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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Fermi and Swift Gamma-Ray Burst Afterglow Population Studies

The new and extreme population of GRBs detected by Fermi-LAT shows several new features in high energy gamma-rays that are providing interesting and unexpected clues into GRB prompt and afterglow emission mechanisms. Over the last 6 years, it has been Swift that has provided the robust data set of UV/optical and X-ray afterglow observations that opened many windows into components of GRB emission structure. The relationship between the LAT GRBs and the well studied, fainter, less energetic GRBs detected by Swift-BAT is only beginning to be explored by multi-wavelength studies. We explore the large sample of GRBs detected by BAT only, BAT and Fermi-GBM, and GBM and LAT, focusing on these samples separately in order to search for statistically significant differences between the populations, using only those GRBs with measured redshifts in order to physically characterize these objects. We disentangle which differences are instrumental selection effects versus intrinsic properties, in order to better understand the nature of the special characteristics of the LAT bursts.

Racusin, Judith I.↗
NASA NTRS2011

Fermi and Swift Gamma-Ray Burst Afterglow Population Studies

The new and extreme population of GRBs detected by Fermi -LAT shows several new features in high energy gamma-rays that are providing interesting and unexpected clues into GRB prompt and afterglow emission mechanisms. Over the last 6 years, it has been Swift that has provided the robust dataset of UV/optical and X-ray afterglow observations that opened many windows into components of GRB emission structure. The relationship between the LAT detected GRBs and the well studied, fainter, less energetic GRBs detected by Swift -BAT is only beginning to be explored by multi-wavelength studies. We explore the large sample of GRBs detected by BAT only, BAT and Fermi -GBM, and GBM and LAT, focusing on these samples separately in order to search for statistically significant differences between the populations, using only those GRBs with measured redshifts in order to physically characterize these objects. We disentangle which differences are instrumental selection effects versus intrinsic properties, in order to better understand the nature of the special characteristics of the LAT bursts.

Racusin, Judith L.↗
NASA NTRS2017

An Assessment of Land Surface and Lightning Characteristics Associated with Lightning-Initiated Wildfires

Can we use modeled information of the land surface and characteristics of lightning beyond flash occurrence to increase the identification and prediction of wildfires? Combine observed cloud-to-ground (CG) flashes with real-time land surface model output, and Compare data with areas where lightning did not start a wildfire to determine what land surface conditions and lightning characteristics were responsible for causing wildfires. Statistical differences between suspected fire-starters and non-fire-starters were peak-current dependent 0-10 cm Volumetric and Relative Soil Moisture comparisons were statistically dependent to at least the p = 0.05 independence level for both polarity flash types Suspected fire-starters typically occurred in areas of lower soil moisture than non-fire-starters. GVF value comparisons were only found to be statistically dependent for -CG flashes. However, random sampling of the -CG non-fire starter dataset revealed that this relationship may not always hold.

wildfire↗
DOE OSTI2012

Use of Stable Isotopes in Forensic Analysis of Microorganisms

The use of isotopic signatures for forensic analysis of biological materials is well-established, and the same general principles that apply to interpretation of stable isotope content of C, N, O, and H apply to the analysis of microorganisms. Heterotrophic microorganisms derive their isotopic content from their growth substrates, which are largely plant and animal products, and the water in their culture medium. Thus the isotope signatures of microbes are tied to their growth environment. The C, N, O, and H isotope ratios of spores have been demonstrated to constitute highly discriminating signatures for sample matching. They can rule out specific samples of media and/or water as possible production media, and can predict isotope ratio ranges of the culture media and water used to produce a given sample. These applications have been developed and tested through analyses of approximately 250 samples of Bacillus subtilis spores and over 500 samples of culture media, providing a strong statistical basis for data interpretation. A Bayesian statistical framework for integrating stable isotope data with other types of signatures derived from microorganisms has been able to characterize the culture medium used to produce spores of various Bacillus species, leveraging isotopic differences in different medium types and demonstrating the power of data integration for forensic investigations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Theory of Electron Imaging in Small Devices

