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DOE OSTI2017

A Comprehensive Set of Impact Data for Common Aerospace Metals

Our results for the two sets of impact experiments are reported here. In order to assist with model development using the impact data reported, the materials are mechanically characterized using a series of standard experiments. The first set of impact data comes from a series of coefficient of restitution experiments, in which a 2 meter long pendulum is used to study "in context" measurements of the coefficient of restitution for eight different materials (6061-T6 Aluminum, Phosphor Bronze alloy 510, Hiperco, Nitronic 60A, Stainless Steel 304, Titanium, Copper, and Annealed Copper). The coefficient of restitution is measured via two different techniques: digital image correlation and laser Doppler vibrometry. Due to the strong agreement of the two different methods, only results from the digital image correlation are reported. The coefficient of restitution experiments are "in context" as the scales of the geometry and impact velocities are representative of common features in the motivating application for this research. Finally, a series of compliance measurements are detailed for the same set of materials. Furthermore, the compliance measurements are conducted using both nano-indentation and micro-indentation machines, providing sub-nm displacement resolution and uN force resolution. Good agreement is seen for load levels spanned by both machines. As the transition from elastic to plastic behavior occurs at contact displacements on the order of 30 nm, this data set provides a unique insight into the transitionary region.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Enrichable consortia of microbial symbionts degrade macroalgal polysaccharides in Kyphosus fish

ABSTRACT Coastal herbivorous fishes consume macroalgae, which is then degraded by microbes along their digestive tract. However, there is scarce genomic information about the microbiota that perform this degradation. This study explores the potential of Kyphosus gastrointestinal microbial symbionts to collaboratively degrade and ferment polysaccharides from red, green, and brown macroalgae through in silico study of carbohydrate-active enzyme and sulfatase sequences. Recovery of metagenome-assembled genomes (MAGs) from previously described Kyphosus gut metagenomes and newly sequenced bioreactor enrichments reveals differences in enzymatic capabilities between the major microbial taxa in Kyphosus guts. The most versatile of the recovered MAGs were from the Bacteroidota phylum, whose MAGs house enzyme collections able to decompose a variety of algal polysaccharides. Unique enzymes and predicted degradative capacities of genomes from the Bacillota (genus Vallitalea ) and Verrucomicrobiota (order Kiritimatiellales ) highlight the importance of metabolic contributions from multiple phyla to broaden polysaccharide degradation capabilities. Few genomes contain the required enzymes to fully degrade any complex sulfated algal polysaccharide alone. The distribution of suitable enzymes between MAGs originating from different taxa, along with the widespread detection of signal peptides in candidate enzymes, is consistent with cooperative extracellular degradation of these carbohydrates. This study leverages genomic evidence to reveal an untapped diversity at the enzyme and strain level among Kyphosus symbionts and their contributions to macroalgae decomposition. Bioreactor enrichments provide a genomic foundation for degradative and fermentative processes central to translating the knowledge gained from this system to the aquaculture and bioenergy sectors. IMPORTANCE Seaweed has long been considered a promising source of sustainable biomass for bioenergy and aquaculture feed, but scalable industrial methods for decomposing terrestrial compounds can struggle to break down seaweed polysaccharides efficiently due to their unique sulfated structures. Fish of the genus Kyphosus feed on seaweed by leveraging gastrointestinal bacteria to degrade algal polysaccharides into simple sugars. This study reconstructs metagenome-assembled genomes for these gastrointestinal bacteria to enhance our understanding of herbivorous fish digestion and fermentation of algal sugars. Investigations at the gene level identify Kyphosus guts as an untapped source of seaweed-degrading enzymes ripe for further characterization. These discoveries set the stage for future work incorporating marine enzymes and microbial communities in the industrial degradation of algal polysaccharides.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Non-residential Electricity Prices: A Review of Data Sources and Estimation Methods

