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Dehydroaromatization of methane and methane co-aromatization process with propane:Reaction mechanism,catalyst design,carbon deposition and process optimization 认领 引用
1
作者 Yu Gu Shujia Zhang +4 位作者 Minglu Xu Hao Yan Minghao Zhou Lei Wang Hui Shi 《Chinese Journal of Catalysis》 SCIE EI CAS CSCD 2026年第5期25-60,共36页
Natural gas,as a fossil energy source,possesses abundant reserves in nature.It is cleaner and more environmentally benign compared to coal and crude oil.Converting natural gas via catalytic routes into more valuable c... Natural gas,as a fossil energy source,possesses abundant reserves in nature.It is cleaner and more environmentally benign compared to coal and crude oil.Converting natural gas via catalytic routes into more valuable chemicals,such as benzene and methanol,can both reduce the transportation costs of natural gas and increase the supply of commodity chemicals.It also serves as a significant supplement to the current petrochemical industry,holding broad application prospects.The aromatization reaction of methane is a critical technique in the methane conversion pathway,in which aromatics like benzene,toluene,and naphthalene can be produced via high-temperature dehydrogenation.Such a process has drawn significant research attention over the past three decades.This paper attempts to provide a detailed introduction to the development of research on this reaction.By examining various aspects including reaction thermodynamics,catalyst composition,reaction intermediates/mechanism,coke properties,anti-coking measures and process intensification,it aims to offer readers a comprehensive understanding of this reaction.Additionally,by discussing the co-aromatization of methane with higher hydrocarbons like propane,it tries to expand the cognitive boundaries related to methane aromatization reactions,thereby tending to offer deeper insights into the aromatization process of feedstock with compositions similar to real natural gas.In the end,the current research status in the field of methane aromatization is summarized,and future research directions are outlined as well. 展开更多
关键词 Methane dehydroaromatization Methane propane co-aromatization Catalyst design Reaction mechanism Coke Process optimization
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Ensemble learning-assisted inverse design and closed-loop process optimization for smoothing by spectral dispersion gratings 认领 引用
2
作者 Yixin Liu Yunxia Jin +6 位作者 Yuxiang Qiu Yuxing Han Rui Wang Lingjie Yu Yibing Zhang Hongchao Cao Jianda Shao 《Advanced Photonics Nexus》 CSCD 2026年第5期211-224,共14页
To address the challenge of complex mapping between process parameters and optical performance in smoothing by spectral dispersion(SSD)gratings,we propose an inverse design and process optimization framework based on ... To address the challenge of complex mapping between process parameters and optical performance in smoothing by spectral dispersion(SSD)gratings,we propose an inverse design and process optimization framework based on ensemble learning.By constructing a weighted-average ensemble learning model,this framework establishes a complete mapping chain of“target performance–predicted structure–executable process,”realizing a closed-loop optimization workflow of“design–prediction–fabrication–verification.”The coefficient of determination for its structural parameter predictions is above 0.955,with a mean absolute error of less than 0.85%.Through systematic comparison of the correlations between model predictions and measured data,we confirm that the framework captures genuine dependencies among process parameters,providing further insights for achieving more reliable process mapping.Experimental validation shows that SSD gratings fabricated based on this framework exhibit a deviation of less than 1.5%between the measured diffraction efficiency and the design target.We not only verify the effectiveness of the closed-loop optimization workflow but also mark a paradigm shift in process development from empirical trial-and-error to data-driven intelligent design.The validated interpretable inverse design framework provides a pathway for the intelligent and controllable fabrication of gratings and other micro-nano optical components. 展开更多
关键词 machine learning ensemble learning smoothing by spectral dispersion grating process optimization framework
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Research on Construction Process Optimization and Cost Control in Building Projects 认领 引用
3
作者 LIU Dehua 《外文科技期刊数据库（文摘版）工程技术》 2026年第2期124-128,共5页
