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Stochastic Methods For Uncertainty Quantification In Radiation Transport, Erin D. Fichtl Jul 2009

Stochastic Methods For Uncertainty Quantification In Radiation Transport, Erin D. Fichtl

Nuclear Engineering ETDs

The use of stochastic spectral expansions, specifically generalized polynomial chaos (gPC) and Karhunen-Loeve (KL) expansions, is investigated for uncertainty quantification in radiation transport. The gPC represents second-order random processes in terms of an expansion of orthogonal polynomials of random variables. The KL expansion is a Fourier-type expansion that represents a second-order random process with known covariance function in terms of a set of uncorrelated random variables and the eigenmodes of the covariance function. The flux and, in multiplying materials, the k-eigenvalue, which are the problem unknowns, are always expanded in a gPC expansion since their covariance functions are also unknown. …


Time Dependent Non-Extinction Probability For Fast Burst Reactors, Michael Gregson Jul 2009

Time Dependent Non-Extinction Probability For Fast Burst Reactors, Michael Gregson

Nuclear Engineering ETDs

Sandia National Laboratories has successfully operated fast burst reactors over the past four decades. Fast burst reactors refer to a type of reactor that is able to achieve intense neutron pulses in very short periods of time using fissile material. Typically these systems are comprised of enriched metallic uranium fuel. During operation of a fast burst reactor, a phenomena known as a pre-initiation has been known to take place. A pre-initiation occurs when the neutron population exceeds some fiducial prior to achieving the final reactivity state in a pulse operation. Reactivity is determined from the physical configuration of the reactor …


Extended Kalman Filter Implementation For The Khepera Ii Mobile Robot, Thomas J. Otahal, Herbert G. Tanner Jan 2009

Extended Kalman Filter Implementation For The Khepera Ii Mobile Robot, Thomas J. Otahal, Herbert G. Tanner

Mechanical Engineering Faculty Publications

The accurate estimation of robot position and orientation in real-time is one of the fundamental challenges in mobile robotics. The Extended Kalman Filter is a nonlinear real-time recursive time domain filter that combines available sensor data to produce an accurate estimate of state, and has been successfully applied to the localization problem in mobile robotics and aircraft navigation. This report describes an Extended Kalman Filter implementa- tion for the Khepera II mobile robotics platform that seeks to produce accurate localization estimates in real-time using wheel odometry data, IR sensor range data, and compass heading data.


An Introduction To Dezert-Smarandache Theory (Dsmt), Jean Dezert, Florentin Smarandache Jan 2009

An Introduction To Dezert-Smarandache Theory (Dsmt), Jean Dezert, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

The management and combination of uncertain, imprecise, fuzzy and even paradoxical or highly conflicting sources of information has always been, and still remains today, of primal importance for the development of reliable modern information systems involving artificial reasoning. In this introduction, we present a survey of our recent theory of plausible and paradoxical reasoning, known as Dezert-Smarandache Theory (DSmT), developed for dealing with imprecise, uncertain and conflicting sources of information. We focus our presentation on the foundations of DSmT and on its most important rules of combination, rather than on browsing specific applications of DSmT available in literature. Several simple …