The latest progress in the process optimization and stability improvement of third-generation cephalosporins in recent years was reviewed.The introduction of green chemistry,enzyme catalysis,nanotechnology,lyophilizat...The latest progress in the process optimization and stability improvement of third-generation cephalosporins in recent years was reviewed.The introduction of green chemistry,enzyme catalysis,nanotechnology,lyophilization,and nitrogen-filled packaging technologies can only improve production efficiency and reduce the generation of by-products,but also significantly extend the shelf life of drugs.In the future,process automation and intelligent technology will further optimize the large-scale production process,and the combination of nanotechnology and precision drug delivery will promote the improvement of effect in clinical applications.展开更多
High ammonia-nitrogen digestate has become a key bottleneck limiting the anaerobic digestion of organic solid waste.Vacuum ammonia stripping can simultaneously remove and recover ammonia nitrogen,which has attracted a...High ammonia-nitrogen digestate has become a key bottleneck limiting the anaerobic digestion of organic solid waste.Vacuum ammonia stripping can simultaneously remove and recover ammonia nitrogen,which has attracted a lot of attention in recent years.To investigate the parameter effects on the efficiency and mass transfer,five combination conditions(53℃ 15 kPa,60°C 20 kPa,65°C 25 kPa,72°C 35 kPa,and 81°C 50 kPa)were conducted for ammonia stripping of sludge digestate.The results showed that 80%of ammonia nitrogen was stripped in 45 min for all experimental groups,but the ammonia transfer coefficient varied under different conditions,which increased with the rising of boiling point temperature,and reached the maximum value(39.0 mm/hr)at 81°C 50 kPa.The ammonia nitrogen removal efficiency was more than 80%for 30 min vacuum stripping after adjusting the initial pH to above 9.5,and adjustment of the initial alkalinity also affects the pH value of liquid digestate.It was found that pH and alkalinity are the key factors influencing the ammonia nitrogen dissociation and removal efficiency,while temperature and vacuum mainly affect the ammonia nitrogen mass transfer and removal velocity.In terms of the mechanism of vacuum ammonia stripping,it underwent alkalinity destruction,pH enhancement,ammonia nitrogen dissociation,and free ammonia removal.In this study,two-stage experiments of alkalinity destruction and ammonia removal were also carried out,which showed that the two-stage configuration was beneficial for ammonia removal.It provides a theoretical basis and practical technology for the vacuum ammonia stripping from liquid digestate of organic solid waste.展开更多
A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are ...A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are modeled by level set functions.Secondly,the mathematical model of the additive direction optimization problem is established,and an improved particle swarm optimization algorithm is designed to decide the best additive direction.Then,the two-step strategy is used to plan the hybrid manufacturing alternating sequence.The target parts are directly divided into various processing regions;each processing region is optimized based on manufacturability and manufacturing efficiency,and the optimal hybrid manufacturing alternating sequence is obtained by merging some processing regions.Finally,the method is used to outline the process plan of the designed example model and applied to the actual hybrid manufacturing process of the model.The manufacturing result shows that the method can meet the main considerations in hybrid manufacturing.In addition,the degree of automation of process planning is high,and the dependence on manual intervention is low.展开更多
The optimization of reaction processes is crucial for the green, efficient, and sustainable development of the chemical industry. However, how to address the problems posed by multiple variables, nonlinearities, and u...The optimization of reaction processes is crucial for the green, efficient, and sustainable development of the chemical industry. However, how to address the problems posed by multiple variables, nonlinearities, and uncertainties during optimization remains a formidable challenge. In this study, a strategy combining interpretable machine learning with metaheuristic optimization algorithms is employed to optimize the reaction process. First, experimental data from a biodiesel production process are collected to establish a database. These data are then used to construct a predictive model based on artificial neural network (ANN) models. Subsequently, interpretable machine learning techniques are applied for quantitative analysis and verification of the model. Finally, four metaheuristic optimization algorithms are coupled with the ANN model to achieve the desired optimization. The research results show that the methanol: palm fatty acid distillate (PFAD) molar ratio contributes the most to the reaction outcome, accounting for 41%. The ANN-simulated annealing (SA) hybrid method is more suitable for this optimization, and the optimal process parameters are a catalyst concentration of 3.00% (mass), a methanol: PFAD molar ratio of 8.67, and a reaction time of 30 min. This study provides deeper insights into reaction process optimization, which will facilitate future applications in various reaction optimization processes.展开更多
Aluminum alloys manufactured using traditional processes are increasingly unable to meet the high flexibility and performance requirements of modern engineering.In this study,Al-Mg-Sc-Zr alloys were manufactured via l...Aluminum alloys manufactured using traditional processes are increasingly unable to meet the high flexibility and performance requirements of modern engineering.In this study,Al-Mg-Sc-Zr alloys were manufactured via laser powder bed fusion(LPBF)to obtain high-performance aluminum alloys.To this end,process parameter optimization and heat treatment were adopted.The optimal process parameters were determined by initially analyzing the relative density and defect distribution under varying energy densities.The sample obtained under the optimal process parameters exhibited a relative density of 99.84%.Subsequently,the corresponding phase compositions,microstructures,and mechanical performance of the as-fabricated specimens were determined using the optimal process parameters before and after heat treatment.The microstructures of the samples showed typical equiaxed columnar bimodal grain structures,with Al_(3)(Sc,Zr)precipitates detected.The samples exhibited no significant anisotropy before and after heat treatment,while the grain orientation differences were dominated by high-angle grain boundaries.The mechanical properties of all the samples were characterized using tensile and hardness tests.The yield strength,ultimate tensile strength,and elongation of the sample were 475.0 MPa,508.2 MPa,and 8.3%,respectively.Overall,samples with high density,low porosity,high strength,and high plasticity were obtained by process parameter optimization and appropriate heat treatment.展开更多
Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is co...Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.展开更多
In the cooling crystallization process of thiourea,a significant issue is the excessively wide crystal size distribution(CSD)and the abundance of fine crystals.This investigation delves into the growth kinetics and me...In the cooling crystallization process of thiourea,a significant issue is the excessively wide crystal size distribution(CSD)and the abundance of fine crystals.This investigation delves into the growth kinetics and mechanisms governing thiourea crystals during the cooling crystallization process.The fitting results indicate that the crystal growth rate coefficient,falls within the range of 10^(-7)to 10^(-8)m·s^(-1).Moreover,with decreasing crystallization temperature,the growth process undergoes a transition from diffusion-controlled to surface reaction-controlled,with temperature primarily influencing the surface reaction process and having a limited impact on the diffusion process.Comparing the crystal growth rate,and the diffusion-limited growth rate,at different temperatures,it is observed that the crystal growth process can be broadly divided into two stages.At temperatures above 25℃,1/qd(qd is diffusion control index)approaches 1,indicating the predominance of diffusion control.Conversely,at temperatures below 25℃,1/qd increases rapidly,signifying the dominance of surface reaction control.To address these findings,process optimization was conducted.During the high-temperature phase(35-25℃),agitation was increased to reduce the limitations posed by bulk-phase diffusion in the crystallization process.In the low-temperature phase(25-15℃),agitation was reduced to minimize crystal breakage.The optimized process resulted in a thiourea crystal product with a particle size distribution predominantly ranging from 0.7 to 0.9 mm,accounting for 84%of the total.This study provides valuable insights into resolving the issue of excessive fine crystals in the thiourea crystallization process.展开更多
In order to obtain better quality cookies, food 3D printing technology was employed to prepare cookies. The texture, color, deformation, moisture content, and temperature of the cookie as evaluation indicators, the in...In order to obtain better quality cookies, food 3D printing technology was employed to prepare cookies. The texture, color, deformation, moisture content, and temperature of the cookie as evaluation indicators, the influences of baking process parameters, such as baking time, surface heating temperature and bottom heating temperature, on the quality of the cookie were studied to optimize the baking process parameters. The results showed that the baking process parameters had obvious effects on the texture, color, deformation, moisture content, and temperature of the cookie. All of the roasting surface heating temperature, bottom heating temperature and baking time had positive influences on the hardness, crunchiness, crispiness, and the total color difference(ΔE) of the cookie. When the heating temperatures of the surfac and bottom increased, the diameter and thickness deformation rate of the cookie increased. However,with the extension of baking time, the diameter and thickness deformation rate of the cookie first increased and then decreased. With the surface heating temperature of 180 ℃, the bottom heating temperature of 150 ℃, and baking time of 15 min, the cookie was crisp and moderate with moderate deformation and uniform color. There was no burnt phenomenon with the desired quality. Research results provided a theoretical basis for cookie manufactory based on food 3D printing technology.展开更多
The aim is to remove copper from a pyrite cinder by optimizing the chlorination roasting process using re-sponse surface methodology （RSM） and the reaction mechanism of chlorination roasting based on thermodynamic c...The aim is to remove copper from a pyrite cinder by optimizing the chlorination roasting process using re-sponse surface methodology （RSM） and the reaction mechanism of chlorination roasting based on thermodynamic calculation was discussed. A quadratic model was suggested by RSM to correlate the key parameters, namely, dos-age of chlorinating agent, roasting temperature and roasting time to the copper volatilization ratio. The results indi- cate that the model is well consistent with the experimental data at a correlation coefficient （R2） of 0.95, and the dosage of chlorinating agent and roasting temperature both have significant effects on the copper volatilization ratio. However, a roasting temperature exceeding 1170 ~C decreases the volatilization ratio. The optimum conditions for removing copper from the cinder were identified as chlorinating agent dosage at 5%, roasting temperature at i155.10 ℃ and roasting time of 10 min; under Such a conditiom a copper volatilization ratid of 95.16% Was a- chieved from the cinder. Thermodynamic calculation shows that SiO2 in the pellet plays a key role in the chlorine re-lease from calcium chloride, and the chlorine release reactions cannot occur without it.展开更多
Application of statistical methods to optimize the process parameters was achieved by employing full factorial design of experiments,which was accomplished by cladding using stepwise ramped laser power.The correlation...Application of statistical methods to optimize the process parameters was achieved by employing full factorial design of experiments,which was accomplished by cladding using stepwise ramped laser power.The correlations between clad geometry and dilution(clad characteristics)and the main process parameters laser power(P_(l)),cladding speed(v_(c)),the powder feed rate(m)were obtained through application of variance analysis technique(ANOVA).The obtained correlations between the main processing parameters and the clad characteristics are discussed and a statistical model was developed.The desirability investigations using the developed statistical model were performed by considering the clad geometry,aspect ratio,dilution and hardness.Optimal parameters for cladding Stellite 6 on AISI 420 steel substrate and for cladding Nucalloy 488V on S355 J2 steel substrate were obtained.The optimal processing parameters can be applied to clad other materials with similar chemical compositions.展开更多