This paper presents a review of electricity price data sources and estimation methods for non-residential consumers, including a detailed empirical study of tariff-based prices collected as part of Lawrence Berkeley Lab's Tariff Analysis Project (TAP). We compare the TAP data to two other data sources: utility-level annual sales, revenues and consumer counts published by the Energy Information Administration (EIA), and the Typical Bills reports published by the Edison Electric Institute. A brief overview of the types of rate structures included in the TAP database illustrates the often complex relationship between the consumer's energy use and the costs they see on their electricity bills. We provide mathematical definitions of the different types of electricity price that are useful in cost-benefit analysis, construct estimation methods appropriate to each data set, compare the results, and evaluate the relative strengths and weaknesses of each approach. We also examine how price variation is driven by differences in season, region, industry business model, and variables characterizing consumer energy use. Tables of regional price estimates for each data source, based on 2015 data, are included in the Appendix to this paper.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1981

Design of an arc-free thermal blanket

The success of a multilayer thermal blanket in eliminating arcing is discussed. Arcing is eliminated by limiting the surface potential to well below the threshold level for discharge. This is achieved by enhancing the leakage current which results in conduction of the excess charge to the spacecraft structure. The thermal blanket consists of several layers of thermal control (space approved) materials, bonded together, with Kapton on the outside, arranged in such a way that when the outer surface is charged by electron irradiation, a strong electric field is set up on the Kapton layer resulting in a greatly improved conductivity. The basic properties of matter utilized in designing this blanket method of charge removal, and optimum thermo-optical properties are summarized.

Fellas, C. N.↗

NASA NTRS1982

A time-dependent ice sheet model - Preliminary results

A numerical model of ice sheet flow is developed, and preliminary results are described. This model includes vertical resolution of temperature, stress, and strain rate which represents a considerable improvement over previous vertically averaged ice sheet models. The model follows the flow of ice along a flow line within an ice sheet drainage basin. Longitudinal stresses and basal sliding are included. Basal sliding is dependent on the base shear stress and a specified distribution of basal water pressure. The numerical methods used to solve the coupled set of stress and velocity equations for the static and time-evolutionary cases are discussed. A steady state profile simulating an ice stream is calculated for a particular set of input parameters, and changes in the profile are examined for different choices of parameters. Preliminary studies of response behavior are completed using a simplified ice sheet geometry with a fixed terminus or grounding line. The results of these studies illustrate ice sheet thinning in response to a lowered sea level or to a reduction in the extent of ice rises (or pinning points) within ice shelves.

Bindschadler, R. A.↗

NASA NTRS1984

Asteroid Lightcurve Inversion

The application of convex profile inversion (CPI) to the interpretation of asteroid lightcurves is discussed. This technique investigates the problem of extracting information about an asteroid's shape from its lightcurve. Whenever four ideal conditions are met, P is an estimator for the asteroids mean cross section C, a convex set defined as the average of all cross sections C(Z) cut by planes a distance z above the asteroids equatorial plane. C is therefore a 2-D average of the asteroids 3-D shape. The method is tested by inverting lightcurves generated analytically for geometrically scattered ellipsoids (GSE's) with semiaxes a or = B or = C. Using a defined 'distance measure' to quantify the difference between any two profiles, the deviation of P from C for GSE's as a function of lightcurve noise level, rotation phase sampling interval delta theta, and departure from ideal conditions is calibrated. The distance between P and a circle provides a gauge of the asteroid's nonsphericity and incorporates all the information contained in the lightcurve.

Ostrow, S. J.↗

NASA NTRS1990

Feasibility study, software design, layout and simulation of a two-dimensional fast Fourier transform machine for use in optical array interferometry

The NASA-Cornell Univ.-Worcester Polytechnic Institute Fast Fourier Transform (FFT) chip based on the architecture of the systolic FFT computation as presented by Boriakoff is implemented into an operating device design. The kernel of the system, a systolic inner product floating point processor, was designed to be assembled into a systolic network that would take incoming data streams in pipeline fashion and provide an FFT output at the same rate, word by word. It was thoroughly simulated for proper operation, and it has passed a comprehensive set of tests showing no operational errors. The black box specifications of the chip, which conform to the initial requirements of the design as specified by NASA, are given. The five subcells are described and their high level function description, logic diagrams, and simulation results are presented. Some modification of the Read Only Memory (ROM) design were made, since some errors were found in it. Because a four stage pipeline structure was used, simulating such a structure is more difficult than an ordinary structure. Simulation methods are discussed. Chip signal protocols and chip pinout are explained.

