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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Multi-Physics Simulations of Heat Pipe Micro Reactor

System Analysis Module (SAM) is under development at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. This report presents the development of new capabilities for modeling the heat pipe type reactor systems. The need for power at remote locations away from a reliable electrical grid is an important niche for nuclear energy. Heat pipe-cooled fast-spectrum nuclear reactors are well suited for these applications. The key feature of the heat pipe reactors is the use of heat pipes for heat removal from the reactor core. The heat pipe makes use of the phase change of the working fluid and transports a large amount of heat from the evaporator to the condensation end with very small temperature drops. In contrast to the traditional nuclear reactor system that makes use of pumped loop for extracting the thermal power, the heat pipe reactors make use of hundreds of heat pipes for removing the thermal power (including the decay heat) passively. This could potentially significantly improve the reliability and safety of the reactor systems. The essential part in the analysis of a heat pipe type reactor is the modeling of heat transport inside the heat pipe. The capability of SAM was extended to enable the modeling of the conventional heat pipe. The full suite of non-LWR codes for confirmatory analysis at NRC is known as the Comprehensive Reactor Analysis Bundle (CRAB). It makes use of existing NRC codes, and integrates them with several codes developed through the DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In this report, the heat pipe micro reactor is simulated using three submodules under CRAB. The MAMMOTH module is used to simulate the reactor kinetics behavior of the micro reactor; the SAM module is used to simulate the heat conduction in the reactor core and heat removal through the heat pipe heat exchangers and Reactor Cavity Cooling System (RCCS); and the MOOSE Tensor Mechanics module is used to simulate the thermal expansion of the reactor cores. The different sub-models are coupled together using MOOSE’s MultiApp system and executed using the BlueCrab application. The new capability has been demonstrated by a steady-state operation analysis, a failure of a single central heat pipe transient analysis, and a loss of heat sink transient analysis. The fully coupled model is shown to work well.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Holistic Fuel Cell Electric Vehicle/Hydrogen Station Optimization Model (CRADA CRD-18-00745 Final Report)

The National Renewable Energy Lab (NREL), Argonne National Lab (ANL), Sandia National Lab (SNL), and Frontier Energy, Inc comprise a team that will perform a review of currently available models that can simulate both a hydrogen station and a fuel cell electric vehicle (FCEV), and whose owners are willing to make them available freely. We will then down select to a single model or model pair, secure agreements for their free use, and validate the resulting model or coupled models. For example, we may evaluate an existing 1-D hydrogen fueling model developed by Kyushu University for the Japanese New Energy and Industrial Technology Development Organization (NEDO). The validation will take place using data from various sources, potentially including the European Joint Research Center (JRC) HyTransfer project, SAE testing performed by Powertech to validate SAE J2601, and whole-station validation using the NREL’s Hydrogen Infrastructure Testing and Research Facility (HITRF). The team will make the model and all the validation data open to the public at the end of the project.

1-D hydrogen fueling model↗
NASA NTRS1996

High Temperature Degradation Mechanisms in Polymer Matrix Composites

Polymer matrix composites are increasingly used in demanding structural applications in which they may be exposed to harsh environments. The durability of such materials is a major concern, potentially limiting both the integrity of the structures and their useful lifetimes. The goal of the current investigation is to develop a mechanism-based model of the chemical degradation which occurs, such that given the external chemical environment and temperatures throughout the laminate, laminate geometry, and ply and/or constituent material properties, we can calculate the concentration of diffusing substances and extent of chemical degradation as functions of time and position throughout the laminate. This objective is met through the development and use of analytical models, coupled to an analysis-driven experimental program which offers both quantitative and qualitative information on the degradation mechanism. Preliminary analyses using a coupled diffusion/reaction model are used to gain insight into the physics of the degradation mechanisms and to identify crucial material parameters. An experimental program is defined based on the results of the preliminary analysis which allows the determination of the necessary material coefficients. Thermogravimetric analyses are carried out in nitrogen, air, and oxygen to provide quantitative information on thermal and oxidative reactions. Powdered samples are used to eliminate diffusion effects. Tests in both inert and oxidative environments allow the separation of thermal and oxidative contributions to specimen mass loss. The concentration dependency of the oxidative reactions is determined from the tests in pure oxygen. Short term isothermal tests at different temperatures are carried out on neat resin and unidirectional macroscopic specimens to identify diffusion effects. Mass loss, specimen shrinkage, the formation of degraded surface layers and surface cracking are recorded as functions of exposure time. Geometry effects in the neat resin, and anisotropic diffusion effects in the composites, are identified through the use of specimens with different aspect ratios. The data is used with the model to determine reaction coefficients and effective diffusion coefficients. The empirical and analytical correlations confirm the preliminary model results which suggest that mass loss at lower temperatures is dominated by oxidative reactions and that these reaction are limited by diffusion of oxygen from the surface. The mechanism-based model is able to successfully capture the basic physics of the degradation phenomena under a wide range of test conditions. The analysis-based test design is successful in separating out oxidative, thermal, and diffusion effects to allow the determination of material coefficients. This success confirms the basic picture of the process; however, a more complete understanding of some aspects of the physics are required before truly predictive capability can be achieved.

