In the current practice of multi-axis machining of freeform surfaces, the interface surface between the roughing and finishing process is simply an offset surface of the nominal surface. While there have already been ...In the current practice of multi-axis machining of freeform surfaces, the interface surface between the roughing and finishing process is simply an offset surface of the nominal surface. While there have already been attempts at minimizing the machining time by considering the kinematic capacities of the machine tool and/or the physical constraints such as the cutting force, they all target independently at either the finishing or the roughing process alone and are based on the simple premise of an offset interface surface. Conceivably, since the total machining time should count that of both roughing and finishing process and both of them crucially depend on the interface surface, it is natural to ask if, under the same kinematic capacities and the same physical constraints, there is a nontrivial interface surface whose corresponding total machining time will be the minimum among all the possible（infinite） choices of interface surfaces, and this is the motivation behind the work of this paper. Specifically, with respect to the specific type of iso-planar milling for both roughing and finishing, we present a practical algorithm for determining such an optimal interface surface for an arbitrary freeform surface. While the algorithm is proposed for iso-planar milling, it can be easily adapted to other types of milling strategy such as contour milling. Both computer simulation and physical cutting experiments of the proposed method have convincingly demonstrated its advantages over the traditional simple offset method.展开更多
The surface texture of mineral flotation froth is well acknowledged as an important index of the flotation process.The surface texture feature closely relates to the flotation working conditions and hence can be used ...The surface texture of mineral flotation froth is well acknowledged as an important index of the flotation process.The surface texture feature closely relates to the flotation working conditions and hence can be used as a visual indicator for the zinc fast roughing working condition. A novel working condition identification method based on the dual-tree complex wavelet transform(DTCWT) is proposed for process monitoring of zinc fast roughing.Three-level DTCWT is implemented to decompose the froth image into different directions and resolutions in advance, and then the energy parameter of each sub-image is extracted as the froth texture feature. Then, an improved random forest integrated classification(i RFIC) with 10-fold cross-validation model is introduced as the classifier to identify the roughing working condition, which effectively improves the shortcomings of the single model and overcomes the characteristic redundancy but achieves higher generalization performance. Extensive experiments have verified the effectiveness of the proposed method.展开更多
Based on the characteristics of ferritic SUS430 heating and deformation,and combined with the features of the 1780 mm hot-rolling mill,a roughing model was introduced in two aspects:optimizing the rough rolling passes...Based on the characteristics of ferritic SUS430 heating and deformation,and combined with the features of the 1780 mm hot-rolling mill,a roughing model was introduced in two aspects:optimizing the rough rolling passes and improving the width control precision.Through reducing the rough rolling passes,the rough rolling time can be shortened,the precision rolling startup temperature can be raised and the yield of the hot-rolled products can be increased.Moreover,on the premise that the slab width fluctuation was great,the precision of the width control can be improved through optimizing the parameters of the hot-rolling width control model.The result shows that the optimization and perfection of the original rolling process of the stainless steel 430 series further improved its capacity and product quality.展开更多
We report a method for increasing the mechanical strength of carbon nanotube(CNT)fibers while enabling the uniform adhesion of cerium oxide(CeO_(2))abrasive particles to them using polyethyleneimine(PEI).Results show ...We report a method for increasing the mechanical strength of carbon nanotube(CNT)fibers while enabling the uniform adhesion of cerium oxide(CeO_(2))abrasive particles to them using polyethyleneimine(PEI).Results show that 5%of PEI increases the tensile strength of CNT fibers by approximately 175%.CeO_(2) particles were uniformly deposited on the reinforced CNT fibers by electrophoretic deposition.A flexible polishing tool was fabricated by weaving the CeO_(2)-CNT fibers into a non-woven fabric substrate.When used to polish potassium dihydrogen phosphate crystals,the tool reduced the surface roughness from 200 to 7.6 nm within 10 min.This approach has potential use for the development of new precision processing tools.展开更多
Interfacial interactions between rough mineral particles have garnered considerable attention as they directly determine particle agglomeration and floatability.This study comprehensively investigates the agglomeratio...Interfacial interactions between rough mineral particles have garnered considerable attention as they directly determine particle agglomeration and floatability.This study comprehensively investigates the agglomeration characteristics of siderite particles after argon(Ar)plasma surface modification through settling tests,flocs size measurements,and fractal dimension calculations.Ar plasma surface modification promotes the agglomeration of siderite particles,as evidenced by increased floc size and density.The agglomeration mechanism induced by Ar plasma surface modification is evaluated using a theoretical model combining the surface element integration(SEI)approach,differential geometry,and the composite Simpson's rule.Changes in surface roughness,wettability,and charge are considered in this model.Compared to the unpretreated siderite particles,the energy barrier for interaction of the 30-min Ar plasma-pretreated siderite particles decreases from 2.3×10-^(17)J to 1.6×10^(-17)J.This reduction provides strong evidence for the agglomeration behavior of siderite particles.Furthermore,flotation experiments confirm that Ar plasma surface modification is conducive to the aggregation flotation of siderite.These findings offer crucial insights into particle aggregation and dispersion behaviors,with notable application in mineral flotation.展开更多
