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Computation of analytical bounds for cross section self-shielding factors

Description: The shielding factor method (SFM) is a frequently used economical procedure for computing the effective multigroup cross sections needed in reactor analysis. While initially developed and employed in codes used by the fast reactor community, the method has been receiving increased attention in recent years from the electric utility industry, for applications to power reactors. A fundamental problem regarding the method's applicability is to determine the limits of the range of values within which a cross section shielding factor is restricted, and whether these limits are physically meaningful. In a previous paper strict upper and lower bounds for the transport f-factor and for the sum of reaction f-factors were derived and discussed. The purpose of the present work is to present extensions of the methodology used for the upper and lower bounds of the transport f-factor and reaction f-factors.
Date: January 1, 1979
Creator: Barhen, J. & Cacuci, D.G.
Partner: UNT Libraries Government Documents Department

Benchmarking of EPRI-cell epithermal methods with the point-energy discrete-ordinates code (OZMA)

Description: The purpose of the present study is to benchmark E-C resonance-shielding and cell-averaging methods against a rigorous deterministic solution on a fine-group level (approx. 30 groups between 1 eV and 5.5 keV). The benchmark code used is OZMA, which solves the space-dependent slowing-down equations using continuous-energy discrete ordinates or integral transport theory to produce fine-group cross sections. Results are given for three water-moderated lattices - a mixed oxide, a uranium method, and a tight-pitch high-conversion uranium oxide configuration. The latter two lattices were chosen because of the strong self shielding of the /sup 238/U resonances.
Date: January 1, 1982
Creator: Williams, M.L.; Wright, R.Q.; Barhen, J. & Rothenstein, W.
Partner: UNT Libraries Government Documents Department

Nonlinear sensitivity and uncertainty analysis in support of the blowdown heat transfer program. [Test 177 at Thermal-Hydraulic Test Facility]

Description: A nonlinear uncertainty analysis methodology based on the use of first and second order sensitivity coefficients is presented. As a practical demonstration, an uncertainty analysis of several responses of interest is performed for Test 177, which is part of a series of tests conducted at the Thermal-Hydraulic Test Facility (THTF) of the ORNL Engineering Technology Division Pressurized Water Reactor-Blowdown Heat Transfer (PWR-BDHT) program. These space- and time-dependent responses are: mass flow rate, temperature, pressure, density, enthalpy, and water qualtiy - in several volumetric regions of the experimental facility. The analysis shows that, over parts of the transient, the responses behave as linear functions of the input parameters; in these cases, their standard deviations are of the same order of magnitude as those of the input parameters. Otherwise, the responses exhibit nonlinearities and their standard deviations are considerably larger. The analysis also shows that the degree of nonlinearity of the responses is highly dependent on their volumetric locations.
Date: November 1, 1980
Creator: Ronen, Y.; Bjerke, M.A.; Cacuci, D.G. & Barhen, J.
Partner: UNT Libraries Government Documents Department

Global optimization for multisensor fusion in seismic imaging

Description: The accurate imaging of subsurface structures requires the fusion of data collected from large arrays of seismic sensors. The fusion process is formulated as an optimization problem and yields an extremely complex energy surface. Due to the very large number of local minima to be explored and escaped from, the seismic imaging problem has typically been tackled with stochastic optimization methods based on Monte Carlo techniques. Unfortunately, these algorithms are very cumbersome and computationally intensive. Here, the authors present TRUST--a novel deterministic algorithm for global optimization that they apply to seismic imaging. The excellent results demonstrate that TRUST may provide the necessary breakthrough to address major scientific and technological challenges in fields as diverse as seismic modeling, process optimization, and protein engineering.
Date: June 1, 1997
Creator: Barhen, J.; Protopopescu, V. & Reister, D.
Partner: UNT Libraries Government Documents Department

Spectral imaging applications: Remote sensing, environmental monitoring, medicine, military operations, factory automation and manufacturing

