Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Surface roughness”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

A comparison between backscattering models for rough surfaces

The ease of applicability of three scattering models is examined. This is accomplished by considering the time taken to numerically evaluate these models and by comparing their predictions as a function of surface roughness, frequency, incident angle and polarization with the moment-method solution in two dimensions. The complexity of the analytic models in three dimensions and their analytic reduction to high- and low-frequency regions are also compared. The selected models are an integral equation model (IEM), a full wave model (FWM), and the phase perturbation model (PPM). It is noted that in three dimensions, the full-wave model requires an evaluation of a tenfold integral and the phase perturbation model requires a fourfold and a twofold integral, whereas the integral equation model is an algebraic equation in like polarization under single scattering conditions. It is found that both the IEM and PPM agree with the moment-method solution from low to high frequencies numerically.

Chen, K. S.↗
NASA NTRS2015

Measuring Skew in Average Surface Roughness as a Function of Surface Preparation

Characterizing surface roughness is important for predicting optical performance. Better measurement of surface roughness reduces grinding saving both time and money and allows the science requirements to be better defined. In this study various materials are polished from a fine grind to a fine polish. Each sample's RMS surface roughness is measured at 81 locations in a 9x9 square grid using a Zygo white light interferometer at regular intervals during the polishing process. Each data set is fit with various standard distributions and tested for goodness of fit. We show that the skew in the RMS data changes as a function of polishing time.

Stahl, Mark T.↗
NASA NTRS1988

Polarimetric microwave scattering from known randomly rough surfaces

Scattering from rough surfaces is reviewed, and artificial randomly rough surfaces are described. Measurements were made from 4 to 18 GHz for the 4 linear polarization states. The target consists of a metalized randomly rough surface constructed from known surface statistical information. The surface was generated using surface generation routines on the computer, and then the data was converted for the machining of the surface on a computer controlled mill. Bistatic and monostatic measurements were acquired at incident angles from 25 to 60 deg. At the 13.5 to 18 GHz frequencies, the effects of backscatter enhancement and depolarization effects can be studied in a regime which does not satisfy Kirchoff or small perturbation assumptions. This allows scattering mechanisms to be introduced into models, which may show missing elements in the more standard formulations. At lower frequency bands such as 4 to 8.5 GHz the scattering behavior was also examined to see the behavior as assumptions of other formulations are satisfied.

Nance, C. E.↗
NASA NTRS1989

Surface roughness of flat and curved optical surfaces

Surface roughness measurement has several applications. Even a few A roughness will cause scattered light in optical systems. Smooth surfaces are required in a wide variety of instruments. For example, the outputs of the high power lasers are limited by the surface roughness of mirrors and windows. Similarly, the information storage capacity of magnetic media is limited by the roughness of the surface. Roughness reduces the resolving power of optics and distorts images. The performance of certain thin film components in electronic industries is affected by the roughness on the film surface. X-ray astronomical telescopes require smooth curved surfaces. To improve the surface quality, super sensitive detection methods are required. Wide ranging measurement techniques are developed based on interferometry, electron microscopy, C-rays, ellipsometry, light scattering, and using mechanical stylus, etc. Though there are several techniques available for measurement and evaluation of the surfaces, no single technique is fully adequate. Also, the technique used should be nondestructive and highly sensitive. So, an optical heterodyne profilometer was fabricated. Its current sensitivity is much better than 10A rms. It is a noncontact and nondestructive technique. The instrument can be operated even by unskilled personnel for routine measurements.

George, M. C.↗
NASA NTRS2006

The Aquarius Scatterometer: An Active System for Measuring Surface Roughness for Sea-Surface Brightness Temperature Correction

The Aquarius scatterometer is a total-power L-band radar system for estimating ocean surface roughness. Its measurements will enable the removal of wind effects from the Aquarius radiometer ocean-surface brightness temperature measurements being used to retrieve ocean salinity. The Aquarius scatterometer is a relatively simple, low-spatial resolution power-detecting radar, without ranging capability. But to meet its science requirement, it must be very stable, with repeatability on the order of 0.1 dB over several days, and calibrated accuracy to this level over several months. Data from this instrument over land as well as ocean areas will be available for a variety of geophysical applications.

