Search NASA⌕ Search

SEARCH · Search NASA

Results for “variance component analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

A Multi-State Model for Catalyzing the National Home Energy Retrofit Market (Final Technical Report)

In the fall of 2010, the Alabama Department of Economic and Community Affairs (ADECA) launched the Multi-State Model for Catalyzing the National Home Energy Retrofit Market Project (Multi-State Project). This residential energy efficiency pilot program was a collaborative effort among the states of Alabama, Massachusetts, Virginia, and Washington, and was funded by competitive State Energy Program (SEP) awards through the U.S. Department of Energy (DOE). The objective of this project was to catalyze the home energy efficiency retrofit market in select areas within the state of Alabama. To achieve this goal, the project addressed a variety of marketplace elements that did not exist, or were underdeveloped, at the outset of the effort. These included establishing minimum standards and credentials for marketplace suppliers, educating and engaging homeowners on the benefits of energy efficiency and addressing real or perceived financial barriers to investments in whole-home energy efficiency, among others. The anticipated effect of the activities would be increased market demand for retrofits, improved audit to retrofit conversion rates and growth in overall community understanding of energy efficiency. The four-state collaborative was created with the intent of accelerating market transformation by allowing each state to learn from their peers, each of whom possessed different starting points, resources, and strategies for achieving the overall objective. The four partner states engaged the National Association of State Energy Officials (NASEO) to oversee a project steering committee and to manage the project evaluation for all four states. The steering committee, comprised of key program partners, met on a regular basis to provide overall project coordination, guidance, and progress assessment. While there were variances in program design among the states, there were several common elements: use of the Energy Performance Score (EPS) platform; an audit and home energy rating tool; emphasis on community based coordination and partnerships; marketing and outreach to increase homeowner participation; training for market actors; access to financing options including rebates, incentives, and loan products; and an in depth process evaluation to support continual program improvement and analysis. In Alabama, Nexus Energy Center operated energy efficiency retrofit programs in Huntsville and Birmingham. In the Huntsville community the AlabamaWISE program was available in five Alabama counties: Cullman, Lawrence, Limestone, Madison, and Morgan. In Birmingham, the program was available to residents in Jefferson and Shelby Counties. In both communities, the program was similar in terms of program design but tailored marketing and partnerships to address the unique local conditions and population of each community. ADECA and the Southeast Energy Efficiency Alliance (SEEA) provided overall project management services and common resources to the local program administrator Nexus Energy Center, including contracted services for contractor training, quality assurance testing, data collection and reporting, and compliance. The fundamental components of the AlabamaWISE program included a vertical contractor-based business model; comprehensive energy assessments; third-party quality assurance; rebates for installation of energy saving measures; accessible, low-interest financing; targeted and inbound marketing; Energy Performance Score (EPS) tool to engage and educate homeowners; training for auditors, contractors, and real estate professionals; and online resources for education and program enrollment. Program participants were eligible to receive rebates or financing toward the assessments and upgrades to their home provided they reached at least 20 percent deemed or modeled energy savings. The design of each program focused on addressing several known barriers including: limited homeowner knowledge on the benefits of energy efficiency, lack of financing options, lack of community support for energy efficiency programs, and lack of trained market actors including contractors and real estate professionals. The programs were able to make progress on addressing all of these barriers and were most successful in offering financing options and training market actors. The most challenging barriers proved to be the act of building a market for energy efficiency where none previously existed, convincing homeowners of the value in investing in energy efficiency (and therefore completing retrofits), engaging electric and natural gas utilities to partner on delivery, and achieving the overall project target of 1,365 completed retrofits. The components that proved to be the most valuable to program success were engaged contractor networks that could promote and endorse the program, partnerships with local business and organizations, and the access to rebates, incentives and financing mechanisms. The programs were successful in building relationships with a variety of community participants including: local contractors, Associations of REALTORS, home builders associations, universities, utilities, local and state governments, and other non-profit organizations. Throughout this program, 933 building audits and 795 building retrofits were completed making homes in Alabama more comfortable, less expensive to operate, more valuable to the marketplace, and safer and healthier for families. Continuing on this momentum, Nexus Energy Center plans to continue operating and expanding operations in Alabama as a Home Performance with ENERGY STAR sponsor and will continue to provide energy services and education to communities in Alabama.

