Phase-Based Optical Flow Method with Optimized Parameter Settings for Enhancing Displacement Measurement Adaptability

To enhance the applicability and measurement accuracy of phase-based optical flow method using complex steerable pyramids in structural displacement measurement engineering applications, an improved method of optimizing parameter settings is proposed. The optimized parameters include the best measurement points of the Region of Interest (ROI) and the levels of pyramid filters. Additionally, to address the issue of updating reference frames in practical applications due to the difficulty in estimating the maximum effective measurement value, a mechanism for dynamically updating reference frames is introduced. Experimental results demonstrate that compared to representative image gradient-based displacement measurement methods, the proposed method exhibits higher measurement accuracy in engineering applications. This provides reliable data support for structural damage identification research based on vibration signals and is expected to broaden the engineering application prospects for structural health monitoring.

Process Parameters Optimization of Laser Cladding for HT200 with 316L Coating Based on Response Surface Method

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.

Optimization Study of Active-Passive Heating System Parameters in Village Houses in the Southern Xinjiang Province

Aiming at the problems of large energy consumption and serious pollution of winter heating existing in the rural buildings in Southern Xinjiang,a combined active-passive heating system was proposed,and the simulation software was used to optimize the parameters of the system,according to the parameters obtained from the optimization,a test platform was built and winter heating test was carried out.The simulation results showed that the thickness of the air layer of 75 mm,the total area of the vent holes of 0.24 m^(2),and the thickness of the insulation layer of 120 mm were the optimal construction for the passive part;solar collector area of 28 m^(2),hot water storage tank volume of 1.4 m^(3),mass flow rate of 800 kg/h on the collector side,mass flow rate of 400 kg/h on the heat exchanger side,and output power of auxiliary heat source of 5∼9 kWwere the optimal constructions for active heating system.Test results showed that during the heating period,the system could provide sufficient heat to the room under different heating modes,and the indoor temperature reached over 18°C,which met the heating demand.The economic and environmental benefits of the system were analyzed,and the economic benefits of the systemwere better than coal-fired heating,and the CO_(2) emissionswere reduced by 3,292.25 kg compared with coalfiredheating.The results of the study showed that the combinedactive-passiveheating systemcouldeffectively solve the heating problems existing in rural buildings in Southern Xinjiang,and it also laid the theoretical foundation for the popularization of the combined heating systems.

Interpretable machine learning optimization(InterOpt)for operational parameters:A case study of highly-efficient shale gas development

An algorithm named InterOpt for optimizing operational parameters is proposed based on interpretable machine learning,and is demonstrated via optimization of shale gas development.InterOpt consists of three parts:a neural network is used to construct an emulator of the actual drilling and hydraulic fracturing process in the vector space(i.e.,virtual environment);:the Sharpley value method in inter-pretable machine learning is applied to analyzing the impact of geological and operational parameters in each well(i.e.,single well feature impact analysis):and ensemble randomized maximum likelihood(EnRML)is conducted to optimize the operational parameters to comprehensively improve the efficiency of shale gas development and reduce the average cost.In the experiment,InterOpt provides different drilling and fracturing plans for each well according to its specific geological conditions,and finally achieves an average cost reduction of 9.7%for a case study with 104 wells.

