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
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
Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers of...Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost.展开更多
To address the challenges of high energy consumption and prominent costs in the traditional three-columns distillation process for cellulosic fuel ethanol,a distillation–molecular sieve coupling separation process is...To address the challenges of high energy consumption and prominent costs in the traditional three-columns distillation process for cellulosic fuel ethanol,a distillation–molecular sieve coupling separation process is proposed.This process integrates a three-column(crude distillation column,first distillation column,second distillation column)system with a 3A molecular sieve adsorption deep dehydration unit.A thermal coupling network is constructed via differential pressure design(steam from medium/high-pressure columns as mutual heat sources,reboiler liquid waste heat for feed preheating),and molecular sieve adsorption conditions are optimized.The study first performs a thermodynamic consistency test on the ethanol–water system,determines optimal non-random two-liquid(NRTL)model binary interaction parameters via experimental data regression for Aspen Plus simulation.Aiming at minimum total annual cost(TAC),Aspen Plus is used to optimize process parameters(theoretical tray number,feed location,reflux ratio,side-draw position,etc.).Economic analysis shows this process reduces CO_(2) emission costs by 27.56%,TAC by 15.58%(to 5.123×10^(6) USD·a^(−1)),and increases ethanol purity to>99.6%,providing an effective solution for green,efficient separation.展开更多
A new 18-lump kinetic model for naphtha catalytic reforming reactions is discussed. By developing this model as a user module, a whole industrial continuous catalytic reforming process is simulated on Aspen plus plat-...A new 18-lump kinetic model for naphtha catalytic reforming reactions is discussed. By developing this model as a user module, a whole industrial continuous catalytic reforming process is simulated on Aspen plus plat-form. The technique utilizes the strong databases, complete sets of modules, and flexible simulation tools of the Aspen plus system and retains the characteristics of the proposed kinetic model. The calculated results are in fair agreement with the actual operating data. Based on the model of the whole reforming process, the process is opti-mized and the optimization results are tested in the actual industrial unit for about two months. The test shows that the process profit increases about 1000yuan·h-1 averagely, which is close to the calculated result.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
The outstanding growth in the applications of large language models(LLMs)demonstrates the significance of adaptive and efficient prompt engineering tactics.The existing methods may not be variable,vigorous and streaml...The outstanding growth in the applications of large language models(LLMs)demonstrates the significance of adaptive and efficient prompt engineering tactics.The existing methods may not be variable,vigorous and streamlined in different domains.The offered study introduces an immediate optimization outline,named PROMPTx-PE,that is going to yield a greater level of precision and strength when it comes to the assignments that are premised on LLM.The proposed systemfeatures a timely selection schemewhich is informed by reinforcement learning,a contextual layer and a dynamic weighting module which is regulated by Lyapunov-based stability guidelines.The PROMPTx-PE dynamically varies the exploration and exploitation of the prompt space,depending on real-time feedback and multi-objective reward development.Extensive testing on both benchmark(GLUE,SuperGLUE)and domain-specific data(Healthcare-QA and Industrial-NER)demonstrates a large best performance to be 89.4%and a strong robustness disconnect with under 3%computation expense.The results confirm the effectiveness,consistency,and scalability of PROMPTx-PE as a platform of adaptive prompt engineering based on recent uses of LLMs.展开更多
In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In additi...In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In addition,methods for deploying multiple cameras for motion capture of users(e.g.,performers)are widely used in computer graphics.As the need to minimize and optimize the number of cameras grows to reduce costs,various technologies and research approaches focused on Optimal Camera Placement(OCP)are continually being proposed.However,as most existing studies assume homogeneous camera setups,there is a growing demand for studies on heterogeneous camera setups.For instance,technical demands keep emerging in scenarios with minimal camera configurations,especially regarding cost factors,the physical placement of cameras given the spatial structure,and image capture strategies for heterogeneous cameras,such as high-resolution RGB cameras and depth cameras.In this study,we propose a pre-visualization and simulation method for the optimal placement of heterogeneous cameras in XR environments,accounting for both the specifications of heterogeneous cameras(e.g.,field of view)and the physical configuration(e.g.,wall configuration)in real-world spaces.The proposed method performs a visibility analysis of cameras by considering each camera’s field-of-view volume,resolution,and unique characteristics,along with physicalspace constraints.This approach enables the optimal position and rotation of each camera to be recommended,along with the minimum number of cameras required.In the results of our study conducted in heterogeneous camera combinations,the proposed method achieved 81.7%~82.7%coverage of the target visual information using only 2~3 cameras.In contrast,single(or homogeneous)-typed cameras were required to use 11 cameras for 81.6%coverage.Accordingly,we found that camera deployment resources can be reduced with the proposed approaches.展开更多
