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
Objective:To investigate the application effects of intelligent guidance systems in optimizing health check-up process management.Methods:A total of 400 examinees who underwent physical examinations at the hospital’s...Objective:To investigate the application effects of intelligent guidance systems in optimizing health check-up process management.Methods:A total of 400 examinees who underwent physical examinations at the hospital’s Health Management Center from January to December 2024 were randomly divided into a control group(200 cases)and an observation group(200 cases).The control group used traditional manual guidance methods,while the observation group employed the intelligent guidance system.The study compared two groups in terms of completion time,waiting time for each procedure,check-up efficiency scores,examinee satisfaction,and report issuance time.Results:The overall examination time in the observation group(85.3±12.7 minutes)was significantly shorter than that in the control group(142.6±18.5 minutes)(P<0.01);average waiting time per procedure decreased by 62.4%;check-up efficiency scores(8.9±0.8 points)were significantly higher than those in the control group(5.2±1.1 points)(P<0.01);satisfaction reached 96.5%,significantly higher than the control group’s 78.0%(P<0.01);and report issuance time was advanced by 1.5 days.Conclusion:Intelligent guidance systems can significantly optimize check-up processes,improve work efficiency,and examinee satisfaction,demonstrating significant clinical application value.展开更多
The latest progress in the process optimization and stability improvement of third-generation cephalosporins in recent years was reviewed.The introduction of green chemistry,enzyme catalysis,nanotechnology,lyophilizat...The latest progress in the process optimization and stability improvement of third-generation cephalosporins in recent years was reviewed.The introduction of green chemistry,enzyme catalysis,nanotechnology,lyophilization,and nitrogen-filled packaging technologies can only improve production efficiency and reduce the generation of by-products,but also significantly extend the shelf life of drugs.In the future,process automation and intelligent technology will further optimize the large-scale production process,and the combination of nanotechnology and precision drug delivery will promote the improvement of effect in clinical applications.展开更多
High ammonia-nitrogen digestate has become a key bottleneck limiting the anaerobic digestion of organic solid waste.Vacuum ammonia stripping can simultaneously remove and recover ammonia nitrogen,which has attracted a...High ammonia-nitrogen digestate has become a key bottleneck limiting the anaerobic digestion of organic solid waste.Vacuum ammonia stripping can simultaneously remove and recover ammonia nitrogen,which has attracted a lot of attention in recent years.To investigate the parameter effects on the efficiency and mass transfer,five combination conditions(53℃ 15 kPa,60°C 20 kPa,65°C 25 kPa,72°C 35 kPa,and 81°C 50 kPa)were conducted for ammonia stripping of sludge digestate.The results showed that 80%of ammonia nitrogen was stripped in 45 min for all experimental groups,but the ammonia transfer coefficient varied under different conditions,which increased with the rising of boiling point temperature,and reached the maximum value(39.0 mm/hr)at 81°C 50 kPa.The ammonia nitrogen removal efficiency was more than 80%for 30 min vacuum stripping after adjusting the initial pH to above 9.5,and adjustment of the initial alkalinity also affects the pH value of liquid digestate.It was found that pH and alkalinity are the key factors influencing the ammonia nitrogen dissociation and removal efficiency,while temperature and vacuum mainly affect the ammonia nitrogen mass transfer and removal velocity.In terms of the mechanism of vacuum ammonia stripping,it underwent alkalinity destruction,pH enhancement,ammonia nitrogen dissociation,and free ammonia removal.In this study,two-stage experiments of alkalinity destruction and ammonia removal were also carried out,which showed that the two-stage configuration was beneficial for ammonia removal.It provides a theoretical basis and practical technology for the vacuum ammonia stripping from liquid digestate of organic solid waste.展开更多
A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are ...A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are modeled by level set functions.Secondly,the mathematical model of the additive direction optimization problem is established,and an improved particle swarm optimization algorithm is designed to decide the best additive direction.Then,the two-step strategy is used to plan the hybrid manufacturing alternating sequence.The target parts are directly divided into various processing regions;each processing region is optimized based on manufacturability and manufacturing efficiency,and the optimal hybrid manufacturing alternating sequence is obtained by merging some processing regions.Finally,the method is used to outline the process plan of the designed example model and applied to the actual hybrid manufacturing process of the model.The manufacturing result shows that the method can meet the main considerations in hybrid manufacturing.In addition,the degree of automation of process planning is high,and the dependence on manual intervention is low.展开更多