Currently, the majority of copper tailings are not effectively developed. Worldwide, large amounts of copper tailings generated from copper production are continuously dumped, posing a potential environmental threat. ...Currently, the majority of copper tailings are not effectively developed. Worldwide, large amounts of copper tailings generated from copper production are continuously dumped, posing a potential environmental threat. Herein, the recovery of iron from copper tailings via low-temperature direct reduction and magnetic separation was conducted; process optimization was carried out, and the corresponding mineralogy was investigated. The reduction time, reduction temperature, reducing agent (coal), calcium chloride additive, grinding time, and magnetic field intensity were examined for process optimization. Mineralogical analyses of the sample, reduced pellets, and magnetic concentrate under various conditions were performed by X-ray diffraction, optical microscopy, and scanning electron microscopy-energy-dispersive X-ray spectrometry to elucidate the iron reduction and growth mechanisms. The results indicated that the optimum parameters of iron recovery include a reduction temperature of 1150A degrees C, a reduction time of 120 min, a coal dosage of 25%, a calcium chloride dosage of 2.5%, a magnetic field intensity of 100 mT, and a grinding time of 1 min. Under these conditions, the iron grade in the magnetic concentrate was greater than 90%, with an iron recovery ratio greater than 95%.展开更多
The influence of a key process variable on the mold filling characteristics of AZ91 Mg-alloy was studied in the low pressure EPC process.The applied flow quantity of insert gas from 1 to 5 m~3/h associated with the pr...The influence of a key process variable on the mold filling characteristics of AZ91 Mg-alloy was studied in the low pressure EPC process.The applied flow quantity of insert gas from 1 to 5 m~3/h associated with the pressurizing rate in the low pressure EPC casting process was considered for rectangle and L-shape plate casting. The experimental results show that there is an optimal flow quantity of insert gas for good mold filling characteristics in AZ91 Mg-alloy low-pressure EPC process. The optimal flow quantity of insert gas for the specimens is 3 to 4 m~3/h. Either less or higher than the optimal flow quantity of insert gas would lead to misrun defects or folds, blisters and porosity defects. The practice of hub casting confirmed that the low-pressure EPC process with an optimal processing variable exemplified as 4 m~3/h gas flow quantity was capable of producing complicated magnesium castings without misrun defects.展开更多
The probabilistic modeling is applied to calculate microstructural features of the thin complex smprolloy turbine blades cast by the vacuum investment process. The random distribution, orientation and physical mechani...The probabilistic modeling is applied to calculate microstructural features of the thin complex smprolloy turbine blades cast by the vacuum investment process. The random distribution, orientation and physical mechanism of the nucleation, the growth kinetics of dendrites and the columnar-to-equiaxed transition (CET) are considered.Capitalizing on these simulating schemes, the comprehensive influence of key process variables on the scale and uniformity of grains has been involved quantitatively. The validity of the modeling is confirmed by selection of the optimum process variables.展开更多
In this paper, based on the principle of heat transfer and thermal elastic-plastic theory, the heat treatment process optimization scheme for face gears is proposed according to the structural characteristics of the f...In this paper, based on the principle of heat transfer and thermal elastic-plastic theory, the heat treatment process optimization scheme for face gears is proposed according to the structural characteristics of the face gear and material properties of 12Cr2Ni4 steel. To simulate the effect of carburizing and quenching process on tooth deformation and residual stress distribution, a heat treatment analysis model of face gears is established, and the microstructure, stress and deformation of face gear teeth changing with time are analyzed. The simulation results show that face gear tooth hardness increases, tooth surface residual compressive stress increases and tooth deformation decreases after heat treatment process optimization. It is beneficial to improving the fatigue strength and performance of face gears.展开更多
The RTS technology can produce ultra-low sulfur diesel at lower costs using available hydrogenation catalyst and device.However,with the increase of the mixing proportion of secondary processed diesel fuel in the feed...The RTS technology can produce ultra-low sulfur diesel at lower costs using available hydrogenation catalyst and device.However,with the increase of the mixing proportion of secondary processed diesel fuel in the feed,the content of nitrogen compounds and polycyclic aromatic hydrocarbons in the feed increased,leading to the acceleration of the deactivation rate of the primary catalyst and the shortening of the service cycle.In order to fully understand the reason of catalyst deactivation,the effect of mixing secondary processed diesel fuel oil on the operating stability of the catalyst in the first reactor was investigated in a medium-sized fixed-bed hydrogenation unit.The results showed that the nitrogen compounds mainly affected the initial activity of the catalyst,but had little effect on the stability of the catalyst.The PAHs had little effect on the initial activity of the catalyst,but could significantly accelerate the deactivation of the catalyst.Combined with the analysis of the reason of catalyst deactivation and the study of RTS technology,the direction of RTS technology process optimization was put forward,and the stability of catalyst was improved obviously after process optimization.展开更多