In view of the frequent deterioration of molten steel quality during the tundish filling process,the slag-steel-air interface behavior in a tundish,including liquid level fluctuation,slag eyes,slag entrapment and air ...In view of the frequent deterioration of molten steel quality during the tundish filling process,the slag-steel-air interface behavior in a tundish,including liquid level fluctuation,slag eyes,slag entrapment and air suction during the steady-state casting and filling process,was comparatively studied through physical modeling and mathematical simulation methods.During the filling process,the liquid surface forms a large-size slag eye under the impact of molten steel from a ladle shroud,which simultaneously results in a violent fluctuation of liquid level.Concurrently,the liquid flow entrains the air phase and the cover slag into the tundish impact zone,resulting in slag entrapment and air suction.At filling flow rates of 1.5Q,2.0Q,and 2.5Q(Q is the flow rate under steady-state casting),the amount of slag entrapped is 8.39×10^(-5),9.65×10^(-5),and 12.7×10^(-5)m^(3),respectively,while the volume of air aspirated is 0.84×10^(-4),1.47×10^(-4),and 2.01×10^(-4)m^(3),indicating that slag entrapment and air suction intensify with an increase in tundish filling flow rate.Flow field characterization identifies eddy currents in the impact zone as the primary driver of the above phenomena.Proper filling process parameters were proposed to improve the steel quality during the tundish filling.展开更多
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
In the electroslag remelting(ESR)process,it mainly relies on thermal experiments or analysis via mechanistic models to realize the physical fields simulation of the electromagnetic field and temperature field coupled ...In the electroslag remelting(ESR)process,it mainly relies on thermal experiments or analysis via mechanistic models to realize the physical fields simulation of the electromagnetic field and temperature field coupled transfer,which has the limitations of high cost,a large amount of calculating data and high computing power requirements.A novel network based on physics-informed neural network(PINN)was designed to realize the fast and high-fidelity prediction of the distribution of electromagnetic field and temperature field in ESR process.The physical laws were combined with the deep learning network through PINN,and physical constraints were embedded to achieve effective solution of partial differential equations(PDEs).PINN was used to minimize the loss function consisting of data error,physical information error and boundary condition error.The physical laws and boundary condition constraints in the ESR process were considered to maintain high PDE solution accuracy under different spatial and temporal resolutions.Automatic differentiation(Autodiff)technique and gradient descent algorithm were used to optimize the network parameters.The experimental results show that compared with the mechanistic models,PINN can effectively replace thermal experiments to realize the physical field simulation of ESR process with only a few experimental data,which can avoid the disadvantages of pure data-driven network simulation that requires a large amount of training data.Moreover,the solution of PINN has good physical interpretability and reliability of simulation results.For simulating electromagnetic field and temperature field distribution,the training time of the network is only 140 and 203 s,and the regression indicators of root mean square error can reach 12.65 and 13.76,respectively.展开更多
With growing concerns over environmental issues,ethylene manufacturing is shifting from a sole focus on economic benefits to an additional consideration of environmental impacts.The operation of the thermal cracking f...With growing concerns over environmental issues,ethylene manufacturing is shifting from a sole focus on economic benefits to an additional consideration of environmental impacts.The operation of the thermal cracking furnace in ethylene manufacturing determines not only the profitability of an ethylene plant but also the carbon emissions it releases.While multi-objective optimization of the thermal cracking furnace to balance profit with environmental impact is an effective solution to achieve green ethylene man-ufacturing,it carries a high computational demand due to the complex dynamic processes involved.In this work,artificial intelligence(AI)is applied to develop a novel hybrid model based on physically consistent machine learning(PCML).This hybrid model not only reduces the computational demand but also retains the interpretability and scalability of the model.With this hybrid model,the computational demand of the multi-objective dynamic optimization is reduced to 77 s.The optimization results show that dynamically adjusting the operating variables with coke formation can effectively improve profit and reduce CO_(2)emissions.In addition,the results from this study indicate that sacrificing 28.97%of the annual profit can significantly reduce the annual CO_(2)emissions by 42.89%.The key findings of this study highlight the great potential for green ethylene manufacturing based on AI through modeling and optimization approaches.This study will be important for industrial practitioners and policy-makers.展开更多