This study investigated surface roughness,the wettability behavior,and surface energy of Co-based alloy specimens textured using the biomimetic Laser Surface Texturing(LST)method.The surface texture was inspired by th...This study investigated surface roughness,the wettability behavior,and surface energy of Co-based alloy specimens textured using the biomimetic Laser Surface Texturing(LST)method.The surface texture was inspired by the patterns found on marine shells.The impacts of the parameters on wettability,Surface Free Energy(SFE),surface topography,and texture roughness generated by the laser beam tracking a spiral path were investigated.Reducing spiral pitch produces more complicated and chaotic surface patterns.Most surfaces are hydrophobic,and surface roughness and topography influence the Contact Angle(CA).Topography and roughness were affected by frequency and scanning speed;a decrease in scanning speed and frequency generated more chaotic and irregular surface textures.With general factorial analysis and Analysis of Variance(ANOVA),our statistical study reveals that accounting for 88%of the influence,the scanning speed is the primary factor influencing surface roughness.On the other hand,the spiral pitch is essential for defining the struc-tural features of the surface,even if it less influences roughness.The SFE of laser-textured CoCr28Mo alloy specimens was optimizable within the range of 14-32 mN/m.The relevant findings offer valuable insights into optimizing LST for the specific surface properties of the Co-based alloy.展开更多
Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogen...Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogeneity remains challenging.To address this,this study first captures the morphology of large-scale(1000 mm × 1000 mm) slate and granite joints via 3D laser scanning.Analysis of these surfaces and corresponding push/pull tests on carved specimens revealed a potential correlation between the heterogeneity of roughness and shear strength.A comparative evaluation of five statistical metrics identified information entropy(Hs) as the most robust indicator for quantifying rock joint heterogeneity.Further analysis using Hsreveals that the heterogeneity is anisotropic and,critically,that shear strength heterogeneity is governed not only by roughness heterogeneity but is also significantly influenced by the mean roughness value,normal stress,and intact rock tensile strength.Consequently,a simple comparison of roughness Hsvalues is insufficient for reliably comparing shear strength heterogeneity.To overcome this limitation,a theoretical framework is developed to explicitly map fundamental roughness statistics(mean and heterogeneity) to shear strength heterogeneity.This framework culminates in a practical workflow that allows for the rapid,field-based assessment of shear strength heterogeneity using readily obtainable rock joint roughness data.展开更多
Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sen...Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sensitive to long-wavelength(15–120 m)and lateral irregularities,which are often overlooked in traditional roughness models.This study aims to construct a three-dimensional runway roughness modeling framework integrating"precise detection-spectrum analysis-spatial reconstruction"in response to this issue.Combining the elevation data of 37 runways(5 asphalt runways and 32 cement runways)measured by a vehicle-mounted laser profilometer and the BeiDou positioning system,the power spectrum analysis was carried out by the Burg method and the spectrum models of asphalt and cement runways were fitted respectively.Meanwhile,a new exponential lateral coherence function was proposed.Finally,the three-dimensional spatial model was reconstructed by using the transfer function and genetic algorithm.The results show that the error of the measured elevation data is less than 1 cm.The spectral characteristics of different pavement types are significantly different.Among them,the R^(2) of the asphalt runway fitted with the Sussman model is greater than 0.9.The cement runway needs to be characterized by a piecewise function to represent the spectral mutation.The fitting error of the new index's lateral coherence function has been reduced to 0.012.The reconstructed three-dimensional model is in good agreement with the theoretical value and the error does not exceed 0.18 mm^(2) m/c.Finally,a three-dimensional model of 0–20 m in the lateral direction and 3000 m in the longitudinal direction is generated,providing support for aircraft vibration simulation and pavement maintenance.展开更多
Microbially induced calcium carbonate precipitation(MICP)is an eco-friendly technology for soil improvement.Although numerous experiments have been conducted to solidify sand foundations using MICP,the mechanisms by w...Microbially induced calcium carbonate precipitation(MICP)is an eco-friendly technology for soil improvement.Although numerous experiments have been conducted to solidify sand foundations using MICP,the mechanisms by which grain interfacial morphologies influencethe MICP process remain unclear.This study utilized 3D-printed flowcells with different boundary morphologies to investigate the effects of interfacial morphologies on the MICP process.CaCO_(3)precipitation characteristics were investigated through microscopic observation and image quantificationanalysis.The results indicate that low flowvelocities near the interface promote bacterial accumulation due to reduced hydrodynamic shear forces.Rough interfaces,compared to smooth ones,enhance bacterial adsorption owing to the larger regions of low flowvelocity,increased surface area,and the formation of local eddies,which promote greater CaCO_(3)precipitation.Compared to the regions away from the interface,a higher abundance of small CaCO_(3)crystals is observed near the interface because of the high urease activity from bacteria and the reduced shear-induced entrainment due to the low flowvelocity.Besides,larger crystals also preferentially precipitate in proximity to interfaces as the low flowvelocity enhances crystal growth according to the particle attachment theory.The presence of rough interfaces further reduces flowvelocities,leading to the precipitation of larger and more densely packed CaCO_(3)crystals.Therefore,rough interfaces promote the microbially induced calcium carbonate precipitation.This work is expected to enhance the understanding of microbially induced calcium carbonate precipitation characteristics on solid surfaces such as soil grains and contribute to the optimization of MICP applications.展开更多