Cunningham, Ronan A.↗
NASA NTRS1997

High Temperature Degradation Mechanisms in Polymer Matrix Composites

Polymer matrix composites are increasingly used in demanding structural applications in which they may be exposed to harsh environments. The durability of such materials is a major concern, potentially limiting both the integrity of the structures and their useful lifetimes. The goal of the current investigation is to develop a mechanism-based model of the chemical degradation which occurs, such that given the external chemical environment and temperatures throughout the laminate, laminate geometry, and ply and/or constituent material properties, we can calculate the concentration of diffusing substances and extent of chemical degradation as functions of time and position throughout the laminate. This objective is met through the development and use of analytical models, coupled to an analysis-driven experimental program which offers both quantitative and qualitative information on the degradation mechanism. Preliminary analyses using coupled diffusion/reaction model are used to gain insight into the physics of the degradation mechanisms and to identify crucial material parameters. An experimental program is defined based on the results of the preliminary analysis which allows the determination of the necessary material coefficients. Thermogravimetric analyses are carried out in nitrogen, air, and oxygen to provide quantitative information on thermal and oxidative reactions. Powdered samples are used to eliminate diffusion effects. Tests in both inert and oxidative environments allow the separation of thermal and oxidative contributions to specimen mass loss. The concentration dependency of the oxidative reactions is determined from the tests in pure oxygen. Short term isothermal tests at different temperatures are carried out on neat resin and unidirectional macroscopic specimens to identify diffusion effects. Mass loss, specimen shrinkage, the formation of degraded surface layers and surface cracking are recorded as functions of exposure time. Geometry effects in the neat resin, and anisotropic diffusion effects in the composites, are identified through the use of specimens with different aspect ratios. The data is used with the model to determine reaction coefficients and effective diffusion coefficients. The empirical and analytical correlations confirm the preliminary model results which suggest that mass loss at lower temperatures is dominated by oxidative reactions and that these reaction are limited by diffusion of oxygen from the surface. The mechanism-based model is able to successfully capture the basic physics of the degradation phenomena under a wide range of test conditions. The analysis-based test design is successful in separating out oxidative, thermal, and diffusion effects to allow the determination of material coefficients. This success confirms the basic picture of the process; however, a more complete understanding of some aspects of the physics are required before truly predictive capability can be achieved.

Cunningham, Ronan A.↗
NASA NTRS2010

Space Weather Models, Tools and Services at the Community Coordinated Modeling Center

The Community Coordinated Modeling center (CCMC) is a multi-agency partnership to support the research and developmental work necessary to substantially increase space weather modeling capabilities and to facilitate advanced models deployment in forecasting operations. The CCMC conducts unbiased model testing and validation and evaluates model readiness for operational environment. Space weather models and coupled model chains hosted at the CCMC range from the solar corona to the Earth's upper atmosphere. CCMC has developed a number of real-time modeling systems, as well as a large number of modeling and data products tailored to address the space weather needs of NASA's robotic missions. The presentation will demonstrate the rapid progress towards development the system allowing using products derived from space weather models in applications associated with National Space Weather needs. The adaptable Integrated Space Weather Analysis (ISWA) System developed at CCMC for NASA-relevant space weather information combines forecasts based on advanced space weather models hosted at CCMC with concurrent space environment information. The system is also enabling post-impact analysis and flexible dissemination of space weather information.