The research in this program involved theoretical investigations of the transport of charge in graphene and small heterostructure devices. There is an important trend toward imaging electronic systems in real space, with the goal of understanding the specifics of individual samples rather than settling for ensemble and statistical descriptions. For example one of our goals has been the understanding of scanning probe microscopy (SPM) imaging of systems in which the motion of the carriers is restricted to two degrees of freedom, such as in grapheme and the two dimensional electron (and hole) gas (2DEGs and 2DHGs) in GaAs/AlGaAs heterostructures, or when the motion is restricted to one degree of freedom as in nanowires. SPM imaging uses the tip of a movable charged probe to alter the electrons locally, depleting or alternatively increasing the amount of charges in the electron gas just below the tip results in a change to the flow pattern of the charge. The focus of this research was on understanding how the tunable tip affects functional aspects of the device that can be used to understand electronic and transport properties. For instance, scanning over the device while measuring the conductance results in conductance maps, an imaging of the charge transport. This imaging is often semi-direct and requires theory and interpretation to extract all that can be deduced about the underlying physical quantities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

ANALYSIS OF SAFETY IMPACTS FROM EXTERNAL FLOODING USING THE RISK-INFORMED SAFETY MARGIN CHARACTERIZATION (RISMC) TOOLKIT

The existing fleet of U.S. nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates. In order to evaluate the impact of these factors on the safety of the plant, the Risk-Informed Safety Margin Characterization (RISMC) project aims to provide insight to decision makers through a series of simulations of the plant dynamics for different initial conditions (e.g., probabilistic analysis and uncertainty quantification). This paper demonstrates how Idaho National Laboratory (INL) researchers use the RISMC Toolkit to investigate complex nuclear plant phenomena using RAVEN and RELAP-7. The analysis focused on a highly relevant topic currently facing some nuclear power plants – specifically flooding issues. This research and development looked at challenges to a hypothetical pressurized water reactor, including: (1) a potential loss of off-site power followed by the possible loss of all diesel generators (i.e., a station black-out event), (2) earthquake induced station-blackout, and (3) a potential earthquake induced tsunami flood. The analysis is performed by using a set of codes: a thermal-hydraulic code (RELAP-7), a flooding simulation tool (NEUTRINO) and a stochastic analysis tool (RAVEN) – these are currently under development at INL. Using RAVEN, we were able to perform multiple RELAP-7 simulation runs by changing specific parts of the model in order to reflect specific aspects of different scenarios, including both the failure and recovery of critical components. The simulation employed traditional statistical tools (such as Monte-Carlo sampling) and more advanced machine-learning based algorithms to perform uncertainty quantification in order to understand changes in system performance and limitations as a consequence of power uprate. Qualitative and quantitative results obtained gave a detailed picture of the issues associated with potential accident scenarios. These types of insights can provide useful material for decision makers to perform risk-informed margins management.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

