[en] Three-dimensional finite element calculations for the response of the prestressed concrete reactor vessel for the 2240 MW HTGR which evaluated the stress distributions and concentrations were accomplished. Constitutive equations utilized in this evaluation were linear elastic, Von Mises elastic-plastic and the empirical Kotsovos-Newman concrete fit with and without steel reinforcing. Ultimate values of the internal pressures without initial prestress were obtained. Also stresses in the annular concrete retaining cover over the stream generator were evaluated

[en] Calculated response for the Indian Point reactor containment building to static internal pressure and one case of a dynamic pressure representing hydrogen combustion and detonation are presented. Comparison of the potential failure modes is made. 9 figures

[en] Several data-classification schemes were developed by the Los Alamos National Laboratory to detect potential uranium mineralization in the Montrose 1⁰ x 2⁰ quadrangle, Colorado. A first step was to develop and refine the techniques necessary to digitize, integrate, and register various large geological, geochemical, and geophysical data sets, including Landsat 2 imagery, for the Montrose quadrangle, Colorado, using a grid resolution of 1 km. All data sets for the Montrose quadrangle were registered to the Universal Transverse Mercator projection. The data sets include hydrogeochemical and stream sediment analyses for 23 elements, uranium-to-thorium ratios, airborne geophysical survey data, the locations of 90 uranium occurrences, a geologic map and Landsat 2 (bands 4 through 7) imagery. Geochemical samples were collected from 3965 locations in the 19 200 km² quadrangle; aerial data were collected on flight lines flown with 3 to 5 km spacings. These data sets were smoothed by universal kriging and interpolated to a 179 x 119 rectangular grid. A mylar transparency of the geologic map was prepared and digitized. Locations for the known uranium occurrences were also digitized. The Landsat 2 imagery was digitally manipulated and rubber-sheet transformed to quadrangle boundaries and bands 4 through 7 were resampled to both a 1-km and 100-m resolution. All possible combinations of three, for all data sets, were examined for general geologic correlations by utilizing a color microfilm output. Subsets of data were further examined for selected test areas. Two classification schemes for uranium mineralization, based on selected test areas in both the Cochetopa and Marshall Pass uranium districts, are presented. Areas favorable for uranium mineralization, based on these schemes, were identified and are discussed

[en] At the Los Alamos National Laboratory the finite element method has been used to predict the response of several types of concrete structures to severe accident conditions that could occur at nuclear power plants. Both prestressed and normally reinforced concrete structures have been analyzed to determine their responses to seismic events and quasistatic and dynamic pressure loads. Structures analyzed include concete containment buildings, prestressed concrete reactor vessels, and concrete shear walls. Finite element models of the structures have been developed with both the NONSAP-C and ADINA computer codes. Because the purpose of our analyses has generally been to determine failure loads and modes of failure, calculations are carried out well into the nonlinear range. Therefore, the computer codes have to include concrete constitutive models that treat concrete cracking and crushing and other nonlinear effects. In the paper we describe the concrete constitutive models and their application and discuss the shortcomings of the models in the structural simulations. We also discuss the numerical procedures used in our analyses and suggest some improvements that should make the analysis of concrete structures numerically stable to the point of failure. In several of the analyses presented, we compare computed response with measured response through at least the linear range. Our analysis of the shear wall response includes comparisons with test data to failure