Laser powder bed fusion(LPBF)has made significant progress in producing solid and porous metal parts with complex shapes and geometries.However,LPBF produced parts often have defects(e.g.,porosity,residual stress,and i...Laser powder bed fusion(LPBF)has made significant progress in producing solid and porous metal parts with complex shapes and geometries.However,LPBF produced parts often have defects(e.g.,porosity,residual stress,and incomplete melting)that hinder its large-scale industrial commercialization.The LPBF process involves complex heat transfer andfluidflow,and the melt pool is a critical component of the process.The melt pool stability is a critical factor in determining the microstructure,mechanical properties,and corrosion resistance of LPBF produced metal parts.Furthermore,optimizing process parameters for new materials and designed structures is challenging due to the complexity of the LPBF process.This requires numerous trial-and-error cycles to minimize defects and enhance properties.This review examines the behavior of the melt pool during the LPBF process,including its effects and formation mechanisms.This article summarizes the experimental results and simulations of melt pool and identifies various factors that influence its behavior,which facilitates a better understanding of the melt pool's behavior during LPBF.This review aims to highlight key aspects of the investigation of melt pool tracks and microstructural characterization,with the goal of enhancing a better understanding of the relationship between alloy powder-process-microstructure-properties in LPBF from both single-and multi-melt pool track perspectives.By identifying the challenges and opportunities in investigating single-and multi-melt pool tracks,this review could contribute to the advancement of LPBF processes,optimal process window,and quality optimization,which ultimately improves accuracy in process parameters and efficiency in qualifying alloy powders.展开更多
The study was aimed to obtain the optimum conditions for vacuum frying and predicting the moisture lost during rice straw mushrooms stem chip production. The raw materials were obtained from the local farmer around th...The study was aimed to obtain the optimum conditions for vacuum frying and predicting the moisture lost during rice straw mushrooms stem chip production. The raw materials were obtained from the local farmer around the campus. A completely randomized factorial experimental design and Duncan＇s multiple range tests were used to achieve the objectives. Three temperatures, i.e. 80, 90 and 100 ℃ and five frying time, i.e. 3, 6, 9, and 15 minutes with a 2 mm slice thickness were studied to determine the optimum condition and predict the moisture decrease. Results showed that the vacuum frying time in general affects the chips color and oil uptake significantly （p 〈 0.01） and correlated with the moisture decrease. The chips moisture content decline significantly after vacuum frying at 90 ℃ and 100 ℃ for 3 minutes. While for the 80 ℃ vacuum frying, the significant decrease of moisture occurred due to the increase of vacuum frying time from 3 to 6 minutes （p 〈 0.01）. The optimum conditions for a 2 mm slice thickness chips making are vacuum frying at 100 ℃ for 3 minutes. The chips moisture lost followed generally a two-stage of falling rate pattern during vacuum frying, and each could be well predicted by an exponential equation （R2 = 0.99）.展开更多
[Objective] The aim was to obtain higher COD removal rate so as to guide the process of citric acid industrial wastewater. [Method] The effects of controllable factors, acidification time, hydraulic retention time, an...[Objective] The aim was to obtain higher COD removal rate so as to guide the process of citric acid industrial wastewater. [Method] The effects of controllable factors, acidification time, hydraulic retention time, and influent COD concentration, in-anaerobic treatment process of citric acid wastewater on COD removal rate were studied and the COD removal rate was optimized by response surface method. [Result] There was no interaction between acidification time and the other two factors. It was showed that hydraulic retention time and influent COD concentration had significant effect on COD removal rate and there was interaction between the two factors. The optimum COD removing process conditions was as follows: acidification time 1.53 h, hydraulic retention time 3.52 h and influent COD concentration 2 698 mg/L. Under the optimized conditions, the COD removal rate was 93.31% and it was much closed to the experimental result, 93.29%. [Conclusion] Using response surface method to optimize the anaerobic treatment of citric acid wastewater can result in optimized achievement.展开更多
Objective: to observe the effect of emergency nursing process optimization on emergency patient rescue efficiency. Methods: conducting a retrospective study on the emergency patients in our hospital from August 2019 t...Objective: to observe the effect of emergency nursing process optimization on emergency patient rescue efficiency. Methods: conducting a retrospective study on the emergency patients in our hospital from August 2019 to August 2021, numbering 136 samples according to admission order with No. 1-68 as the control group and No. 69-136 as the observation group;performing routine emergency care to the former group, and performing optimized emergency process to the latter group underwent optimization;comparing the difference between groups on first aid process, first aid effect and satisfaction. Results: the triage, intravenous medication, examination, treatment, ecg monitoring and hospitalization time in observation group were significantly shorter than those in control group, and p < 0.05;the success rate and overall satisfaction of observation group were significantly higher than those in control group, and p < 0.05. Conclusion: optimized emergency nursing process can effectively shorten the rescue time, improve the emergency rescue efficiency, and make the patients and their families become relatively more satisfied.展开更多
The idea of genetic engineering is introduced into the area of product design to improve the design efficiency. A method towards design process optimization based on the design process gene is proposed through analyzi...The idea of genetic engineering is introduced into the area of product design to improve the design efficiency. A method towards design process optimization based on the design process gene is proposed through analyzing the correlation between the design process gene and characteristics of the design process. The concept of the design process gene is analyzed and categorized into five categories that are the task specification gene, the concept design gene, the overall design gene, the detailed design gene and the processing design gene in the light of five design phases. The elements and their interactions involved in each kind of design process gene signprocess gene mapping is drawn with its structure disclosed based on its function that process gene.展开更多
基金Supported by the Funds from Central Government for Guiding Local Science and Technology Development(ZY20230102)Planning Project of Scientific Research and Technology Development in Guilin(20220104-4,20210202-1)Science and Technology Planing Project of Guangxi(Guike AB24010263).