EPRI Software for Estimating Decommissioning Waste Volumes - 16046

EPRI has adapted computer software that can estimate the volume and activity content of waste resulting from the dismantlement of nuclear facilities. This software, designated as Automatic Estimation of the Radiological Inventory or AERI, was originally developed by Iberdrola for use by ENRESA in Spain. The software estimates the radiological inventory for all the components and civil structures of the plant or other facility that are included in the physical inventory. The radiological inventory shows the internal and external surface contamination, as well as the volumetric contamination. The processes of the software are able to estimate both the specific activity levels (in Bq/g or pCi/g) for each radionuclide and the surface activity (Bq/cm{sup 2} or dpm/100 cm{sup 2}) for components and civil structures located in the radiological areas. AERI allows the user to extrapolate, through a statistical approach, the contamination levels obtained by sampling data in specific components and civil structures to the entire facility. The main benefits and values obtained with AERI are the following: - The radiological inventory of the plant can be obtained from a limited set of radiological sampling data. Using the mathematical models allows for the optimization of the number of sampling and analysis that needs to be done. The uncertainties of the calculations are reduced with more data. The user must balance the level of uncertainty of the calculations and the number of sample data they will use. - The automatic management of radiological data in short computing times allows for the execution of several scenarios in a reasonable time. Therefore, different radioactive waste and decommissioning hypotheses can be tested. For example, inventory and data can be split into two different set. One of them can be used for obtaining radiological inventory for early dismantling (3 years, as example) and the second one for deferred dismantling (25 years.) - The software supports the planning and implementation of decommissioning strategies for nuclear plants. For instance, several decontamination factors can be evaluated, assuming different level for decontamination of materials, and results for materials from several streams and use of different container types may be included in each evaluation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Systematic search for tidal features around nearby galaxies: I. Enhanced SDSS imaging of the Local Volume

In hierarchical models of galaxy formation, stellar tidal streams are expected around most, if not all, galaxies. Although these features may provide useful diagnostics of the Λ CDM model, their observational properties remain poorly constrained because they are challenging to detect and interpret and have been studied in detail for only a sparse sampling of galaxy population. More quantitative, systematic approaches are required. We advocate statistical analysis of the counts and properties of such features in archival wide-field imaging surveys for a direct comparison against results from numerical simulations. We aim to study systematically the frequency of occurrence and other observational properties of tidal features around nearby galaxies. The sample we construct will act as a foundational dataset for statistical comparison with cosmological models of galaxy formation. Our approach is based on a visual classification of diffuse features around a volume-limited sample of nearby galaxies, using a post-processing of Sloan Digital Syk Survey (SDSS) imaging optimized for the detection of stellar structure with low surface brightness. At a limiting surface brightness of 28 mag arcsec –2 , 14% of the galaxies in our sample exhibit evidence of diffuse features likely to have arisen from minor merging events. Our technique recovers all previously known streams in our sample and yields a number of new candidates. Consistent with previous studies, coherent arc-like features and shells are the most common type of tidal structures found in this study. Here, we conclude that although some detections are ambiguous and could be corroborated or refuted with deeper imaging, our technique provides a reliable foundation for the statistical analysis of diffuse circumgalactic features in wide-area imaging surveys, and for the identification of targets for follow-up studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Advanced detector signal acquisition and electron beam scanning for high resolution SEM imaging

We report the advancement of materials science at the mesoscale requires improvements in both sampling volumes/areas and spatial resolution in order to make statistically significant measurements of microstructures that influence higher-order material properties, such as fatigue and fracture. Therefore, SEM-based techniques have become desirable due to improvements in imaging resolution, large sample handling capability, and flexibility for in-situ instrumentation. By using fast sampling of SEM electron detector signals, intrinsic beam scanning defects have been identified that are related to the response time of the SEM electron beam deflectors and electron detectors. Mitigation of these beam scanning defects using detector sampling approaches and an adaptive model for settling time is shown to produce higher resolution SEM images, at faster image acquisition times, with a means to quantify the different response functions for various beam deflectors and detectors including those for electrons and ions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Response Variability in Commercial MOSFET SEE Qualification

Single-event effects (SEE) evaluation of five different part types of next generation, commercial trench MOSFETs indicates large part-to-part variation in determining a safe operating area (SOA) for drain-source voltage (V DS ) following a test campaign that exposed >50 samples per part type to heavy ions. These results suggest a determination of a SOA using small sample sizes may fail to capture the full extent of the part-to-part variability. An example method is discussed for establishing a Safe Operating Area using a one-sided statistical tolerance limit based on the number of test samples. Finally, burn-in is shown to be a critical factor in reducing part-to-part variation in part response. Implications for radiation qualification requirements are also explored.

