Studying and understanding of the surface topography variation are the basis for analyzing tribological problems,and characterization of worn surface is necessary.Fractal geometry offers a more accurate description fo...Studying and understanding of the surface topography variation are the basis for analyzing tribological problems,and characterization of worn surface is necessary.Fractal geometry offers a more accurate description for surface roughness that topographic surfaces are statistically self-similar and can be quantitatively evaluated by fractal parameters.The change regularity of worn surface topography is one of the most important aspects of running-in study.However,the existing research normally adopts only one friction matching pair to explore the surface topography change,which interrupts the running-in wear process and makes the experimental result lack authenticity and objectivity.In this paper,to investigate the change regularity of surface topography during the real running-in process,a series of running-in tests by changing friction pairs under the same operating conditions are conducted on UMT-II Universal Multifunction Tester.The surface profile data are acquired by MiaoXAM2.5X-50X Ultrahigh Precision Surface 3D Profiler and analyzed using fractal dimension D,scale coefficient C and characteristic roughness Ra ＊based on root mean square（RMS） method.The characterization effects of the three parameters are discussed and compared.The results obtained show that there exists remarkable fractal feature of surface topography during running-in process,both D and Ra ＊increase gradually,while C decreases slowly as the wear-in process goes on,and all parameters tend to be stable when the wear process steps into the normal wear process.Ra ＊illustrates higher sensitivity for rough surface characterization compared with the other two parameters.In addition,the running-in test carried with a set of identical surface properties is more scientific and reasonable than the traditional one.The proposed research further indicates that the fractal method can quantitatively measure the rough surface,which also provides an evidence for running-in process identification and tribology design.展开更多
The details of the special three-dimensional micro-nano scale ripples with a period of hundreds of microns on the surfaces of a Zr-based and a La-based metallic glass irradiated separately by single laser pulse are in...The details of the special three-dimensional micro-nano scale ripples with a period of hundreds of microns on the surfaces of a Zr-based and a La-based metallic glass irradiated separately by single laser pulse are investigated.We use the small-amplitude capillary wave theory to unveil the ripple formation mechanism through considering each of the molten metallic glasses as an incompressible viscous fluid.A generalized model is presented to describe the special morphology,which fits the experimental result well.It is also revealed that the viscosity brings about the biggest effect on the monotone decreasing nature of the amplitude and the wavelength of the surface ripples.The greater the viscosity is,the shorter the amplitude and the wavelength are.展开更多
Introduction:Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment,processes which occur at heig...Introduction:Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment,processes which occur at heights of only several centimeters.Currently,future climate models predict temperature at 2 m above ground,leaving ground-surface microclimate not well characterized.Methods:Using a network of field temperature sensors and climate models,a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature.Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution.Results:The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing,south-facing,valley,and ridgeline topographic settings,and when compared to measured temperatures yielded an R2 of 0.88,0.80,0.88,and 0.80,respectively.Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures,resulting in R2 values of 0.86,0.77,0.72,and 0.79 for north-facing,south-facing,valley,and ridgeline topographic settings.Quasi-Poisson regressions predicting recruitment of Quercus kelloggii(black oak)seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m.Conclusion:Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment.Such methods could be applied to improve projections of species’range shifts under climate change.Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.展开更多
基金supported by National Natural Science Foundation of China (Grant No.50975276,Grant No.50475164)National Basic Research Program of China (973 Program,Grant No.2007CB607605)Doctoral Programs Foundation of Ministry of Education of China (Grant No.200802900513)
文摘Studying and understanding of the surface topography variation are the basis for analyzing tribological problems,and characterization of worn surface is necessary.Fractal geometry offers a more accurate description for surface roughness that topographic surfaces are statistically self-similar and can be quantitatively evaluated by fractal parameters.The change regularity of worn surface topography is one of the most important aspects of running-in study.However,the existing research normally adopts only one friction matching pair to explore the surface topography change,which interrupts the running-in wear process and makes the experimental result lack authenticity and objectivity.In this paper,to investigate the change regularity of surface topography during the real running-in process,a series of running-in tests by changing friction pairs under the same operating conditions are conducted on UMT-II Universal Multifunction Tester.The surface profile data are acquired by MiaoXAM2.5X-50X Ultrahigh Precision Surface 3D Profiler and analyzed using fractal dimension D,scale coefficient C and characteristic roughness Ra ＊based on root mean square（RMS） method.The characterization effects of the three parameters are discussed and compared.The results obtained show that there exists remarkable fractal feature of surface topography during running-in process,both D and Ra ＊increase gradually,while C decreases slowly as the wear-in process goes on,and all parameters tend to be stable when the wear process steps into the normal wear process.Ra ＊illustrates higher sensitivity for rough surface characterization compared with the other two parameters.In addition,the running-in test carried with a set of identical surface properties is more scientific and reasonable than the traditional one.The proposed research further indicates that the fractal method can quantitatively measure the rough surface,which also provides an evidence for running-in process identification and tribology design.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.10572002,10732010,and 11332002)
文摘The details of the special three-dimensional micro-nano scale ripples with a period of hundreds of microns on the surfaces of a Zr-based and a La-based metallic glass irradiated separately by single laser pulse are investigated.We use the small-amplitude capillary wave theory to unveil the ripple formation mechanism through considering each of the molten metallic glasses as an incompressible viscous fluid.A generalized model is presented to describe the special morphology,which fits the experimental result well.It is also revealed that the viscosity brings about the biggest effect on the monotone decreasing nature of the amplitude and the wavelength of the surface ripples.The greater the viscosity is,the shorter the amplitude and the wavelength are.
基金We gratefully acknowledge funding support from the National Science Foundation Macrosystems Biology Program,NSF#EF-1065864,and thank our collaborating investigators(A.Hall,L.Hannah,M.Moritz,M.North,K.Redmond,H.Regan,A.Syphard).The manuscript was improved by comments from H.Regan.S.McKnight and A.Shepard coordinated field site set-up,while E.Conlisk,S.Dashiell,L.di Scipio,E.Hopkins,A.MacDonald,K.Maher,J.McClure,P.Prather,E.Peck,R.Swab,and W.Wilkinson contributed to data collection and maintenance of the common gardens and field sensors.We thank the USDA Forest Service and Tejon Ranch Company for access to field sites.P.Slaughter has been instrumental with development of the field data processing system and database ingest software.Lastly,we would like to thank The Earth Research Institute staff at UC Santa Barbara for their assistance and support.
文摘Introduction:Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment,processes which occur at heights of only several centimeters.Currently,future climate models predict temperature at 2 m above ground,leaving ground-surface microclimate not well characterized.Methods:Using a network of field temperature sensors and climate models,a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature.Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution.Results:The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing,south-facing,valley,and ridgeline topographic settings,and when compared to measured temperatures yielded an R2 of 0.88,0.80,0.88,and 0.80,respectively.Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures,resulting in R2 values of 0.86,0.77,0.72,and 0.79 for north-facing,south-facing,valley,and ridgeline topographic settings.Quasi-Poisson regressions predicting recruitment of Quercus kelloggii(black oak)seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m.Conclusion:Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment.Such methods could be applied to improve projections of species’range shifts under climate change.Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.