Description: This paper reviews the activities at OKSI related to imaging spectroscopy presenting current and future applications of the technology. The authors discuss the development of several systems including hardware, signal processing, data classification algorithms and benchmarking techniques to determine algorithm performance. Signal processing for each application is tailored by incorporating the phenomenology appropriate to the process, into the algorithms. Pixel signatures are classified using techniques such as principal component analyses, generalized eigenvalue analysis and novel very fast neural network methods. The major hyperspectral imaging systems developed at OKSI include the Intelligent Missile Seeker (IMS) demonstration project for real-time target/decoy discrimination, and the Thermal InfraRed Imaging Spectrometer (TIRIS) for detection and tracking of toxic plumes and gases. In addition, systems for applications in medical photodiagnosis, manufacturing technology, and for crop monitoring are also under development.
Date: December 31, 1996
Creator: Gat, N.; Subramanian, S.; Barhen, J. & Toomarian, N.
Partner: UNT Libraries Government Documents Department

On the parallelization of the acoustic wave equation with absorbing boundary conditions

Description: Many practical problems involve wave propagation through atmosphere, oceans, or terrestrial crust. Modeling and analysis of these problems is usually done in (semi)infinite domains, but numerical calculations obviously impose restriction to finite domains. To mimic the actual behavior in the (semi)infinite medium, artificial absorbing boundary conditions are imposed at the boundaries, whereby waves can only exit, but not enter the finite computational domain. Efficient absorbing boundary conditions are difficult to analyze and costly to run. In particular, it is of interest to assess whether the wave equation with (approximate or exact) absorbing boundary conditions admits a suitable diagonalization. This would open the possibility for parallelizing many important numerical codes used in applications. In this paper the authors propose a set of stable, local, absorbing boundary conditions for the discrete acoustic wave equation. They show that the acoustic wave equation with absorbing boundary conditions cannot be exactly diagonalized.
Date: July 1, 1998
Creator: White, C.T.; Protopopescu, V.A. & Barhen, J.
Partner: UNT Libraries Government Documents Department

Single-Iteration Learning Algorithm for Feed-Forward Neural Networks

Description: A new methodology for neural learning is presented, whereby only a single iteration is required to train a feed-forward network with near-optimal results. To this aim, a virtual input layer is added to the multi-layer architecture. The virtual input layer is connected to the nominal input layer by a specird nonlinear transfer function, and to the fwst hidden layer by regular (linear) synapses. A sequence of alternating direction singular vrdue decompositions is then used to determine precisely the inter-layer synaptic weights. This algorithm exploits the known separability of the linear (inter-layer propagation) and nonlinear (neuron activation) aspects of information &ansfer within a neural network.
Date: July 31, 1999
Creator: Barhen, J.; Cogswell, R. & Protopopescu, V.
Partner: UNT Libraries Government Documents Department

DeepNet: An Ultrafast Neural Learning Code for Seismic Imaging

Description: A feed-forward multilayer neural net is trained to learn the correspondence between seismic data and well logs. The introduction of a virtual input layer, connected to the nominal input layer through a special nonlinear transfer function, enables ultrafast (single iteration), near-optimal training of the net using numerical algebraic techniques. A unique computer code, named DeepNet, has been developed, that has achieved, in actual field demonstrations, results unattainable to date with industry standard tools.
Date: July 10, 1999
Creator: Barhen, J.; Protopopescu, V. & Reister, D.
Partner: UNT Libraries Government Documents Department

Systematic methodology for the reduction of uncertainties in transient thermal-hydraulics by using in-bundle measurement data

Description: The development of a systematic methodology for the reduction of uncertainties in transient thermal-hydraulics by using in-bundle measurement data is presented. The adjustment of the system parameters and responses and the reduction in their respective uncertainties is treated as a time-dependent constrained minimization problem. An on-line (i.e., real time) large scale optimization scheme is also outlined. Although formulated within the framework of reactor safety analysis, the proposed methodology can be directly applied to other areas, for instance to time-dependent fuel cycle optimization and uncertainty analysis.
Date: January 1, 1980
Creator: Barhen, J.; Cacuci, D.G.; Wagschal, J.J. & Mullins, C.B.
Partner: UNT Libraries Government Documents Department