Objective To optimize the ultrasonic extraction process for benzoic acid as a harmful substance in Paeonia lactiflora Pall.(P.lactiflora Pall.).Methods Methanol and ethanol solutions at different concentration gradien...Objective To optimize the ultrasonic extraction process for benzoic acid as a harmful substance in Paeonia lactiflora Pall.(P.lactiflora Pall.).Methods Methanol and ethanol solutions at different concentration gradients(25,50,75%)were prepared to investigate the effects of extraction solvents on the extraction efficiency of benzoic acid.The influences of ultrasonic frequency(35,50 Hz),ultrasonic power(40,60,80,100 W),ultrasonic time(10,20,30,40,50,60 minutes),and ultrasonic temperature(20,30,40,50℃)on the extraction efficiency were examined.Orthogonal experiments were conducted to analyze the effects of temperature,time,and ultrasonic power on the extraction efficiency and to screen the optimal ultrasonic extraction process.Results Various influencing factors had certain effects on the extraction efficiency of benzoic acid from P.lactiflora Pall.Single-factor analysis revealed that 25%methanol,ultrasonic frequency of 50 Hz,ultrasonic power of 40 W,ultrasonic time of 10minutes,and ultrasonic temperature of 30℃yielded the highest extraction efficiency for benzoic acid.The order of influence of different factors on the extraction efficiency was temperature>time>power.The optimal conditions obtained from orthogonal experiments were:extraction solvent of 25%methanol,ultrasonic frequency of 50 Hz,ultrasonic time of 20 minutes,ultrasonic power of 40 W,and ultrasonic temperature of 30℃.Conclusion Under the conditions of 25%methanol as the extraction solvent,ultrasonic frequency of 50 Hz,ultrasonic time of 20 minutes,ultrasonic power of 40 W,and ultrasonic temperature of 30℃,the extraction efficiency of benzoic acid from P.lactiflora Pall.was the highest.This method offers advantages such as simple operation,small sample size requirement,and low solvent consumption,providing a reliable analytical approach for quality control and safety evaluation of P.lactiflora Pall.展开更多
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
[Objectives] To optimize the crystallization process of ceftriaxone sodium using response surface methodology (RSM) for enhancing both the crystallization rate and the quality of the final product. [Methods] Four key ...[Objectives] To optimize the crystallization process of ceftriaxone sodium using response surface methodology (RSM) for enhancing both the crystallization rate and the quality of the final product. [Methods] Four key factors, including crystallization temperature, stirring speed, solvent drop rate, and seed crystal content, were employed as independent variables, while the crystallization rate served as the response variable. The Box-Behnken response surface method was utilized for the optimization design. [Results] The optimal parameters for the crystallization process, determined through optimization, were as follows: a temperature of 10.6 ℃, a stirring rate of 150 rpm, a solvent drop rate of 1.50 mL/min, and a seed crystal content of 0.12 g. Validation tests conducted under these conditions yielded an average crystallization rate of 94.38% for the refined product. [Conclusions] The crystallization efficiency of ceftriaxone sodium is markedly enhanced, thereby offering substantial support for its industrial production and clinical application.展开更多
This paper examines the challenges in the technical briefing process for construction projects,including a three-level system and issues related to formalization.An optimization approaches was introduced based on the ...This paper examines the challenges in the technical briefing process for construction projects,including a three-level system and issues related to formalization.An optimization approaches was introduced based on the PDCA cycle,alongside the application of BIM and AR technologies.The key preparatory measures were outlined in this study and the functions of the management system was mentioned.Through case comparisons,this paper demonstrated that these optimizations can significantly improve efficiency and quality,support the development of an evaluation system to verify results,and highlight the critical role of organizational support.展开更多
In the project procurement management process of telecommunication enterprises,due to the complexity of technology,the professional procurement project manager is responsible for the whole process of professional proc...In the project procurement management process of telecommunication enterprises,due to the complexity of technology,the professional procurement project manager is responsible for the whole process of professional procurement in a one-stop way.The integration of this management process superficially improves labor productivity,but in essence lacks effective checks and balances and supervision.In order to supervise the project procurement management process and ensure the legal compliance of procurement management,this paper studies the project procurement management process of telecommunication enterprises,proposes the optimization process of project procurement management in the segmentation of purchasing manager-business manager,and constructs a matrix project procurement management model,which will contribute to the overall improvement of the telecommunication enterprises’procurement performance.展开更多
Silicone material extrusion(MEX)is widely used for processing liquids and pastes.Owing to the uneven linewidth and elastic extrusion deformation caused by material accumulation,products may exhibit geometric errors an...Silicone material extrusion(MEX)is widely used for processing liquids and pastes.Owing to the uneven linewidth and elastic extrusion deformation caused by material accumulation,products may exhibit geometric errors and performance defects,leading to a decline in product quality and affecting its service life.This study proposes a process parameter optimization method that considers the mechanical properties of printed specimens and production costs.To improve the quality of silicone printing samples and reduce production costs,three machine learning models,kernel extreme learning machine(KELM),support vector regression(SVR),and random forest(RF),were developed to predict these three factors.Training data were obtained through a complete factorial experiment.A new dataset is obtained using the Euclidean distance method,which assigns the elimination factor.It is trained with Bayesian optimization algorithms for parameter optimization,the new dataset is input into the improved double Gaussian extreme learning machine,and finally obtains the improved KELM model.The results showed improved prediction accuracy over SVR and RF.Furthermore,a multi-objective optimization framework was proposed by combining genetic algorithm technology with the improved KELM model.The effectiveness and reasonableness of the model algorithm were verified by comparing the optimized results with the experimental results.展开更多