Boriakoff, Valentin↗

NASA NTRS1992

Integration of satellite and surface data using a radiative-convective oceanic boundary-layer model

A mixing-line boundary-layer model is used to retrieve cloud-top height from satellite-derived cloud-top temperatures, using 700-hPa National Meteorological Center (NMC) analyses and the Comprehensive Ocean and Atmosphere Data Set (COADS) surface data as supporting datasets. Results are compared with the fixed-lapse-rate method of retrieving boundary-layer depth from sea surface temperatures (SST) and cloud-top temperatures. A radiative-convective equilibrium boundary-layer model is used to retrieve boundary-layer structure given SST and surface wind, satellite cloud-top temperatures and cloud fraction, and the 700-hPa NMC thermodynamic analyses. Good agreement is found between the COADS data and the model solutions for low-level temperature and moisture. This suggests that equilibrium boundary-layer models may be of use over remote oceans in the retrieval of boundary-layer structure.

Betts, Alan K.↗

DOE OSTI2019

Status Report: Design and Fabricate Installation-Ready Test Capsule for the In-Situ Measurement of Elastic Properties Using an Optical Fiber-Based Measurement Technique

Microstructure evolution due to irradiation in a nuclear reactor can have a dramatic effect on material properties. A better understanding of this evolution is necessary for developing improved nuclear fuels and materials. The ability to measure such changes in real time is extremely limited due to the harsh conditions, high radiation fields, and limited access of the reactor environment. Through carefully designed experiments, measurement of elastic properties can be tied directly to microstructure. We present the methodology, design, and deployment plan for an instrument that has been developed to monitor grain microstructural changes during irradiation. Our measurement approach involves exciting and measuring the resonant frequency of a thin cantilever beam. Excitation and detection of the flexural vibrations of the beam are accomplished using optical methods that require only an optical fiber connection between the instrumentation and the sample. This technique has been demonstrated in a laboratory setting to monitor the recrystallization of highly textured copper during high temperature annealing. A test capsule incorporating this technique has been developed for in reactor testing. The capsule has been designed to be compatible with a reusable test module that allows simplified insertion in the TREAT reactor at INL. An exact replica of the instrument described in this Status Report, constructed from Quality Level 3 materials, is slated to be inserted into the TREAT reactor in FY19.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

SU-D-202-02: Quantitative Imaging: Correlation Between Image Feature Analysis and the Accuracy of Manually Drawn Contours On PET Images

Purpose: To evaluate the correlation between image features and the accuracy of manually drawn target contours on synthetic PET images Methods: A digital PET phantom was used in combination with Monte Carlo simulation to create a set of 26 simulated PET images featuring a variety of tumor shapes and activity heterogeneity. These tumor volumes were used as a gold standard in comparisons with manual contours delineated by 10 radiation oncologist on the simulated PET images. Metrics used to evaluate segmentation accuracy included the dice coefficient, false positive dice, false negative dice, symmetric mean absolute surface distance, and absolute volumetric difference. Image features extracted from the simulated tumors consisted of volume, shape complexity, mean curvature, and intensity contrast along with five texture features derived from the gray-level neighborhood difference matrices including contrast, coarseness, busyness, strength, and complexity. Correlation between these features and contouring accuracy were examined. Results: Contour accuracy was reasonably well correlated with a variety of image features. Dice coefficient ranged from 0.7 to 0.90 and was correlated closely with contrast (r=0.43, p=0.02) and complexity (r=0.5, p<0.001). False negative dice ranged from 0.10 to 0.50 and was correlated closely with contrast (r=0.68, p<0.001) and complexity (r=0.66, p<0.001). Absolute volumetric difference ranged from 0.0002 to 0.67 and was correlated closely with coarseness (r=0.46, p=0.02) and complexity (r=0.49, p=0.008). Symmetric mean absolute difference ranged from 0.02 to 1 and was correlated closely with mean curvature (r=0.57, p=0.02) and contrast (r=0.6, p=0.001). Conclusion: The long term goal of this study is to assess whether contouring variability can be reduced by providing feedback to the practitioner based on image feature analysis. The results are encouraging and will be used to develop a statistical model which will enable a prediction of contour accuracy based purely on image feature analysis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Current Efforts in Immobilized Low-Activity Waste Glass Testing to Support the Hanford Site Integrated Disposal Facility - 17119