Kuznetsova, M. M.↗
NASA NTRS2011

Validation of Space Weather Models at Community Coordinated Modeling Center

The Community Coordinated Modeling Center (CCMC) is a multi-agency partnership to support the research and developmental work necessary to substantially increase space weather modeling capabilities and to facilitate advanced models deployment in forecasting operations. Space weather models and coupled model chains hosted at the CCMC range from the solar corona to the Earth's upper atmosphere. CCMC has developed a number of real-time modeling systems, as well as a large number of modeling and data products tailored to address the space weather needs of NASA's robotic missions. The CCMC conducts unbiased model testing and validation and evaluates model readiness for operational environment. CCMC has been leading recent comprehensive modeling challenges under GEM, CEDAR and SHINE programs. The presentation will focus on experience in carrying out comprehensive and systematic validation of large sets of. space weather models

Kuznetsova, M. M.↗
DOE OSTI2018

Impacts of Broad-Scale Surface Freshening of the Southern Ocean in a Coupled Climate Model

The Southern Ocean surface has freshened in recent decades, increasing water column stability and reducing upwelling of warmer subsurface waters. The majority of CMIP5 models underestimate or fail to capture this historical surface freshening, yet little is known about the impact of this model bias on regional ocean circulation and hydrography. Here experiments are performed using a global coupled climate model with additional freshwater applied to the Southern Ocean to assess the influence of recent surface freshening. The simulations explore the impact of persistent and long-term broad-scale freshening as a result of processes including precipitation minus evaporation changes. Thus, unlike previous studies, the freshening is applied as far north as 55°S, beyond the Antarctic ice margin. It is found that imposing a large-scale surface freshening causes a surface cooling and sea ice increase under preindustrial conditions, because of a reduction in ocean convection and weakened entrainment of warm subsurface waters into the surface ocean. This is consistent with intermodel relationships between CMIP5 models and the simulations, suggesting that models with larger surface freshening also exhibit stronger surface cooling and increased sea ice. Additional experiments are conducted with surface salinity restoration applied to capture observed regional salinity trends. Remarkably, without any mechanical wind trend forcing, these simulations accurately represent the spatial pattern of observed surface temperature and sea ice trends around Antarctica. This study highlights the importance of accurately simulating changes in Southern Ocean salinity to capture changes in ocean circulation, sea surface temperature, and sea ice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Lessons learned in coupling atmospheric models across scales for onshore and offshore wind energy

Abstract. The Mesoscale to Microscale Coupling team, part of the U.S. Department of Energy Atmosphere to Electrons (A2e) initiative, has studied various important challenges related to coupling mesoscale models to microscale models for the use case of wind energy development and operation. Several coupling methods and techniques for generating turbulence at the microscale that is subgrid to the mesoscale have been evaluated for a variety of cases. Case studies included flat-terrain, complex-terrain, and offshore environments. Methods were developed to bridge the terra incognita, which scales from about 100 m through the depth of the boundary layer. The team used wind-relevant metrics and archived code, case information, and assessment tools and is making those widely available. Lessons learned and discerned best practices are described in the context of the cases studied for the purpose of enabling further deployment of wind energy.

17 WIND ENERGY↗
DOE OSTI2019

Coupled Geomechanical Modeling to Assess Cap Rock Integrity and Mechanical Fault Stability: Application to Farnsworth Field Unit Project