The isothermal compression test for Ti-6Al-7Nb alloy was conducted by using Gleeble-3800 thermal simulator.The hot deformation behavior of Ti-6Al-7Nb alloy was investigated in the deformation temperature ranges of 940...The isothermal compression test for Ti-6Al-7Nb alloy was conducted by using Gleeble-3800 thermal simulator.The hot deformation behavior of Ti-6Al-7Nb alloy was investigated in the deformation temperature ranges of 940-1030℃and the strain rate ranges of 0.001-10 s^(-1).Meanwhile,the activation energy of thermal deformation was computed.The results show that the flow stress of Ti-6Al-7Nb alloy increases with increasing the strain rate and decreasing the deformation temperature.The activation energy of thermal deformation for Ti-6Al-7Nb alloy is much greater than that for self-diffusion ofα-Ti andβ-Ti.Considering the influence of strain on flow stress,the strain-compensated Arrhenius constitutive model of Ti-6Al-7Nb alloy was established.The error analysis shows that the model has higher accuracy,and the correlation coefficient r and average absolute relative error are 0.9879 and 4.11%,respectively.The processing map(PM)of Ti-6Al-7Nb alloy was constructed by the dynamic materials model and Prasad instability criterion.According to PM and microstructural observation,it is found that the main form of instability zone is local flow,and the deformation mechanisms of the stable zone are mainly superplasticity and dynamic recrystallization.The optimal processing parameters of Ti-6Al-7Nb alloy are determined as follows:960-995℃/0.01-0.18 s^(-1)and 1000-1030℃/0.001-0.01 s^(-1).展开更多
The current methods used to industrially produce sinomenine hydrochloride involve several issues,including high solvent toxicity,long process flow,and low atomic utilization efficiency,and the greenness scores of the ...The current methods used to industrially produce sinomenine hydrochloride involve several issues,including high solvent toxicity,long process flow,and low atomic utilization efficiency,and the greenness scores of the processes are below 65 points.To solve these problems,a new process using anisole as the extractant was proposed.Anisole exhibits high selectivity for sinomenine and can be connected to the subsequent water-washing steps.After alkalization of the medicinal material,heating extraction,water washing,and acidification crystallization were carried out.The process was modeled and optimized.The design space was constructed.The recommended operating ranges for the critical process parameters were 3.0–4.0 h for alkalization time,60.0–80.0℃ for extraction temperature,2.0–3.0(volume ratio)for washing solution amount,and 2.0–2.4 mol·L^(-1) for hydrochloric acid concentration.The new process shows good robustness because different batches of medicinal materials did not greatly impact crystal purity or sinomenine transfer rate.The sinomenine transfer rate was about 20%higher than that of industrial processes.The greenness score increased to 90 points since the novel process proposed in this research solves the problems of long process flow,high solvent toxicity,and poor atomic economy,better aligning with the concept of green chemistry.展开更多
Understanding and clarifying the evolution of microstructure and performance of Al-Zr-Sc alloy wires during processing paths is a crucial issue in developing heat-resistant conductors with high strength and high elect...Understanding and clarifying the evolution of microstructure and performance of Al-Zr-Sc alloy wires during processing paths is a crucial issue in developing heat-resistant conductors with high strength and high electrical conductivity(EC).In this study,the microstructure evolution and corresponding performance changes of Al-0.2Zr-0.06Sc alloy wires produced by three processing paths are investigated.Results indicate that ageing treatment+hot extrusion+cold drawing processing path can produce the highest strength Al-Zr-Sc wires attributed to favorable interactions among precipitation strengthening of Al_(3)(Zr,Sc)phases,grain boundary strengthening and dislocation strengthening.High EC is attained by the hot extrusion+ageing treatment+cold drawing processing path,which reveals the importance of dynamic precipitation of Al_(3)Sc phases during hot extrusion and further precipitation of solute atoms during ageing treatment for improving the EC.The processing path using hot extrusion+cold drawing+ageing treatment achieves the highest EC of the Al-Zr-Sc wire,but the strength decreases significantly due to the loss of dislocation strengthening.Additionally,the pinning effect of Al_(3)Sc and Al_(3)(Zr,Sc)ensures good heat resistance of Al-Zr-Sc wires.These results provide guidance for the process design of Al-Zr-Sc wires with variable combinations of strength and EC.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
The optimization system, which was the subject of our study, is an autonomous chain for the automatic management of cyanide consumption. It is in the phase of industrial automation which made it possible to use the ma...The optimization system, which was the subject of our study, is an autonomous chain for the automatic management of cyanide consumption. It is in the phase of industrial automation which made it possible to use the machines in order to reduce the workload of the worker while keeping a high productivity and a quality in great demand. Furthermore, the use of cyanide in leaching tanks is a necessity in the gold recovery process. This consumption of cyanide must be optimal in these tanks in order to have a good recovery while controlling the concentration of cyanide. Cyanide is one of the most expensive products for mining companies. On a completely different note, we see huge variations during the addition of cyanide. Following a recommendation from the metallurgical and operations teams, the control team carried out an analysis of the problem while proposing a solution to reduce the variability around plus or minus 10% of the addition setpoint through automation. It should be noted that this automatic optimization by monitoring the concentration of cyanide, made use of industrial automation which is a technique which ensures the operation of the ore processing chain without human intervention. In other words, it made it possible to substitute a machine for man. So, this leads us to conduct a study on concentration levels in the real world. The results show that the analysis of the modeling of the cyanide consumption optimization system is an appropriate solution to eradicate failures in the mineral processing chain. The trend curves demonstrate this resolution perfectly.展开更多