Minimal cut-set methodology for artificial intelligence applications

Description: This paper reviews minimal cut-set theory and illustrates its application with an example. The minimal cut-set approach uses disjunctive normal form in Boolean algebra and various Boolean operators to simplify very complicated tree structures composed of AND/OR gates. The simplification process is automated and performed off-line using existing computer codes to implement the Boolean reduction on the finite, but large tree structure. With this approach, on-line expert diagnostic systems whose response time is critical, could determine directly whether a goal is achievable by comparing the actual system state to a concisely stored set of preprocessed critical state elements.
Date: January 1, 1984
Creator: Weisbin, C.R.; de Saussure, G.; Barhen, J.; Oblow, E.M. & White, J.C.
Partner: UNT Libraries Government Documents Department

Oil reservoir properties estimation using neural networks

Description: This paper investigates the applicability as well as the accuracy of artificial neural networks for estimating specific parameters that describe reservoir properties based on seismic data. This approach relies on JPL`s adjoint operators general purpose neural network code to determine the best suited architecture. The authors believe that results presented in this work demonstrate that artificial neural networks produce surprisingly accurate estimates of the reservoir parameters.
Date: February 1, 1997
Creator: Toomarian, N.B.; Barhen, J.; Glover, C.W. & Aminzadeh, F.
Partner: UNT Libraries Government Documents Department

Neural network accuracy measures and data transforms applied to the seismic parameter estimation problem

Description: The accuracy of an artificial neural network (ANN) algorithm is a crucial issue in the estimation of an oil field reservoir`s properties from remotely sensed seismic data. This paper demonstrates the use of the k-fold cross validation technique to obtain confidence bounds on an ANN`s accuracy statistic from a finite sample set. In addition, we also show that an ANN`s classification accuracy is dramatically improved by transforming the ANN`s input feature space to a dimensionally smaller, new input space. The new input space represents a feature space that maximizes the linear separation between classes. Thus, the ANN`s convergence time and accuracy are improved because the ANN must merely find nonlinear perturbations to the starting linear decision boundaries. These techniques for estimating ANN accuracy bounds and feature space transformations are demonstrated on the problem of estimating the sand thickness in an oil field reservoir based only on remotely sensed seismic data.
Date: January 1, 1997
Creator: Glover, C.W.; Barhen, J.; Aminzadeh, F. & Toomarian, N.B.
Partner: UNT Libraries Government Documents Department

Chemical detection using the airborne thermal infrared imaging spectrometer (TIRIS)

Description: A methodology is described for an airborne, downlooking, longwave infrared imaging spectrometer based technique for the detection and tracking of plumes of toxic gases. Plumes can be observed in emission or absorption, depending on the thermal contrast between the vapor and the background terrain. While the sensor is currently undergoing laboratory calibration and characterization, a radiative exchange phenomenology model has been developed to predict sensor response and to facilitate the sensor design. An inverse problem model has also been developed to obtain plume parameters based on sensor measurements. These models, the sensors, and ongoing activities are described.
Date: April 1, 1997
Creator: Gat, N.; Subramanian, S.; Sheffield, M.; Erives, H. & Barhen, J.
Partner: UNT Libraries Government Documents Department

Application of Global Optimization to the Estimation of Surface-Consistent Residual Statics