This article focuses on construction process optimization and project cost control, delving into how improved construction techniques and technological innovations can facilitate effective cost management in building ... This article focuses on construction process optimization and project cost control, delving into how improved construction techniques and technological innovations can facilitate effective cost management in building projects. It elaborates on the fundamental concepts and key components of construction processes, analyzes the constituent elements of project costs and their core management objectives, while comprehensively explaining how construction technology levels decisively influence project expenses. The study also examines common cost control challenges in current practices—such as low material efficiency due to outdated methods, project delays and labor waste caused by suboptimal workflow designs, and hidden costs resulting from inadequate site management. To address these issues, the paper proposes concrete solutions including proactive adoption of eco-friendly construction technologies and advanced materials, rational adjustments to construction workflows and site layouts, and full utilization of information-based tools like BIM for precision management. To ensure sustained cost-reduction benefits from these optimizations, the article outlines detailed implementation measures: enhancing employee training and technical briefings, establishing end-to-end cost monitoring systems, strictly enforcing standardized procedures, and strengthening inspection and evaluation mechanisms. This work provides valuable theoretical foundations and practical guidance for construction enterprises to elevate operational efficiency and achieve superior economic outcomes. 展开更多
关键词 Construction process optimization Cost control BIM technology Green construction Project management
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Research on Process Optimization and Quality Control of Oral Tablets 认领 引用
4
作者 Chao Zhou Jin Yang +2 位作者 Qihong Chen Jun Qi Yu Wang 《Journal of Clinical and Nursing Research》 2026年第5期321-327,共7页
Oral tablets are the most widely used solid dosage form in clinical practice with the highest patient compliance.Their preparation process and quality control directly affect the safety and efficacy of medicines.This ... Oral tablets are the most widely used solid dosage form in clinical practice with the highest patient compliance.Their preparation process and quality control directly affect the safety and efficacy of medicines.This paper conducts an in-depth study on the process optimization and quality control of oral tablets,analyzes the key problems in quality control,and proposes practical optimization and control strategies.It aims to provide a reference for improving the production quality of oral tablets. 展开更多
关键词 Oral tablets Process optimization Quality control
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Synergistic performance and yield improvement of embedded RRAM product through process optimization in 40 nm CMOS platform 认领 引用
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作者 Zhenchao Sui Yanqing Wu +1 位作者 Zhichao Lv Xing Zhang 《Journal of Semiconductors》 EI CAS CSCD 2026年第3期65-71,共7页
To address the challenges of complexity,power consumption,and cost constraints in traditional display driver integrated circuits(DDICs)caused by external NOR Flash and SRAM,this work proposes an embedded resistive ran... To address the challenges of complexity,power consumption,and cost constraints in traditional display driver integrated circuits(DDICs)caused by external NOR Flash and SRAM,this work proposes an embedded resistive random-access memory(RRAM)integration solution based on a 40 nm high-voltage CMOS logic platform.Targeting the yield fluctuations and stability challenges during RRAM mass production,systematic process optimizations are implemented to achieve synergistic improvements in RRAM performance and yield.Through modifications to the film sputtering and pre-deposition treatment,the withinwafer resistance uniformity(RSU)of the oxygen-deficient layer(ODL)thin film is improved from 11%to 8%,while inter-wafer process stability variation reduces from 23%to below 6%.Consequently,the yield of 8 Mb RRAM embedded mass production products increases from 87%to 98.5%.In terms of device performance,the RRAM demonstrates a fast 4.8 ns read speed,exceptional read disturb immunity of 3×108 cycles at 95℃,103 write/erase endurance cycles for the 1 Mb cells,and data retention of 12.5 years at 125℃.Post high-temperature operating life(HTOL)testing exhibits stable high/low resistance window.This study provides process optimization strategies and a reliability assurance framework for the mass production of highly integrated,low-power embedded RRAM display driver IC. 展开更多