Abstract The SWP project is located in a mature waterflood undergoing conversion to CO2-WAG operations in the Farnsworth, Texas, USA. Anthropogenic CO2 is sourced from a fertilizer and an ethanol plant. This work utilizes Farnsworth’s full-field, history-matched, compositional hydrodynamic coupled geomechanical model for assessing the impact of stress changes observed through the history matched field life. Production and injection induced stress changes, fault stability and caprock integrity investigations are performed to project the potential for fault reactivation and the loss of caprock integrity under shear failure. A static mechanical earth model (MEM) was constructed for use in transient coupled geomechanical model based on the existing Southwest Regional Partnership (SWP) geological model. The static MEM inherits the stratigraphic and structural features of the geologic model and incorporates additional overburden, underburden, and sideburden formations required to impose mechanical boundary conditions. Mechanical properties were distributed in the 3D MEM through integration of geophysical logs and 3-dimensional seismic elastic inversion properties using a combination of Bayesian and stochastic interpolation methods. These data are further enhanced by lab derived strength and failure criteria for the caprock interval. Additionally, interpreted faults and other geological features were included as part of the static structural framework to fully represent subsurface hydraulic and mechanical systems and appropriately integrate heterogeneity. Two-way coupling of hydrodynamic flow and geomechanical simulations incorporates the Kozeny-Carman relationship for updating permeability and is history matched through primary, secondary (waterflooding) and tertiary (CO2 WAG) recovery periods before performing a twenty year forecast. Two-way simulations are performed to understand the effective stress perturbations imposed by field operations: water injection and the more recent implementation of WAG. Evaluation of Mohr circles with liquid production and field pressure charts as well as slip tendency and distance to failure metrics indicate that neither our faults or cap rock are critically stressed. This paper presents the results of the Farnsworth initial attempts to integrate the seismic driven 3D MEM into coupled hydrodynamic geomechanical history match simulation workflow.

02 PETROLEUM↗
NASA NTRS2007

Parallelization of the Coupled Earthquake Model

This Web-based tsunami simulation system allows users to remotely run a model on JPL s supercomputers for a given undersea earthquake. At the time of this reporting, predicting tsunamis on the Internet has never happened before. This new code directly couples the earthquake model and the ocean model on parallel computers and improves simulation speed. Seismometers can only detect information from earthquakes; they cannot detect whether or not a tsunami may occur as a result of the earthquake. When earthquake-tsunami models are coupled with the improved computational speed of modern, high-performance computers and constrained by remotely sensed data, they are able to provide early warnings for those coastal regions at risk. The software is capable of testing NASA s satellite observations of tsunamis. It has been successfully tested for several historical tsunamis, has passed all alpha and beta testing, and is well documented for users.

Block, Gary↗
DOE OSTI2025

Dynamical coupled-channel models for hadron dynamics

Dynamical coupled-channel (DCC) approaches parametrize the interactions and dynamics of two and more hadrons and their response to different electroweak probes. The inclusion of unitarity, three-body channels, and other properties from scattering theory allows for a reliable extraction of resonance spectra and their properties from data. Here, we review the formalism and application of the ANL-Osaka, the Juelich-Bonn-Washington, and other DCC approaches in the context of light baryon resonances from meson, (virtual) photon, and neutrino-induced reactions, as well as production reactions, strange baryons, light mesons, heavy meson systems, exotics, and baryon-baryon interactions. Finally, we also provide a connection of the formalism to study finite-volume spectra obtained in Lattice QCD, and review applications involving modern statistical and machine learning tools.

Amplitude analysis↗
DOE OSTI2023

Contrasting effects of lake breeze and urbanization on heat stress in Chicago metropolitan area

This study used the latest Weather Research and Forecasting (WRF) model coupled with multi -layer urban canopy models to investigate contrasting effects from urbanization and lake breeze on summer heat stress over the Chicago metropolitan area (CMA). Comparisons between the model and in situ observations show that this coupled modeling system better captures urban locations' diurnal pattern of surface air temperature, skin temperature and relative humidity, with root mean square error reduced from 1.58 to 1.80 degrees C to 1.14-1.31 degrees C, 3.11-3.55 degrees C to 1.81-2.21 degrees C, and 10.73-11.35% to 7.84-8.60%, respectively, compared to WRF without coupling the urban canopy models. Two sensitivity experiments were conducted to isolate the influence of lake breeze and urbanization: one replaced the urban land use with cropland over the CMA, and the other filled all of Lake Michigan with cropland. Three different heat stress indices were computed to assess the uncertainties of heat stress response to changes in air temperature, relative humidity, and wind conditions. Results show that, when the lake has the largest cooling effect on air temperature, it also increases the relative humidity the most, and vice versa for urban warming and drying effects. Urbanization intensifies heat stress at night, and extends the heat caution period by up to 4 h over inland urban grids; the lake breeze relieves heat stress during afternoon (when the heat stress is the worst), and shortens the heat caution period by 1-3 h over inland urban grids and 3-4 h over coastal urban grids. In conclusion, the intensification of heat stress over the CMA due to urbanization is more than four times greater than the reduction from the lake breeze in the late afternoon and evening.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Coupled THMC models for bentonite in an argillite repository for nuclear waste: Illitization and its effect on swelling stress under high temperature