Hack and slash your way to a delectable West China dish谁说美食必须精致?新疆大盘鸡的灵魂就是粗放You’ve driven 300 miles over the endless Gobi desert without a sign of life in any direction.The sun sets as the heat of...Hack and slash your way to a delectable West China dish谁说美食必须精致?新疆大盘鸡的灵魂就是粗放You’ve driven 300 miles over the endless Gobi desert without a sign of life in any direction.The sun sets as the heat of the day cools into night.Then you see,in the middle of nowhere,a small restaurant by the highway.You enter with a gust of wind and sand whirling around your boots like a Wild West movie,and say展开更多
Surface morphologies and microstructures of C 60 /Ag composite films were studied by atomic force microscope (AFM) and transmission electron microscope (TEM). The surface roughness depended on the substrate temperatur...Surface morphologies and microstructures of C 60 /Ag composite films were studied by atomic force microscope (AFM) and transmission electron microscope (TEM). The surface roughness depended on the substrate temperature, and the transition of surface morphology of rough→smooth→rough was observed when the substrate temperature increased from -50 to 120℃. Although the rms values are similar, the scaling properties of the thermal roughing and the kinetic roughing surfaces are quite different. The relations between the scaling properties, microstructures and roughing mechanisms are discussed based on the AFM and TEM results.展开更多
Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain c...Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.展开更多
Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC...Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC is a nonlinear system with a lot of overlapping information.In this paper,a dataset of eight roughness statistical parameters covering 112 digital joints is established.Then,the principal component analysis method is introduced to extract the significant information,which solves the information overlap problem of roughness characterization.Based on the two principal components of extracted features,the white shark optimizer algorithm was introduced to optimize the extreme gradient boosting model,and a new machine learning(ML)prediction model was established.The prediction accuracy of the new model and the other 17 models was measured using statistical metrics.The results show that the prediction result of the new model is more consistent with the real JRC value,with higher recognition accuracy and generalization ability.展开更多
The roughness of the fracture surface directly affects the strength,deformation,and permeability of the surrounding rock in deep underground engineering.Understanding the effect of high temperature and thermal cycle o...The roughness of the fracture surface directly affects the strength,deformation,and permeability of the surrounding rock in deep underground engineering.Understanding the effect of high temperature and thermal cycle on the fracture surface roughness plays an important role in estimating the damage degree and stability of deep rock mass.In this paper,the variations of fracture surface roughness of granite after different heating and thermal cycles were investigated using the joint roughness coefficient method(JRC),three-dimensional(3D)roughness parameters,and fractal dimension(D),and the mechanism of damage and deterioration of granite were revealed.The experimental results show an increase in the roughness of the granite fracture surface as temperature and cycle number were incremented.The variations of JRC,height parameter,inclination parameter and area parameter with the temperature conformed to the Boltzmann's functional distribution,while the D decreased linearly as the temperature increased.Besides,the anisotropy index(Ip)of the granite fracture surface increased as the temperature increased,and the larger parameter values of roughness characterization at different temperatures were attained mainly in directions of 20°–40°,60°–100°and 140°–160°.The fracture aperture of granite after fracture followed the Gauss distribution and the average aperture increased with increasing temperature,which increased from 0.665 mm at 25℃to 1.058 mm at 800℃.High temperature caused an uneven thermal expansion,water evaporation,and oxidation of minerals within the granite,which promoted the growth and expansion of microfractures,and reduced interparticle bonding strength.In particular,the damage was exacerbated by the expansion and cracking of the quartz phase transition after T>500℃.Thermal cycles contributed to the accumulation of this damage and further weakened the interparticle bonding forces,resulting in a significant increase in the roughness,anisotropy,and aperture of the fracture surface after five cycles.展开更多
Two-terminal(2-T)perovskite(PVK)/CuIn(Ga)Se_(2)(CIGS)tandem solar cells(TSCs)have been considered as an ideal tandem cell because of their best bandgap matching regarding to Shockley–Queisser(S–Q)limits.However,the ...Two-terminal(2-T)perovskite(PVK)/CuIn(Ga)Se_(2)(CIGS)tandem solar cells(TSCs)have been considered as an ideal tandem cell because of their best bandgap matching regarding to Shockley–Queisser(S–Q)limits.However,the nature of the irregular rough morphology of commercial CIGS prevents people from improving tandem device performances.In this paper,D-homoserine lactone hydrochloride is proven to improve coverage of PVK materials on irregular rough CIGS surfaces and also passivate bulk defects by modulating the growth of PVK crystals.In addition,the minority carriers near the PVK/C60 interface and the incompletely passivated trap states caused interface recombination.A surface reconstruction with 2-thiopheneethylammonium iodide and N,N-dimethylformamide assisted passivates the defect sites located at the surface and grain boundaries.Meanwhile,LiF is used to create this field effect,repelling hole carriers away from the PVK and C60 interface and thus reducing recombination.As a result,a 2-T PVK/CIGS tandem yielded a power conversion efficiency of 24.6%(0.16 cm^(2)),one of the highest results for 2-T PVK/CIGS TSCs to our knowledge.This validation underscores the potential of our methodology in achieving superior performance in PVK/CIGS tandem solar cells.展开更多
