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
This study addresses the energy-intensive challenge of small-scale biogas upgrading by optimizing a chemical absorption process employing methyl diethanolamine(MDEA).Focusing on a typical distributed application of 30...This study addresses the energy-intensive challenge of small-scale biogas upgrading by optimizing a chemical absorption process employing methyl diethanolamine(MDEA).Focusing on a typical distributed application of 300 Nm^(3)/d,we developed an integrated simulation-optimization framework using Aspen HYSYS 14.0 to systematically evaluate the effects of critical operating parameters—absorption pressure,MDEA concentration,flow rate,temperature,number of trays,and reboiler duty—on methane purity and energy consumption.The key finding is the identification of an optimal parameter set:absorption pressure of 1200 kPa,MDEA concentration of 20mol%,lean flow rate of 2.5 kmol/h,temperature of 298.15 K,20 absorber trays,10 regenerator trays,and a reboiler duty of 4 kW,which enabled the product gas to achieve a high CH4 concentration of 97mol%,compliant with pipeline standards.A detailed energy consumption analysis revealed that the reboiler is the most energy-intensive unit,accounting for 75.40%of the total 5.29 kW energy consumption,followed by the gas compressor(23.38%).The specific energy consumption for CH4 recovery and the Energy Consumption Index(ECI)were quantified at 0.8852 kWh/kg CH_(4)and 6.82,respectively.This work provides a validated optimization strategy and critical energy breakdown,offering practical guidance for enhancing the technical and economic viability of small-scale,centralized biogas purification systems.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
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
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 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
Simulations of photoresist etching,aerial image,exposure,and post-bake processes are integrated to obtain a photolithography process simulation for microelectromechanical system（MEMS） and integrated circuit（IC） fa...Simulations of photoresist etching,aerial image,exposure,and post-bake processes are integrated to obtain a photolithography process simulation for microelectromechanical system（MEMS） and integrated circuit（IC） fabrication based on three-dimensional （3D） cellular automata（CA）. The simulation results agree well with available experimental results. This indicates that the 3D dynamic CA model for the photoresist etching simulation and the 3D CA model for the post-bake simulation could be useful for the monolithic simulation of various lithography processes. This is determined to be useful for the device-sized fabrication process simulation of IC and MEMS.展开更多
Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley a...Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.展开更多
Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing addit...Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing additive-induced defects,and alleviating residual stress and deformation,all of which are critical for enhancing the mechanical performance of the manufactured parts.Integrating interlayer friction stir processing(FSP)into WAAM significantly enhances the quality of deposited materials.However,numerical simulation research focusing on elucidating the associated thermomechanical coupling mechanisms remains insufficient.A comprehensive numerical model was developed to simulate the thermomechanical coupling behavior in friction stir-assisted WAAM.The influence of post-deposition FSP on the coupled thermomechanical response of the WAAM process was analyzed quantitatively.Moreover,the residual stress distribution and deformation behavior under both single-layer and multilayer deposition conditions were investigated.Thermal analysis of different deposition layers in WAAM and friction stir-assisted WAAM was conducted.Results show that subsequent layer deposition induces partial remelting of the previously solidified layer,whereas FSP does not cause such remelting.Furthermore,thermal stress and deformation analysis confirm that interlayer FSP effectively mitigates residual stresses and distortion in WAAM components,thereby improving their structural integrity and mechanical properties.展开更多
Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy...Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy plates.First,finite element simulations of casting processes were carried out with various parameters to build a dataset.Subsequently,different machine learning algorithms were employed to achieve high precision in predicting temperature fields,mushy zone locations,mushy zone inclination angle,and billet grain size.Finally,the process parameters were quickly optimized using a strategy consisting of random generation,prediction,and screening,allowing the mushy zone to be controlled to the desired target.The optimized parameters are 1234℃for heating mold temperature,47 mm/min for casting speed,and 10 L/min for cooling water flow rate.The optimized mushy zone is located in the middle of the second heat insulation section and has an inclination angle of roughly 7°.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.
基金funded by Shenzhen Science and Technology Program,grant number No.ZDSYS20230626091400001No.KCXST20221021111609024No.KCXFZ20240903093459001.