关键词 embedded RRAM 40 nm CMOS display driver IC process uniformity optimization yield improvement
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Research Progress on Process Optimization and Performance Control of Additive Manufacturing for Refractory Metals 认领 引用
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作者 Lu Durui Song Suocheng Lu Bingheng 《稀有金属材料与工程》 SCIE EI CAS CSCD 北大核心 2026年第2期345-364,共20页
Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durabili... Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durability,and corrosion resistance.These metals have body-centered cubic crystal structure,characterized by limited slip systems and impeded dislocation motion,resulting in significant low-temperature brittleness,which poses challenges for the conventional processing.Additive manufacturing technique provides an innovative approach,enabling the production of intricate parts without molds,which significantly improves the efficiency of material usage.This review provides a comprehensive overview of the advancements in additive manufacturing techniques for the production of refractory metals,such as W,Ta,Mo,and Nb,particularly the laser powder bed fusion.In this review,the influence mechanisms of key process parameters(laser power,scan strategy,and powder characteristics)on the evolution of material microstructure,the formation of metallurgical defects,and mechanical properties were discussed.Generally,optimizing powder characteristics,such as sphericity,implementing substrate preheating,and formulating alloying strategies can significantly improve the densification and crack resistance of manufactured parts.Meanwhile,strictly controlling the oxygen impurity content and optimizing the energy density input are also the key factors to achieve the simultaneous improvement in strength and ductility of refractory metals.Although additive manufacturing technique provides an innovative solution for processing refractory metals,critical issues,such as residual stress control,microstructure and performance anisotropy,and process stability,still need to be addressed.This review not only provides a theoretical basis for the additive manufacturing of high-performance refractory metals,but also proposes forward-looking directions for their industrial application. 展开更多
关键词 refractory metals additive manufacturing mechanical properties microstructure evolution optimization of printing process
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A novel wire arc additive and subtractive hybrid manufacturing process optimization method 认领 引用
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作者 GUO Yiming ZHANG Wanyuan +2 位作者 XIAO Mingkun SONG Shida ZHANG Xiaoyong 《Journal of Southeast University(English Edition)》 EI CAS 2025年第1期109-117,共9页
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
关键词 wire arc additive manufacturing hybrid manufacturing process optimization manufacturability
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Reaction process optimization based on interpretable machine learning and metaheuristic optimization algorithms 认领 引用 被引量：1
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作者 Dian Zhang Bo Ouyang Zheng-Hong Luo 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2025年第8期77-85,共9页
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
关键词 Reaction process optimization Interpretable machine learning Metaheuristic optimization algorithm Biodiesel
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Process Optimization,Microstructure Characterization,and Mechanical Properties of Al-Mg-Sc-Zr alloys Prepared via Laser Powder Bed Fusion 认领 引用 被引量：4
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作者 Yunfei Nie Haibin Wu +6 位作者 Qian Tang Hao Yi Changliang Qin Binsheng Wang Zhonghua Li Kun Li Quanquan Han 《Additive Manufacturing Frontiers》 CSCD 2025年第1期136-146,共11页
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 Al3(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
关键词 Laser powder bed fusion Al-Mg-Sc-Zr alloy Processing optimization Microstructure characterization Mechanical properties
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Vacuum ammonia stripping from liquid digestate:Effects of pH,alkalinity,temperature,negative pressure and process optimization 认领 引用
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作者 Qiuhong Chen Donghai Yang +3 位作者 Xiang Chen Xiankai Wang Bin Dong Xiaohu Dai 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2025年第3期638-650,共13页
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
关键词 Liquid digestate Vacuum ammonia stripping Alkalinity Mass transfer Process optimization