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
This study investigates the dry reformation of methane(DRM)over Ni/Al_(2)O_(3)catalysts in a dielectric barrier discharge(DBD)non-thermal plasma reactor.A novel hybrid machine learning(ML)model is developed to optimiz...This study investigates the dry reformation of methane(DRM)over Ni/Al_(2)O_(3)catalysts in a dielectric barrier discharge(DBD)non-thermal plasma reactor.A novel hybrid machine learning(ML)model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data.To address the non-linear and complex nature of the plasma-catalytic DRM process,the hybrid ML model integrates three well-established algorithms:regression trees,support vector regression,and artificial neural networks.A genetic algorithm(GA)is then used to optimize the hyperparameters of each algorithm within the hybrid ML model.The ML model achieved excellent agreement with the experimental data,demonstrating its efficacy in accurately predicting and optimizing the DRM process.The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance.We found that the optimal discharge power(20 W),CO_(2)/CH_(4)molar ratio(1.5),and Ni loading(7.8 wt%)resulted in the maximum energy yield at a total flow rate of∼51 mL/min.Furthermore,we investigated the relative significance of each operating parameter on the performance of the plasma-catalytic DRM process.The results show that the total flow rate had the greatest influence on the conversion,with a significance exceeding 35%for each output,while the Ni loading had the least impact on the overall reaction performance.This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets,enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.展开更多
Hydroconversion of coal tar to produce aromatic hydrocarbons(BTX)represents a crucial strategy for the highvalue hierarchical utilization of coal.This study focused on the hydrocracking of hydrorefined products derive...Hydroconversion of coal tar to produce aromatic hydrocarbons(BTX)represents a crucial strategy for the highvalue hierarchical utilization of coal.This study focused on the hydrocracking of hydrorefined products derived from coal tar to enhance the production of benzene,toluene,and xylene(BTX).Various reaction conditions,including reaction temperature,hydrogen pressure,space velocity,and hydrogen-to-oil volume ratio,were systematically explored to optimize BTX yields while also considering the process’s economic feasibility.The results indicate that increasing the reaction temperature from 360℃ to 390℃ significantly favors the production of BTX,with yields increasing from 21.42%to 41.14%.Similarly,an increase in hydrogen pressure from 4 MPa to 6 MPa boosts BTX production,with yields rising from 36.31%to 41.14%.Reducing the space velocity from 2 h^(-1) to 0.5 h^(-1) also favors the BTX production process,with yields increasing from 37.96%to 45.13%.Furthermore,raising the hydrogen-to-oil volume ratio from 750 to 1500 improves BTX yields from 41.61%to 45.44%.Through economic analysis,the optimal conditions for BTX production were identified as a reaction temperature of 390℃,hydrogen pressure of 5-6 MPa,space velocity of 1 h^(-1),and hydrogen-to-oil volume ratio of 1000,achieving a BTX yield of 43.73%.This investigation highlights the importance of a holistic evaluation of hydrocracking conditions to optimize BTX production.Furthermore,the findings offer valuable insights for the design and operation of industrial hydrocracking processes aimed at efficiently converting coal tar-derived hydrorefined feedstock into BTX.展开更多
In order to improve the sealing surface performance of gray cast iron gas gate valves and achieve precise molding control of the cladding layer,as well as to reveal the influence of laser cladding process parameters o...In order to improve the sealing surface performance of gray cast iron gas gate valves and achieve precise molding control of the cladding layer,as well as to reveal the influence of laser cladding process parameters on the morphology and structure of the cladding layer,we prepared the 316L coating on HT 200 by using Design-Expert software central composite design(CCD)based on response surface analysis.We built a regression prediction model and analyzed the ANOVA with the inspection results.With a target cladding layer width of 3.5 mm and height of 1.3 mm,the process parameters were optimized to obtain the best combination of process parameters.The microstructure,phases,and hardness variations of the cladding layer from experiments with optimal parameters were analyzed by the metallographic microscope,confocal microscope,and microhardness instrument.The experimental results indicate that laser power has a significant impact on the cladding layer width,followed by powder feed rate;scan speed has a significant impact on the cladding layer height,followed by powder feed rate.The HT200 substrate and 316L can metallurgically bond well,and the cladding layer structure consists of dendritic crystals,columnar crystals,and equiaxed crystals in sequence.The optimal process parameter combination satisfying the morphology requirements is laser power(A)of 1993 W,scan speed(B)of 8.949 mm/s,powder feed rate(C)of 1.408 r/min,with a maximum hardness of 1564.3 HV0.5,significantly higher than the hardness of the HT200 substrate.展开更多
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.
