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At least 127 records · Page 7

Sensitivity analysis applied to SiC failure probability in TRISO modeled with BISON

Here, a sensitivity analysis on the failure probability of the Silicon Carbide (SiC) layer in tristructural isotropic (TRISO) nuclear fuel during transient conditions predicted by the BISON fuel performance code is performed. The principal goal of the analysis is to understand the most important parameters dictating SiC failure behavior in BISON during Reactivity Initiated Accidents (RIAs). SiC brittle fracture probability is modeled using Weibull statistics. A total of seven inputs related to SiC failure has been selected for the analysis, including the Weibull statistics parameters, elastic moduli for SiC and Pyrolitic Carbon (PyC) and SiC stress-free temperature. A 1D TRISO BISON model has been established for various reactivity insertions performed at the Nuclear Safety Research Reactor (NSRR). The principal advantage associated with the 1D TRISO model developed in this work is its computational efficiency. The Sobol variance decomposition method is used, and the sensitivity indices are presented for eight different values of the energy deposition. The results show that the two most important parameters impacting the predicted SiC failure probability are the Weibull modulus and the characteristic stress, and a co-variance amongst these parameters is obtained for low reactivity insertions. An additional new finding of this work is that the relative importance of Weibull parameters depends on the energy deposition, and thus reactivity, regime. For low energy depositions, two parameters are of influence on SiC failure probability, while for high energy depositions only one parameter impacts failure probability results. Moreover, optimization of the Weibull modulus and characteristic stress is performed by minimizing the RMSE between BISON failure probability predictions and experimental failure fractions for each energy deposition. This work also demonstrates the validity of the NSRR tests BISON simulations and of the respective sensitivity analysis results as conservative, yet indicative for slower transients characterized by lower deposited energies. Such verification is achieved through the partial extension of the analysis to a group Control Rod Withdrawal reproduced from a previous study. Another novel result of this analysis is that no single set of Weibull parameters can reproduce all reactivity insertion experimental failure results, which is related to the intrinsic nature of SiC failure properties, and a new range for the parameters is proposed to produce a failure probability envelope that encompasses the experimental fractions. Additionaly, this work proposes a new approach for future failure analysis with BISON, consisting in the use of Weibull parameters ranges, rather than fixed sets, along with failure envelopes generation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Statistical Downscaling of Climate Models for Solar Resource Assessment

This study presents the development of statistical models to efficiently downscale future projections of solar irradiance for solar energy applications. A climate data set simulated from a Regional Climate Model (RCM) obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) is selected as input to the statistical models to create high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). Our approach builds statistical downscaling models that (1) regrid RCM data (0.22 degree and daily spatiotemporal resolution), (2) correct bias of GHI projections, (3) downscale the future GHI project from daily-scale to hourly-scale, and (4) spatially downscale to generate GHI at 8-km resolution. To calibrate and validate the statistical models, we adapt and use the National Solar Radiation Database (NSRDB). Preliminary results show that the statistical downscaling approach downscales future projections of GHI under two climate scenarios (RCP4.5 and RCP8.5) with a nBIAS of 3%, nMAE of 34% and nRMSE of 46% estimated against NSRDB for the contiguous United State. This presentation will summarize the implemented methodology and validation results as well as future extension of this research.

climate data↗

Reactor Network Analysis with Various Reaction Mechanisms to Investigate Hydrogen vs. Methane Fuel at Varying Flame Temperatures with Experimental Data

Emissions data were evaluated for a set of test hardware that adapts Collins Aerospace’s aeroengine liquid fueled injector technology to a ground-based turbine. The hardware was specifically developed to operate on 100% hydrogen; however it has the ability to operate on both pure methane and hydrogen and mixtures in between. 16 injector configurations and seven factors (air split, fuel and air swirl, pressure drop, preheat temperature, fuel composition, and flame temperature) were investigated based on a Box Behnken statistical model. Of the 16, configuration 3 was selected for further discussion being in the middle of the statistical design space. A chemical reactor network was developed based on the experimental data obtained and was assessed with three different mechanisms: GRI Mech 3.0, UCSD, and Galway. All factors were held constant except the fuel composition to directly compare chemical pathways for methane and hydrogen. This study was conducted across different flame temperatures of 1500K, 1675K, and 1850K for both hydrogen and methane. Additional lower flame temperatures of 1100K and 1300K were evaluated for hydrogen. Moreover, results for fully premixed and non-premixed results were compared to obtain information on the implications of mixedness on emissions. These results were compared with the Leonard and Stegmaier plot for methane and a similar plot was constructed for hydrogen.