Review of Design of Process Parameters for Squeeze Casting

Squeeze casting(SC)is an advanced net manufacturing process with many advantages for which the quality and properties of the manufactured parts depend strongly on the process parameters.Unfortunately,a universal efficient method for the determination of optimal process parameters is still unavailable.In view of the shortcomings and development needs of the current research methods for the setting of SC process parameters,by consulting and analyzing the recent research literature on SC process parameters and using the CiteSpace literature analysis software,manual reading and statistical analysis,the current state and characteristics of the research methods used for the determination of SC process parameters are summarized.The literature data show that the number of pub-lications in the literature related to the design of SC process parameters generally trends upward albeit with signifi-cant fluctuations.Analysis of the research focus shows that both“mechanical properties”and“microstructure”are the two main subjects in the studies of SC process parameters.With regard to materials,aluminum alloys have been extensively studied.Five methods have been used to obtain SC process parameters:Physical experiments,numeri-cal simulation,modeling optimization,formula calculation,and the use of empirical values.Physical experiments are the main research methods.The main methods for designing SC process parameters are divided into three categories:Fully experimental methods,optimization methods that involve modeling based on experimental data,and theoreti-cal calculation methods that involve establishing an analytical formula.The research characteristics and shortcomings of each method were analyzed.Numerical simulations and model-based optimization have become the new required methods.Considering the development needs and data-driven trends of the SC process,suggestions for the develop-ment of SC process parameter research have been proposed.

Pulsed gas–liquid discharge plasma catalytic degradation of bisphenol A over graphene/Cd S:process parameters optimization and O_(3)activation mechanism analysis

In the present work,pulsed gas–liquid hybrid discharge plasma coupled with graphene/Cd S catalyst was evaluated to eliminate bisphenol A(BPA)in wastewater.The optimization of a series of process parameters was performed in terms of BPA degradation performance.The experimental results demonstrated that nearly 90%of BPA(20 mg l^(-1))in the synthetic wastewater(p H=7.5,σ=10μS m^(-1))was degraded by the plasma catalytic system over 0.2 g l^(-1)graphene/Cd S at 19k V with a 4 l min^(-1)air flow rate and 10 mm electrode gap within 60 min.The BPA removal rate increased with increasing the discharge voltage and decreasing the initial BPA concentration or solution conductivity.Nevertheless,either too high or too low an air flow rate,electrode gap,catalyst dosage or initial solution p H would lead to a decrease in BPA degradation.Moreover,optical emission spectroscopy was used to gain information on short-lived reactive species formed from the pulsed gas–liquid hybrid discharge plasma system.The results indicated the existence of several highly oxidative free radicals such as·O and·OH.Finally,the activation pathway of O_(3)on the catalyst surface was analyzed by density functional theory.

Hot-deformation kinetics analysis and extrusion parameter optimization of a dilute rare-earth free magnesium alloy

The fundamental research on thermo-mechanical conditions provides an experimental basis for high-performance Mg-Al-Ca-Mn alloys.However, there is a lack of systematical investigation for this series alloys on the hot-deformation kinetics and extrusion parameter optimization. Here, the flow behavior, constitutive model, dynamic recrystallization(DRX) kinetic model and processing map of a dilute rare-earth free Mg-1.3Al-0.4Ca-0.4Mn(AXM100, wt.%) alloy were studied under different hot-compressive conditions. In addition, the extrusion parameter optimization of this alloy was performed based on the hot-processing map. The results showed that the conventional Arrhenius-type strain-related constitutive model only worked well for the flow curves at high temperatures and low strain rates. In comparison, using the machine learning assisted model(support vector regression, SVR) could effectively improve the accuracy between the predicted and experimental values. The DRX kinetic model was established, and a typical necklace-shaped structure preferentially occurred at the original grain boundaries and the second phases. The DRX nucleation weakened the texture intensity, and the further growth caused the more scattered basal texture. The hot-processing maps at different strains were also measured and the optimal hot-processing range could be confirmed at the deformation temperatures of 600~723 K and the strain rates of 0.018~0.563 s^(-1). Based on the optimum hot-processing range, a suitable extrusion parameter was considered as 603 K and 0.1 mm/s and the as-extruded alloy in this parameter exhibited a good strength-ductility synergy(yield strength of ~ 232.1 MPa, ultimate strength of ~ 278.2 MPa and elongation-to-failure of ~ 20.1%). Finally, the strengthening-plasticizing mechanisms and the relationships between the DRXed grain size, yield strength and extrusion parameters were analyzed.