scatterometers↗
NASA NTRS2006

Terahertz NDE for Metallic Surface Roughness Evaluation

Metallic surface roughness in a nominally smooth surface is a potential indication of material degradation or damage. When the surface is coated or covered with an opaque dielectric material, such as paint or insulation, then inspecting for surface changes becomes almost impossible. Terahertz NDE is a method capable of penetrating the coating and inspecting the metallic surface. The terahertz frequency regime is between 100 GHz and 10 THz and has a free space wavelength of 300 micrometers at 1 THz. Pulsed terahertz radiation, can be generated and detected using optical excitation of biased semiconductors with femtosecond laser pulses. The resulting time domain signal is 320 picoseconds in duration. In this application, samples are inspected with a commercial terahertz NDE system that scans the sample and generates a set of time-domain signals that are a function of the backscatter from the metallic surface. Post processing is then performed in the time and frequency domains to generate C-scan type images that show scattering effects due to surface non-uniformity.

Madaras, Eric I.↗
NASA NTRS1986

Parameterization of albedo, thermal inertia, and surface roughness of desert scrub/sandy soil surface

Spectral albedo, A sub n, for the direct solar beam is defined as A sub n (r sub i,s, theta sub 0) = r sub i exp(-s tan theta sub 0)1-I(s) where I(s) is the integral over all reflection angles describing the interception by the absorbing plants of the flux reflected from the soil, r sub i soil reflectance, assumed Lambertian, S the projection on a vertical plane of plants per unit surface area, and theta sub 0 is the solar zenith angle. Hemispheric reflectance for the direct solar beam equals 1-I(s) times the reflectance to the zenith. The values of s of 0.1, 0.2, and 0.3 respectively quantify sparse, moderately dense, and very dense desert scrub. Thin plants are assumed to be of negligible thermal inertia, and thus directly yield the absorbed insolation to the atmosphere. Surface thermal inertia is therefore effectively reduced. The ratio of surface roughness height to plant height is parameterized for sparse, moderately dense, and very dense desert-scrub as a function of s based on data expressing the dependence of this ratio on plant silhouette.

Otterman, J.↗
NASA NTRS2012

Curb Mounting, Vertical Mobility, and Inverted Mobility on Rough Surfaces Using Microspine-Enabled Robots

Three robots that extend microspine technology to enable advanced mobility are presented. First, the Durable Reconnaissance and Observation Platform (DROP) and the ReconRobotics Scout platform use a new rotary configuration of microspines to provide improved soldier-portable reconnaissance by moving rapidly over curbs and obstacles, transitioning from horizontal to vertical surfaces, climbing rough walls and surviving impacts. Next, the four-legged LEMUR robot uses new configurations of opposed microspines to anchor to both manmade and natural rough surfaces. Using these anchors as feet enables mobility in unstructured environments, from urban disaster areas to deserts and caves.

microspines↗
NASA NTRS1987

A parameterization of the effect of surface roughness on microwave emission

A simple model is developed to represent the net effect of surface roughness on the microwave emission from soils. The reflectivity of a rough soil surface is defined in a theoretical model that includes both coherent and incoherent reflectivities in terms of the statistical properties of the rough surface, i.e., the surface height standard deviation and its horizontal correlation length. It is shown that the rough surface reflectivity obtained from this theoretical model can be presented in a form that is simply the reflectivity of a smooth surface attenuated by a 'rough thickness'. It is found that the rough thickness can be parameterized as a function of the statistical slope ratio of a rough surface by a simple power-law relationship. Since the slope of a rough surface can be determined experimentally, the rough thickness can be quantitatively estimated from the parametric representation. Model calculations show that this simple model can provide reasonably accurate results of predicted brightness temperatures that agree well with field measurements within experimental uncertainty.