文摘Objective:To investigate the application effects of intelligent guidance systems in optimizing health check-up process management.Methods:A total of 400 examinees who underwent physical examinations at the hospital’s Health Management Center from January to December 2024 were randomly divided into a control group(200 cases)and an observation group(200 cases).The control group used traditional manual guidance methods,while the observation group employed the intelligent guidance system.The study compared two groups in terms of completion time,waiting time for each procedure,check-up efficiency scores,examinee satisfaction,and report issuance time.Results:The overall examination time in the observation group(85.3±12.7 minutes)was significantly shorter than that in the control group(142.6±18.5 minutes)(P<0.01);average waiting time per procedure decreased by 62.4%;check-up efficiency scores(8.9±0.8 points)were significantly higher than those in the control group(5.2±1.1 points)(P<0.01);satisfaction reached 96.5%,significantly higher than the control group’s 78.0%(P<0.01);and report issuance time was advanced by 1.5 days.Conclusion:Intelligent guidance systems can significantly optimize check-up processes,improve work efficiency,and examinee satisfaction,demonstrating significant clinical application value.
基金Supported by the Funds from Central Government for Guiding Local Science and Technology Development(ZY20230102)Planning Project of Scientific Research and Technology Development in Guilin(20220104-4,20210202-1)Science and Technology Planing Project of Guangxi(Guike AB24010263).
文摘The latest progress in the process optimization and stability improvement of third-generation cephalosporins in recent years was reviewed.The introduction of green chemistry,enzyme catalysis,nanotechnology,lyophilization,and nitrogen-filled packaging technologies can only improve production efficiency and reduce the generation of by-products,but also significantly extend the shelf life of drugs.In the future,process automation and intelligent technology will further optimize the large-scale production process,and the combination of nanotechnology and precision drug delivery will promote the improvement of effect in clinical applications.
基金supported by the National Key Research and Development Program of China(No.2020YFC1908702)the National Natural Science Foundation of China(No.52131002)+1 种基金the Science and Technology Commission of Shanghai Municipality(No.22dz1209200)China Three Gorges Corporation(No.202403018).
文摘High ammonia-nitrogen digestate has become a key bottleneck limiting the anaerobic digestion of organic solid waste.Vacuum ammonia stripping can simultaneously remove and recover ammonia nitrogen,which has attracted a lot of attention in recent years.To investigate the parameter effects on the efficiency and mass transfer,five combination conditions(53℃ 15 kPa,60°C 20 kPa,65°C 25 kPa,72°C 35 kPa,and 81°C 50 kPa)were conducted for ammonia stripping of sludge digestate.The results showed that 80%of ammonia nitrogen was stripped in 45 min for all experimental groups,but the ammonia transfer coefficient varied under different conditions,which increased with the rising of boiling point temperature,and reached the maximum value(39.0 mm/hr)at 81°C 50 kPa.The ammonia nitrogen removal efficiency was more than 80%for 30 min vacuum stripping after adjusting the initial pH to above 9.5,and adjustment of the initial alkalinity also affects the pH value of liquid digestate.It was found that pH and alkalinity are the key factors influencing the ammonia nitrogen dissociation and removal efficiency,while temperature and vacuum mainly affect the ammonia nitrogen mass transfer and removal velocity.In terms of the mechanism of vacuum ammonia stripping,it underwent alkalinity destruction,pH enhancement,ammonia nitrogen dissociation,and free ammonia removal.In this study,two-stage experiments of alkalinity destruction and ammonia removal were also carried out,which showed that the two-stage configuration was beneficial for ammonia removal.It provides a theoretical basis and practical technology for the vacuum ammonia stripping from liquid digestate of organic solid waste.
基金The National Natural Science Foundation of China(No.52305381)the Natural Science Foundation of Jiangsu Province(No.BK20210351)the Fundamental Research Funds for the Central Universities(No.30923011008).
文摘A reasonable process plan is an important basis for implementing wire arc additive and subtractive hybrid manufacturing(ASHM),and a new optimization method is proposed.Firstly,the target parts and machining tools are modeled by level set functions.Secondly,the mathematical model of the additive direction optimization problem is established,and an improved particle swarm optimization algorithm is designed to decide the best additive direction.Then,the two-step strategy is used to plan the hybrid manufacturing alternating sequence.The target parts are directly divided into various processing regions;each processing region is optimized based on manufacturability and manufacturing efficiency,and the optimal hybrid manufacturing alternating sequence is obtained by merging some processing regions.Finally,the method is used to outline the process plan of the designed example model and applied to the actual hybrid manufacturing process of the model.The manufacturing result shows that the method can meet the main considerations in hybrid manufacturing.In addition,the degree of automation of process planning is high,and the dependence on manual intervention is low.