Cleanup plans for Hanford site high-level radioactive mixed tank waste calls for separating the waste into high-level waste (HLW) and low-activity waste (LAW) fractions. The fractions will be vitrified separately at the Hanford Tank Waste Treatment and Immobilization Plant (WTP). The HLW glass will be sent to an offsite geological disposal facility while the immobilized low-activity waste (ILAW) glass will be disposed at the onsite Integrated Disposal Facility (IDF). In order to inform models used to predict the performance of ILAW glass at IDF, it is necessary to understand the corrosion behavior of the glass. In this paper, we discuss tests that account for the effects of 1) solution chemistry, 2) the ion exchange reaction, and 3) secondary phase formation on the glass dissolution rate. To quantify the effects of solution chemistry, specifically changes in pH, T, and Si concentration, the single-pass flow-through (SPFT) test method is applied. A designed set of these tests results in a set of kinetic rate law parameters that are used in a glass dissolution rate law based on transition-state theory. Furthermore, for SPFT tests with relatively high concentrations of Si, an ion exchange rate is provided. Additionally, through tests such as the pressurized unsaturated flow (PUF) test method, a suite of secondary phases can be compiled. The collection of kinetic rate law parameters, the ion exchange term, and the suite of secondary phases are provided to IDF performance assessment (PA) modelers. Lastly, we present a description of the efforts made to verify and validate the use of these parameters and secondary phases through the use of a field lysimeter present at the Hanford site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Weak Lensing by Galaxy Clusters: from Pixels to Cosmology

The story of the origin and evolution of our Universe is told, equivalently, by space-time itself and by the structures that grow inside of it. Clusters of galaxies are the frontier of bottom-up structure formation. They are the most massive objects to have collapsed at the present epoch. By that virtue, their abundance and structural parameters are highly sensitive to the composition and evolution of the Universe. The most common probe of cluster cosmology, abundance, uses samples of clusters selected by some observable. Applying a mass-observable relation (MOR), cosmological parameters can be constrained by comparing the sample to predicted cluster abundances as a function of observable and redshift. Arguably, however, cluster probes have not yet entered the era of per cent level precision cosmology. The primary reason for this is our imperfect understanding of the MORs. The overall normalization, the slope of mass vs. observable, the redshift evolution, and the degree and correlation of intrinsic scatters of observables at fixed mass have to be constrained for interpreting abundances correctly. Mass measurement of clusters by means of the differential deflection of light from background sources in their gravitational field, i.e. weak lensing, is a powerful approach for achieving this. This thesis presents new methods for and scientific results of weak lensing measurements of clusters of galaxies. The former include, on the data reduction side, (i) the correction of CCD images for non-linear effects due to the electric fields of accumulated charges and (ii) a method for masking artifact features in sets of overlapping images of the sky by comparison to the median image. Also, (iii) I develop a method for the selection of background galaxy samples based on their color and apparent magnitude that includes a new correction for contamination with cluster member galaxies. The main scientific results are the following. (i) For the Hubble Frontier Field cluster RXC J2248.7--4431 our lensing analysis constrains mass and concentration of the cluster halo and we confirm the large mass predicted by X-ray and Sunyaev-Zel’dovich (SZ) observations. The study of cluster members shows the relation of galaxy morphology to luminosity and environment. (ii) Our lensing mass measurements for 12 clusters are consistent with X-ray masses derived under the assumption of hydrostatic equilibrium of the intra-cluster gas. We confirm the MORs derived by the South Pole Telescope collaboration for the detection significance of the cluster SZ signal in their survey. We find discrepancies, however, with the Planck SZ MOR. We hypothesize that these are related either to a shallower slope of the MOR or a size-, redshift- or noise-dependent bias in SZ signal extraction. (iii) Finally, using a combination of simulations and theoretical models for the variation of cluster profiles at fixed mass, we find that the latter is a significant contribution to the uncertainty of cluster lensing mass measurements. A cosmic variance model, such as the one we develop, is necessary for MOR constraints to be accurate at the level required for future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2010

