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  • 1
    Electronic Resource
    Electronic Resource
    Neural network models of potential energy surfaces (1995)
    College Park, Md. : American Institute of Physics (AIP)
    The Journal of Chemical Physics 103 (1995), S. 4129-4137 
    Details
    ISSN: 1089-7690
    Source: AIP Digital Archive
    Topics: Physics , Chemistry and Pharmacology
    Notes: Neural networks provide an efficient, general interpolation method for nonlinear functions of several variables. This paper describes the use of feed-forward neural networks to model global properties of potential energy surfaces from information available at a limited number of configurations. As an initial demonstration of the method, several fits are made to data derived from an empirical potential model of CO adsorbed on Ni(111). The data are error-free and geometries are selected from uniform grids of two and three dimensions. The neural network model predicts the potential to within a few hundredths of a kcal/mole at arbitrary geometries. The accuracy and efficiency of the neural network in practical calculations are demonstrated in quantum transition state theory rate calculations for surface diffusion of CO/Ni(111) using a Monte Carlo/path integral method. The network model is much faster to evaluate than the original potential from which it is derived. As a more complex test of the method, the interaction potential of H2 with the Si(100)-2×1 surface is determined as a function of 12 degrees of freedom from energies calculated with the local density functional method at 750 geometries. The training examples are not uniformly spaced and they depend weakly on variables not included in the fit. The neural net model predicts the potential at geometries outside the training set with a mean absolute deviation of 2.1 kcal/mole. © 1995 American Institute of Physics.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1063/1.469597
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  • 2
    Electronic Resource
    Electronic Resource
    The structure of variable property, compressible mixing layers in binary gas mixtures (1996)
    [S.l.] : American Institute of Physics (AIP)
    Physics of Fluids 8 (1996), S. 1945-1953 
    Details
    ISSN: 1089-7666
    Source: AIP Digital Archive
    Topics: Physics
    Notes: We present the results of a study of the structure of a parallel compressible mixing layer in a binary mixture of gases. The gases included in this study are hydrogen (H2), helium (He), nitrogen (N2), oxygen (O2), neon (Ne) and argon (Ar). Profiles of the variation of the Lewis and Prandtl numbers across the mixing layer for all 30 combinations of gases are given. It is shown that the Lewis number can vary by as much as a factor of 8 and the Prandtl number by a factor of 2 across the mixing layer. Thus assuming constant values for the Lewis and Prandtl numbers of a binary gas mixture in the shear layer, as is done in many theoretical studies, is a poor approximation. We also present profiles of the velocity, mass fraction, temperature and density for representative binary gas mixtures at zero and supersonic Mach numbers. We show that the shape of these profiles is strongly dependent on which gases are in the mixture as well as on whether the denser gas is in the fast stream or the slow stream. © 1996 American Institute of Physics.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1063/1.869103
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  • 3
    Electronic Resource
    Electronic Resource
    One- and two-dimensional simulations of ultra-short-pulse reflectometry (abstract) : Proceedings of the eleventh topical conference on high temperature plasma diagnostics (1997)
    [S.l.] : American Institute of Physics (AIP)
    Review of Scientific Instruments 68 (1997), S. 477-477 
    Details
    ISSN: 1089-7623
    Source: AIP Digital Archive
    Topics: Physics , Electrical Engineering, Measurement and Control Technology
    Notes: Ultra-short-pulse reflectometry is studied by means of the numerical integration of one- and two-dimensional full-wave equations for ordinary and extraordinary modes propagating in a plasma. The numerical calculations illustrate the use of the reflection of ultra-short-pulse microwaves as an effective probe of the density or magnetic profile in the presence of density or magnetic fluctuations in the plasma. Bragg resonance effects can be identified in the reflected signals, which give information on fluctuations. It is also demonstrated that ultra-short-pulse reflectometry can be used to perform correlation reflectometry measurements in which correlation lengths for density fluctuations are deduced from the observed cross-correlation function of phase shifts as a function of frequency. © 1997 American Institute of Physics.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1063/1.1148224
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  • 4
    Electronic Resource
    Electronic Resource
    One- and two-dimensional simulations of ultra-short-pulse reflectometry (1997)
    [S.l.] : American Institute of Physics (AIP)
    Review of Scientific Instruments 68 (1997), S. 1238-1243 
    Details
    ISSN: 1089-7623
    Source: AIP Digital Archive
    Topics: Physics , Electrical Engineering, Measurement and Control Technology
    Notes: Ultra-short-pulse reflectometry is studied by means of the numerical integration of one- and two-dimensional full-wave equations for ordinary and extraordinary modes propagating in a plasma. The numerical calculations illustrate the use of the reflection of ultra-short-pulse microwaves as an effective probe of the density or magnetic profile in the presence of density or magnetic fluctuations in the plasma. Bragg resonance effects can be identified in the reflected signals, which give information on fluctuations. It is also demonstrated that ultra-short-pulse reflectometry can be used to perform correlation reflectometry measurements in which correlation lengths for density fluctuations are deduced from the observed cross-correlation function of phase shifts as a function of frequency. © 1997 American Institute of Physics.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1063/1.1147896
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