基金supported by the Heilongjiang Provincial Administration of Traditional Chinese Medicine Project(ZHY18-153).
文摘Objective To optimize the ultrasonic extraction process for benzoic acid as a harmful substance in Paeonia lactiflora Pall.(P.lactiflora Pall.).Methods Methanol and ethanol solutions at different concentration gradients(25,50,75%)were prepared to investigate the effects of extraction solvents on the extraction efficiency of benzoic acid.The influences of ultrasonic frequency(35,50 Hz),ultrasonic power(40,60,80,100 W),ultrasonic time(10,20,30,40,50,60 minutes),and ultrasonic temperature(20,30,40,50℃)on the extraction efficiency were examined.Orthogonal experiments were conducted to analyze the effects of temperature,time,and ultrasonic power on the extraction efficiency and to screen the optimal ultrasonic extraction process.Results Various influencing factors had certain effects on the extraction efficiency of benzoic acid from P.lactiflora Pall.Single-factor analysis revealed that 25%methanol,ultrasonic frequency of 50 Hz,ultrasonic power of 40 W,ultrasonic time of 10minutes,and ultrasonic temperature of 30℃yielded the highest extraction efficiency for benzoic acid.The order of influence of different factors on the extraction efficiency was temperature>time>power.The optimal conditions obtained from orthogonal experiments were:extraction solvent of 25%methanol,ultrasonic frequency of 50 Hz,ultrasonic time of 20 minutes,ultrasonic power of 40 W,and ultrasonic temperature of 30℃.Conclusion Under the conditions of 25%methanol as the extraction solvent,ultrasonic frequency of 50 Hz,ultrasonic time of 20 minutes,ultrasonic power of 40 W,and ultrasonic temperature of 30℃,the extraction efficiency of benzoic acid from P.lactiflora Pall.was the highest.This method offers advantages such as simple operation,small sample size requirement,and low solvent consumption,providing a reliable analytical approach for quality control and safety evaluation of P.lactiflora Pall.
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 Central Guided Local Science and Technology Development Funds(ZY20230102)Guilin Scientific Research and Technology Development Programme Project(2023010301-1,20220104-4)+1 种基金Guangxi Science and Technology Programme Project(GK AB24010263)Guangxi Innovation Driving Development Special Funds Project(GK AA22096020).
文摘[Objectives] To optimize the crystallization process of ceftriaxone sodium using response surface methodology (RSM) for enhancing both the crystallization rate and the quality of the final product. [Methods] Four key factors, including crystallization temperature, stirring speed, solvent drop rate, and seed crystal content, were employed as independent variables, while the crystallization rate served as the response variable. The Box-Behnken response surface method was utilized for the optimization design. [Results] The optimal parameters for the crystallization process, determined through optimization, were as follows: a temperature of 10.6 ℃, a stirring rate of 150 rpm, a solvent drop rate of 1.50 mL/min, and a seed crystal content of 0.12 g. Validation tests conducted under these conditions yielded an average crystallization rate of 94.38% for the refined product. [Conclusions] The crystallization efficiency of ceftriaxone sodium is markedly enhanced, thereby offering substantial support for its industrial production and clinical application.
文摘This paper examines the challenges in the technical briefing process for construction projects,including a three-level system and issues related to formalization.An optimization approaches was introduced based on the PDCA cycle,alongside the application of BIM and AR technologies.The key preparatory measures were outlined in this study and the functions of the management system was mentioned.Through case comparisons,this paper demonstrated that these optimizations can significantly improve efficiency and quality,support the development of an evaluation system to verify results,and highlight the critical role of organizational support.
文摘In the project procurement management process of telecommunication enterprises,due to the complexity of technology,the professional procurement project manager is responsible for the whole process of professional procurement in a one-stop way.The integration of this management process superficially improves labor productivity,but in essence lacks effective checks and balances and supervision.In order to supervise the project procurement management process and ensure the legal compliance of procurement management,this paper studies the project procurement management process of telecommunication enterprises,proposes the optimization process of project procurement management in the segmentation of purchasing manager-business manager,and constructs a matrix project procurement management model,which will contribute to the overall improvement of the telecommunication enterprises’procurement performance.
基金supported by the National Key R&D Program of China(No.2022YFA1005204l)。
文摘Silicone material extrusion(MEX)is widely used for processing liquids and pastes.Owing to the uneven linewidth and elastic extrusion deformation caused by material accumulation,products may exhibit geometric errors and performance defects,leading to a decline in product quality and affecting its service life.This study proposes a process parameter optimization method that considers the mechanical properties of printed specimens and production costs.To improve the quality of silicone printing samples and reduce production costs,three machine learning models,kernel extreme learning machine(KELM),support vector regression(SVR),and random forest(RF),were developed to predict these three factors.Training data were obtained through a complete factorial experiment.A new dataset is obtained using the Euclidean distance method,which assigns the elimination factor.It is trained with Bayesian optimization algorithms for parameter optimization,the new dataset is input into the improved double Gaussian extreme learning machine,and finally obtains the improved KELM model.The results showed improved prediction accuracy over SVR and RF.Furthermore,a multi-objective optimization framework was proposed by combining genetic algorithm technology with the improved KELM model.The effectiveness and reasonableness of the model algorithm were verified by comparing the optimized results with the experimental results.