Grimes, Elizabeth M.↗
DOE OSTI2020

Improved Parametric Models for Explosion Pressure Signals Derived From Large Datasets

Accurate recording and characterization of explosion-induced pressure signals are key components of the forensic analysis of explosion events in the atmosphere. Parametric overpressure models based on several key waveform features (peak overpressure, positive pulse duration, and impulse) are widely used to estimate explosion energy in terms of trinitrotoluene equivalent yield. However, those models are often developed by a limited dataset, including only a few events or recordings at relatively short propagation distances. Here, we develop empirical waveform-parameter models based on a regression analysis of a large set of data curated from four chemical explosion experiments including 16 detonations. We measured peak overpressure and impulse for positive and negative phases from 1000 pressure signals recorded at local ranges (<20 km) with scaled distance up to 8000 m/kg 1/3 . Additionally, the measured waveform parameters showed large variation with respect to observing distances indicating the effects of atmospheric propagation. In this study, a second-order polynomial model was used in a least-squares regression to account for those propagation effects and to improve data fitting. In addition to model parameters for waveform features, we also determined range-dependent model uncertainties based on data variance. The model uncertainty represents the prediction error of our models and can be critical to evaluating the uncertainty of yield estimate.

58 GEOSCIENCES↗
DOE OSTI2013

PRIMORDIAL GRAVITATIONAL WAVE DETECTABILITY WITH DEEP SMALL-SKY COSMIC MICROWAVE BACKGROUND EXPERIMENTS

We use the Bayesian estimation on direct T - Q - U cosmic microwave background (CMB) polarization maps to forecast errors on the tensor-to-scalar power ratio r, and hence on primordial gravitational waves, as a function of sky coverage f{sub sky}. This map-based likelihood filters the information in the pixel-pixel space into the optimal combinations needed for r detection for cut skies, providing enhanced information over a first-step linear separation into a combination of E, B, and mixed modes, and ignoring the latter. With current computational power and for typical resolutions appropriate for r detection, the large matrix inversions required are accurate and fast. Our simulations explore two classes of experiments, with differing bolometric detector numbers, sensitivities, and observational strategies. One is motivated by a long duration balloon experiment like Spider, with pixel noise {proportional_to}{radical}(f{sub sky}) for a specified observing period. This analysis also applies to ground-based array experiments. We find that, in the absence of systematic effects and foregrounds, an experiment with Spider-like noise concentrating on f{sub sky} {approx} 0.02-0.2 could place a 2{sigma}{sub r} Almost-Equal-To 0.014 boundary ({approx}95% confidence level), which rises to 0.02 with an l-dependent foreground residual left over from an assumed efficient component separation. We contrast this with a Planck-like fixed instrumental noise as f{sub sky} varies, which gives a Galaxy-masked (f{sub sky} = 0.75) 2{sigma}{sub r} Almost-Equal-To 0.015, rising to Almost-Equal-To 0.05 with the foreground residuals. Using as the figure of merit the (marginalized) one-dimensional Shannon entropy of r, taken relative to the first 2003 WMAP CMB-only constraint, gives -2.7 bits from the 2012 WMAP9+ACT+SPT+LSS data, and forecasts of -6 bits from Spider (+ Planck); this compares with up to -11 bits for CMBPol, COrE, and PIXIE post-Planck satellites and -13 bits for a perfectly noiseless cosmic variance limited experiment. We thus confirm the wisdom of the current strategy for r detection of deeply probed patches covering the f{sub sky} minimum-error trough with balloon and ground experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Unexpected topology of the temperature fluctuations in the cosmic microwave background

We study the topology generated by the temperature fluctuations of the cosmic microwave background (CMB) radiation, as quantified by the number of components and holes, formally given by the Betti numbers, in the growing excursion sets. We compare CMB maps observed by the Planck satellite with a thousand simulated maps generated according to the $Λ$CDM paradigm with Gaussian distributed fluctuations. The comparison is multi-scale, being performed on a sequence of degraded maps with mean pixel separation ranging from 0.05 to 7.33°. The survey of the CMB over S 2 is incomplete due to obfuscation effects by bright point sources and other extended foreground objects like our own galaxy. To deal with such situations, where analysis in the presence of “masks” is of importance, we introduce the concept of relative homology. The parametric χ 2 -test shows differences between observations and simulations, yielding p -values at percent to less than permil levels roughly between 2 and 7°, with the difference in the number of components and holes peaking at more than 3 σ sporadically at these scales. The highest observed deviation between the observations and simulations for b 0 and b 1 is approximately between 3 σ and 4 σ at scales of 3–7°. There are reports of mildly unusual behaviour of the Euler characteristic at 3.66° in the literature, computed from independent measurements of the CMB temperature fluctuations by Planck ’s predecessor, the Wilkinson Microwave Anisotropy Probe (WMAP) satellite. The mildly anomalous behaviour of the Euler characteristic is phenomenologically related to the strongly anomalous behaviour of components and holes, or the zeroth and first Betti numbers, respectively. Further, since these topological descriptors show consistent anomalous behaviour over independent measurements of Planck and WMAP, instrumental and systematic errors may be an unlikely source. These are also the scales at which the observed maps exhibit low variance compared to the simulations, and approximately the range of scales at which the power spectrum exhibits a dip with respect to the theoretical model. Non-parametric tests show even stronger differences at almost all scales. Crucially, Gaussian simulations based on power-spectrum matching the characteristics of the observed dipped power spectrum are not able to resolve the anomaly. Understanding the origin of the anomalies in the CMB, whether cosmological in nature or arising due to late-time effects, is an extremely challenging task. Regardless, beyond the trivial possibility that this may still be a manifestation of an extreme Gaussian case, these observations, along with the super-horizon scales involved, may motivate the study of primordial non-Gaussianity. Alternative scenarios worth exploring may be models with non-trivial topology, including topological defect models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Co-registered Topographical, Band Excitation Nanomechanical, and Mass Spectral Imaging Using a Combined Atomic Force Microscopy/Mass Spectrometry Platform