文摘The latest progress in the process optimization and stability improvement of third-generation cephalosporins in recent years was reviewed.The introduction of green chemistry,enzyme catalysis,nanotechnology,lyophilization,and nitrogen-filled packaging technologies can only improve production efficiency and reduce the generation of by-products,but also significantly extend the shelf life of drugs.In the future,process automation and intelligent technology will further optimize the large-scale production process,and the combination of nanotechnology and precision drug delivery will promote the improvement of effect in clinical applications.
基金supported by the National Key Research and Development Program of China(No.2020YFC1908702)the National Natural Science Foundation of China(No.52131002)+1 种基金the Science and Technology Commission of Shanghai Municipality(No.22dz1209200)China Three Gorges Corporation(No.202403018).
文摘High ammonia-nitrogen digestate has become a key bottleneck limiting the anaerobic digestion of organic solid waste.Vacuum ammonia stripping can simultaneously remove and recover ammonia nitrogen,which has attracted a lot of attention in recent years.To investigate the parameter effects on the efficiency and mass transfer,five combination conditions(53℃ 15 kPa,60°C 20 kPa,65°C 25 kPa,72°C 35 kPa,and 81°C 50 kPa)were conducted for ammonia stripping of sludge digestate.The results showed that 80%of ammonia nitrogen was stripped in 45 min for all experimental groups,but the ammonia transfer coefficient varied under different conditions,which increased with the rising of boiling point temperature,and reached the maximum value(39.0 mm/hr)at 81°C 50 kPa.The ammonia nitrogen removal efficiency was more than 80%for 30 min vacuum stripping after adjusting the initial pH to above 9.5,and adjustment of the initial alkalinity also affects the pH value of liquid digestate.It was found that pH and alkalinity are the key factors influencing the ammonia nitrogen dissociation and removal efficiency,while temperature and vacuum mainly affect the ammonia nitrogen mass transfer and removal velocity.In terms of the mechanism of vacuum ammonia stripping,it underwent alkalinity destruction,pH enhancement,ammonia nitrogen dissociation,and free ammonia removal.In this study,two-stage experiments of alkalinity destruction and ammonia removal were also carried out,which showed that the two-stage configuration was beneficial for ammonia removal.It provides a theoretical basis and practical technology for the vacuum ammonia stripping from liquid digestate of organic solid waste.
基金The National Natural Science Foundation of China(No.52305381)the Natural Science Foundation of Jiangsu Province(No.BK20210351)the Fundamental Research Funds for the Central Universities(No.30923011008).
文摘A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are modeled by level set functions.Secondly,the mathematical model of the additive direction optimization problem is established,and an improved particle swarm optimization algorithm is designed to decide the best additive direction.Then,the two-step strategy is used to plan the hybrid manufacturing alternating sequence.The target parts are directly divided into various processing regions;each processing region is optimized based on manufacturability and manufacturing efficiency,and the optimal hybrid manufacturing alternating sequence is obtained by merging some processing regions.Finally,the method is used to outline the process plan of the designed example model and applied to the actual hybrid manufacturing process of the model.The manufacturing result shows that the method can meet the main considerations in hybrid manufacturing.In addition,the degree of automation of process planning is high,and the dependence on manual intervention is low.
基金supported by the National Natural Science Foundation of China(22408227,22238005)the Postdoctoral Research Foundation of China(GZC20231576).
文摘The optimization of reaction processes is crucial for the green, efficient, and sustainable development of the chemical industry. However, how to address the problems posed by multiple variables, nonlinearities, and uncertainties during optimization remains a formidable challenge. In this study, a strategy combining interpretable machine learning with metaheuristic optimization algorithms is employed to optimize the reaction process. First, experimental data from a biodiesel production process are collected to establish a database. These data are then used to construct a predictive model based on artificial neural network (ANN) models. Subsequently, interpretable machine learning techniques are applied for quantitative analysis and verification of the model. Finally, four metaheuristic optimization algorithms are coupled with the ANN model to achieve the desired optimization. The research results show that the methanol: palm fatty acid distillate (PFAD) molar ratio contributes the most to the reaction outcome, accounting for 41%. The ANN-simulated annealing (SA) hybrid method is more suitable for this optimization, and the optimal process parameters are a catalyst concentration of 3.00% (mass), a methanol: PFAD molar ratio of 8.67, and a reaction time of 30 min. This study provides deeper insights into reaction process optimization, which will facilitate future applications in various reaction optimization processes.
基金supported by National Natural Science Foundation of China(Grant Nos.5233500651975073)State Key Laboratory of Mechanical Transmission for Advanced Equipment(Grant No.SKLMT-MSKFKT-202104).