3-Dvelocity and temperature fields of mold filling and solidification processes of large-sized castingswere calculated,and the efficiency and accuracy of numerical calculation were studied.The mold filling andsolidifi...3-Dvelocity and temperature fields of mold filling and solidification processes of large-sized castingswere calculated,and the efficiency and accuracy of numerical calculation were studied.The mold filling andsolidification processes of large-sized stainless steel,iron and aluminum alloy castings were simulated by using ofnew scheme;their casting processes were optimized,and then applied to produce castings.展开更多
In order to reduce the shrinkage porosity of nickel-based superalloy castings in the investment casting process,the effects of different gating systems on mold filling,solidification process,and prediction of shrinkag...In order to reduce the shrinkage porosity of nickel-based superalloy castings in the investment casting process,the effects of different gating systems on mold filling,solidification process,and prediction of shrinkage porosity of aero-engine turbine nozzle castings were investigated by simulation and experimental methods.Results show that the design of the vertical runner would cause greater turbulence of the melt in the riser during the mold filling process,and the outer runner is not necessary.With the decrease in number of runners,the hot spot moves down towards the casting,and the shrinkage and porosity defects are formed in the casting below the riser.In the original designs,a certain tendency of shrinkage and porosity defect is found in the vanes,inner rings,and outer rings of the castings by both simulation prediction and experiment.Finally,based on the processing optimization,the aero-engine turbine nozzle casting with no shrinkage and porosity defects is obtained.展开更多
Although the shell mould casting process has a wide range of application in many fields,the prediction of casting defects is still a problem.In the present work,a typical leaf spring bracket casting of ZG310-570 was f...Although the shell mould casting process has a wide range of application in many fields,the prediction of casting defects is still a problem.In the present work,a typical leaf spring bracket casting of ZG310-570 was fabricated by shell mold casting.The finite element model and ProCAST software were utilized for simulating the filling and solidification processes of the casting;and the formation mechanism of the gas pore,and shrinkage porosity defects were analyzed.The results indicate that the gas pore and shrinkage porosity defects are formed due to air entrapment,insufficient feeding and non-sequential solidification.Subsequently,through changing the position of risers,adding a connecting channel between the risers,and setting blind risers at the U-shaped brackets,an optimized gating and feeding system was established to improve the quality of the casting.After optimization,the gas pore and shrinkage porosity defects of the leaf spring bracket casting are effectively eliminated.The experiment results with the optimized casting process are in good agreement with the numerical simulation,which verifies the validity of the finite element model in the shell mould casting.展开更多
The production and energy coupling system is used to mainly present energy flow, material flow, information flow, and their coupling interaction. Through the modeling and simulation of this system, the performance of ...The production and energy coupling system is used to mainly present energy flow, material flow, information flow, and their coupling interaction. Through the modeling and simulation of this system, the performance of energy flow can be analyzed and optimized in the process industry. In order to study this system, the component based hybrid Petri net methodology (CpnHPN) is proposed, synthesizing a number of extended Petri net methods and using the concept of energy place, material place, and information place. Through the interface place in CpnHPN, the component based encapsulation is established, which enables the production and energy coupling system to be built, analyzed, and optimized on the multi-level framework. Considering the block and brief simulation for hybrid system, the CpnHPN model is simulated with Simulink/Stateflow. To illustrate the use of the proposed methodology, the application of CpnHPN in the energy optimization of chlorine balance system is provided.展开更多
The present paper shows how the Schuster Schwarzschild method developed originally inastrophysics can be adopted to simulate the performance of the primary reforming furnace in an am-monia plant.This method facilitate...The present paper shows how the Schuster Schwarzschild method developed originally inastrophysics can be adopted to simulate the performance of the primary reforming furnace in an am-monia plant.This method facilitates the simulation of heat transfer and reaction in the furnace andimproves the computational efficiency.Simulation analysis is carried out to find ways of saving ener-gy.Appropriate reduction in fuel gas loading and partially shifting of the reforming load from theprimary to the secondary reformer by regulating the operating conditions can result in substantial en-ergy saving.Optimization calculations with various objective functions and constraints required areperformed.The optimization results may serve as guideline for plant operation and control.展开更多