The advancement of a hybrid atomic force microscopy/mass spectrometry imaging platform demonstrating for the first time co-registered topographical, band excitation nanomechanical, and mass spectral imaging of a surface using a single instrument is reported. The mass spectrometry-based chemical imaging component of the system utilized nanothermal analysis probes for pyrolytic surface sampling followed by atmospheric pressure chemical ionization of the gas phase species produced with subsequent mass analysis. We discuss the basic instrumental setup and operation and the multimodal imaging capability and utility are demonstrated using a phase separated polystyrene/poly(2-vinylpyridine) polymer blend thin film. The topography and band excitation images showed that the valley and plateau regions of the thin film surface were comprised primarily of one of the two polymers in the blend with the mass spectral chemical image used to definitively identify the polymers at the different locations. Data point pixel size for the topography (390 nm x 390 nm), band excitation (781 nm x 781 nm), mass spectrometry (690 nm x 500 nm) images was comparable and submicrometer in all three cases, but the data voxel size for each of the three images was dramatically different. The topography image was uniquely a surface measurement, whereas the band excitation image included information from an estimated 10 nm deep into the sample and the mass spectral image from 110-140 nm in depth. Moreover, because of this dramatic sampling depth variance, some differences in the band excitation and mass spectrometry chemical images were observed and were interpreted to indicate the presence of a buried interface in the sample. The spatial resolution of the mass spectral image was estimated to be between 1.5 m 2.6 m, based on the ability to distinguish surface features in that image that were also observed in the other images.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Fuel Cycle Research & Development Technical Monthly – May 2012

Management and Integration LANL - Initial coordination meetings with NE and NA-20 were held the first week of May. Additional meetings, to include NA-82 and the new Proliferation and Terrorism Risk Assessment task are scheduled for June. Work package planning as part of the NTD transition is ongoing. Microcalorimetry LANL - Some parts to attempt repair of a malfunctioning water chiller that has been holding up work on the current detector array have arrived. We will attempt to begin running the compressor/cryostat next week to resume work on commissioning the detector array. We have also been working on a backup plan to temporarily move our system to a different lab space. Completed data analysis and prepared a paper summarizing Pu measurements for peer-review journal. Two members of our team presented work at the SORMA West 2012 conference. Completed data analysis and prepared a milestone report summarizing the development of Monte Carlo tools to study systematic errors. Electrochemical Sensor INL - The second sensor test was stopped short due to the work stand-down. Some activities related to this work have resumed, but not all. The sensor used during the second test was removed from the furnace and it showed cracks and later crumbled when being rinsed for sample preparation. The sensor material will be submitted to SEM analysis once work is resumed in the facilities where analysis is performed. A third sensor test has started. Tests with different arrangements will continue and will be oriented based on post-test analysis of the first three sensor tests. Materials with different annealing temperatures will also be prepared for analysis. Lead slowing down spectrometer LANL - Continued work on perturbation method for LSDS analysis. We are running simulations to delineate issues and are checking additional data libraries to see whether there are differences in simulation results. Electrochemical sensor INL - The second sensor test was stopped short due to the work stand-down. Some activities related to this work have resumed, but not all. The sensor used during the second test was removed from the furnace and it showed cracks and later crumbled when being rinsed for sample preparation. The sensor material will be submitted to SEM analysis once work is resumed in the facilities where analysis is performed. A third sensor test has started. Tests with different arrangements will continue and will be oriented based on post-test analysis of the first three sensor tests. Materials with different annealing temperatures will also be prepared for analysis. Fast Neutron Multiplicity analysis INL - The University of Michigan team continues its work on the post-experiment analysis of the validation data from JRC ISPRA, as well as scoping studies using the simulation tool MCNPX-PoliMi. At INL, our new staff member working on this project is now working to model performance capabilities for the fast-neutrons scintillator design concepts. At INL our primary analysis approach is focused on the Feynman mean-to-variance approach. At the University of Michigan, the primary analysis approach is multiplicity coincidence analysis. Fast Neutron Imaging to Quantify Nuclear Materials ORNL - Completed additional measurements of the two 'trainer' configurations as well as calibration measurements with sources on an x-y stage. The imager was shipped to Pantex for an NA-22 obligation at the end of May. Lead Slowing Down Spectrometer LANL - Continued to look into He4 detector. A Swiss company was located that makes He4 detectors and associated electronics. Had a teleconference with them to assess the possible help we can get from them. We are also looking in to constructing one locally. Ongoing perturbation calculations are providing information on the fundamental systematic error limits of LSDS. In order to achieve separating the contribution of Pu and 235U to the signal, there will need to be tight controls on systematic errors. Multi-isotope Process Monitor PNNL - Attended a training call in advanced multivariate classification and analysis methods. These methods were applied to the multivariate analysis of fuel characteristics based on simulated gamma. Work continued on a computational framework to quantify the impact of gamma-ray counting statistical precision on principal component regression (PCR) analysis of a multi-component (i.e. multi-isotope) gammaray spectrum. Tests of the simulation framework are anticipated to begin in early June. Development of a proposal to instrument H-Canyon is being prepared in conjunction with SRNL and the NNSA's NGSI program is ongoing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