Investigation of influence factors on CO_(2) flowback characteristics and optimization of flowback parameters during CO_(2) dry fracturing in tight gas reservoirs

CO_(2) dry fracturing is a promising alternative method to water fracturing in tight gas reservoirs,especially in water-scarce areas such as the Loess Plateau.The CO_(2) flowback efficiency is a critical factor that affects the final gas production effect.However,there have been few studies focusing on the flowback characteristics after CO_(2) dry fracturing.In this study,an extensive core-to-field scale study was conducted to investigate CO_(2) flowback characteristics and CH_(4) production behavior.Firstly,to investigate the impact of core properties and production conditions on CO_(2) flowback,a series of laboratory experiments at the core scale were conducted.Then,the key factors affecting the flowback were analyzed using the grey correlation method based on field data.Finally,taking the construction parameters of Well S60 as an example,a dual-permeability model was used to characterize the different seepage fields in the matrix and fracture for tight gas reservoirs.The production parameters after CO_(2) dry fracturing were then optimized.Experimental results demonstrate that CO_(2) dry fracturing is more effective than slickwater fracturing,with a 9.2%increase in CH_(4) recovery.The increase in core permeability plays a positive role in improving CH_(4) production and CO_(2) flowback.The soaking process is mainly affected by CO_(2) diffusion,and the soaking time should be controlled within 12 h.Increasing the flowback pressure gradient results in a significant increase in both CH_(4) recovery and CO_(2) flowback efficiency.While,an increase in CO_(2) injection is not conducive to CH_(4) production and CO_(2) flowback.Based on the experimental and field data,the important factors affecting flowback and production were comprehensively and effectively discussed.The results show that permeability is the most important factor,followed by porosity and effective thickness.Considering flowback efficiency and the influence of proppant reflux,the injection volume should be the minimum volume that meets the requirements for generating fractures.The soaking time should be short which is 1 day in this study,and the optimal bottom hole flowback pressure should be set at 10 MPa.This study aims to improve the understanding of CO_(2) dry fracturing in tight gas reservoirs and provide valuable insights for optimizing the process parameters.

Optimal Structural Parameters for a Plastic Centrifugal Pump Inducer

The aim of the study is to determine the optimal structural parameters for a plastic centrifugal pump inducer within the framework of an orthogonal experimental method.For this purpose,a numerical study of the related flow field is performed using CFX.The shaft power and the head of the pump are taken as the evaluation indicators.Accordingly,the examined variables are the thickness(S),the blade cascade degree(t),the blade rim angle(β1),the blade hub angle(β2)and the hub length(L).The impact of each structural parameter on each evaluation index is examined and special attention is paid to the following combinations:S2 mm,t 2,β1235°,β2360°and L 140 mm(corresponding to a maximum head of 98.15 m);S 5 mm,t 1.6,β1252°,β2350°and L 140 mm(corresponding to a minimum shaft power of 63.06 KW).Moreover,using least squares and fish swarm algorithms,the pump shaft power and head are further optimized,yielding the following optimal combination:S 5 mm,t 1.9,β1252°,β2360°and L 145 mm(corresponding to the maximum head of 91.90 m,and a minimum shaft power of 64.83 KW).

Fracture propagation,proppant transport and parameter optimization of multi-well pad fracturing treatment

This paper establishes a 3D multi-well pad fracturing numerical model coupled with fracture propagation and proppant migration based on the displacement discontinuity method and Eulerian-Eulerian frameworks,and the fracture propagation and proppant distribution during multi-well fracturing are investigated by taking the actual multi-well pad parameters as an example.Fracture initiation and propagation during multi-well pad fracturing are jointly affected by a variety of stress interference mechanisms such as inter-cluster,inter-stage,and inter-well,and the fracture extension is unbalanced among clusters,asymmetric on both wings,and dipping at heels.Due to the significant influence of fracture morphology and width on the migration capacity of proppant in the fracture,proppant is mainly placed in the area near the wellbore with large fracture width,while a high-concentration sandwash may easily occur in the area with narrow fracture width as a result of quick bridging.On the whole,the proppant placement range is limited.Increasing the well-spacing can reduce the stress interference of adjacent wells and promote the uniform distribution of fractures and proppant on both wings.The maximum stimulated reservoir volume or multi-fracture uniform propagation can be achieved by optimizing the well spacing.Although reducing the perforation-cluster spacing also can improve the stimulated reservoir area,a too low cluster spacing is not conducive to effectively increasing the propped fracture area.Since increasing the stage time lag is beneficial to reduce inter-stage stress interference,zipper fracturing produces more uniform fracture propagation and proppant distribution.