文摘Aluminum alloys manufactured using traditional processes are increasingly unable to meet the high flexibility and performance requirements of modern engineering.In this study,Al-Mg-Sc-Zr alloys were manufactured via laser powder bed fusion(LPBF)to obtain high-performance aluminum alloys.To this end,process parameter optimization and heat treatment were adopted.The optimal process parameters were determined by initially analyzing the relative density and defect distribution under varying energy densities.The sample obtained under the optimal process parameters exhibited a relative density of 99.84%.Subsequently,the corresponding phase compositions,microstructures,and mechanical performance of the as-fabricated specimens were determined using the optimal process parameters before and after heat treatment.The microstructures of the samples showed typical equiaxed columnar bimodal grain structures,with Al_(3)(Sc,Zr)precipitates detected.The samples exhibited no significant anisotropy before and after heat treatment,while the grain orientation differences were dominated by high-angle grain boundaries.The mechanical properties of all the samples were characterized using tensile and hardness tests.The yield strength,ultimate tensile strength,and elongation of the sample were 475.0 MPa,508.2 MPa,and 8.3%,respectively.Overall,samples with high density,low porosity,high strength,and high plasticity were obtained by process parameter optimization and appropriate heat treatment.
基金financially supported by the Technology Development Fund of China Academy of Machinery Science and Technology(No.170221ZY01)。
文摘Additive manufacturing technology is highly regarded due to its advantages,such as high precision and the ability to address complex geometric challenges.However,the development of additive manufacturing process is constrained by issues like unclear fundamental principles,complex experimental cycles,and high costs.Machine learning,as a novel artificial intelligence technology,has the potential to deeply engage in the development of additive manufacturing process,assisting engineers in learning and developing new techniques.This paper provides a comprehensive overview of the research and applications of machine learning in the field of additive manufacturing,particularly in model design and process development.Firstly,it introduces the background and significance of machine learning-assisted design in additive manufacturing process.It then further delves into the application of machine learning in additive manufacturing,focusing on model design and process guidance.Finally,it concludes by summarizing and forecasting the development trends of machine learning technology in the field of additive manufacturing.
基金supported by Priority Academic Program Development of Jiangsu Higher Educatior(PPZY2015A044).
文摘In the cooling crystallization process of thiourea,a significant issue is the excessively wide crystal size distribution(CSD)and the abundance of fine crystals.This investigation delves into the growth kinetics and mechanisms governing thiourea crystals during the cooling crystallization process.The fitting results indicate that the crystal growth rate coefficient,falls within the range of 10^(-7)to 10^(-8)m·s^(-1).Moreover,with decreasing crystallization temperature,the growth process undergoes a transition from diffusion-controlled to surface reaction-controlled,with temperature primarily influencing the surface reaction process and having a limited impact on the diffusion process.Comparing the crystal growth rate,and the diffusion-limited growth rate,at different temperatures,it is observed that the crystal growth process can be broadly divided into two stages.At temperatures above 25℃,1/qd(qd is diffusion control index)approaches 1,indicating the predominance of diffusion control.Conversely,at temperatures below 25℃,1/qd increases rapidly,signifying the dominance of surface reaction control.To address these findings,process optimization was conducted.During the high-temperature phase(35-25℃),agitation was increased to reduce the limitations posed by bulk-phase diffusion in the crystallization process.In the low-temperature phase(25-15℃),agitation was reduced to minimize crystal breakage.The optimized process resulted in a thiourea crystal product with a particle size distribution predominantly ranging from 0.7 to 0.9 mm,accounting for 84%of the total.This study provides valuable insights into resolving the issue of excessive fine crystals in the thiourea crystallization process.
基金Supported by Heilongjiang Provincial Fruit Tree Modernization Agro-industrial Technology Collaborative Innovation and Promotion System Project(2019-13)。
文摘In order to obtain better quality cookies, food 3D printing technology was employed to prepare cookies. The texture, color, deformation, moisture content, and temperature of the cookie as evaluation indicators, the influences of baking process parameters, such as baking time, surface heating temperature and bottom heating temperature, on the quality of the cookie were studied to optimize the baking process parameters. The results showed that the baking process parameters had obvious effects on the texture, color, deformation, moisture content, and temperature of the cookie. All of the roasting surface heating temperature, bottom heating temperature and baking time had positive influences on the hardness, crunchiness, crispiness, and the total color difference(ΔE) of the cookie. When the heating temperatures of the surfac and bottom increased, the diameter and thickness deformation rate of the cookie increased. However,with the extension of baking time, the diameter and thickness deformation rate of the cookie first increased and then decreased. With the surface heating temperature of 180 ℃, the bottom heating temperature of 150 ℃, and baking time of 15 min, the cookie was crisp and moderate with moderate deformation and uniform color. There was no burnt phenomenon with the desired quality. Research results provided a theoretical basis for cookie manufactory based on food 3D printing technology.
基金Item Sponsored by National Natural Science Foundation of China(u0837602,51104076)
文摘The aim is to remove copper from a pyrite cinder by optimizing the chlorination roasting process using re-sponse surface methodology （RSM） and the reaction mechanism of chlorination roasting based on thermodynamic calculation was discussed. A quadratic model was suggested by RSM to correlate the key parameters, namely, dos-age of chlorinating agent, roasting temperature and roasting time to the copper volatilization ratio. The results indi- cate that the model is well consistent with the experimental data at a correlation coefficient （R2） of 0.95, and the dosage of chlorinating agent and roasting temperature both have significant effects on the copper volatilization ratio. However, a roasting temperature exceeding 1170 ~C decreases the volatilization ratio. The optimum conditions for removing copper from the cinder were identified as chlorinating agent dosage at 5%, roasting temperature at i155.10 ℃ and roasting time of 10 min; under Such a conditiom a copper volatilization ratid of 95.16% Was a- chieved from the cinder. Thermodynamic calculation shows that SiO2 in the pellet plays a key role in the chlorine re-lease from calcium chloride, and the chlorine release reactions cannot occur without it.