An Evaluation of the Large‐Scale Atmospheric Circulation and Its Variability in CESM2 and Other CMIP Models

Abstract The Community Earth System Model 2 (CESM2) is the latest Earth System Model developed by the National Center for Atmospheric Research in collaboration with the university community and is significantly advanced in most components compared to its predecessor (CESM1). Here, CESM2's representation of the large‐scale atmospheric circulation and its variability is assessed. Further context is providedthrough comparison to the CESM1 large ensemble and other models from the Coupled Model Intercomparison Project (CMIP5 and CMIP6). This includes an assessment of the representation of jet streams and storm tracks, stationary waves, the global divergent circulation, the annular modes, the North Atlantic Oscillation, and blocking. Compared to CESM1, CESM2 is substantially improved in the representation of the storm tracks, Northern Hemisphere (NH) stationary waves, NH winter blocking and the global divergent circulation. It ranks within the top 10% of CMIP class models in many of these features. Some features of the Southern Hemisphere (SH) circulation have degraded, such as the SH jet strength, stationary waves, and blocking, although the SH jet stream is placed at approximately the correct location. This analysis also highlights systematic deficiencies in these features across the new CMIP6 archive, such as the continued tendency for the SH jet stream to be placed too far equatorward, the North Atlantic westerlies to be too strong over Europe, the storm tracks as measured by low‐level meridional wind variance to be too weak and a lack of blocking in the North Atlantic sector.

Simpson, Isla R.↗
DOE OSTI2021

Exploration of multifidelity UQ sampling strategies for computer network applications.

Network modeling is a powerful tool to enable rapid analysis of complex systems that can be challenging to study directly using physical testing. Here, two approaches are considered: emulation and simulation. The former runs real software on virtualized hardware, while the latter mimics the behavior of network components and their interactions in software. Although emulation provides an accurate representation of physical networks, this approach alone cannot guarantee the characterization of the system under realistic operative conditions. Operative conditions for physical networks are often characterized by intrinsic variability (payload size, packet latency, etc.) or a lack of precise knowledge regarding the network configuration (bandwidth, delays, etc.); therefore uncertainty quantification (UQ) strategies should be also employed. UQ strategies require multiple evaluations of the system with a number of evaluation instances that roughly increases with the problem dimensionality, i.e., the number of uncertain parameters. It follows that a typical UQ workflow for network modeling based on emulation can easily become unattainable due to its prohibitive computational cost. In this paper, a multifidelity sampling approach is discussed and applied to network modeling problems. The main idea is to optimally fuse information coming from simulations, which are a low-fidelity version of the emulation problem of interest, in order to decrease the estimator variance. By reducing the estimator variance in a sampling approach it is usually possible to obtain more reliable statistics and therefore a more reliable system characterization. Several network problems of increasing difficulty are presented. For each of them, the performance of the multifidelity estimator is compared with respect to the single fidelity counterpart, namely, Monte Carlo sampling. For all the test problems studied in this work, the multifidelity estimator demonstrated an increased efficiency with respect to MC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Improved Infrared Optical Constants from Pressed Pellets: II. Ellipsometric n and k Values for Ammonium Sulfate with Variability Analysis