Permissible Exposure Level for Lunar Dusts: Gaps are Closing

Space faring nations plan to return human explorers to the moon within the next decade. Experience during the Apollo flights suggests that lunar dust will invariably get into the habitat where the finest portion (less than 5 micrometers) could be inhaled by the crew before it is cleared from the atmosphere. NASA is developing a database from which a 6-month, episodic exposure standard for lunar dust can be set. Three kinds of moon dust were prepared from a parent sample of Apollo 14 regolith #14003,96. Our goal was to prepare each type of dust sample with a mean diameter less than 2 m, which is suitable for instillation into the lungs of rats. The three samples were prepared as follows: separation from the parent sample using a fluidized bed, grinding using a jet mill grinder, or grinding with a ball-mill grinder. Grinding simulated restoration of surface activation of dust expected to occur at the surface of the moon on native lunar dust. We used two grinding methods because they seemed to produce different modes of activation. The effects of grinding were preserved by maintaining the dust in ultra-pure nitrogen until immediately before it was placed in suspension for administration to rats. The dust was suspended in physiological saline with 10% Survanta, a lung surfactant. Rats were given intratrachael instillations of the dust suspension at three doses. In addition to the three moon dusts (A, C and E), we instilled the same amount of a negative control (TiO2, B) and a highly-toxic, positive control (quartz, D). These additional mineral dusts were selected because they have well-established and very different permissible exposure levels (PELs). Our goal was to determine where lunar dusts fit between these extremes, and then estimate a PEL for each lunar dust. We evaluated many indices of toxicity to the lung. The figure shows the changes in lactate dehydrogenase (LDH), a marker of cell death, for the five dusts. Benchmark dose software (Version 2.1.2) from the Environmental Protection Agency was used to estimate the 10% effect levels (BMD(sub 10)) using five models. The best-fitting model was used to estimate the optimal BMD(sub 10) (table)

James, John T.↗

DOE OSTI2021

Explore Spatio‐Temporal Learning of Large Sample Hydrology Using Graph Neural Networks

Abstract Streamflow forecasting over gauged and ungauged basins play a vital role in water resources planning, especially under the changing climate. Increased availability of large sample hydrology data sets, together with recent advances in deep learning techniques, has presented new opportunities to explore temporal and spatial patterns in hydrological signatures for improving streamflow forecasting. The purpose of this study is to adapt and benchmark several state‐of‐the‐art graph neural network (GNN) architectures, including ChebNet, Graph Convolutional Network (GCN), and GraphWaveNet, for end‐to‐end graph learning. We explicitly represent river basins as nodes in a graph, learn the spatiotemporal nodal dependencies, and then use the learned relations to predict streamflow simultaneously across all nodes in the graph. The efficacy of the developed GNN models is investigated using the Catchment Attributes and MEteorology for Large‐sample Studies (CAMELS) data set under two settings, fixed graph topology (transductive learning), and variable graph topology (inductive learning), with the latter applicable to prediction in ungauged basins (PUB). Results indicate that GNNs are generally robust and computationally efficient, achieving similar or better performance than a baseline model trained using the long short‐term memory (LSTM) network. Further analyses are conducted to interpret the graph learning process at the edge and node levels and to investigate the effect of different model configurations. We conclude that graph learning constitutes a viable machine learning‐based method for aggregating spatiotemporal information from a multitude of sources for streamflow forecasting

Sun, Alexander Y.↗

DOE OSTI2023

Analytical Large-Signal Modeling of Inverter-Based Microgrids With Koopman Operator Theory for Autonomous Control

The microgrid (MG) plays a crucial role in the energy transition, but its nonlinearity presents a significant challenge for large-signal power systems studies in the electromagnetic transient (EMT) time scale. In this paper, we develop a large-signal linear MG model that considers the detailed dynamics of the primary and zero-control levels based on the Koopman operator (KO) theory. Firstly, a set of observable functions is carefully designed to capture the nonlinear dynamics of the MG. The corresponding linear KO is then analytically derived based on these observables, resulting in the linear representation of the original nonlinear MG with observables as the new coordinate. The influence of external input on the system dynamics is also considered during the derivation, enabling control of the MG. We solve the voltage control problem using the traditional linear quadratic integrator (LQI) method to demonstrate that textbook linear control techniques can accurately control the original nonlinear MG via the developed KO-linearized MG model. Our proposed KO linearization method is generic and can be easily extended for different control objectives and MG structures using our analytical derivation procedure. Here, we validate the effectiveness of our methodology through various case studies.

