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Nelson, G. D.

Publications and source records attributed to Nelson, G. D..

11 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Proton and Electron Threshold Energy Measurements for Extravehicular Activity Space Suits

Construction of ISS will require more than 1000 hours of EVA. Outside of ISS during EVA, astronauts and cosmonauts are likely to be exposed to a large fluence of electrons and protons. Development of radiation protection guidelines requires the determination of the minimum energy of electrons and protons that penetrate the suits at various locations. Measurements of the water-equivalent thickness of both US. and Russian EVA suits were obtained by performing CT scans. Specific regions of interest of the suits were further evaluated using a differential range shift technique. This technique involved measuring thickness ionization curves for 6-MeV electron and 155-MeV proton beams with ionization chambers using a constant source-to-detector distance. The thicknesses were obtained by stacking polystyrene slabs immediately upstream of the detector. The thicknesses of the 50% ionizations relative to the maximum ionizations were determined. The detectors were then placed within the suit and the stack thickness adjusted until the 50% ionization was reestablished. The difference in thickness between the 50% thicknesses was then used with standard range-energy tables to determine the threshold energy for penetration. This report provides a detailed description of the experimental arrangement and results.

Moyers, M. F.↗
NASA NTRS1980

Granulation in a main-sequence F-type star

The modal approach developed by Nelson and Musman (1977) is used to investigate convection in an F-type main-sequence star (effective temperature of 7300 K, g = 10,000 cm per sec per sec). The convective velocities and intensity contrasts are found to be larger than in the sun. Even though the convective flux is less than 1% of the total flux at a mean optical depth of unity, the spectral-energy distribution is strongly reddened as a result of the fluctuating opacity. This has important implications in the conversion scale from observed colors to effective temperature. The scale of the surface granulation is expected to be in the range 1000-5000 km. Calculations of the combined H-He I and He II convection zones support the prediction of Toomre et al. (1976) that the stable region between the zones is well mixed

Nelson, G. D.↗
NASA NTRS1978

A two-dimensional solar model

A two-dimensional, nearly flux constant solar atmosphere which includes a physical model of granulation is presented. If the inhomogeneous character of the solar photosphere is neglected in the construction of empirical models, the result is an underestimate of the temperature gradient in the layers below a Rosseland optical depth of 0.5 and an overestimate of the convective flux penetration into the observable layers. The two-dimensional model adequately reproduces the mean limb darkening, the magnitude and center-to-limb variation of the intensity fluctuations, and the rms vertical and horizontal convective velocities.

Nelson, G. D.↗
NASA NTRS1975

Boundary-detection algorithm for locating edges in digital imagery

The author has identified the following significant results. Initial development of a computer program which implements a boundary detection algorithm to detect edges in digital images is described. An evaluation of the boundary detection algorithm was conducted to locate boundaries of lakes from LANDSAT-1 imagery. The accuracy of the boundary detection algorithm was determined by comparing the area within boundaries of lakes located using digitized LANDSAT imagery with the area of the same lakes planimetered from imagery collected from an aircraft platform.

Myers, V. I.↗
NASA NTRS1974

Use of remote sensing techniques for inventorying and planning utilization of land resources in South Dakota

The basic procedures for interpreting remote sensing imagery to rapidly develop general soils and land use inventories were developed and utilized in Pennington County, South Dakota. These procedures and remote sensing data products were illustrated and explained to many user groups, some of whom are interested in obtaining similar data. The general soils data were integrated with land soils data supplied by the county director of equalization to prepare a land value map. A computer print-out of this map indicating a land value for each quarter section is being used in tax reappraisal of Pennington County. The land use data provided the land use planners with the present use of land in Pennington County. Additional uses of remote sensing applications are also discussed including tornado damage assessment, hail damage evaluation, and presentation of soil and land value information on base maps assembled from ERTS-1 imagery.

Myers, V. I.↗
NASA NTRS1972

A comparative study of nonparametric methods for pattern recognition

The applied research discussed in this report determines and compares the correct classification percentage of the nonparametric sign test, Wilcoxon's signed rank test, and K-class classifier with the performance of the Bayes classifier. The performance is determined for data which have Gaussian, Laplacian and Rayleigh probability density functions. The correct classification percentage is shown graphically for differences in modes and/or means of the probability density functions for four, eight and sixteen samples. The K-class classifier performed very well with respect to the other classifiers used. Since the K-class classifier is a nonparametric technique, it usually performed better than the Bayes classifier which assumes the data to be Gaussian even though it may not be. The K-class classifier has the advantage over the Bayes in that it works well with non-Gaussian data without having to determine the probability density function of the data. It should be noted that the data in this experiment was always unimodal.

Hahn, S. F.↗
NASA NTRS1972

Pattern recognition systems and procedures

The objectives of the pattern recognition tasks are to develop (1) a man-machine interactive data processing system; and (2) procedures to determine effective features as a function of time for crops and soils. The signal analysis and dissemination equipment, SADE, is being developed as a man-machine interactive data processing system. SADE will provide imagery and multi-channel analog tape inputs for digitation and a color display of the data. SADE is an essential tool to aid in the investigation to determine useful features as a function of time for crops and soils. Four related studies are: (1) reliability of the multivariate Gaussian assumption; (2) usefulness of transforming features with regard to the classifier probability of error; (3) advantage of selecting quantizer parameters to minimize the classifier probability of error; and (4) advantage of using contextual data. The study of transformation of variables (features), especially those experimental studies which can be completed with the SADE system, will be done.

Nelson, G. D.↗
NASA NTRS1972

Pattern recognition system and procedures

The ratio transformation technique is used to determine effective features as function of time in remote multiple sensing of crops and soils. The selection of quantizer parameters for a two-class recognition problem under the criteria of minimizing the probability of errors is also discussed.

Nelson, G. D.↗
NASA NTRS1970

Recognition of crops and soils by spot density measurements of imagery

Computerized techniques and methods were used to conduct preliminary soil and crop identification experiments. The soil identification experiment was conducted by making densitometer measurements on Ektachrome infrared film exposed at 14,000 feet. The density measurements were analyzed by plotting sample probability density functions, two-dimensional scatter plots, and the use of K-class I to determine the complete set of classification results for one, two, three and four features. Due to the presence of nineteen classes, crop identification experiments were more difficult to formulate. Classes of corn, fallow, harvested wheat, roadways, trees and water were classified 75 percent correct.

Nelson, G. D.↗