基金carried out under project number M72.7.09328 within the framework of the Research Program of the Materials innovation institute M2i(www.m2i.nl)。
文摘Application of statistical methods to optimize the process parameters was achieved by employing full factorial design of experiments,which was accomplished by cladding using stepwise ramped laser power.The correlations between clad geometry and dilution(clad characteristics)and the main process parameters laser power(P_(l)),cladding speed(v_(c)),the powder feed rate(m)were obtained through application of variance analysis technique(ANOVA).The obtained correlations between the main processing parameters and the clad characteristics are discussed and a statistical model was developed.The desirability investigations using the developed statistical model were performed by considering the clad geometry,aspect ratio,dilution and hardness.Optimal parameters for cladding Stellite 6 on AISI 420 steel substrate and for cladding Nucalloy 488V on S355 J2 steel substrate were obtained.The optimal processing parameters can be applied to clad other materials with similar chemical compositions.
基金financially supported by the National Natural Science Foundation of China (No. 51674026)
文摘Currently, the majority of copper tailings are not effectively developed. Worldwide, large amounts of copper tailings generated from copper production are continuously dumped, posing a potential environmental threat. Herein, the recovery of iron from copper tailings via low-temperature direct reduction and magnetic separation was conducted; process optimization was carried out, and the corresponding mineralogy was investigated. The reduction time, reduction temperature, reducing agent (coal), calcium chloride additive, grinding time, and magnetic field intensity were examined for process optimization. Mineralogical analyses of the sample, reduced pellets, and magnetic concentrate under various conditions were performed by X-ray diffraction, optical microscopy, and scanning electron microscopy-energy-dispersive X-ray spectrometry to elucidate the iron reduction and growth mechanisms. The results indicated that the optimum parameters of iron recovery include a reduction temperature of 1150A degrees C, a reduction time of 120 min, a coal dosage of 25%, a calcium chloride dosage of 2.5%, a magnetic field intensity of 100 mT, and a grinding time of 1 min. Under these conditions, the iron grade in the magnetic concentrate was greater than 90%, with an iron recovery ratio greater than 95%.
文摘The influence of a key process variable on the mold filling characteristics of AZ91 Mg-alloy was studied in the low pressure EPC process.The applied flow quantity of insert gas from 1 to 5 m~3/h associated with the pressurizing rate in the low pressure EPC casting process was considered for rectangle and L-shape plate casting. The experimental results show that there is an optimal flow quantity of insert gas for good mold filling characteristics in AZ91 Mg-alloy low-pressure EPC process. The optimal flow quantity of insert gas for the specimens is 3 to 4 m~3/h. Either less or higher than the optimal flow quantity of insert gas would lead to misrun defects or folds, blisters and porosity defects. The practice of hub casting confirmed that the low-pressure EPC process with an optimal processing variable exemplified as 4 m~3/h gas flow quantity was capable of producing complicated magnesium castings without misrun defects.
文摘The probabilistic modeling is applied to calculate microstructural features of the thin complex smprolloy turbine blades cast by the vacuum investment process. The random distribution, orientation and physical mechanism of the nucleation, the growth kinetics of dendrites and the columnar-to-equiaxed transition (CET) are considered.Capitalizing on these simulating schemes, the comprehensive influence of key process variables on the scale and uniformity of grains has been involved quantitatively. The validity of the modeling is confirmed by selection of the optimum process variables.
基金Funded by Key Project of Advanced Research Foundation(No.9140A18020113xx)Advanced Research Foundation Project(No.9140A18020212xx)Advanced Research Projects(Nos.5131802xx and 5131812xx)
文摘In this paper, based on the principle of heat transfer and thermal elastic-plastic theory, the heat treatment process optimization scheme for face gears is proposed according to the structural characteristics of the face gear and material properties of 12Cr2Ni4 steel. To simulate the effect of carburizing and quenching process on tooth deformation and residual stress distribution, a heat treatment analysis model of face gears is established, and the microstructure, stress and deformation of face gear teeth changing with time are analyzed. The simulation results show that face gear tooth hardness increases, tooth surface residual compressive stress increases and tooth deformation decreases after heat treatment process optimization. It is beneficial to improving the fatigue strength and performance of face gears.
基金This work was financially supported by the Technology Development Project of SINOPEC(121025)All of the staff in our laboratory had provided a lot of support in the analysis of oil samples and catalyst characterization.
文摘The RTS technology can produce ultra-low sulfur diesel at lower costs using available hydrogenation catalyst and device.However,with the increase of the mixing proportion of secondary processed diesel fuel in the feed,the content of nitrogen compounds and polycyclic aromatic hydrocarbons in the feed increased,leading to the acceleration of the deactivation rate of the primary catalyst and the shortening of the service cycle.In order to fully understand the reason of catalyst deactivation,the effect of mixing secondary processed diesel fuel oil on the operating stability of the catalyst in the first reactor was investigated in a medium-sized fixed-bed hydrogenation unit.The results showed that the nitrogen compounds mainly affected the initial activity of the catalyst,but had little effect on the stability of the catalyst.The PAHs had little effect on the initial activity of the catalyst,but could significantly accelerate the deactivation of the catalyst.Combined with the analysis of the reason of catalyst deactivation and the study of RTS technology,the direction of RTS technology process optimization was put forward,and the stability of catalyst was improved obviously after process optimization.