Subsurface manipulations such as those expected from the disposal of heat-emanating radioactive waste in deep repositories can induce strongly coupled Thermal (T), hydrological (H), mechanical (M) and chemical (C) processes. Adequate coupled THMC models are highly desirable or even indispensable for performance assessment of such repositories, for examples for the analysis of bentonite-based engineered barrier system (EBS) surrounding the emplaced waste. In this study, we present coupled THMC model simulations of a generic nuclear waste repository in an argillite with a bentonite-based buffer. The objective is to evaluate the chemical changes in the EBS bentonite and their effect on mechanical behavior under high temperature, attempting to shed light on whether EBS bentonite can sustain temperatures higher than 100 °C without significant impact on barrier's performance. Two scenarios were simulated for comparison: a case in which the temperature near the waste canister peaks at 200 °C and a case in which the temperature at the same spot culminate with about 100 °C. Simulations for a generic case with Kunigel-VI bentonite as backfill and Opalinus Clay as host rock were conducted for 1000 years and reported in the previous study (Zheng et al., 2015). In this paper, simulations for 100,000 years have been done for two types of bentonite-based buffer materials: Kunigel-VI and FEBEX bentonite. This enables us to evaluate how different types of bentonite behave in terms of the illitization and its impact on swelling stress and whether we can generalize these results to support decision making. The simulations show the occurrence of illitization in the bentonite buffer and the enhancement of illitization under high temperature. However, FEBEX bentonite undergoes less illitization mainly due to the higher ion concentration in pore water and the lower content of K-feldspar in the bentonite mineral composition. Moreover, the reduction of swelling stress by chemical changes is more pronounced for Kunigel-VI bentonite than for FEBEX bentonite. Furthermore, the results of our model simulations suggest that an argillite repository with a bentonite-based EBS that is similar to FEBEX bentonite could sustain temperatures much higher than 100 °C as far as illitization concerns. Model results also reveal that illitization is stabilized after about 2000 years in bentonite near the waste package, but continues in bentonite near the bentonite-argillite interface, which manifests the strong effect of geochemical interaction between EBS bentonite and host rock on long term illitization in bentonite.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1982

Gain selection method and model for coupled propulsion and airframe systems

A longitudinal model is formulated for an advanced fighter from three subsystem models: the inlet, the engine, and the airframe. Notable interaction is found in the coupled system. A procedure, based on eigenvalue sensitivities, is presented which indicates the importance of the feedback gains to the optimal solution. This allows ineffectual gains to be eliminated; thus, hardware and expense may be saved in the realization of the physical controller.

Murphy, P. C.↗
NASA NTRS2023

The Projected Future Degradation in Air Quality is Caused by More Abundant Natural Aerosols in a Warmer World

Previous studies suggest that greenhouse gas-induced warming can lead to increased fine particulate matter concentrations and degraded air quality. However, significant uncertainties remain regarding the sign and magnitude of the response to warming and the underlying mechanisms. Here, we show that thirteen models from the Coupled Model Intercomparison Project Phase 6 all project an increase in global average concentrations of fine particulate matter in response to rising carbon dioxide concentrations, but the range of increase across models is wide. The two main contributors to this increase are increased abundance of dust and secondary organic aerosols via intensified West African monsoon and enhanced emissions of biogenic volatile organic compounds, respectively. Much of the inter-model spread is related to different treatment of biogenic volatile organic compounds. Our results highlight the importance of natural aerosols in degrading air quality under current warming, while also emphasizing that improved understanding of biogenic volatile organic compounds emissions due to climate change is essential for numerically assessing future air quality.