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Machine learning application in thermal CO2 hydrogenation:catalyst design,process optimization,and mechanism insights 认领 引用
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作者 Rasoul Salami Tianlong Liu +1 位作者 Xue Han Ying Zheng 《Advanced Powder Materials》 EI CAS CSCD 2025年第6期1-40,共40页
The growing demand for carbon neutrality has heightened the focus on CO2hydrogenation as a viable strategy for transforming carbon dioxide into valuable chemicals and fuels.Advanced machine learning(ML)approaches i... The growing demand for carbon neutrality has heightened the focus on CO2hydrogenation as a viable strategy for transforming carbon dioxide into valuable chemicals and fuels.Advanced machine learning(ML)approaches integrate materials science with artificial intelligence,enabling scientists to identify hidden patterns in datasets,make informed decisions,and reduce the need for labor-intensive,repetitive experimentation.This review provides a comprehensive overview of ML applications in the thermocatalytic hydrogenation of CO2.Following an introduction to ML tools and workflows,various ML algorithms employed in CO2hydrogenation are systematically categorized and reviewed.Next,the application of ML in catalyst discovery is discussed,highlighting its role in identifying optimal compositions and structures.Then,ML-driven strategies for process optimization,particularly in enhancing CO2conversion and product selectivity,are examined.Studies modeling descriptors,spanning catalyst properties and reaction conditions,to predict catalytic performance are analyzed.Consequently,ML-based mechanistic studies are reviewed to elucidate reaction pathways,identify key intermediates,and optimize catalyst performance.Finally,key challenges and future perspectives in leveraging ML for advancing CO2hydrogenation research are presented. 展开更多
关键词 CO2hydrogenation Machine learning Catalyst discovery Process optimization Reaction mechanisms Algorithms Descriptors
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Drying Characteristics and Process Optimization of Banana Slices Using Hot Air-Infrared Combined Drying 认领 引用
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作者 Guofeng Han Chenxi Luo +4 位作者 Xin Liu Yuanyuan Li Yuling Cheng Shuai Huang Dan Huang 《Frontiers in Heat and Mass Transfer》 EI CAS 2025年第6期1981-1999,共19页
Bananas are highly perishable after harvest,and processing them into dried products is a crucial approach to reducing losses and adding their economic values.To address the inefficiency and prolonged duration of tradi... Bananas are highly perishable after harvest,and processing them into dried products is a crucial approach to reducing losses and adding their economic values.To address the inefficiency and prolonged duration of traditional hot air drying(HAD)and the quality inconsistency associated with single infrared drying(IRD),this study proposed a novel hot air-infrared combined drying(HAD-IRD)strategy.The effects of HAD,IRD,and HAD-IRD on the drying kinetics,color,rehydration capacity,moisture diffusion mechanism,and sensory quality of banana slices were systematically investigated.The parameters of the combined drying process were optimized using an L9(33)orthogonal experimental design.Results indicated that both IRD and HAD-IRD significantly reduced drying time compared to single HAD.While single IRD achieved a rapid drying rate,the lack of effective convective airflow led to potential case-hardening and unstable product quality.In contrast,the HAD-IRD strategy demonstrated a synergistic effect.The optimal parameters were determined as follows:hot air temperature of 70℃,infrared temperature of 60℃,and radiation distance of 16 cm.Under these optimized conditions,HAD-IRD reduced the total drying time by over 70%while simultaneously yielding products with superior color,higher sensory scores,and improved rehydration ratio.This study confirms that HAD-IRD is an efficient and high-quality drying method for banana slices,providing a reliable theoretical foundation and technical solution for the drying of thermosensitive fruits. 展开更多
关键词 Banana slices hot air drying(HAD) infrared drying(IRD) combined drying process optimization product quality
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Research Progress on the Process Optimization and Stability Improvement of Third-generation Cephalosporins 认领 引用
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作者 Hao LIU Yanxi LAI +1 位作者 Shengjiu GU Kaimei ZHU 《Medicinal Plant》 2025年第1期23-26,共4页
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
关键词 Third-generation cephalosporins Process optimization Nanotechnology Green chemistry Drug stability