LetΩbe homogeneous of degree zero,integrable on S^(d−1) and have vanishing moment of order one,a be a function on R^(d) such that ∇a∈L^(∞)(R^(d)).Let T*_(Ω,a) be the maximaloperator associated with the d-dimensional...LetΩbe homogeneous of degree zero,integrable on S^(d−1) and have vanishing moment of order one,a be a function on R^(d) such that ∇a∈L^(∞)(R^(d)).Let T*_(Ω,a) be the maximaloperator associated with the d-dimensional Calder´on commutator defined by T*_(Ωa)f(x):=sup_(ε>0)|∫_(|x-y|>ε)^Ω(x-y)/|x-y|^(d+1)(a(x)-a(y))f(y)dy.In this paper,the authors establish bilinear sparse domination for T*_(Ω,a) under the assumption Ω∈L∞(Sd−1).As applications,some quantitative weighted bounds for T*_(Ω,a) are obtained.展开更多
Let Ω be homogeneous of degree zero,integrable on S^(n−1) and have mean value zero,T_(Ω) be the homogeneous singular integral operator with kernel Ω(x)/|x|^(n) and[b,T_(Ω)]be the commutator of T_(Ω)with symbol b∈BMO(...Let Ω be homogeneous of degree zero,integrable on S^(n−1) and have mean value zero,T_(Ω) be the homogeneous singular integral operator with kernel Ω(x)/|x|^(n) and[b,T_(Ω)]be the commutator of T_(Ω)with symbol b∈BMO(R^(n)).In this paper,the authors prove that if sup ζ∈S^(n−1)∫Sn−1^(|Ω(θ)|log^(β)(1/|θ·ζ|)dθ<∞ with β>2,then[b,T_(Ω)]is bounded on Triebel–Lizorkin space F^(0,q)p(R^(n))provided that 1+1/β−1<p,q<β.展开更多
As a non-contact ultra-precision machining method,abrasive water jet polishing(AWJP)has signi-ficant application in optical elements processing due to its stable tool influence function(TIF),no subsurface damage and s...As a non-contact ultra-precision machining method,abrasive water jet polishing(AWJP)has signi-ficant application in optical elements processing due to its stable tool influence function(TIF),no subsurface damage and strong adaptability to workpiece shapes.In this study,the effects of jet pressure,nozzle diameter and impinging angle on the distribution of pressure,velocity and wall shear stress in the polishing flow field were systematically analyzed by computational fluid dynamics(CFD)simulation.Based on the Box-Behnken experimental design,a response surface regression model was constructed to investigate the influence mech-anism of process parameters on material removal rate(MRR)and surface roughness(Ra)of fused silica.And experimental results showed that increasing jet pressure and nozzle diameter significantly improved MRR,consistent with shear stress distribution revealed by CFD simulations.However,increasing jet pressure and impinging angle caused higher Ra values,which was unfavorable for surface quality improvement.Genetic algorithm(GA)was used for multi-objective optimization to establish Pareto solutions,achieving concurrent optimization of polishing efficiency and surface quality.A parameter combination of 2 MPa jet pressure,0.3 mm nozzle diameter,and 30°impinging angle achieved MRR of 169.05μm^(3)/s and Ra of 0.50 nm.Exper-imental verification showed prediction errors of 4.4%(MRR)and 3.8%(Ra),confirming the model’s reliabil-ity.This parameter optimization system provides theoretical basis and technical support for ultra-precision polishing of complex curved optical components.展开更多
A novel method employing magnetic compound fluid(MCF)wheel was proposed for polishing the outer surface of stainless steel tube.Firstly,a polishing apparatus was constructed.In addition,the distribution of the magneti...A novel method employing magnetic compound fluid(MCF)wheel was proposed for polishing the outer surface of stainless steel tube.Firstly,a polishing apparatus was constructed.In addition,the distribution of the magnetic field of MCF wheel on the workpiece surface was explored by Maxwell software and Tesla meter,and the relationship between magnetic field distribution and material removal(MR)on the workpiece surface was investigated.Then,MR model was established and proved by the experiment results under specific experiment conditions.Finally,the influence laws of carbonyl iron powder particle size d_(CIP),abrasive particle size d_(AP),magnet speed n_(m),workpiece speed n_(c),and MCF supply amount V on surface roughness R_(a) and reduction rate were investigated through experiments,and the mechanisms of different parameters on surface quality were explored.Results show that the magnetic induction intensity during polishing is positively correlated with the polished profile of the workpiece.The trend of MR simulation is consistent with that of the experiment value,which proves the accuracy of MR model.When the revolution speeds of magnet and workpiece are 200 and 5000 r/min,respectively,and 2 mL MCF slurry containing 50wt%carbonyl iron powder(15μm),12wt%abrasive particle(7μm),3wt%α-cellulose,and 35wt%magnetic fluid was used,the final surface roughness decreases from 0.411μm to 0.007μm.After polishing for 100 min,the reduction rate is 98.297%,demonstrating that this method is appropriate for polishing the outer surface of tube.展开更多
文摘In the current practice of multi-axis machining of freeform surfaces, the interface surface between the roughing and finishing process is simply an offset surface of the nominal surface. While there have already been attempts at minimizing the machining time by considering the kinematic capacities of the machine tool and/or the physical constraints such as the cutting force, they all target independently at either the finishing or the roughing process alone and are based on the simple premise of an offset interface surface. Conceivably, since the total machining time should count that of both roughing and finishing process and both of them crucially depend on the interface surface, it is natural to ask if, under the same kinematic capacities and the same physical constraints, there is a nontrivial interface surface whose corresponding total machining time will be the minimum among all the possible（infinite） choices of interface surfaces, and this is the motivation behind the work of this paper. Specifically, with respect to the specific type of iso-planar milling for both roughing and finishing, we present a practical algorithm for determining such an optimal interface surface for an arbitrary freeform surface. While the algorithm is proposed for iso-planar milling, it can be easily adapted to other types of milling strategy such as contour milling. Both computer simulation and physical cutting experiments of the proposed method have convincingly demonstrated its advantages over the traditional simple offset method.