43 PARTICLE ACCELERATORS↗
DOE OSTI2012

Fast DRR generation for 2D to 3D registration on GPUs

Purpose: The generation of digitally reconstructed radiographs (DRRs) is the most time consuming step on the CPU in intensity based two-dimensional x-ray to three-dimensional (CT or 3D rotational x-ray) medical image registration, which has application in several image guided interventions. This work presents optimized DRR rendering on graphical processor units (GPUs) and compares performance achievable on four commercially available devices. Methods: A ray-cast based DRR rendering was implemented for a 512 Multiplication-Sign 512 Multiplication-Sign 72 CT volume. The block size parameter was optimized for four different GPUs for a region of interest (ROI) of 400 Multiplication-Sign 225 pixels with different sampling ratios (1.1%-9.1% and 100%). Performance was statistically evaluated and compared for the four GPUs. The method and the block size dependence were validated on the latest GPU for several parameter settings with a public gold standard dataset (512 Multiplication-Sign 512 Multiplication-Sign 825 CT) for registration purposes. Results: Depending on the GPU, the full ROI is rendered in 2.7-5.2 ms. If sampling ratio of 1.1%-9.1% is applied, execution time is in the range of 0.3-7.3 ms. On all GPUs, the mean of the execution time increased linearly with respect to the number of pixels if sampling was used. Conclusions: The presented results outperform other results from the literature. This indicates that automatic 2D to 3D registration, which typically requires a couple of hundred DRR renderings to converge, can be performed quasi on-line, in less than a second or depending on the application and hardware in less than a couple of seconds. Accordingly, a whole new field of applications is opened for image guided interventions, where the registration is continuously performed to match the real-time x-ray.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Precision redshift-space galaxy power spectra using Zel'dovich control variates

Numerical simulations in cosmology require trade-offs between volume, resolution and run-time that limit the volume of the Universe that can be simulated, leading to sample variance in predictions of ensemble-average quantities such as the power spectrum or correlation function(s). Sample variance is particularly acute at large scales, which is also where analytic techniques can be highly reliable. This provides an opportunity to combine analytic and numerical techniques in a principled way to improve the dynamic range and reliability of predictions for clustering statistics. In this paper we extend the technique of Zel'dovich control variates, previously demonstrated for 2-point functions in real space, to reduce the sample variance in measurements of 2-point statistics of biased tracers in redshift space. We demonstrate that with this technique, we can reduce the sample variance of these statistics down to their shot-noise limit out to k ~ 0.2 h Mpc -1 . This allows a better matching with perturbative models and improved predictions for the clustering of e.g. quasars, galaxies and neutral Hydrogen measured in spectroscopic redshift surveys at very modest computational expense. We discuss the implementation of ZCV, give some examples and provide forecasts for the efficacy of the method under various conditions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Operando X-ray Nanocharacterization of Polycrystalline Thin Film Modules

Non-destructive measurement techniques, with high spatial resolution, capable of correlating composition and structure with device properties, are few and far between. For the case of polycrystalline and inhomogeneous materials, the added challenge is that large sampling areas are necessary in order to have a statistical representation of the specimen under study. For the study of grain cores and grain boundaries in polycrystalline solar absorbers this is of particular importance since their dissimilar behavior and variability throughout the samples makes it difficult to draw conclusions and ultimately optimize the materials and devices. Our approach to use state-of-the-art x-ray microscopy to study full module stacks under operating conditions is unique. Understanding the effects of elemental and charge migration under full encapsulation and operating conditions will allow CIGS and CdTe manufactures and in particular our partners in this proposal to modify materials, stacks, architectures, and processing steps to minimize the performance losses through time.