基金the National Natural Science Foundation of China(Grant No.51464035).
文摘The isothermal compression test for Ti-6Al-7Nb alloy was conducted by using Gleeble-3800 thermal simulator.The hot deformation behavior of Ti-6Al-7Nb alloy was investigated in the deformation temperature ranges of 940-1030℃and the strain rate ranges of 0.001-10 s^(-1).Meanwhile,the activation energy of thermal deformation was computed.The results show that the flow stress of Ti-6Al-7Nb alloy increases with increasing the strain rate and decreasing the deformation temperature.The activation energy of thermal deformation for Ti-6Al-7Nb alloy is much greater than that for self-diffusion ofα-Ti andβ-Ti.Considering the influence of strain on flow stress,the strain-compensated Arrhenius constitutive model of Ti-6Al-7Nb alloy was established.The error analysis shows that the model has higher accuracy,and the correlation coefficient r and average absolute relative error are 0.9879 and 4.11%,respectively.The processing map(PM)of Ti-6Al-7Nb alloy was constructed by the dynamic materials model and Prasad instability criterion.According to PM and microstructural observation,it is found that the main form of instability zone is local flow,and the deformation mechanisms of the stable zone are mainly superplasticity and dynamic recrystallization.The optimal processing parameters of Ti-6Al-7Nb alloy are determined as follows:960-995℃/0.01-0.18 s^(-1)and 1000-1030℃/0.001-0.01 s^(-1).
基金supported by the Innovation Team and Talents Cultivation Program of the National Administration of Traditional Chinese Medicine(ZYYCXTD-D-202002)the Fundamental Research Funds for the Central Universities(226-2022-00226).
文摘The current methods used to industrially produce sinomenine hydrochloride involve several issues,including high solvent toxicity,long process flow,and low atomic utilization efficiency,and the greenness scores of the processes are below 65 points.To solve these problems,a new process using anisole as the extractant was proposed.Anisole exhibits high selectivity for sinomenine and can be connected to the subsequent water-washing steps.After alkalization of the medicinal material,heating extraction,water washing,and acidification crystallization were carried out.The process was modeled and optimized.The design space was constructed.The recommended operating ranges for the critical process parameters were 3.0–4.0 h for alkalization time,60.0–80.0℃ for extraction temperature,2.0–3.0(volume ratio)for washing solution amount,and 2.0–2.4 mol·L^(-1) for hydrochloric acid concentration.The new process shows good robustness because different batches of medicinal materials did not greatly impact crystal purity or sinomenine transfer rate.The sinomenine transfer rate was about 20%higher than that of industrial processes.The greenness score increased to 90 points since the novel process proposed in this research solves the problems of long process flow,high solvent toxicity,and poor atomic economy,better aligning with the concept of green chemistry.
基金financially supported by the Key Project of Research and Development in Yunnan Province(Nos.202103AN080001-002 and 202202AG050007-4)Key Project of Yunnan Fundamental Research(No.202101AS070017)the Kunming University of Science and Technology Analysis and Testing Fund(No.2022M20202230013).
文摘Understanding and clarifying the evolution of microstructure and performance of Al-Zr-Sc alloy wires during processing paths is a crucial issue in developing heat-resistant conductors with high strength and high electrical conductivity(EC).In this study,the microstructure evolution and corresponding performance changes of Al-0.2Zr-0.06Sc alloy wires produced by three processing paths are investigated.Results indicate that ageing treatment+hot extrusion+cold drawing processing path can produce the highest strength Al-Zr-Sc wires attributed to favorable interactions among precipitation strengthening of Al_(3)(Zr,Sc)phases,grain boundary strengthening and dislocation strengthening.High EC is attained by the hot extrusion+ageing treatment+cold drawing processing path,which reveals the importance of dynamic precipitation of Al_(3)Sc phases during hot extrusion and further precipitation of solute atoms during ageing treatment for improving the EC.The processing path using hot extrusion+cold drawing+ageing treatment achieves the highest EC of the Al-Zr-Sc wire,but the strength decreases significantly due to the loss of dislocation strengthening.Additionally,the pinning effect of Al_(3)Sc and Al_(3)(Zr,Sc)ensures good heat resistance of Al-Zr-Sc wires.These results provide guidance for the process design of Al-Zr-Sc wires with variable combinations of strength and EC.
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.