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Understanding melt pool characteristics in laser powder bed fusion:An overview of single-and multi-track melt pools for process optimization 认领 引用 被引量：47
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作者 Jincheng Wang Rui Zhu +1 位作者 Yujing Liu Laichang Zhang 《Advanced Powder Materials》 2023年第4期73-113,共41页
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
关键词 Additive manufacturing Laser powder bed fusion Single track Multi track melt pool Selective laser melting Process optimization Powder feedstock Simulation Temperature gradient Defect formation
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Current advances for omics-guided process optimization of microbial manufacturing 认领 引用 被引量：5
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作者 Shengtong Wan Xin Liu +2 位作者 Wentao Sun Bo Lv Chun Li 《Bioresources and Bioprocessing》 SCIE EI 2023年第1期985-1002,共18页
Currently,microbial manufacturing is widely used in various fields,such as food,medicine and energy,for its advantages of greenness and sustainable development.Process optimization is the committed step enabling the c... Currently,microbial manufacturing is widely used in various fields,such as food,medicine and energy,for its advantages of greenness and sustainable development.Process optimization is the committed step enabling the commercialization of microbial manufacturing products.However,the present optimization processes mainly rely on experience or trial-and-error method ignoring the intrinsic connection between cellular physiological requirement and production performance,so in many cases the productivity of microbial manufacturing could not been fully exploited at economically feasible cost.Recently,the rapid development of omics technologies facilitates the comprehensive analysis of microbial metabolism and fermentation performance from multi-levels of molecules,cells and microenvironment.The use of omics technologies makes the process optimization more explicit,boosting microbial manufacturing performance and bringing significant economic benefits and social value.In this paper,the traditional and omics technologies-guided process optimization of microbial manufacturing are systematically reviewed,and the future trend of process optimization is prospected. 展开更多
关键词 Microbial manufacturing Omics Process optimization Fermentation performance
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From statistical analysis to process optimization during cladding using a Nd:YAG laser 认领 引用 被引量：6
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作者 Ya Wei Pathiraj B. Yu Xinghua 《China Welding》 CAS 2022年第4期7-22,共16页
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(Pl),cladding speed(vc),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
关键词 laser cladding statistical model process optimization clad geometry dilution powder efficiency
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MICROSTRVCTURE SIMULATION AND PROCESS OPTIMIZATION OF TURBINE BLADE CASTINGS 认领 引用 被引量：4
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作者 D.Z.Li Z.Y.Hu +1 位作者 Q.Li Y.Y.Li 《Acta Metallurgica Sinica(English Letters)》 EI CAS 1998年第5期383-390,共8页
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
关键词 Probabilistic modeling microstructure process optimization
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Process Optimization of RTS Technology for Ultra-Low Sulfur Diesel 认领 引用 被引量：1
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作者 Ge Panzhu Ding Shi +3 位作者 Xi Yuanbing Zhang Le Nie Hong Li Dadong 《China Petroleum Processing & Petrochemical Technology》 SCIE CAS 2021年第3期104-111,共8页
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
关键词 RTS technology nitrogen compound polycyclic aromatic hydrocarbons catalyst deactivation process optimization
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Process Optimization for AZ91 Mg-alloy Low-pressure EPC Process 认领 引用 被引量：5
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作者 吴和保 《Journal of Wuhan University of Technology(Materials Science)》 SCIE EI CAS 2005年第2期42-44,共3页
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
关键词 magnesium alloy low-pressure casting expandable pattern casting process optimization
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Heat treatment process optimization for face gears based on deformation and residual stress control 认领 引用 被引量：1
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作者 王延忠 兰州 +2 位作者 HOU Liang-wei ZHAO Hong-pu ZHONG Yang 《Journal of Chongqing University》 2015年第1期9-18,共10页
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
关键词 face gear carburizing and quenching deformation residual stress process optimization
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