文摘This study addresses the energy-intensive challenge of small-scale biogas upgrading by optimizing a chemical absorption process employing methyl diethanolamine(MDEA).Focusing on a typical distributed application of 300 Nm^(3)/d,we developed an integrated simulation-optimization framework using Aspen HYSYS 14.0 to systematically evaluate the effects of critical operating parameters—absorption pressure,MDEA concentration,flow rate,temperature,number of trays,and reboiler duty—on methane purity and energy consumption.The key finding is the identification of an optimal parameter set:absorption pressure of 1200 kPa,MDEA concentration of 20mol%,lean flow rate of 2.5 kmol/h,temperature of 298.15 K,20 absorber trays,10 regenerator trays,and a reboiler duty of 4 kW,which enabled the product gas to achieve a high CH4 concentration of 97mol%,compliant with pipeline standards.A detailed energy consumption analysis revealed that the reboiler is the most energy-intensive unit,accounting for 75.40%of the total 5.29 kW energy consumption,followed by the gas compressor(23.38%).The specific energy consumption for CH4 recovery and the Energy Consumption Index(ECI)were quantified at 0.8852 kWh/kg CH_(4)and 6.82,respectively.This work provides a validated optimization strategy and critical energy breakdown,offering practical guidance for enhancing the technical and economic viability of small-scale,centralized biogas purification systems.
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 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.
文摘Simulations of photoresist etching,aerial image,exposure,and post-bake processes are integrated to obtain a photolithography process simulation for microelectromechanical system（MEMS） and integrated circuit（IC） fabrication based on three-dimensional （3D） cellular automata（CA）. The simulation results agree well with available experimental results. This indicates that the 3D dynamic CA model for the photoresist etching simulation and the 3D CA model for the post-bake simulation could be useful for the monolithic simulation of various lithography processes. This is determined to be useful for the device-sized fabrication process simulation of IC and MEMS.
基金supported by the General Program of the National Natural Science Foundation of China(No.52274326)the China Baowu Low Carbon Metallurgy Innovation Foundation(No.BWLCF202109)the Seventh Batch of Ten Thousand Talents Plan of China(No.ZX20220553).
文摘Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.
基金National Key Research and Development Program of China(2022YFB4600902)Shandong Provincial Science Foundation for Outstanding Young Scholars(ZR2024YQ020)。
文摘Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing additive-induced defects,and alleviating residual stress and deformation,all of which are critical for enhancing the mechanical performance of the manufactured parts.Integrating interlayer friction stir processing(FSP)into WAAM significantly enhances the quality of deposited materials.However,numerical simulation research focusing on elucidating the associated thermomechanical coupling mechanisms remains insufficient.A comprehensive numerical model was developed to simulate the thermomechanical coupling behavior in friction stir-assisted WAAM.The influence of post-deposition FSP on the coupled thermomechanical response of the WAAM process was analyzed quantitatively.Moreover,the residual stress distribution and deformation behavior under both single-layer and multilayer deposition conditions were investigated.Thermal analysis of different deposition layers in WAAM and friction stir-assisted WAAM was conducted.Results show that subsequent layer deposition induces partial remelting of the previously solidified layer,whereas FSP does not cause such remelting.Furthermore,thermal stress and deformation analysis confirm that interlayer FSP effectively mitigates residual stresses and distortion in WAAM components,thereby improving their structural integrity and mechanical properties.
基金financially supported by the National Key Research and Development Program of China (No. 2023YFB3812601)the National Natural Science Foundation of China (No. 51925401)the Young Elite Scientists Sponsorship Program by CAST, China (No. 2022QNRC001)。
文摘Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy plates.First,finite element simulations of casting processes were carried out with various parameters to build a dataset.Subsequently,different machine learning algorithms were employed to achieve high precision in predicting temperature fields,mushy zone locations,mushy zone inclination angle,and billet grain size.Finally,the process parameters were quickly optimized using a strategy consisting of random generation,prediction,and screening,allowing the mushy zone to be controlled to the desired target.The optimized parameters are 1234℃for heating mold temperature,47 mm/min for casting speed,and 10 L/min for cooling water flow rate.The optimized mushy zone is located in the middle of the second heat insulation section and has an inclination angle of roughly 7°.