文摘The surface texture of mineral flotation froth is well acknowledged as an important index of the flotation process.The surface texture feature closely relates to the flotation working conditions and hence can be used as a visual indicator for the zinc fast roughing working condition. A novel working condition identification method based on the dual-tree complex wavelet transform(DTCWT) is proposed for process monitoring of zinc fast roughing.Three-level DTCWT is implemented to decompose the froth image into different directions and resolutions in advance, and then the energy parameter of each sub-image is extracted as the froth texture feature. Then, an improved random forest integrated classification(i RFIC) with 10-fold cross-validation model is introduced as the classifier to identify the roughing working condition, which effectively improves the shortcomings of the single model and overcomes the characteristic redundancy but achieves higher generalization performance. Extensive experiments have verified the effectiveness of the proposed method.
文摘Based on the characteristics of ferritic SUS430 heating and deformation,and combined with the features of the 1780 mm hot-rolling mill,a roughing model was introduced in two aspects:optimizing the rough rolling passes and improving the width control precision.Through reducing the rough rolling passes,the rough rolling time can be shortened,the precision rolling startup temperature can be raised and the yield of the hot-rolled products can be increased.Moreover,on the premise that the slab width fluctuation was great,the precision of the width control can be improved through optimizing the parameters of the hot-rolling width control model.The result shows that the optimization and perfection of the original rolling process of the stainless steel 430 series further improved its capacity and product quality.
文摘We report a method for increasing the mechanical strength of carbon nanotube(CNT)fibers while enabling the uniform adhesion of cerium oxide(CeO_(2))abrasive particles to them using polyethyleneimine(PEI).Results show that 5%of PEI increases the tensile strength of CNT fibers by approximately 175%.CeO_(2) particles were uniformly deposited on the reinforced CNT fibers by electrophoretic deposition.A flexible polishing tool was fabricated by weaving the CeO_(2)-CNT fibers into a non-woven fabric substrate.When used to polish potassium dihydrogen phosphate crystals,the tool reduced the surface roughness from 200 to 7.6 nm within 10 min.This approach has potential use for the development of new precision processing tools.
基金financially supported by the National Natural Science Foundation of China(No.52204284)the China Postdoctoral Science Foundation(No.2025MD784125)+2 种基金the Natural Science Foundation of Shaanxi Province,China(No.2024JC-YBQN-0365)the Shaanxi Province Postdoctoral Science Foundation,China(No.2025BSHSDZZ363)Outstanding Youth Science Fund of Xi’an University of Science and Technology,China(No.202308)。
文摘Interfacial interactions between rough mineral particles have garnered considerable attention as they directly determine particle agglomeration and floatability.This study comprehensively investigates the agglomeration characteristics of siderite particles after argon(Ar)plasma surface modification through settling tests,flocs size measurements,and fractal dimension calculations.Ar plasma surface modification promotes the agglomeration of siderite particles,as evidenced by increased floc size and density.The agglomeration mechanism induced by Ar plasma surface modification is evaluated using a theoretical model combining the surface element integration(SEI)approach,differential geometry,and the composite Simpson's rule.Changes in surface roughness,wettability,and charge are considered in this model.Compared to the unpretreated siderite particles,the energy barrier for interaction of the 30-min Ar plasma-pretreated siderite particles decreases from 2.3×10-^(17)J to 1.6×10^(-17)J.This reduction provides strong evidence for the agglomeration behavior of siderite particles.Furthermore,flotation experiments confirm that Ar plasma surface modification is conducive to the aggregation flotation of siderite.These findings offer crucial insights into particle aggregation and dispersion behaviors,with notable application in mineral flotation.
基金the Scientific and Technological Research Council of Türkiye(TÜBiTAK).