Leveraging Gradient-Based Optimizer and Deep Learning for Automated Soil Classification Model

Soil classification is one of the emanating topics and major concerns in many countries.As the population has been increasing at a rapid pace,the demand for food also increases dynamically.Common approaches used by agriculturalists are inadequate to satisfy the rising demand,and thus they have hindered soil cultivation.There comes a demand for computer-related soil classification methods to support agriculturalists.This study introduces a Gradient-Based Optimizer and Deep Learning(DL)for Automated Soil Clas-sification(GBODL-ASC)technique.The presented GBODL-ASC technique identifies various kinds of soil using DL and computer vision approaches.In the presented GBODL-ASC technique,three major processes are involved.At the initial stage,the presented GBODL-ASC technique applies the GBO algorithm with the EfficientNet prototype to generate feature vectors.For soil categorization,the GBODL-ASC procedure uses an arithmetic optimization algorithm(AOA)with a Back Propagation Neural Network(BPNN)model.The design of GBO and AOA algorithms assist in the proper selection of parameter values for the EfficientNet and BPNN models,respectively.To demonstrate the significant soil classification outcomes of the GBODL-ASC methodology,a wide-ranging simulation analysis is performed on a soil dataset comprising 156 images and five classes.The simulation values show the betterment of the GBODL-ASC model through other models with maximum precision of 95.64%.

Analysis of Additional Damping Control Strategy and Parameter Optimization for Improving Small Signal Stability of VSC-HVDC System

The voltage source converter based high voltage direct current(VSC-HVDC)system is based on voltage source converter,and its control system is more complex.Also affected by the fast control of power electronics,oscillation phenomenon in wide frequency domain may occur.To address the problem of small signal stability of the VSCHVDC system,a converter control strategy is designed to improve its small signal stability,and the risk of system oscillation is reduced by attaching a damping controller and optimizing the control parameters.Based on the modeling of the VSC-HVDC system,the general architecture of the inner and outer loop control of the VSCHVDC converter is established;and the damping controllers for DC control and AC control are designed in the phase-locked loop and the inner and outer loop control parts respectively;the state-space statemodel of the control system is established to analyze its performance.And the electromagnetic transient simulation model is built on the PSCAD/EMTDC simulation platform to verify the accuracy of the small signal model.The influence of the parameters of each control part on the stability of the system is summarized.The main control parts affecting stability are optimized for the phenomenon of oscillation due to changes in operation mode occurring on the AC side due to faults and other reasons,which effectively eliminates system oscillation and improves system small signal stability,providing a certain reference for engineering design.

Multi-objective optimization of process parameters for ultra-narrow gap welding based on Universal Kriging and NSGA Ⅱ

The successful confinement of the arc by the flux band depends on the welding process parameters for achieving single-pass,multi-layer, and ultra-narrow gap welding. The sidewall fusion depth, the width of the heat-affected zone, and the line energy are utilized as comprehensive indications of the quality of the welded joint. In order to achieve well fusion and reduce the heat input to the base metal.Three welding process characteristics were chosen as the primary determinants, including welding voltage, welding speed, and wire feeding speed. The metamodel of the welding quality index was built by the orthogonal experiments. The metamodel and NSGA-Ⅱ(Non-dominated sorting genetic algorithm Ⅱ) were combined to develop a multi-objective optimization model of ultra-narrow gap welding process parameters. The results showed that the optimized welding process parameters can increase the sidewall fusion depth, reduce the width of the heataffected zone and the line energy, and to some extent improve the overall quality of the ultra-narrow gap welding process.