The high temperature deformation behaviors of α＋β type titanium alloy TC11 （Ti-6.5Al-3.5Mo-1.5Zr-0.3Si） with coarse lamellar starting microstructure were investigated based on the hot compression tests in the tem...The high temperature deformation behaviors of α＋β type titanium alloy TC11 （Ti-6.5Al-3.5Mo-1.5Zr-0.3Si） with coarse lamellar starting microstructure were investigated based on the hot compression tests in the temperature range of 950-1100 ℃ and the strain rate range of 0.001-10 s-1. The processing maps at different strains were then constructed based on the dynamic materials model, and the hot compression process parameters and deformation mechanism were optimized and analyzed, respectively. The results show that the processing maps exhibit two domains with a high efficiency of power dissipation and a flow instability domain with a less efficiency of power dissipation. The types of domains were characterized by convergence and divergence of the efficiency of power dissipation, respectively. The convergent domain in a＋fl phase field is at the temperature of 950-990 ℃ and the strain rate of 0.001-0.01 s^-1, which correspond to a better hot compression process window of α＋β phase field. The peak of efficiency of power dissipation in α＋β phase field is at 950 ℃ and 0.001 s 1, which correspond to the best hot compression process parameters of α＋β phase field. The convergent domain in β phase field is at the temperature of 1020-1080 ℃ and the strain rate of 0.001-0.1 s^-l, which correspond to a better hot compression process window of β phase field. The peak of efficiency of power dissipation in ℃ phase field occurs at 1050 ℃ over the strain rates from 0.001 s^-1 to 0.01 s^-1, which correspond to the best hot compression process parameters of ,8 phase field. The divergence domain occurs at the strain rates above 0.5 s^-1 and in all the tested temperature range, which correspond to flow instability that is manifested as flow localization and indicated by the flow softening phenomenon in stress-- strain curves. The deformation mechanisms of the optimized hot compression process windows in a＋β and β phase fields are identified to be spheroidizing and dynamic recrystallizing controlled by self-diffusion mechanism, respectively. The microstructure observation of the deformed specimens in different domains matches very well with the optimized results.展开更多
In this paper,a kind of mathematic method for optimizing stretching process of large forgings is proposed.Distributions of effective strain within forged ingots is described by a Gauss function,which is obtained from ...In this paper,a kind of mathematic method for optimizing stretching process of large forgings is proposed.Distributions of effective strain within forged ingots is described by a Gauss function,which is obtained from the simulation of flat-anvil stretching process.Successive stretching is expressed by the superimposing Gauss functions.Optimized stretching process,with both homogeneous and certain strain in the center of forgings,is presented by derivation of this function.The relationship between effective strain and the values of feed is obtained during the successive stretching with a rotation angle of 90° and a feed displacement of 1/2 anvil width.The optimization result is verified by finite element simulation.Optimized value of feed obtained using this method can ensure both uniformity and forging penetration.It provides mathematic model and theoretic basis of optimizing large forging stretching process.展开更多
Long tunnel excavation with tunnel boring ily affected by uncertainties and needs to be adjusted machine （TBM） is a complex and stochastic process. It is eas- according to specific geological conditions in different...Long tunnel excavation with tunnel boring ily affected by uncertainties and needs to be adjusted machine （TBM） is a complex and stochastic process. It is eas- according to specific geological conditions in different tunnel sections, which makes the construction scheduling and management difficult. Based on the rock mass classification, this paper estimates the penetration rate. Using the rate, a cyclic network simulation （CYCLONE） model of TBM boring system is established, and the advance rates under different geological conditions are determined. Then, the impact of different cutter head thrust, which is chosen in reasonable range according to previous experiences, on pro- ject schedule is analyzed. Moreover, the simulation model of mucking system is built to determine the number of muck trains and rail intersections reasonably, regarding the efficiency of muck loading and material transporting. Based on the interaction and interrelation between TBM boring system and mucking system, the combined CY- CLONE model for the entire tunneling process is established. Then reasonable construction schedule, the utilization rate of working resources, and the probability of project completion are obtained through the model programming. At last, a project application shows the feasibility of the presented method.展开更多
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 Supported by the Scientific Research Foundation for High-Level Talents of Zhoukou Normal University(ZKNUC2024018).