文摘This study investigated surface roughness,the wettability behavior,and surface energy of Co-based alloy specimens textured using the biomimetic Laser Surface Texturing(LST)method.The surface texture was inspired by the patterns found on marine shells.The impacts of the parameters on wettability,Surface Free Energy(SFE),surface topography,and texture roughness generated by the laser beam tracking a spiral path were investigated.Reducing spiral pitch produces more complicated and chaotic surface patterns.Most surfaces are hydrophobic,and surface roughness and topography influence the Contact Angle(CA).Topography and roughness were affected by frequency and scanning speed;a decrease in scanning speed and frequency generated more chaotic and irregular surface textures.With general factorial analysis and Analysis of Variance(ANOVA),our statistical study reveals that accounting for 88%of the influence,the scanning speed is the primary factor influencing surface roughness.On the other hand,the spiral pitch is essential for defining the struc-tural features of the surface,even if it less influences roughness.The SFE of laser-textured CoCr28Mo alloy specimens was optimizable within the range of 14-32 mN/m.The relevant findings offer valuable insights into optimizing LST for the specific surface properties of the Co-based alloy.
基金supported by the National Natural Science Foundation of China (Nos.42422705,42207175,42177117 and 42577170)the Ningbo Youth Leading Talent Project (No.2024QL051)+1 种基金the Chinese Academy of Engineering Science and Technology Strategy Consulting Project (No.2025-XZ-57)the Central Government Funding Program for Guiding Local Science and Technology Development (No.2025ZY01028)。
文摘Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogeneity remains challenging.To address this,this study first captures the morphology of large-scale(1000 mm × 1000 mm) slate and granite joints via 3D laser scanning.Analysis of these surfaces and corresponding push/pull tests on carved specimens revealed a potential correlation between the heterogeneity of roughness and shear strength.A comparative evaluation of five statistical metrics identified information entropy(Hs) as the most robust indicator for quantifying rock joint heterogeneity.Further analysis using Hsreveals that the heterogeneity is anisotropic and,critically,that shear strength heterogeneity is governed not only by roughness heterogeneity but is also significantly influenced by the mean roughness value,normal stress,and intact rock tensile strength.Consequently,a simple comparison of roughness Hsvalues is insufficient for reliably comparing shear strength heterogeneity.To overcome this limitation,a theoretical framework is developed to explicitly map fundamental roughness statistics(mean and heterogeneity) to shear strength heterogeneity.This framework culminates in a practical workflow that allows for the rapid,field-based assessment of shear strength heterogeneity using readily obtainable rock joint roughness data.
基金supported by the National Natural Science Foundation of China(Grant No.52402430,52572380)the Natural Science Foundation of Shanghai(Grant No.23ZR1466300).
文摘Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sensitive to long-wavelength(15–120 m)and lateral irregularities,which are often overlooked in traditional roughness models.This study aims to construct a three-dimensional runway roughness modeling framework integrating"precise detection-spectrum analysis-spatial reconstruction"in response to this issue.Combining the elevation data of 37 runways(5 asphalt runways and 32 cement runways)measured by a vehicle-mounted laser profilometer and the BeiDou positioning system,the power spectrum analysis was carried out by the Burg method and the spectrum models of asphalt and cement runways were fitted respectively.Meanwhile,a new exponential lateral coherence function was proposed.Finally,the three-dimensional spatial model was reconstructed by using the transfer function and genetic algorithm.The results show that the error of the measured elevation data is less than 1 cm.The spectral characteristics of different pavement types are significantly different.Among them,the R^(2) of the asphalt runway fitted with the Sussman model is greater than 0.9.The cement runway needs to be characterized by a piecewise function to represent the spectral mutation.The fitting error of the new index's lateral coherence function has been reduced to 0.012.The reconstructed three-dimensional model is in good agreement with the theoretical value and the error does not exceed 0.18 mm^(2) m/c.Finally,a three-dimensional model of 0–20 m in the lateral direction and 3000 m in the longitudinal direction is generated,providing support for aircraft vibration simulation and pavement maintenance.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFC3707900)National Natural Science Foundation of China(Grant No.42230710,42525201)Key task project for joint research and development of the Yangtze River Delta Science and Technology Innovation Community(Grant No.2022CSJGG1200).
文摘Microbially induced calcium carbonate precipitation(MICP)is an eco-friendly technology for soil improvement.Although numerous experiments have been conducted to solidify sand foundations using MICP,the mechanisms by which grain interfacial morphologies influencethe MICP process remain unclear.This study utilized 3D-printed flowcells with different boundary morphologies to investigate the effects of interfacial morphologies on the MICP process.CaCO_(3)precipitation characteristics were investigated through microscopic observation and image quantificationanalysis.The results indicate that low flowvelocities near the interface promote bacterial accumulation due to reduced hydrodynamic shear forces.Rough interfaces,compared to smooth ones,enhance bacterial adsorption owing to the larger regions of low flowvelocity,increased surface area,and the formation of local eddies,which promote greater CaCO_(3)precipitation.Compared to the regions away from the interface,a higher abundance of small CaCO_(3)crystals is observed near the interface because of the high urease activity from bacteria and the reduced shear-induced entrainment due to the low flowvelocity.Besides,larger crystals also preferentially precipitate in proximity to interfaces as the low flowvelocity enhances crystal growth according to the particle attachment theory.The presence of rough interfaces further reduces flowvelocities,leading to the precipitation of larger and more densely packed CaCO_(3)crystals.Therefore,rough interfaces promote the microbially induced calcium carbonate precipitation.This work is expected to enhance the understanding of microbially induced calcium carbonate precipitation characteristics on solid surfaces such as soil grains and contribute to the optimization of MICP applications.
