reaction outcome, accounting for 41%. The ANN-simulated annealing (SA) hybrid method is more suitable for this optimization, and the optimal process parameters are a catalyst concentration of 3.00% (mass), a methanol: PFAD molar ratio of 8.67, and a reaction time of 30 min. This study provides deeper insights into reaction process optimization, which will facilitate future applications in various reaction optimization processes.