文摘Energy shortage has become one of themost concerning issues in the world today,and improving energy utilization efficiency is a key area of research for experts and scholars worldwide.Small-diameter heat exchangers offer advantages such as reduced material usage,lower refrigerant charge,and compact structure.However,they also face challenges,including increased refrigerant pressure drop and smaller heat transfer area inside the tubes.This paper combines the advantages and disadvantages of both small and large-diameter tubes and proposes a combined-diameter heat exchanger,consisting of large and small diameters,for use in the indoor units of split-type air conditioners.There are relatively few studies in this area.In this paper,A theoretical and numerical computation method is employed to establish a theoretical-numerical calculation model,and its reliability is verified through experiments.Using this model,the optimal combined diameters and flow path design for a combined-diameter heat exchanger using R32 as the working fluid are derived.The results show that the heat transfer performance of all combined diameter configurations improves by 2.79%to 8.26%compared to the baseline design,with the coefficient of performance(COP)increasing from 4.15 to 4.27~4.5.These designs can save copper material,but at the cost of an increase in pressure drop by 66.86%to 131.84%.The scheme IIIH,using R32,is the optimal combined-diameter and flow path configuration that balances both heat transfer performance and economic cost.
基金support from the National Key Research and Development Program of China(2022YFC2106300)the National Natural Science Foundation of China(42177400).
文摘To address the challenges of high energy consumption and prominent costs in the traditional three-columns distillation process for cellulosic fuel ethanol,a distillation–molecular sieve coupling separation process is proposed.This process integrates a three-column(crude distillation column,first distillation column,second distillation column)system with a 3A molecular sieve adsorption deep dehydration unit.A thermal coupling network is constructed via differential pressure design(steam from medium/high-pressure columns as mutual heat sources,reboiler liquid waste heat for feed preheating),and molecular sieve adsorption conditions are optimized.The study first performs a thermodynamic consistency test on the ethanol–water system,determines optimal non-random two-liquid(NRTL)model binary interaction parameters via experimental data regression for Aspen Plus simulation.Aiming at minimum total annual cost(TAC),Aspen Plus is used to optimize process parameters(theoretical tray number,feed location,reflux ratio,side-draw position,etc.).Economic analysis shows this process reduces CO_(2) emission costs by 27.56%,TAC by 15.58%(to 5.123×10^(6) USD·a^(−1)),and increases ethanol purity to>99.6%,providing an effective solution for green,efficient separation.
基金Supported by the National Natural Science Foundation of China (No.60421002).
文摘A new 18-lump kinetic model for naphtha catalytic reforming reactions is discussed. By developing this model as a user module, a whole industrial continuous catalytic reforming process is simulated on Aspen plus plat-form. The technique utilizes the strong databases, complete sets of modules, and flexible simulation tools of the Aspen plus system and retains the characteristics of the proposed kinetic model. The calculated results are in fair agreement with the actual operating data. Based on the model of the whole reforming process, the process is opti-mized and the optimization results are tested in the actual industrial unit for about two months. The test shows that the process profit increases about 1000yuan·h-1 averagely, which is close to the calculated result.
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 National Science and Technology Council(NSTC),Taiwan,under grant number 114-2221-E-182-041-MY3by Chang Gung University and Chang Gung Memorial Hospital under project number NERPD4Q0021.
文摘The outstanding growth in the applications of large language models(LLMs)demonstrates the significance of adaptive and efficient prompt engineering tactics.The existing methods may not be variable,vigorous and streamlined in different domains.The offered study introduces an immediate optimization outline,named PROMPTx-PE,that is going to yield a greater level of precision and strength when it comes to the assignments that are premised on LLM.The proposed systemfeatures a timely selection schemewhich is informed by reinforcement learning,a contextual layer and a dynamic weighting module which is regulated by Lyapunov-based stability guidelines.The PROMPTx-PE dynamically varies the exploration and exploitation of the prompt space,depending on real-time feedback and multi-objective reward development.Extensive testing on both benchmark(GLUE,SuperGLUE)and domain-specific data(Healthcare-QA and Industrial-NER)demonstrates a large best performance to be 89.4%and a strong robustness disconnect with under 3%computation expense.The results confirm the effectiveness,consistency,and scalability of PROMPTx-PE as a platform of adaptive prompt engineering based on recent uses of LLMs.
基金supported by the 2024 Research Fund of University of Ulsan.