文摘Hack and slash your way to a delectable West China dish谁说美食必须精致?新疆大盘鸡的灵魂就是粗放You’ve driven 300 miles over the endless Gobi desert without a sign of life in any direction.The sun sets as the heat of the day cools into night.Then you see,in the middle of nowhere,a small restaurant by the highway.You enter with a gust of wind and sand whirling around your boots like a Wild West movie,and say
文摘Surface morphologies and microstructures of C 60 /Ag composite films were studied by atomic force microscope (AFM) and transmission electron microscope (TEM). The surface roughness depended on the substrate temperature, and the transition of surface morphology of rough→smooth→rough was observed when the substrate temperature increased from -50 to 120℃. Although the rms values are similar, the scaling properties of the thermal roughing and the kinetic roughing surfaces are quite different. The relations between the scaling properties, microstructures and roughing mechanisms are discussed based on the AFM and TEM results.
基金funded by the Natural Science Foundation of China(Grant Nos.42377164 and 41972280)the Badong National Observation and Research Station of Geohazards(Grant No.BNORSG-202305).
文摘Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.
基金funding from the National Natural Science Foundation of China (Grant No.42277175)the pilot project of cooperation between the Ministry of Natural Resources and Hunan Province“Research and demonstration of key technologies for comprehensive remote sensing identification of geological hazards in typical regions of Hunan Province” (Grant No.2023ZRBSHZ056)the National Key Research and Development Program of China-2023 Key Special Project (Grant No.2023YFC2907400).
文摘Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC is a nonlinear system with a lot of overlapping information.In this paper,a dataset of eight roughness statistical parameters covering 112 digital joints is established.Then,the principal component analysis method is introduced to extract the significant information,which solves the information overlap problem of roughness characterization.Based on the two principal components of extracted features,the white shark optimizer algorithm was introduced to optimize the extreme gradient boosting model,and a new machine learning(ML)prediction model was established.The prediction accuracy of the new model and the other 17 models was measured using statistical metrics.The results show that the prediction result of the new model is more consistent with the real JRC value,with higher recognition accuracy and generalization ability.
基金funding support from the National Natural Science Foundation of China(Grant No.52274082)the Program of Qingjiang Excellent Young Talents,Jiangxi University of Science and Technology(Grant No.JXUSTQJBJ2020003)the Innovation Fund Designated for Graduate Students of Jiangxi Province(Grant No.YC2023-B215).
文摘The roughness of the fracture surface directly affects the strength,deformation,and permeability of the surrounding rock in deep underground engineering.Understanding the effect of high temperature and thermal cycle on the fracture surface roughness plays an important role in estimating the damage degree and stability of deep rock mass.In this paper,the variations of fracture surface roughness of granite after different heating and thermal cycles were investigated using the joint roughness coefficient method(JRC),three-dimensional(3D)roughness parameters,and fractal dimension(D),and the mechanism of damage and deterioration of granite were revealed.The experimental results show an increase in the roughness of the granite fracture surface as temperature and cycle number were incremented.The variations of JRC,height parameter,inclination parameter and area parameter with the temperature conformed to the Boltzmann's functional distribution,while the D decreased linearly as the temperature increased.Besides,the anisotropy index(Ip)of the granite fracture surface increased as the temperature increased,and the larger parameter values of roughness characterization at different temperatures were attained mainly in directions of 20°–40°,60°–100°and 140°–160°.The fracture aperture of granite after fracture followed the Gauss distribution and the average aperture increased with increasing temperature,which increased from 0.665 mm at 25℃to 1.058 mm at 800℃.High temperature caused an uneven thermal expansion,water evaporation,and oxidation of minerals within the granite,which promoted the growth and expansion of microfractures,and reduced interparticle bonding strength.In particular,the damage was exacerbated by the expansion and cracking of the quartz phase transition after T>500℃.Thermal cycles contributed to the accumulation of this damage and further weakened the interparticle bonding forces,resulting in a significant increase in the roughness,anisotropy,and aperture of the fracture surface after five cycles.
基金supported by“National Natural Science Foundation of China(U21A20171,U20A20245)”“Hubei Provincial Natural Science Foundation of China(2023AFA010)”+1 种基金“Independent Innovation Projects of the Hubei Longzhong Laboratory(2022ZZ-09)”“Social Public Welfare and Basic Research Special Project of Zhongshan(2020B2015).”。
文摘Two-terminal(2-T)perovskite(PVK)/CuIn(Ga)Se_(2)(CIGS)tandem solar cells(TSCs)have been considered as an ideal tandem cell because of their best bandgap matching regarding to Shockley–Queisser(S–Q)limits.However,the nature of the irregular rough morphology of commercial CIGS prevents people from improving tandem device performances.In this paper,D-homoserine lactone hydrochloride is proven to improve coverage of PVK materials on irregular rough CIGS surfaces and also passivate bulk defects by modulating the growth of PVK crystals.In addition,the minority carriers near the PVK/C60 interface and the incompletely passivated trap states caused interface recombination.A surface reconstruction with 2-thiopheneethylammonium iodide and N,N-dimethylformamide assisted passivates the defect sites located at the surface and grain boundaries.Meanwhile,LiF is used to create this field effect,repelling hole carriers away from the PVK and C60 interface and thus reducing recombination.As a result,a 2-T PVK/CIGS tandem yielded a power conversion efficiency of 24.6%(0.16 cm^(2)),one of the highest results for 2-T PVK/CIGS TSCs to our knowledge.This validation underscores the potential of our methodology in achieving superior performance in PVK/CIGS tandem solar cells.