Mo, Tsan↗
NASA NTRS2009

Determining Surface Roughness in Urban Areas Using Lidar Data

An automated procedure has been developed to derive relevant factors, which can increase the ability to produce objective, repeatable methods for determining aerodynamic surface roughness. Aerodynamic surface roughness is used for many applications, like atmospheric dispersive models and wind-damage models. For this technique, existing lidar data was used that was originally collected for terrain analysis, and demonstrated that surface roughness values can be automatically derived, and then subsequently utilized in disaster-management and homeland security models. The developed lidar-processing algorithm effectively distinguishes buildings from trees and characterizes their size, density, orientation, and spacing (see figure); all of these variables are parameters that are required to calculate the estimated surface roughness for a specified area. By using this algorithm, aerodynamic surface roughness values in urban areas can then be extracted automatically. The user can also adjust the algorithm for local conditions and lidar characteristics, like summer/winter vegetation and dense/sparse lidar point spacing. Additionally, the user can also survey variations in surface roughness that occurs due to wind direction; for example, during a hurricane, when wind direction can change dramatically, this variable can be extremely significant. In its current state, the algorithm calculates an estimated surface roughness for a square kilometer area; techniques using the lidar data to calculate the surface roughness for a point, whereby only roughness elements that are upstream from the point of interest are used and the wind direction is a vital concern, are being investigated. This technological advancement will improve the reliability and accuracy of models that use and incorporate surface roughness.

Holland, Donald↗
NASA NTRS1983

Passive microwave sensing of soil moisture content - The effects of soil bulk density and surface roughness

Microwave radiometric measurements over bare fields of different surface roughness were made at frequencies of 1.4 GHz, 5 GHz, and 10.7 GHz to study the frequency dependence, as well as the possible time variation, of surface roughness. An increase in surface roughness was found to increase the brightness temperature of soils and reduce the slope of regression between brightness temperature and soil moisture content. The frequency dependence of the surface roughness effect was relatively weak when compared with that of the vegetation effect. Radiometric time-series observations over a given field indicate that field surface roughness might gradually diminish with time, especially after a rainfall or irrigation. The variation of surface roughness increases the uncertainty of remote soil moisture estimates by microwave radiometry. Three years of radiometric measurements over a test site revealed a possible inconsistency in the soil bulk density determination, which is an important factor in the interpretation of radiometric data.

Wang, J. R.↗
NASA NTRS1982

Passive microwave sensing of soil moisture content: Soil bulk density and surface roughness

Microwave radiometric measurements over bare fields of different surface roughnesses were made at the frequencies of 1.4 GHz, 5 GHz, and 10.7 GHz to study the frequency dependence as well as the possible time variation of surface roughness. The presence of surface roughness was found to increase the brightness temperature of soils and reduce the slope of regression between brightness temperature and soil moisture content. The frequency dependence of the surface roughness effect was relatively weak when compared with that of the vegetation effect. Radiometric time series observation over a given field indicated that field surface roughness might gradually diminish with time, especially after a rainfall or irrigation. This time variation of surface roughness served to enhance the uncertainty in remote soil moisture estimate by microwave radiometry. Three years of radiometric measurements over a test site revealed a possible inconsistency in the soil bulk density determination, which turned out to be an important factor in the interpretation of radiometric data.

Wang, J. R.↗
NASA NTRS1972

Surface roughness effects on bidirectional reflectance

An experimental study of surface roughness effects on bidirectional reflectance of metallic surfaces is presented. A facility capable of irradiating a sample from normal to grazing incidence and recording plane of incidence bidirectional reflectance measurements was developed. Samples consisting of glass, aluminum alloy, and stainless steel materials were selected for examination. Samples were roughened using standard grinding techniques and coated with a radiatively opaque layer of pure aluminum. Mechanical surface roughness parameters, rms heights and rms slopes, evaluated from digitized surface profile measurements are less than 1.0 micrometers and 0.28, respectively. Rough surface specular, bidirectional, and directional reflectance measurements for selected values of polar angle of incidence and wavelength of incident energy within the spectral range of 1 to 14 micrometers are reported. The Beckmann bidirectional reflectance model is compared with reflectance measurements to establish its usefulness in describing the magnitude and spatial distribution of energy reflected from rough surfaces.

Smith, T. F.↗
NASA NTRS1973

Surface roughness effects on bidirectional reflectance.

An experimental study of surface roughness effects on bidirectional reflectance of metallic surfaces is presented. Samples consisting of glass, aluminum alloy, and stainless steel materials were roughened using standard grinding techniques and coated with a radiatively opaque layer of pure aluminum. Surface roughness parameters, rms height and rms slope, were evaluated from digitized surface profile measurements and are less than 1.0 micron, and 0.28, respectively. Rough-surface specular, bidirectional, and directional reflectance measurements for selected values of polar angle and wavelength of incident energy within the range from 10 to 80 deg and from 1 to 14 microns, respectively, are reported. The influence of surface roughness is discussed in terms of rms height and rms slope.

Smith, T. F.↗