文摘The optimization system, which was the subject of our study, is an autonomous chain for the automatic management of cyanide consumption. It is in the phase of industrial automation which made it possible to use the machines in order to reduce the workload of the worker while keeping a high productivity and a quality in great demand. Furthermore, the use of cyanide in leaching tanks is a necessity in the gold recovery process. This consumption of cyanide must be optimal in these tanks in order to have a good recovery while controlling the concentration of cyanide. Cyanide is one of the most expensive products for mining companies. On a completely different note, we see huge variations during the addition of cyanide. Following a recommendation from the metallurgical and operations teams, the control team carried out an analysis of the problem while proposing a solution to reduce the variability around plus or minus 10% of the addition setpoint through automation. It should be noted that this automatic optimization by monitoring the concentration of cyanide, made use of industrial automation which is a technique which ensures the operation of the ore processing chain without human intervention. In other words, it made it possible to substitute a machine for man. So, this leads us to conduct a study on concentration levels in the real world. The results show that the analysis of the modeling of the cyanide consumption optimization system is an appropriate solution to eradicate failures in the mineral processing chain. The trend curves demonstrate this resolution perfectly.
基金supported by 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This project received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 813393the funding from the National Natural Science Foundation of China (No. 52177149)
文摘This study investigates the dry reformation of methane(DRM)over Ni/Al_(2)O_(3)catalysts in a dielectric barrier discharge(DBD)non-thermal plasma reactor.A novel hybrid machine learning(ML)model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data.To address the non-linear and complex nature of the plasma-catalytic DRM process,the hybrid ML model integrates three well-established algorithms:regression trees,support vector regression,and artificial neural networks.A genetic algorithm(GA)is then used to optimize the hyperparameters of each algorithm within the hybrid ML model.The ML model achieved excellent agreement with the experimental data,demonstrating its efficacy in accurately predicting and optimizing the DRM process.The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance.We found that the optimal discharge power(20 W),CO_(2)/CH_(4)molar ratio(1.5),and Ni loading(7.8 wt%)resulted in the maximum energy yield at a total flow rate of∼51 mL/min.Furthermore,we investigated the relative significance of each operating parameter on the performance of the plasma-catalytic DRM process.The results show that the total flow rate had the greatest influence on the conversion,with a significance exceeding 35%for each output,while the Ni loading had the least impact on the overall reaction performance.This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets,enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.
文摘Hydroconversion of coal tar to produce aromatic hydrocarbons(BTX)represents a crucial strategy for the highvalue hierarchical utilization of coal.This study focused on the hydrocracking of hydrorefined products derived from coal tar to enhance the production of benzene,toluene,and xylene(BTX).Various reaction conditions,including reaction temperature,hydrogen pressure,space velocity,and hydrogen-to-oil volume ratio,were systematically explored to optimize BTX yields while also considering the process’s economic feasibility.The results indicate that increasing the reaction temperature from 360℃ to 390℃ significantly favors the production of BTX,with yields increasing from 21.42%to 41.14%.Similarly,an increase in hydrogen pressure from 4 MPa to 6 MPa boosts BTX production,with yields rising from 36.31%to 41.14%.Reducing the space velocity from 2 h^(-1) to 0.5 h^(-1) also favors the BTX production process,with yields increasing from 37.96%to 45.13%.Furthermore,raising the hydrogen-to-oil volume ratio from 750 to 1500 improves BTX yields from 41.61%to 45.44%.Through economic analysis,the optimal conditions for BTX production were identified as a reaction temperature of 390℃,hydrogen pressure of 5-6 MPa,space velocity of 1 h^(-1),and hydrogen-to-oil volume ratio of 1000,achieving a BTX yield of 43.73%.This investigation highlights the importance of a holistic evaluation of hydrocracking conditions to optimize BTX production.Furthermore,the findings offer valuable insights for the design and operation of industrial hydrocracking processes aimed at efficiently converting coal tar-derived hydrorefined feedstock into BTX.
基金Funded by the National Natural Science Foundation of China(No.51975540)。
文摘In order to improve the sealing surface performance of gray cast iron gas gate valves and achieve precise molding control of the cladding layer,as well as to reveal the influence of laser cladding process parameters on the morphology and structure of the cladding layer,we prepared the 316L coating on HT 200 by using Design-Expert software central composite design(CCD)based on response surface analysis.We built a regression prediction model and analyzed the ANOVA with the inspection results.With a target cladding layer width of 3.5 mm and height of 1.3 mm,the process parameters were optimized to obtain the best combination of process parameters.The microstructure,phases,and hardness variations of the cladding layer from experiments with optimal parameters were analyzed by the metallographic microscope,confocal microscope,and microhardness instrument.The experimental results indicate that laser power has a significant impact on the cladding layer width,followed by powder feed rate;scan speed has a significant impact on the cladding layer height,followed by powder feed rate.The HT200 substrate and 316L can metallurgically bond well,and the cladding layer structure consists of dendritic crystals,columnar crystals,and equiaxed crystals in sequence.The optimal process parameter combination satisfying the morphology requirements is laser power(A)of 1993 W,scan speed(B)of 8.949 mm/s,powder feed rate(C)of 1.408 r/min,with a maximum hardness of 1564.3 HV0.5,significantly higher than the hardness of the HT200 substrate.