文摘LetΩbe homogeneous of degree zero,integrable on S^(d−1) and have vanishing moment of order one,a be a function on R^(d) such that ∇a∈L^(∞)(R^(d)).Let T*_(Ω,a) be the maximaloperator associated with the d-dimensional Calder´on commutator defined by T*_(Ωa)f(x):=sup_(ε>0)|∫_(|x-y|>ε)^Ω(x-y)/|x-y|^(d+1)(a(x)-a(y))f(y)dy.In this paper,the authors establish bilinear sparse domination for T*_(Ω,a) under the assumption Ω∈L∞(Sd−1).As applications,some quantitative weighted bounds for T*_(Ω,a) are obtained.
基金Supported by NSFC(No.11971295)Guangdong Higher Education Teaching Reform Project(No.2023307)。
文摘Let Ω be homogeneous of degree zero,integrable on S^(n−1) and have mean value zero,T_(Ω) be the homogeneous singular integral operator with kernel Ω(x)/|x|^(n) and[b,T_(Ω)]be the commutator of T_(Ω)with symbol b∈BMO(R^(n)).In this paper,the authors prove that if sup ζ∈S^(n−1)∫Sn−1^(|Ω(θ)|log^(β)(1/|θ·ζ|)dθ<∞ with β>2,then[b,T_(Ω)]is bounded on Triebel–Lizorkin space F^(0,q)p(R^(n))provided that 1+1/β−1<p,q<β.
文摘As a non-contact ultra-precision machining method,abrasive water jet polishing(AWJP)has signi-ficant application in optical elements processing due to its stable tool influence function(TIF),no subsurface damage and strong adaptability to workpiece shapes.In this study,the effects of jet pressure,nozzle diameter and impinging angle on the distribution of pressure,velocity and wall shear stress in the polishing flow field were systematically analyzed by computational fluid dynamics(CFD)simulation.Based on the Box-Behnken experimental design,a response surface regression model was constructed to investigate the influence mech-anism of process parameters on material removal rate(MRR)and surface roughness(Ra)of fused silica.And experimental results showed that increasing jet pressure and nozzle diameter significantly improved MRR,consistent with shear stress distribution revealed by CFD simulations.However,increasing jet pressure and impinging angle caused higher Ra values,which was unfavorable for surface quality improvement.Genetic algorithm(GA)was used for multi-objective optimization to establish Pareto solutions,achieving concurrent optimization of polishing efficiency and surface quality.A parameter combination of 2 MPa jet pressure,0.3 mm nozzle diameter,and 30°impinging angle achieved MRR of 169.05μm^(3)/s and Ra of 0.50 nm.Exper-imental verification showed prediction errors of 4.4%(MRR)and 3.8%(Ra),confirming the model’s reliabil-ity.This parameter optimization system provides theoretical basis and technical support for ultra-precision polishing of complex curved optical components.
基金National Natural Science Foundation of China(52265056,52262013)Lanzhou Young Talent Program(2023-QN-38)Natural Science Foundation of Gansu Province(23JRRA776)。
文摘A novel method employing magnetic compound fluid(MCF)wheel was proposed for polishing the outer surface of stainless steel tube.Firstly,a polishing apparatus was constructed.In addition,the distribution of the magnetic field of MCF wheel on the workpiece surface was explored by Maxwell software and Tesla meter,and the relationship between magnetic field distribution and material removal(MR)on the workpiece surface was investigated.Then,MR model was established and proved by the experiment results under specific experiment conditions.Finally,the influence laws of carbonyl iron powder particle size d_(CIP),abrasive particle size d_(AP),magnet speed n_(m),workpiece speed n_(c),and MCF supply amount V on surface roughness R_(a) and reduction rate were investigated through experiments,and the mechanisms of different parameters on surface quality were explored.Results show that the magnetic induction intensity during polishing is positively correlated with the polished profile of the workpiece.The trend of MR simulation is consistent with that of the experiment value,which proves the accuracy of MR model.When the revolution speeds of magnet and workpiece are 200 and 5000 r/min,respectively,and 2 mL MCF slurry containing 50wt%carbonyl iron powder(15μm),12wt%abrasive particle(7μm),3wt%α-cellulose,and 35wt%magnetic fluid was used,the final surface roughness decreases from 0.411μm to 0.007μm.After polishing for 100 min,the reduction rate is 98.297%,demonstrating that this method is appropriate for polishing the outer surface of tube.