14 SOLAR ENERGY↗
DOE OSTI2017

Statistical Analyses of Post Irradiation Experiments of the BWR Forsmark

Computer codes which are to be used in nuclear safety research need to be validated prior to their application. For depletion codes, this validation can be done using data from post irradiation experiments (PIE). These experiments consist of a radiochemical analysis of small parts of a fuel rod (FR), which has been irradiated in a nuclear power plant as part of a fuel assembly (FA). This analysis allows the deduction of the isotopic composition of nuclides important for the desired application case. In addition the operation history at the sample location needs to be known and reported with the analysis results. In our work, we perform uncertainty and sensitivity analyses of a model based on a sample from the boiling water reactor (BWR) Forsmark-3 in order to deduce the influence of uncertain system parameters on the nuclide composition of the depleted fuel. In a second step we compare the resulting uncertainties of the nuclide densities with the deviation between their calculated and experimental values. The goal is to obtain quantitative uncertainty data which can be accounted for in a validation procedure. We use the Monte Carlo sampling approach, i.e. repeating the model calculation using statistically varied sets of the uncertain input parameters and analyzing the distributions of the result values statistically. BWR depletion calculations are especially demanding due to the increased complexity and heterogeneity compared to pressurized water reactors (PWR): extensively variable enrichments, complex FA geometries, partial length FRs, strong axially varying moderator density and the common use of gadolinium as burnable absorber in some of the FRs. However, the precise and correct calculation of BWR-depletion is extremely important in view of a possible application in burnup credit for BWR FAs. Therein credit is taken for the reduced reactivity of spent fuel due to the depletion of {sup 235}U for transport and intermediate or final storage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Quantifying and Qualifying Alloys Based on Level of Homogenization: A U–10 wt% Mo Alloy Case Study

Homogenization heat treatment is performed to attain uniformity in microstructure of metals and metal alloys, which is helpful to achieve the desired workability and microstructure in final products, and eventually to gain predictable and consistent performance. Fabrication of fuel plates made from a low-enriched uranium alloy with 10 wt% Mo (U-10Mo) involves multiple thermomechanical processing steps. It is well known that the molybdenum homogeneity in the final formed product affects the fuel performance in the nuclear reactor. To make sure these materials are uniformly homogenized, a statistical method was proposed to quantify and characterize the Mo concentration variation in U-10Mo fuel plates by analyzing the Mo concentration measurement data from scanning electron microscopy–energy dispersive spectroscopy line scans. Statistical tolerance intervals were employed to determine the qualification of U-10Mo fuel plates. We formulate an argument for the minimum number of independent samples required to define fuel plate qualification if no Mo measurement data are available in advance, and demonstrate that the given tolerance interval requirements can be equivalently reduced to a sample variance criterion in this application. The outcome of the statistical analysis can be used to optimize casting design and eventually increase productivity and reduce fabrication cost. The statistical strategy developed in this report can be implemented for other applications, especially in the field of material manufacturing to assess qualification requirements and monitor and improve process design.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Effect of secondary gas-phase reactions (SGR) in pyrolysis of carbon feedstocks for anisotropic carbon materials production – 2: Effects of SGR on tars produced from varying ranks of coal

Herein, this work explores the extent to which secondary gas-phase reactions (SGR) in pyrolysis can be used to modify coal tar chemistries from coals of different ranks in favor of improved anisotropy formation in their respective pitches. Pyrolysis was performed on four different coals of varying bituminous rank (Utah Sufco, Wyoming PRB Black Thunder, Illinois #6, and West Virginia Flying Eagle), with SGR temperatures ranging from 800 to 900° C and nominal SGR gas-phase residence times from 1 to 2.5 s. The oxygen content, aliphatic content, and molecular weight distributions of the coal tar samples were measured to indicate the changes with increasing levels of SGR, and microscopy was also used to measure changes in anisotropy formation in the resulting pitch samples. Generally, for all coals tested, increased levels of pyrolysis SGR led to decreased oxygen and aliphatic content, increased molecular weight sizes, and improved anisotropy formation. However, it was clear that the extent of these property changes depended on the chemistry and rank of the starting coal feedstock. Despite the relatively high rank of the Illinois #6 coal, its respective pitch samples performed poorly in improving anisotropy formation, due to its high sulfur content. The PRB, Sufco, and Flying Eagle coals performed better in their anisotropy formation than Illinois #6, depending on their respective coal ranks. Statistical analysis (analysis of variance, ANOVA) performed on the sample characterization data also suggests that SGR temperature is consistently the most dominant and significant effect on the resulting coal products.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2014