文摘In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In addition,methods for deploying multiple cameras for motion capture of users(e.g.,performers)are widely used in computer graphics.As the need to minimize and optimize the number of cameras grows to reduce costs,various technologies and research approaches focused on Optimal Camera Placement(OCP)are continually being proposed.However,as most existing studies assume homogeneous camera setups,there is a growing demand for studies on heterogeneous camera setups.For instance,technical demands keep emerging in scenarios with minimal camera configurations,especially regarding cost factors,the physical placement of cameras given the spatial structure,and image capture strategies for heterogeneous cameras,such as high-resolution RGB cameras and depth cameras.In this study,we propose a pre-visualization and simulation method for the optimal placement of heterogeneous cameras in XR environments,accounting for both the specifications of heterogeneous cameras(e.g.,field of view)and the physical configuration(e.g.,wall configuration)in real-world spaces.The proposed method performs a visibility analysis of cameras by considering each camera’s field-of-view volume,resolution,and unique characteristics,along with physicalspace constraints.This approach enables the optimal position and rotation of each camera to be recommended,along with the minimum number of cameras required.In the results of our study conducted in heterogeneous camera combinations,the proposed method achieved 81.7%~82.7%coverage of the target visual information using only 2~3 cameras.In contrast,single(or homogeneous)-typed cameras were required to use 11 cameras for 81.6%coverage.Accordingly,we found that camera deployment resources can be reduced with the proposed approaches.
基金support from National Natural Science Foundation of China(Grant No.51874033)to Prof.Hai-Yan Tang.
文摘In view of the frequent deterioration of molten steel quality during the tundish filling process,the slag-steel-air interface behavior in a tundish,including liquid level fluctuation,slag eyes,slag entrapment and air suction during the steady-state casting and filling process,was comparatively studied through physical modeling and mathematical simulation methods.During the filling process,the liquid surface forms a large-size slag eye under the impact of molten steel from a ladle shroud,which simultaneously results in a violent fluctuation of liquid level.Concurrently,the liquid flow entrains the air phase and the cover slag into the tundish impact zone,resulting in slag entrapment and air suction.At filling flow rates of 1.5Q,2.0Q,and 2.5Q(Q is the flow rate under steady-state casting),the amount of slag entrapped is 8.39×10^(-5),9.65×10^(-5),and 12.7×10^(-5)m^(3),respectively,while the volume of air aspirated is 0.84×10^(-4),1.47×10^(-4),and 2.01×10^(-4)m^(3),indicating that slag entrapment and air suction intensify with an increase in tundish filling flow rate.Flow field characterization identifies eddy currents in the impact zone as the primary driver of the above phenomena.Proper filling process parameters were proposed to improve the steel quality during the tundish filling.
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supported by National Natural Science Foundation of China(52274323 and 524743495)the Postdoctoral Fellowship Program of CPSF under Grant Number GZC20240231.
文摘In the electroslag remelting(ESR)process,it mainly relies on thermal experiments or analysis via mechanistic models to realize the physical fields simulation of the electromagnetic field and temperature field coupled transfer,which has the limitations of high cost,a large amount of calculating data and high computing power requirements.A novel network based on physics-informed neural network(PINN)was designed to realize the fast and high-fidelity prediction of the distribution of electromagnetic field and temperature field in ESR process.The physical laws were combined with the deep learning network through PINN,and physical constraints were embedded to achieve effective solution of partial differential equations(PDEs).PINN was used to minimize the loss function consisting of data error,physical information error and boundary condition error.The physical laws and boundary condition constraints in the ESR process were considered to maintain high PDE solution accuracy under different spatial and temporal resolutions.Automatic differentiation(Autodiff)technique and gradient descent algorithm were used to optimize the network parameters.The experimental results show that compared with the mechanistic models,PINN can effectively replace thermal experiments to realize the physical field simulation of ESR process with only a few experimental data,which can avoid the disadvantages of pure data-driven network simulation that requires a large amount of training data.Moreover,the solution of PINN has good physical interpretability and reliability of simulation results.For simulating electromagnetic field and temperature field distribution,the training time of the network is only 140 and 203 s,and the regression indicators of root mean square error can reach 12.65 and 13.76,respectively.
基金the financial support of the National Key Research and Development Program of China(2021YFE0112800)EU RISE project OPTIMAL(101007963).