Infrared spectral imaging is facilitated via the comparison of spectra recorded in situ to a databank of actual or synthetic infrared reflectance spectra. It has recently been shown that reference spectra corresponding to the many different morphological forms of the same chemical can be generated synthetically using the imaginary, k, and real, n, components of the complex refractive index, n~ = n + ik. One method to obtain the n and k vectors is infrared ellipsometry, which measures the changes in amplitude, tan ?, and phase, ?, of polarized light reflected from the sample both as a function of wavenumber and angle of incidence. The method requires specularly reflected light so best results are usually obtained with polished planar samples of large surface area. Due to the difficulties of obtaining such samples, however, we investigate the possibility of pressing powders of neat materials and obtaining the corresponding optical constants from the pellets. In this paper, variability in the sample pellet and preparation method is investigated, as is variability in the fitting procedure for the derived optical constants. The n/k vectors are derived from the measured ellipsometric parameters, tan ? and ?, as they are fit by an oscillator model which yield n(?) and k(?) vectors as a function of wavenumber, ?. Construction of the oscillator model is not automatic and depends on significant input from the analyst as well as the sample’s physical characteristics. For the pellet pressing, the experimental variability was found to be minimized for size-selected powdered samples as gauged by the minimal variance in ? and ? for three different pellets; similarly, the analytical precision for multiple measurements of the same pellet was also quite good, suggesting that a pressed pellet is a viable sample preparation method. The greatest variability came in the analytic fitting procedure with differences up to 20% arising from four different fits to the same data set. The final ellipsometric n/k data are compared to literature values obtained from crystalline (NH4)2SO4 samples as well as single-angle reflectance measurements that also used pressed pellets. Comparison with the previous literature values shows generally good agreement although higher k-values are observed for the independent sets of data derived from pressed pellets. These data are suggested as an improved set of optical constants for (NH4)2SO4.

optical constants, ellipsometry, ammonium sulfate,↗
DOE OSTI2017

Transmutation approximations for the application of hybrid Monte Carlo/deterministic neutron transport to shutdown dose rate analysis

In fusion energy systems (FES) neutrons born from burning plasma activate system components. The photon dose rate after shutdown from resulting radionuclides must be quantified. This shutdown dose rate (SDR) is calculated by coupling neutron transport, activation analysis, and photon transport. The size, complexity, and attenuating configuration of FES motivate the use of hybrid Monte Carlo (MC)/deterministic neutron transport. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) method can be used to optimize MC neutron transport for coupled multiphysics problems, including SDR analysis, using deterministic estimates of adjoint flux distributions. When used for SDR analysis, MS-CADIS requires the formulation of an adjoint neutron source that approximates the transmutation process. In this work, transmutation approximations are used to derive a solution for this adjoint neutron source. It is shown that these approximations are reasonably met for typical FES neutron spectra and materials over a range of irradiation scenarios. When these approximations are met, the Groupwise Transmutation (GT)-CADIS method, proposed here, can be used effectively. GT-CADIS is an implementation of the MS-CADIS method for SDR analysis that uses a series of single-energy-group irradiations to calculate the adjoint neutron source. For a simple SDR problem, GT-CADIS provides speedups of 200 100 relative to global variance reduction with the Forward-Weighted (FW)-CADIS method and 9 ± 5 • 10 4 relative to analog. As a result, this work shows that GT-CADIS is broadly applicable to FES problems and will significantly reduce the computational resources necessary for SDR analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Megavoltage Computed Tomography Image Guidance With Helical Tomotherapy in Patients With Vertebral Tumors: Analysis of Factors Influencing Interobserver Variability

Purpose: To evaluate megavoltage computed tomography (MVCT)-based image guidance with helical tomotherapy in patients with vertebral tumors by analyzing factors influencing interobserver variability, considered as quality criterion of image guidance. Methods and Materials: Five radiation oncologists retrospectively registered 103 MVCTs in 10 patients to planning kilovoltage CTs by rigid transformations in 4 df. Interobserver variabilities were quantified using the standard deviations (SDs) of the distributions of the correction vector components about the observers' fraction mean. To assess intraobserver variabilities, registrations were repeated after {>=}4 weeks. Residual deviations after setup correction due to uncorrectable rotational errors and elastic deformations were determined at 3 craniocaudal target positions. To differentiate observer-related variations in minimizing these residual deviations across the 3-dimensional MVCT from image resolution effects, 2-dimensional registrations were performed in 30 single transverse and sagittal MVCT slices. Axial and longitudinal MVCT image resolutions were quantified. For comparison, image resolution of kilovoltage cone-beam CTs (CBCTs) and interobserver variability in registrations of 43 CBCTs were determined. Results: Axial MVCT image resolution is 3.9 lp/cm. Longitudinal MVCT resolution amounts to 6.3 mm, assessed as full-width at half-maximum of thin objects in MVCTs with finest pitch. Longitudinal CBCT resolution is better (full-width at half-maximum, 2.5 mm for CBCTs with 1-mm slices). In MVCT registrations, interobserver variability in the craniocaudal direction (SD 1.23 mm) is significantly larger than in the lateral and ventrodorsal directions (SD 0.84 and 0.91 mm, respectively) and significantly larger compared with CBCT alignments (SD 1.04 mm). Intraobserver variabilities are significantly smaller than corresponding interobserver variabilities (variance ratio [VR] 1.8-3.1). Compared with 3-dimensional registrations, 2-dimensional registrations have significantly smaller interobserver variability in the lateral and ventrodorsal directions (VR 3.8 and 2.8, respectively) but not in the craniocaudal direction (VR 0.75). Conclusion: Tomotherapy image guidance precision is affected by image resolution and residual deviations after setup correction. Eliminating the effect of residual deviations yields small interobserver variabilities with submillimeter precision in the axial plane. In contrast, interobserver variability in the craniocaudal direction is dominated by the poorer longitudinal MVCT image resolution. Residual deviations after image guidance exist and need to be considered when dose gradients ultimately achievable with image guided radiation therapy techniques are analyzed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Bayesian calibration of irradiated graphite property models under high temperatures