Description: Since the objective function that is used to estimate surface-consistent residual statics can have many local maxima, a global optimization method is required to find the optimum values for the residual statics. As reported in several recent papers, we had developed a new method (TRUST) for solving global optimization problems and had demonstrated it was superior to all competing methods for a standard set of nonconvex benchmark problems. The residual statics problem can be very large with hundreds or thousands of parameters, and large global optimization problems are much harder to solve than small problems. To solve the very challenging residual statics problem, we have made several significant advances in the mathematical description of the residual statics problem (derivation of two novel stack power bounds and disaggregation of the original problem into a large number of small problems). Using the enhanced version of TRUST, we have performed extensive simulations on a realistic sample problem that had been artificially created by large static disruptions. Our simulations have demonstrated that TRUST can reach many plausible distinct ''solutions'' that could not be discovered by more conventional approaches. An unexpected result was that high values of the stack power may be eliminate cycle skips.
Date: October 1999
Creator: Reister, D. B.; Oblow, E. M.; Barhen, J. & DuBose, J. B.
Partner: UNT Libraries Government Documents Department

VITAMIN E: a multipurpose ENDF/B-V coupled neutron-gamma cross section library

Description: The US Department of Energy Office of Fusion Energy and the Division of Reactor Research and Technology jointly sponsored the development of a coupled fine-group cross section library (VITAMIN-C). The experience gained in the generation, validation, and utilization of the VITAMIN-C library along with its broad range of applicability has led to the request for updating this data set using ENDF/B-V. Additional support in this regard has been provided by the Defense Nuclear Agency (DNA) and by EPRI in support of weapons analyses and light water reactor shielding and dosimetry problems, respectively. The rationale for developing the multipurpose ENDF/B-V-based VITAMIN-E library is presented, with special emphasis on new models used in the data generation algorithms. The library specifications and testing procedures are also discussed in detail. The distribution of the VITAMIN-E library is currently subject to the same restrictions as the distribution of the ENDF/B-V data. 2 tables.
Date: January 1, 1979
Creator: Barhen, J.; Cacuci, D.G.; Ford, W.E. III; Roussin, R.W.; Wagschal, J.J.; Weisbin, C.R. et al.
Partner: UNT Libraries Government Documents Department

Optimization and geophysical inverse problems

Description: A fundamental part of geophysics is to make inferences about the interior of the earth on the basis of data collected at or near the surface of the earth. In almost all cases these measured data are only indirectly related to the properties of the earth that are of interest, so an inverse problem must be solved in order to obtain estimates of the physical properties within the earth. In February of 1999 the U.S. Department of Energy sponsored a workshop that was intended to examine the methods currently being used to solve geophysical inverse problems and to consider what new approaches should be explored in the future. The interdisciplinary area between inverse problems in geophysics and optimization methods in mathematics was specifically targeted as one where an interchange of ideas was likely to be fruitful. Thus about half of the participants were actively involved in solving geophysical inverse problems and about half were actively involved in research on general optimization methods. This report presents some of the topics that were explored at the workshop and the conclusions that were reached. In general, the objective of a geophysical inverse problem is to find an earth model, described by a set of physical parameters, that is consistent with the observational data. It is usually assumed that the forward problem, that of calculating simulated data for an earth model, is well enough understood so that reasonably accurate synthetic data can be generated for an arbitrary model. The inverse problem is then posed as an optimization problem, where the function to be optimized is variously called the objective function, misfit function, or fitness function. The objective function is typically some measure of the difference between observational data and synthetic data calculated for a trial model. However, because of incomplete and inaccurate data, the ...
Date: October 1, 2000
Creator: Barhen, J.; Berryman, J.G.; Borcea, L.; Dennis, J.; de Groot-Hedlin, C.; Gilbert, F. et al.
Partner: UNT Libraries Government Documents Department

Nanoscale Science, Engineering and Technology Research Directions

Description: This report describes important future research directions in nanoscale science, engineering and technology. It was prepared in connection with an anticipated national research initiative on nanotechnology for the twenty-first century. The research directions described are not expected to be inclusive but illustrate the wide range of research opportunities and challenges that could be undertaken through the national laboratories and their major national scientific user facilities with the support of universities and industry.
Date: January 1, 1999
Creator: Lowndes, D. H.; Alivisatos, A. P.; Alper, M.; Averback, R. S.; Jacob Barhen, J.; Eastman, J. A. et al.
Partner: UNT Libraries Government Documents Department