文摘With growing concerns over environmental issues,ethylene manufacturing is shifting from a sole focus on economic benefits to an additional consideration of environmental impacts.The operation of the thermal cracking furnace in ethylene manufacturing determines not only the profitability of an ethylene plant but also the carbon emissions it releases.While multi-objective optimization of the thermal cracking furnace to balance profit with environmental impact is an effective solution to achieve green ethylene man-ufacturing,it carries a high computational demand due to the complex dynamic processes involved.In this work,artificial intelligence(AI)is applied to develop a novel hybrid model based on physically consistent machine learning(PCML).This hybrid model not only reduces the computational demand but also retains the interpretability and scalability of the model.With this hybrid model,the computational demand of the multi-objective dynamic optimization is reduced to 77 s.The optimization results show that dynamically adjusting the operating variables with coke formation can effectively improve profit and reduce CO_(2)emissions.In addition,the results from this study indicate that sacrificing 28.97%of the annual profit can significantly reduce the annual CO_(2)emissions by 42.89%.The key findings of this study highlight the great potential for green ethylene manufacturing based on AI through modeling and optimization approaches.This study will be important for industrial practitioners and policy-makers.
文摘3-Dvelocity and temperature fields of mold filling and solidification processes of large-sized castingswere calculated,and the efficiency and accuracy of numerical calculation were studied.The mold filling andsolidification processes of large-sized stainless steel,iron and aluminum alloy castings were simulated by using ofnew scheme;their casting processes were optimized,and then applied to produce castings.
文摘In order to reduce the shrinkage porosity of nickel-based superalloy castings in the investment casting process,the effects of different gating systems on mold filling,solidification process,and prediction of shrinkage porosity of aero-engine turbine nozzle castings were investigated by simulation and experimental methods.Results show that the design of the vertical runner would cause greater turbulence of the melt in the riser during the mold filling process,and the outer runner is not necessary.With the decrease in number of runners,the hot spot moves down towards the casting,and the shrinkage and porosity defects are formed in the casting below the riser.In the original designs,a certain tendency of shrinkage and porosity defect is found in the vanes,inner rings,and outer rings of the castings by both simulation prediction and experiment.Finally,based on the processing optimization,the aero-engine turbine nozzle casting with no shrinkage and porosity defects is obtained.
基金financially supported by the Major Science and Technology Projects in Anhui Province (No. 18030901097)the Natural Science Foundation of Anhui Province (No.1908085QE197)the Fundamental Research Funds for the Central Universities (JZ2018HGBZ0133, JZ2019HGTA0043)
文摘Although the shell mould casting process has a wide range of application in many fields,the prediction of casting defects is still a problem.In the present work,a typical leaf spring bracket casting of ZG310-570 was fabricated by shell mold casting.The finite element model and ProCAST software were utilized for simulating the filling and solidification processes of the casting;and the formation mechanism of the gas pore,and shrinkage porosity defects were analyzed.The results indicate that the gas pore and shrinkage porosity defects are formed due to air entrapment,insufficient feeding and non-sequential solidification.Subsequently,through changing the position of risers,adding a connecting channel between the risers,and setting blind risers at the U-shaped brackets,an optimized gating and feeding system was established to improve the quality of the casting.After optimization,the gas pore and shrinkage porosity defects of the leaf spring bracket casting are effectively eliminated.The experiment results with the optimized casting process are in good agreement with the numerical simulation,which verifies the validity of the finite element model in the shell mould casting.
基金Shanghai Municipal Science & Technology Projects, China (No. 09DZ1203300, No. 10JC1415200)
文摘The production and energy coupling system is used to mainly present energy flow, material flow, information flow, and their coupling interaction. Through the modeling and simulation of this system, the performance of energy flow can be analyzed and optimized in the process industry. In order to study this system, the component based hybrid Petri net methodology (CpnHPN) is proposed, synthesizing a number of extended Petri net methods and using the concept of energy place, material place, and information place. Through the interface place in CpnHPN, the component based encapsulation is established, which enables the production and energy coupling system to be built, analyzed, and optimized on the multi-level framework. Considering the block and brief simulation for hybrid system, the CpnHPN model is simulated with Simulink/Stateflow. To illustrate the use of the proposed methodology, the application of CpnHPN in the energy optimization of chlorine balance system is provided.
文摘The present paper shows how the Schuster Schwarzschild method developed originally inastrophysics can be adopted to simulate the performance of the primary reforming furnace in an am-monia plant.This method facilitates the simulation of heat transfer and reaction in the furnace andimproves the computational efficiency.Simulation analysis is carried out to find ways of saving ener-gy.Appropriate reduction in fuel gas loading and partially shifting of the reforming load from theprimary to the secondary reformer by regulating the operating conditions can result in substantial en-ergy saving.Optimization calculations with various objective functions and constraints required areperformed.The optimization results may serve as guideline for plant operation and control.