Graphite under high temperatures and irradiation is central to advanced reactors. We develop a Bayesian calibration framework for graphite property models that explicitly represents model-data mismatch via a Gaussian-process discrepancy. The approach propagates uncertainty from parameters, experimental noise, and model form, with a hierarchical variance structure to capture group and cross-group noise. Using two predictive models across five grades (IG-110, NBG-18, PCEA, NBG-17, 2114) and four properties-irradiation-induced dimension change, creep, Young’s modulus change ratio, and coefficient of thermal expansion change ratio-we obtain average predictive-error reductions of 54%, 65%, 17%, and 17% when discrepancy is included. We illustrate engineering impact with a multiphysics model of a very-high-temperature reactor prismatic reflector brick, analyzing stresses under high fluence and temperature. Accounting for model discrepancy markedly improves predictive accuracy and provides a robust basis for reliable graphite component design in advanced reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2018

Evapotranspiration simulations in ISIMIP2a—Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets

Actual land evapotranspiration (ET) is a key component of the global hydrological cycle and an essential variable determining the evolution of hydrological extreme events under different climate change scenarios. However, recently available ET products show persistent uncertainties that are impeding a precise attribution of human-induced climate change. Here, we aim at comparing a range of independent global monthly land ET estimates with historical model simulations from the global water, agriculture, and biomes sectors participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). Among the independent estimates, we use the EartH2Observe Tier-1 dataset (E2O), two commonly used reanalyses, a pre-compiled ensemble product (LandFlux-EVAL), and an updated collection of recently published datasets that algorithmically derive ET from observations or observations-based estimates (diagnostic datasets). A cluster analysis is applied in order to identify spatiotemporal differences among all datasets and to thus identify factors that dominate overall uncertainties. The clustering is controlled by several factors including the model choice, the meteorological forcing used to drive the assessed models, the data category (models participating in the different sectors of ISIMIP2a, E2O models, diagnostic estimates, reanalysis-based estimates or composite products), the ET scheme, and the number of soil layers in the models. By using these factors to explain spatial and spatio-temporal variabilities in ET, we and that the model choice mostly dominates (24%{40% of variance explained), except for spatio-temporal patterns of total ET, where the forcing explains the largest fraction of the variance (29%). The most dominant clusters of datasets are further compared with individual diagnostic and reanalysis-based estimates to assess their representation of selected heat waves and droughts in the Great Plains, Central Europe and Western Russia. Although most of the ET estimates capture these extreme events, the generally large spread among the entire ensemble indicates substantial uncertainties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Effective cosmic density field reconstruction with convolutional neural network

ABSTRACT We present a cosmic density field reconstruction method that augments the traditional reconstruction algorithms with a convolutional neural network (CNN). Following previous work, the key component of our method is to use the reconstructed density field as the input to the neural network. We extend this previous work by exploring how the performance of these reconstruction ideas depends on the input reconstruction algorithm, the reconstruction parameters, and the shot noise of the density field, as well as the robustness of the method. We build an eight-layer CNN and train the network with reconstructed density fields computed from the Quijote suite of simulations. The reconstructed density fields are generated by both the standard algorithm and a new iterative algorithm. In real space at z = 0, we find that the reconstructed field is 90 per cent correlated with the true initial density out to $k\sim 0.5 \, \mathrm{ h}\, \rm {Mpc}^{-1}$, a significant improvement over $k\sim 0.2 \, \mathrm{ h}\, \rm {Mpc}^{-1}$ achieved by the input reconstruction algorithms. We find similar improvements in redshift space, including an improved removal of redshift space distortions at small scales. We also find that the method is robust across changes in cosmology. Additionally, the CNN removes much of the variance from the choice of different reconstruction algorithms and reconstruction parameters. However, the effectiveness decreases with increasing shot noise, suggesting that such an approach is best suited to high density samples. This work highlights the additional information in the density field beyond linear scales as well as the power of complementing traditional analysis approaches with machine learning techniques.