25 ENERGY STORAGE↗

DOE OSTI2015

Near-surface Density Currents Observed in the Southeast Pacific Stratocumulus-topped Marine Boundary Layer

Density currents (i.e. cold pools or outflows) beneath marine stratocumulus clouds are characterized using a 30-d data set of ship-based observations obtained during the 2008 Variability of American Monsoon Systems (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) in the southeast Pacific. An objective method identifies 71 density current fronts using an air density criterion and isolates each density current’s core (peak density) and tail (dissipating) zone. Compared to front and core zones, most density current tails exhibited weaker density gradients and wind anomalies elongated about the axis of the mean wind. The mean cloud-level advection relative to the surface layer wind (1.9 m s-1) nearly matches the mean density current propagation speed (1.8 m s-1). The similarity in speeds allows drizzle cells to deposit tails in their wakes. Based on high-resolution scanning Doppler lidar data, prefrontal updrafts had a mean intensity of 0.91 m s-1, reached an average altitude of 800 m, and were often surmounted by low-lying shelf clouds not connected to the overlying stratocumulus cloud. Nearly 90% of density currents were identified when C-band radar estimated 30-km diameter areal average rain rates exceeded 1 mm d-1. Rather than peaking when rain rates are highest overnight, density current occurrence peaks between 0600 and 0800 local solar time when enhanced local drizzle co-occurs with shallow subcloud dry and stable layers. The dry layers may contribute to density current formation by enhancing subcloud evaporation of drizzle. Density currents preferentially occur in regions of open cells but also occur in regions of closed cells.

density currents↗

DOE OSTI2020

Probing interfacial momentum closures in two-phase bubbly flow with machine learning-aided methods

Computational fluid dynamics (CFD) approach has already reached a high level of maturity for single-phase flows, however the development of closure models for two-phase flow requires additional attention. Multiphase CFD (M-CFD) methods resolve the conservation equations for mass, momentum and energy while differing in the approaches and strategies adopted in the physical closure models. The most widely adopted framework for M-CFD is the Eulerian-Eulerian two-fluid approach which assumes that all phases are co-existing inside each computational cell. For each fluid, the full set of conservation equations is solved; therefore, each fluid has a different velocity field. For adiabatic two-phase flow, the mechanisms of the interfacial momentum transfer are modeled by the interfacial forces representing different physical mechanisms. One of the crucial issues in the development and application of two-fluid model is the understanding of the interfacial momentum closures which determines the bubble distribution and migration behaviors. Dedicated experiments are performed to support the physical understanding and drive the closures’ development. However, limitations exist due to the uncertainties in the experimental measurement and the simplified analytical assumptions which have difficulties on representing the complex non-linear flow fields. In this paper, a data-driven approach, Feature Similarity Measurement (FSM), is developed and proposed to resolve the challenges of modeling the interfacial forces closures. Case study is performed with two-phase flow scenarios where the high-fidelity experimental data is available. Within the Eulerian-Eulerian two-fluid framework, only momentum equations for gas and liquid phases are solved and reduced-order interfacial momentum closures are aided with FSM. Predictions of void fraction and velocity fields are analyzed and demonstrate the potential of machine learning-driven interfacial forces closures.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Analyses of Field Test Data at the Atucha-1 Spent Fuel Pools

A field test was conducted at the Atucha-1 spent nuclear fuel pools to validate a software package for gross defect detection that is used in conjunction with the inspection tool, Spent Fuel Neutron Counter (SFNC). A set of measurements was taken with the SFNC and the software predictions were compared with these data and analyzed. The data spanned a wide range of cooling times and a set of burnup levels leading to count rates from the several hundreds to around twenty per second. The current calibration in the software using linear fitting required the use of multiple calibration factors to cover the entire range of count rates recorded. The solution to this was to use power regression data fitting to normalize the predicted response and derive one calibration factor that can be applied to the entire set of data. The resulting comparisons between the predicted and measured responses were generally good and provided a quantitative method of detecting missing fuel in virtually all situations. Since the current version of the software uses the linear calibration method, it would need to be updated with the new power regression method to make it more user-friendly for real time verification and fieldable for the range of responses that will be encountered.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