基金Project (51005112) supported by the National Natural Science Foundation of ChinaProject (2010ZF56019) supported by the Aviation Science Foundation of China+1 种基金Project (GJJ11156) supported by the Education Commission of Jiangxi Province, ChinaProject(GF200901008) supported by the Open Fund of National Defense Key Disciplines Laboratory of Light Alloy Processing Science and Technology, China
文摘The high temperature deformation behaviors of α＋β type titanium alloy TC11 （Ti-6.5Al-3.5Mo-1.5Zr-0.3Si） with coarse lamellar starting microstructure were investigated based on the hot compression tests in the temperature range of 950-1100 ℃ and the strain rate range of 0.001-10 s-1. The processing maps at different strains were then constructed based on the dynamic materials model, and the hot compression process parameters and deformation mechanism were optimized and analyzed, respectively. The results show that the processing maps exhibit two domains with a high efficiency of power dissipation and a flow instability domain with a less efficiency of power dissipation. The types of domains were characterized by convergence and divergence of the efficiency of power dissipation, respectively. The convergent domain in a＋fl phase field is at the temperature of 950-990 ℃ and the strain rate of 0.001-0.01 s^-1, which correspond to a better hot compression process window of α＋β phase field. The peak of efficiency of power dissipation in α＋β phase field is at 950 ℃ and 0.001 s 1, which correspond to the best hot compression process parameters of α＋β phase field. The convergent domain in β phase field is at the temperature of 1020-1080 ℃ and the strain rate of 0.001-0.1 s^-l, which correspond to a better hot compression process window of β phase field. The peak of efficiency of power dissipation in ℃ phase field occurs at 1050 ℃ over the strain rates from 0.001 s^-1 to 0.01 s^-1, which correspond to the best hot compression process parameters of ,8 phase field. The divergence domain occurs at the strain rates above 0.5 s^-1 and in all the tested temperature range, which correspond to flow instability that is manifested as flow localization and indicated by the flow softening phenomenon in stress-- strain curves. The deformation mechanisms of the optimized hot compression process windows in a＋β and β phase fields are identified to be spheroidizing and dynamic recrystallizing controlled by self-diffusion mechanism, respectively. The microstructure observation of the deformed specimens in different domains matches very well with the optimized results.
基金the National Science Support Project found by the Ministry of Science and Technology of China (No.2007BAE51B04)
文摘In this paper,a kind of mathematic method for optimizing stretching process of large forgings is proposed.Distributions of effective strain within forged ingots is described by a Gauss function,which is obtained from the simulation of flat-anvil stretching process.Successive stretching is expressed by the superimposing Gauss functions.Optimized stretching process,with both homogeneous and certain strain in the center of forgings,is presented by derivation of this function.The relationship between effective strain and the values of feed is obtained during the successive stretching with a rotation angle of 90° and a feed displacement of 1/2 anvil width.The optimization result is verified by finite element simulation.Optimized value of feed obtained using this method can ensure both uniformity and forging penetration.It provides mathematic model and theoretic basis of optimizing large forging stretching process.
基金Supported by National Natural Science Foundation of China (No.50709024)Program for New Century Excellent Talents in University (No. NCET-08-0391)
文摘Long tunnel excavation with tunnel boring ily affected by uncertainties and needs to be adjusted machine （TBM） is a complex and stochastic process. It is eas- according to specific geological conditions in different tunnel sections, which makes the construction scheduling and management difficult. Based on the rock mass classification, this paper estimates the penetration rate. Using the rate, a cyclic network simulation （CYCLONE） model of TBM boring system is established, and the advance rates under different geological conditions are determined. Then, the impact of different cutter head thrust, which is chosen in reasonable range according to previous experiences, on pro- ject schedule is analyzed. Moreover, the simulation model of mucking system is built to determine the number of muck trains and rail intersections reasonably, regarding the efficiency of muck loading and material transporting. Based on the interaction and interrelation between TBM boring system and mucking system, the combined CY- CLONE model for the entire tunneling process is established. Then reasonable construction schedule, the utilization rate of working resources, and the probability of project completion are obtained through the model programming. At last, a project application shows the feasibility of the presented method.