Astronomy & Astrophysics↗
DOE OSTI2021

Towards a Robust Sampling Approach: A Computational Review and Design

As pointed out in several other works, the estimation of the reliability of the electrical grid can not be conducted without the estimation of the stochastic phenomena of electicity demand and electricity production by variable renewable sources. Therefore, sampling procedures have become integral in the design of engineering structures and analysis. Commonly referred to as Monte Carlo uncertainty analysis or integration, the general objective of these procedures is to establish specifics about the uncertainty of an output characteristic of such an engineering system, given uncertainty about its input characteristics. These sampling procedures are applied in a context in which establishing such specifics cannot be performed through other means. Variance-reduction techniques are designed to lessen the variability among estimators to estimate statistics of those output uncertainties. Importance-sampling techniques, on the other hand, are designed to reduce the number of samples needed to estimate a particular statistic—e.g., a tail probability. The combination of these approaches can reduce the computational burden considerably for a particular estimator and statistic. Importance sampling—geared and designed as it is toward improving a particular estimator—suffers, unfortunately, from the unintended consequence of reducing the performance of other estimators in terms of their variance. The objective of this paper is to offer an alternative sampling procedure where this variance does not grow unacceptably large for a suite of estimators. Moreover, it is anticipated that, with additional knowledge of how an engineering output characteristic responds to its input characteristics, tuning parameters of the input’s sampling procedure can be set to improve the output characteristic’s estimation. This work proves the effectiveness of the suggested alternative approach. Such positive outcome will lead to a decrease of the computational burden of performing stochastic optimization of integrated energy systems (e.g., components dispatch, and portfolio composition). In particular, capturing the contribution to the overall system cost of rare and unlikely events and patterns of the electricity demand and production will become less computationally expensive. This is due to the fact that the approach demonstrated here will allow the sampling of those rare occurrences more frequently without misrepresenting their probabilistic impacts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

Analysis of the Tank 6F Final Characterization Samples-2012 (U)

The Savannah River National Laboratory (SRNL) was requested by Savannah River Remediation (SRR) to provide sample preparation and analysis of the Tank 6F final characterization samples to determine the residual tank inventory prior to grouting. Fourteen residual Tank 6F solid samples from three areas on the floor of the tank were collected and delivered to SRNL between May and August 2011. These Tank 6F samples were homogenized and combined into three composite samples based on a proportion compositing scheme and the resulting composite samples were analyzed for radiological, chemical and elemental components. Additional measurements performed on the Tank 6F composite samples include bulk density and water leaching of the solids to account for water soluble components. The composite Tank 6F samples were analyzed and the data reported in triplicate. Sufficient quality assurance standards and blanks were utilized to demonstrate adequate characterization of the Tank 6F samples. The main evaluation criteria were target detection limits specified in the technical task request document. While many of the target detection limits were met for the species characterized for Tank 6F some were not met. In a few cases, the relatively high levels of radioactive species of the same element or a chemically similar element precluded the ability to measure some isotopes to low levels. The isotopes whose detection limits were not met in all cases included Sn-126, Sb-126, Sb-126m, Eu-152, Cm-243 and Cf-249. SRNL, in conjunction with the customer, reviewed all of these cases and determined that the impacts of not meeting the target detection limits were acceptable. Based on the analyses of variance (ANOVA) for the inorganic constituents of Tank 6F, all the inorganic constituents displayed heterogeneity. The inorganic results demonstrated consistent differences across the composite samples: lowest concentrations for Composite Sample 1, intermediate-valued concentrations for Composite Sample 2, and highest concentrations for Composite Sample 3. The Hg and Mo results suggest possible measurement outliers. However, the magnitudes of the differences between the Hg 95% upper confidence limit (UCL95) results with and without the outlier and the magnitudes of the differences between the Mo UCL95 results with and without the outlier do not appear to have practical significance. It is recommended to remove the potential measurement outliers. Doing so is conservative in the sense of producing a higher UCL95 for Hg and Mo than if the potential outliers were included in the calculations. In contrast to the inorganic results, most of the radionuclides did not demonstrate heterogeneity among the three Tank 6F composite sample characterization results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Analysis of the Tank 6F Final Characterization Samples-2012

