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Wang, C.

Publications and source records attributed to Wang, C..

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Exact-to-precision generalized perturbation for neutron transport calculation

This manuscript extends the exact-to-precision generalized perturbation theory (E{sub P}GPT), introduced previously, to neutron transport calculation whereby previous developments focused on neutron diffusion calculation only. The E{sub P}GPT collectively denotes new developments in generalized perturbation theory (GPT) that place premium on computational efficiency and defendable accuracy in order to render GPT a standard analysis tool in routine design and safety reactor calculations. EPGPT constructs a surrogate model with quantifiable accuracy which can replace the original neutron transport model for subsequent engineering analysis, e.g. functionalization of the homogenized few-group cross sections in terms of various core conditions, sensitivity analysis and uncertainty quantification. This is achieved by reducing the effective dimensionality of the state variable (i.e. neutron angular flux) by projection onto an active subspace. Confining the state variations to the active subspace allows one to construct a small number of what is referred to as the 'active' responses which are solely dependent on the physics model rather than on the responses of interest, the number of input parameters, or the number of points in the state phase space. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Effects of nanosecond-scale prepulse on generation of high-energy protons in target normal sheath acceleration

A pulse cleaner based on noncollinear optical-parametric amplification and second-harmonic generation processes is used to improve the contrast of a laser of peak intensity {approx}2 Multiplication-Sign 10{sup 19} W/cm{sup 2} to {approx}10{sup 11} at 100 ps before the peak of the main pulse. A 7 MeV proton beam is observed when a 2.5 {mu}m-thick Al foil is irradiated by this high-contrast laser. The maximum proton energy decreases to 2.9 MeV when a low-contrast ({approx}10{sup 8}) laser is used. Two-dimensional particle-in-cell simulations combined with MULTI simulations show that the maximum proton energy sensitively relies on the detecting direction. The ns-time-scale prepulse can bend a thin target before the main pulse arrives, which reduces maximum proton energy in the target normal sheath acceleration.

43 PARTICLE ACCELERATORS↗
DOE OSTI2012

Mu2e Conceptual Design Report

Mu2e at Fermilab will search for charged lepton flavor violation via the coherent conversion process mu- N --> e- N with a sensitivity approximately four orders of magnitude better than the current world's best limits for this process. The experiment's sensitivity offers discovery potential over a wide array of new physics models and probes mass scales well beyond the reach of the LHC. We describe herein the conceptual design of the proposed Mu2e experiment. This document was created in partial fulfillment of the requirements necessary to obtain DOE CD-1 approval, which was granted July 11, 2012.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

A reactor core on-line monitoring program - COMP

A program named COMP is developed for on-line monitoring PWRs' in-core power distribution in this paper. Harmonics expansion method is used in COMP. The Unit 1 reactor of Daya Bay Nuclear Power Plant (Daya Bay NPP) in China is considered for verification. The numerical results show that the maximum relative error between measurement and reconstruction results from COMP is less than 5%, and the computing time is short, indicating that COMP is capable for online monitoring PWRs. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Construction of accuracy-preserving surrogate for the eigenvalue radiation diffusion and/or transport problem

The construction of surrogate models for high fidelity models is now considered an important objective in support of all engineering activities which require repeated execution of the simulation, such as verification studies, validation exercises, and uncertainty quantification. The surrogate must be computationally inexpensive to allow its repeated execution, and must be computationally accurate in order for its predictions to be credible. This manuscript introduces a new surrogate construction approach that reduces the dimensionality of the state solution via a range-finding algorithm from linear algebra. It then employs a proper orthogonal decomposition-like approach to solve for the reduced state. The algorithm provides an upper bound on the error resulting from the reduction. Different from the state-of-the-art, the new approach allows the user to define the desired accuracy a priori which controls the maximum allowable reduction. We demonstrate the utility of this approach using an eigenvalue radiation diffusion model, where the accuracy is selected to match machine precision. Results indicate that significant reduction is possible for typical reactor assembly models, which are currently considered expensive given the need to employ very fine mesh many group calculations to ensure the highest possible fidelity for the downstream core calculations. Given the potential for significant reduction in the computational cost, we believe it is possible to rethink the manner in which homogenization theory is currently employed in reactor design calculations. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

An EPGPT-based approach for uncertainty quantification

Generalized Perturbation Theory (GPT) has been widely used by many scientific disciplines to perform sensitivity analysis and uncertainty quantification. This manuscript employs recent developments in GPT theory, collectively referred to as Exact-to-Precision Generalized Perturbation Theory (EPGPT), to enable uncertainty quantification for computationally challenging models, e.g. nonlinear models associated with many input parameters and many output responses and with general non-Gaussian parameters distributions. The core difference between EPGPT and existing GPT is in the way the problem is formulated. GPT formulates an adjoint problem that is dependent on the response of interest. It tries to capture via the adjoint solution the relationship between the response of interest and the constraints on the state variations. EPGPT recasts the problem in terms of a smaller set of what is referred to as the 'active' responses which are solely dependent on the physics model and the boundary and initial conditions rather than on the responses of interest. The objective of this work is to apply an EPGPT methodology to propagate cross-sections variations in typical reactor design calculations. The goal is to illustrate its use and the associated impact for situations where the typical Gaussian assumption for parameters uncertainties is not valid and when nonlinear behavior must be considered. To allow this demonstration, exaggerated variations will be employed to stimulate nonlinear behavior in simple prototypical neutronics models. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2006

Plasmapause Equatorial Shape Determination via the Minimum L Algorithm: Description and Evaluation

The Minimum L Algorithm for determining the equatorial shape of the plasmapause using NASA IMAGE Extreme Ultraviolet (EUV) imagery is described and analyzed. The algorithm operates without human intervention given a single EUV image in which the plasmasphere silhouette boundary has been identified. For each line of sight (LOS) through pixels on the 13 plasmasphere silhouette boundary, the algorithm first finds all magnetic dipole 14 field lines intersected by the LOS and then returns as the plasmasphere s boundary the field line with the minimum L value. The analysis considers the reasonableness, applicability, and accuracy of the algorithm and contrasts it with 17 the well-known Edge Algorithm is also introduced. Application of all three algorithms to real EUV imagery is demonstrated.

Newman, Timothy S.↗
NASA NTRS2004

Data assimilation of ground GPG total electron content into a physics-based ionosheric model by use of the Kalman filter

A three-dimensional (3-D) Global Assimilative Ionospheric Model (GAIM) is currently being developed by a joint University of Southern California and Jet Propulsion Laboratory (JPL) team. To estimate the electron density on a global grid, GAIM uses a first-principles ionospheric physics model and the Kalman filter as one of its possible estimation techniques.

ionosphere forecast data assimilation Kalman filte↗