Parameter Optimization of Intercalated Meltblown Nonwovens Based on NSGA-II

The preparation process parameters of intercalated meltblown nonwoven materials are complicated, and the relationship between process parameters, structural variables, and product performance needs to be investigated to establish a good mechanism for product performance regulation. In this study, we first used Wilcoxon test and Pearson correlation analysis to investigate the effect of intercalation rate on structural variables and product performance. Then, regression models were constructed to predict the values of each structural variable under different combinations of process parameters. Finally, we constructed a multi-objective constrained optimization problem based on the stepwise regression model and the product variable conditions. The problem was solved using the NSGA-II algorithm. The optimal was achieved when the acceptance distance was 2.892 cm and the hot air speed was 2000 r/min.

Simulation Research on the Effect of Spreading Process Parameters on the Quality of Lunar Regolith Powder Bed in Additive Manufacturing

Lunar surface additive manufacturing with lunar regolith is a key step in in-situ resource utilization.The powder spreading process is the key process,which has a major impact on the quality of the powder bed and the precision of molded parts.In this study,the discrete element method(DEM)was adopted to simulate the powder spreading process with a roller.The three powder bed quality indicators,including the molding layer offset,voidage fraction,and surface roughness,were established.Besides,the influence of the three process parameters,which are roller’s translational speed,rotational speed,and powder spreading layer thickness on the powder bed quality indicators was also analyzed.The results show that with the reduction of the powder spreading layer thickness and the increase of the rotational speed,the offset increased significantly;when the translational speed increased,the offset first increased and then decreased,which resulted in an extreme value;with the increase of the layer thickness and the decrease of the translational speed,the values for voidage fraction and surface roughness significantly reduced.The powder bed quality indicators were adopted as the optimization objective,and the multi-objective parameter optimization was carried out.The predicted optimal powder spreading parameters and powder bed quality indicators were then obtained.Moreover,the optimal values were then verified.This study can provide informative guidance for in-situ manufacturing at the moon in future deep space exploration missions.

High temperature deformation behavior and optimization of hot compression process parameters in TC11 titanium alloy with coarse lamellar original microstructure

The high temperature deformation behaviors of α＋β type titanium alloy TC11 （Ti-6.5Al-3.5Mo-1.5Zr-0.3Si） with coarse lamellar starting microstructure were investigated based on the hot compression tests in the temperature range of 950-1100 ℃ and the strain rate range of 0.001-10 s-1. The processing maps at different strains were then constructed based on the dynamic materials model, and the hot compression process parameters and deformation mechanism were optimized and analyzed, respectively. The results show that the processing maps exhibit two domains with a high efficiency of power dissipation and a flow instability domain with a less efficiency of power dissipation. The types of domains were characterized by convergence and divergence of the efficiency of power dissipation, respectively. The convergent domain in a＋fl phase field is at the temperature of 950-990 ℃ and the strain rate of 0.001-0.01 s^-1, which correspond to a better hot compression process window of α＋β phase field. The peak of efficiency of power dissipation in α＋β phase field is at 950 ℃ and 0.001 s 1, which correspond to the best hot compression process parameters of α＋β phase field. The convergent domain in β phase field is at the temperature of 1020-1080 ℃ and the strain rate of 0.001-0.1 s^-l, which correspond to a better hot compression process window of β phase field. The peak of efficiency of power dissipation in ℃ phase field occurs at 1050 ℃ over the strain rates from 0.001 s^-1 to 0.01 s^-1, which correspond to the best hot compression process parameters of ,8 phase field. The divergence domain occurs at the strain rates above 0.5 s^-1 and in all the tested temperature range, which correspond to flow instability that is manifested as flow localization and indicated by the flow softening phenomenon in stress-- strain curves. The deformation mechanisms of the optimized hot compression process windows in a＋β and β phase fields are identified to be spheroidizing and dynamic recrystallizing controlled by self-diffusion mechanism, respectively. The microstructure observation of the deformed specimens in different domains matches very well with the optimized results.