The Savannah River National Laboratory (SRNL) was requested by Savannah River Remediation (SRR) to provide sample preparation and analysis of the Tank 6F final characterization samples to determine the residual tank inventory prior to grouting. Fourteen residual Tank 6F solid samples from three areas on the floor of the tank were collected and delivered to SRNL between May and August 2011. These Tank 6F samples were homogenized and combined into three composite samples based on a proportion compositing scheme and the resulting composite samples were analyzed for radiological, chemical and elemental components. Additional measurements performed on the Tank 6F composite samples include bulk density and water leaching of the solids to account for water soluble components. The composite Tank 6F samples were analyzed and the data reported in triplicate. Sufficient quality assurance standards and blanks were utilized to demonstrate adequate characterization of the Tank 6F samples. The main evaluation criteria were target detection limits specified in the technical task request document. While many of the target detection limits were met for the species characterized for Tank 6F some were not met. In a few cases, the relatively high levels of radioactive species of the same element or a chemically similar element precluded the ability to measure some isotopes to low levels. The isotopes whose detection limits were not met in all cases included Sn-126, Sb-126, Sb-126m, Eu-152, Cm- 243 and Cf-249. SRNL, in conjunction with the customer, reviewed all of these cases and determined that the impacts of not meeting the target detection limits were acceptable. Based on the analyses of variance (ANOVA) for the inorganic constituents of Tank 6F, all the inorganic constituents displayed heterogeneity. The inorganic results demonstrated consistent differences across the composite samples: lowest concentrations for Composite Sample 1, intermediate-valued concentrations for Composite Sample 2, and highest concentrations for Composite Sample 3. The Hg and Mo results suggest possible measurement outliers. However, the magnitudes of the differences between the Hg 95% upper confidence limit (UCL95) results with and without the outlier and the magnitudes of the differences between the Mo UCL95 results with and without the outlier do not appear to have practical significance. It is recommended to remove the potential measurement outliers. Doing so is conservative in the sense of producing a higher UCL95 for Hg and Mo than if the potential outliers were included in the calculations. In contrast to the inorganic results, most of the radionuclides did not demonstrate heterogeneity among the three Tank 6F composite sample characterization results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Advancing Development of Emissions Detection (Final Report)

This document is the final report to the U.S. Department of Energy (DOE for contract DE-FE0031873) awarded to Colorado State University (CSU). CSU and partners at Harrisburg University of Science and Technology, University of Texas Arlington, and University of Texas at Austin organized several testing rounds to provide knowledge focused on advancing the detection capabilities of emissions monitoring devices. With this funding opportunity the research group began by establishing the Advancing the Development of Emission Detection (ADED) program, with the goal focused on enhancing the accuracy, reliability, and field applicability of methane detection technologies. This effort aimed to address the critical challenges of identifying and quantifying methane emissions while enabling industry stakeholders to meet regulatory compliance and environmental sustainability goals. The program engaged with industry, government, and technology stakeholders to promote adoption and consensus on testing techniques for methane detection solutions. Methane, a potent greenhouse gas, contributes significantly to global warming, and the oil and natural gas (O&G) sector is a primary source of methane emissions. Regulatory measures such as leak detection and repair (LDAR) programs have been implemented to address emissions. However, traditional LDAR approaches, reliant on handheld and component-level measurements, are resource-intensive. To address these limitations and move with evolving regulations, advanced methane technologies are emerging. These solutions include ground-based sensors, mobile systems (e.g., drones, vehicles, and aircraft), and satellite-based platforms. They offer innovative capabilities for autonomous monitoring, larger spatial coverage, and emission quantification using methods such as tracer gas techniques and inverse modeling with Gaussian plume analysis. The ADED program began with creating protocols for methane controlled release (CR) testing these continuous monitoring (CM) and survey technologies that detect and monitor methane emissions at O&G facilities. The protocols were then implemented throughout testing of CM and survey devices at CSU’s Methane Emissions Technology Evaluation Center (METEC) facility from 2021 through 2024. As apart of the protocol, solutions that tested under the ADED program installed their solutions at METEC, documented their system under test, and provided detection reports to the METEC team for analysis. The METEC team would provide the solutions with analyzed reports of their emissions and ground truth data of the releases conducted during their testing session. Under the ADED program, CMs were also tested at O&G facilities for a six week test run of challenge release (ChR) releases. The findings from the ADED program underscore the critical role of collaborative research and innovation in tackling methane emissions, offering a pathway for the oil and gas sector to achieve significant environmental and economic benefits. Results from METEC testing saw improvement of performance and accuracy across all solutions over the extent of the ADED experiments. The results also showed a variance in CM solution performance between CRs and ChRs. That variance pushed the team to further analyze the differences between CR testing environments and field conditions. With the drive from regulations and that variance in field conditions, the ADED team began designing a new CR testing protocol and additions to the METEC testing facility. The METEC team is furthering the progress made through the ADED program with awarded funding from DE-FE0032276. This funding pushes the development of METEC’s addition with new equipment, allowing for an updated facility layout. METEC still facilitates for traditional facilities, with a legacy pad, while expanding an new design based on how O&G infrastructure has Final Report - Contract Number: DE-FE0031873 been changed over the last decade. Throughout the ADED program the team has also been working with international partners to ensure staying in the trend globally. International partners have been essential in moving the new protocol forward to implement into CR testing at the METEC facility in Spring 2025.

42 ENGINEERING↗