基金the Australian Government Research Training Program Scholarship,and the Australian Research Council through Discovery Projects(DP110101653,DP130103592)。
文摘Laser powder bed fusion(LPBF)has made significant progress in producing solid and porous metal parts with complex shapes and geometries.However,LPBF produced parts often have defects(e.g.,porosity,residual stress,and incomplete melting)that hinder its large-scale industrial commercialization.The LPBF process involves complex heat transfer andfluidflow,and the melt pool is a critical component of the process.The melt pool stability is a critical factor in determining the microstructure,mechanical properties,and corrosion resistance of LPBF produced metal parts.Furthermore,optimizing process parameters for new materials and designed structures is challenging due to the complexity of the LPBF process.This requires numerous trial-and-error cycles to minimize defects and enhance properties.This review examines the behavior of the melt pool during the LPBF process,including its effects and formation mechanisms.This article summarizes the experimental results and simulations of melt pool and identifies various factors that influence its behavior,which facilitates a better understanding of the melt pool's behavior during LPBF.This review aims to highlight key aspects of the investigation of melt pool tracks and microstructural characterization,with the goal of enhancing a better understanding of the relationship between alloy powder-process-microstructure-properties in LPBF from both single-and multi-melt pool track perspectives.By identifying the challenges and opportunities in investigating single-and multi-melt pool tracks,this review could contribute to the advancement of LPBF processes,optimal process window,and quality optimization,which ultimately improves accuracy in process parameters and efficiency in qualifying alloy powders.
文摘The study was aimed to obtain the optimum conditions for vacuum frying and predicting the moisture lost during rice straw mushrooms stem chip production. The raw materials were obtained from the local farmer around the campus. A completely randomized factorial experimental design and Duncan＇s multiple range tests were used to achieve the objectives. Three temperatures, i.e. 80, 90 and 100 ℃ and five frying time, i.e. 3, 6, 9, and 15 minutes with a 2 mm slice thickness were studied to determine the optimum condition and predict the moisture decrease. Results showed that the vacuum frying time in general affects the chips color and oil uptake significantly （p 〈 0.01） and correlated with the moisture decrease. The chips moisture content decline significantly after vacuum frying at 90 ℃ and 100 ℃ for 3 minutes. While for the 80 ℃ vacuum frying, the significant decrease of moisture occurred due to the increase of vacuum frying time from 3 to 6 minutes （p 〈 0.01）. The optimum conditions for a 2 mm slice thickness chips making are vacuum frying at 100 ℃ for 3 minutes. The chips moisture lost followed generally a two-stage of falling rate pattern during vacuum frying, and each could be well predicted by an exponential equation （R2 = 0.99）.
文摘[Objective] The aim was to obtain higher COD removal rate so as to guide the process of citric acid industrial wastewater. [Method] The effects of controllable factors, acidification time, hydraulic retention time, and influent COD concentration, in-anaerobic treatment process of citric acid wastewater on COD removal rate were studied and the COD removal rate was optimized by response surface method. [Result] There was no interaction between acidification time and the other two factors. It was showed that hydraulic retention time and influent COD concentration had significant effect on COD removal rate and there was interaction between the two factors. The optimum COD removing process conditions was as follows: acidification time 1.53 h, hydraulic retention time 3.52 h and influent COD concentration 2 698 mg/L. Under the optimized conditions, the COD removal rate was 93.31% and it was much closed to the experimental result, 93.29%. [Conclusion] Using response surface method to optimize the anaerobic treatment of citric acid wastewater can result in optimized achievement.
文摘Objective: to observe the effect of emergency nursing process optimization on emergency patient rescue efficiency. Methods: conducting a retrospective study on the emergency patients in our hospital from August 2019 to August 2021, numbering 136 samples according to admission order with No. 1-68 as the control group and No. 69-136 as the observation group;performing routine emergency care to the former group, and performing optimized emergency process to the latter group underwent optimization;comparing the difference between groups on first aid process, first aid effect and satisfaction. Results: the triage, intravenous medication, examination, treatment, ecg monitoring and hospitalization time in observation group were significantly shorter than those in control group, and p < 0.05;the success rate and overall satisfaction of observation group were significantly higher than those in control group, and p < 0.05. Conclusion: optimized emergency nursing process can effectively shorten the rescue time, improve the emergency rescue efficiency, and make the patients and their families become relatively more satisfied.
文摘The idea of genetic engineering is introduced into the area of product design to improve the design efficiency. A method towards design process optimization based on the design process gene is proposed through analyzing the correlation between the design process gene and characteristics of the design process. The concept of the design process gene is analyzed and categorized into five categories that are the task specification gene, the concept design gene, the overall design gene, the detailed design gene and the processing design gene in the light of five design phases. The elements and their interactions involved in each kind of design process gene signprocess gene mapping is drawn with its structure disclosed based on its function that process gene.