Climate and Earth system modelling↗
DOE OSTI2016

Future changes in regional precipitation simulated by a half-degree coupled climate model: Sensitivity to horizontal resolution

The global fully coupled half-degree Community Climate System Model Version 4 (CCSM4) was integrated for a suite of climate change ensemble simulations including five historical runs, five Representative Concentration Pathway 8.5 [RCP8.5) runs, and a long Pre-Industrial control run. This study focuses on precipitation at regional scales and its sensitivity to horizontal resolution. The half-degree historical CCSM4 simulations are compared to observations, where relevant, and to the standard 1° CCSM4. Both the halfdegree and 1° resolutions are coupled to a nominal 1° ocean. North American and South Asian/Indian monsoon regimes are highlighted because these regimes demonstrate improvements due to higher resolution, primarily because of better-resolved topography. Agriculturally sensitive areas are analyzed and include Southwest, Central, and Southeast U.S., Southern Europe, and Australia. Both mean and extreme precipitation is discussed for convective and large-scale precipitation processes. Convective precipitation tends to decrease with increasing resolution and large-scale precipitation tends to increase. Improvements for the half-degree agricultural regions can be found for mean and extreme precipitation in the Southeast U.S., Southern Europe, and Australian regions. Climate change responses differ between the model resolutions for the U.S. Southwest/Central regions and are seasonally dependent in the Southeast and Australian regions. Both resolutions project a clear drying signal across Southern Europe due to increased greenhouse warming. As a result, differences between resolutions tied to the representation of convective and large-scale precipitation play an important role in the character of the climate change and depend on regional influences.

58 GEOSCIENCES↗
DOE OSTI2023

Integrable field theories and their CCFT duals

We compute the Mellin transforms of various two-dimensional integrable S-matrices, providing the first explicit, non-perturbative realizations of celestial CFT. In two dimensions, the Mellin transform is simply the Fourier transform in rapidity space, and the “celestial correlator” has no position dependence. The simplified setting allows us to study the analytic properties of CCFT correlators exactly as a function of the conformal dimensions. We find that the correlators exist as real distributions of the conformal weights, with asymptotics controlled by the mass spectrum and three-point couplings of the model. Coupling these models to a flat space limit of JT gravity preserves integrability and dresses the amplitudes by a rapidly varying gravitational phase. We find that the coupling to gravity smooths out certain singular aspects of the Mellin-transformed correlators.

2D Gravity↗
DOE OSTI2018

MULTI-PRED: A Software Module for Predictive Modeling of Coupled Multi-Physics Systems: User's Manual

This User’s Manual describes the code module MULTI-PRED, written in FORTRAN which implements the methodology for “predictive modeling of coupled multi-physics systems (PM-CMPS)” formulated by Cacuci (2014). This methodology fully takes into account the coupling terms between the systems but requires only the computational resources that would be needed to perform predictive modeling on each system separately. The PM-CMPS methodology uses the maximum entropy principle to construct an optimal approximation of the unknown a priori distribution based on a priori known mean values and uncertainties characterizing the experimental and computational parameters and results of interest responses, called for the multi-physics models under consideration. This “maximum entropy” a priori distribution is combined, using Bayes’ theorem, with the “likelihood” provided by the multi-physics simulation models to obtain a formal posterior distribution. Subsequently, the posterior distribution thus obtained is evaluated using the saddle-point method to obtain analytical expressions for the optimally predicted values for the multi-physics models parameters and responses along with corresponding reduced uncertainties. Noteworthy, the predictive modeling methodology for the coupled systems is constructed such that the systems can be considered sequentially rather than simultaneously, while preserving exactly the same results as if the systems were treated simultaneously. Consequently, very large coupled systems, which could perhaps exceed available computational resources if treated simultaneously, can be treated with the PM-CMPS methodology presented in this work sequentially and without any loss of generality or information, requiring just the resources that would be needed if the systems were treated sequentially. Three illustrative demonstration problems are also provided. The first problem presents the application of the PM-CMPS methodology to a simple particle diffusion problem which admits a closed-form analytical solution which facilitates a rapid understanding of this methodology and its predicted results. The second demonstration problem presents the application of the PM-CMPS methodology to the problem of inverse prediction, from detector responses in the presence of counting uncertainties, of the thickness of a homogeneous slab of material containing uniformly distributed gamma-emitting sources, for optically thin and thick slabs. This problem highlights the essential role played by the relative uncertainties (or, conversely, accuracies) of measured and computed responses. The third demonstration problem presents the application of the PM-CMPS methodology to the F-area cooling towers at the Savannah River National Lab. This problem demonstrates that the PM-CMPS methodology reduces the predicted response uncertainties not only at locations where measurements are available, but also at locations where measurements are not available.

97 MATHEMATICS AND COMPUTING↗