SU-E-J-85: Leave-One-Out Perturbation (LOOP) Fitting Algorithm for Absolute Dose Film Calibration

Purpose: To introduce an outliers-recognition fitting routine for film dosimetry. It cannot only be flexible with any linear and non-linear regression but also can provide information for the minimal number of sampling points, critical sampling distributions and evaluating analytical functions for absolute film-dose calibration. Methods: The technique, leave-one-out (LOO) cross validation, is often used for statistical analyses on model performance. We used LOO analyses with perturbed bootstrap fitting called leave-one-out perturbation (LOOP) for film-dose calibration . Given a threshold, the LOO process detects unfit points (“outliers”) compared to other cohorts, and a bootstrap fitting process follows to seek any possibilities of using perturbations for further improvement. After that outliers were reconfirmed by a traditional t-test statistics and eliminated, then another LOOP feedback resulted in the final. An over-sampled film-dose- calibration dataset was collected as a reference (dose range: 0-800cGy), and various simulated conditions for outliers and sampling distributions were derived from the reference. Comparisons over the various conditions were made, and the performance of fitting functions, polynomial and rational functions, were evaluated. Results: (1) LOOP can prove its sensitive outlier-recognition by its statistical correlation to an exceptional better goodness-of-fit as outliers being left-out. (2) With sufficient statistical information, the LOOP can correct outliers under some low-sampling conditions that other “robust fits”, e.g. Least Absolute Residuals, cannot. (3) Complete cross-validated analyses of LOOP indicate that the function of rational type demonstrates a much superior performance compared to the polynomial. Even with 5 data points including one outlier, using LOOP with rational function can restore more than a 95% value back to its reference values, while the polynomial fitting completely failed under the same conditions. Conclusion: LOOP can cooperate with any fitting routine functioning as a “robust fit”. In addition, it can be set as a benchmark for film-dose calibration fitting performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Intensity of sample processing methods impacts wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes

Wastewater SARS-CoV-2 surveillance has been deployed since the beginning of the COVID-19 pandemic to monitor the dynamics in virus burden in local communities. Genomic surveillance of SARS-CoV-2 in wastewater, particularly efforts aimed at whole genome sequencing for variant tracking and identification, are still challenging due to low target concentration, complex microbial and chemical background, and lack of robust nucleic acid recovery experimental procedures. The intrinsic sample limitations are inherent to wastewater and are thus unavoidable. Here, we use a statistical approach that couples correlation analyses to a random forest-based machine learning algorithm to evaluate potentially important factors associated with wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes, with a specific focus on the breadth of genome coverage. We collected 182 composite and grab wastewater samples from the Chicago area between November 2020 to October 2021. Samples were processed using a mixture of processing methods reflecting different homogenization intensities (HA + Zymo beads, HA + glass beads, and Nanotrap), and were sequenced using one of the two library preparation kits (the Illumina COVIDseq kit and the QIAseq DIRECT kit). Technical factors evaluated using statistical and machine learning approaches include sample types, certain sample intrinsic features, and processing and sequencing methods. The results suggested that sample processing methods could be a predominant factor affecting sequencing outcomes, and library preparation kits was considered a minor factor. Finally, a synthetic SARS-CoV-2 RNA spike-in experiment was performed to validate the impact from processing methods and suggested that the intensity of the processing methods could lead to different RNA fragmentation

60 APPLIED LIFE SCIENCES↗