PROCESSING PARAMETER OPTIMIZATION OF FDM BASED ON ROBUST DESIGN

The influence of processing parameters on the precision of parts fabricated by fused deposition modeling （FDM） technology is studied based on a series of performed experiments. Processing parameters of FDM in terms of wire-width compensation, extrusion velocity, filing velocity, and layer thickness are chosen as the control fac- tors. Robust design analysis and multi-index fuzzy comprehensive assessment method are used to obtain the opti- mal parameters. Results show that the influencing degrees of these four factors on the precision of as-processed parts are different. The optimizations of individual parameters and their combined effects are of the same impor- tance for a high precision manufacturing.

Investigation on the Optimizing Range of CombustionChamber Configuration Parameters of DSCS

Aim To obtain an optimizing range of the main configuration parameters of double swirls combustion system (DSCS) Methods To analyze the influence of DS combustion cham-ber configuration parameters on fuel spray and mixing by means of the fuel jet developmentperiphery charts obtained by the high speed photography with a modeling test device deve-loped by authors,and to examine it by the tests on a single cylinder diesel engine.Resultsand Conclusion The mixing process can be divided into four phases.The optimizing range of the ration of the inner chamber diameter to the cylinder bore,d2/D,is 0.4-0.7; and the outerchamber diameter,d1 the height of the circular ridge to the piston top face,h1,the radius of outer/inner chamber circle,R1,R2 ,the max depth of outer/inner chamber bowl,H1,H2,etc. are also important

Application of EBSD technique to ultrafine grained and nanostructured materials processed by severe plastic deformation:Sample preparation, parameters optimization and analysis

With the help of FESEM, high resolution electron backscatter diffraction can investigate the grains/subgrains as small as a few tens of nanometers with a good angular resolution （~0.5°）. Fast development of EBSD speed （up to 1100 patterns per second） contributes that the number of published articles related to EBSD has been increasing sharply year by year. This paper reviews the sample preparation, parameters optimization and analysis of EBSD technique, emphasizing on the investigation of ultrafine grained and nanostructured materials processed by severe plastic deformation （SPD）. Detailed and practical parameters of the electropolishing, silica polishing and ion milling have been summarized. It is shown that ion milling is a real universal and promising polishing method for EBSD preparation of almost all materials. There exists a maximum value of indexed points as a function of step size. The optimum step size depends on the magnification and the board resolution/electronic step size. Grains/subgrains and texture, and grain boundary structure are readily obtained by EBSD. Strain and stored energy may be analyzed by EBSD.

Effects of vacuum magnetic field region on the compact torus trajectory in a tokamak plasma

The trajectory of the compact torus(CT)within a tokamak discharge is crucial to fueling.In this study,we developed a penetration model with a vacuum magnetic field region to accurately determine CT trajectories in tokamak discharges.This model was used to calculate the trajectory and penetration parameters of CT injections by applying both perpendicular and tangential injection schemes in both HL-2A and ITER tokamaks.For perpendicular injection along the tokamak's major radius direction from the outboard,CTs with the same injection parameters exhibited a 0.08 reduction in relative penetration depth when injected into HL-2A and a 0.13reduction when injected into ITER geometry when considering the vacuum magnetic field region compared with cases where this region was not considered.In addition,we proposed an optimization method for determining the CT's initial injection velocity to accurately calculate the initial injection velocity of CTs for central fueling in tokamaks.Furthermore,this paper discusses schemes for the tangential injection of CT into tokamak discharges.The optimal injection angle and CT magnetic moment direction for injection into both HL-2A and ITER were determined through numerical simulations.Finally,the kinetic energy loss occurring when the CT penetrated the vacuum magnetic field region in ITER was reduced byΔEk=975.08 J by optimizing the injection angle for the CT injected into ITER.These results provide valuable insights for optimizing injection angles in fusion experiments.Our model closely represents actual experimental scenarios and can assist the design of CT parameters.