08 HYDROGEN↗

Correlation of the ionisation response at selected points of IC sensitive regions with SEE sensitivity parameters under pulsed laser irradiation

The statistics of the ionisation response amplitude measured at selected points and their surroundings within sensitive regions of integrated circuits (ICs) under focused femtosecond laser irradiation is obtained for samples chosen from large batches of two types of ICs. A correlation between these data and the results of full-chip scanning is found for each type. The criteria for express validation of IC single-event effect (SEE) hardness based on ionisation response measurements at selected points are discussed. (laser applications and other topics in quantum electronics)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Climate Change Impacts at Department of Defense

This project is aimed at providing the U.S. Department of Defense (DoD) with a comprehensive analysis of the uncertainty associated with generating climate projections at the regional scale that can be used by stakeholders and decision makers to quantify and plan for the impacts of future climate change at specific locations. The merits and limitations of commonly used downscaling models, ranging from simple to complex, are compared, and their appropriateness for application at installation scales is evaluated. Downscaled climate projections are generated at selected DoD installations using dynamic and statistical methods with an emphasis on generating probability distributions of climate variables and their associated uncertainties. The sites selection and selection of variables and parameters for downscaling was based on a comprehensive understanding of the current and projected roles that weather and climate play in operating, maintaining, and planning DoD facilities and installations.

54 ENVIRONMENTAL SCIENCES↗

Composite Spectral Energy Distributions and Infrared–Optical Colors of Type 1 and Type 2 Quasars

We present observed mid-infrared and optical colors and composite spectral energy distributions (SEDs) of type 1 (broad-line) and 2 (narrow-line) quasars selected from Sloan Digital Sky Survey (SDSS) spectroscopy. A significant fraction of powerful quasars are obscured by dust and are difficult to detect in optical photometric or spectroscopic surveys. However, these may be more easily identified on the basis of mid-infrared (MIR) colors and SEDs. Using samples of SDSS type 1 and 2 matched in redshift and [O iii] luminosity, we produce composite rest-frame 0.2–15 μm SEDs based on SDSS, UKIDSS, and Wide-field Infrared Survey Explorer photometry and perform model fits using simple galaxy and quasar SED templates. The SEDs of type 1 and 2 quasars are remarkably similar, with the differences explained primarily by the extinction of the quasar component in the type 2 systems. For both types of quasar, the flux of the active galactic nucleus (AGN) relative to the host galaxy increases with AGN luminosity (L{sub [OIII]}) and redder observed MIR color, but we find only weak dependencies of the composite SEDs on mechanical jet power as determined through radio luminosity. We conclude that luminous quasars can be effectively selected using simple MIR color criteria similar to those identified previously (W1--W2>0.7; Vega), although these criteria miss many heavily obscured objects. Obscured quasars can be further identified based on optical–IR colors (for example, (u--W3 [AB])>1.4(W1--W2 [Vega])+3.2). These results illustrate the power of large statistical studies of obscured quasars selected on the basis of MIR and optical photometry.

79 ASTRONOMY AND ASTROPHYSICS↗

On Concavity and Utilization Analytics of Wide-Area Network Transport Protocols

Wide-area data transfers in high-performance computing infrastructures and big data applications are increasingly carried over dynamically provisioned dedicated network connections, which provide high capacities with no competing traffic. Throughput of TCP and UDT over wide-area connections depends, often in a complex non-linear way, on the congestion control mechanism, buffer sizes, and the number of parallel streams. In addition, our extensive TCP and UDT throughput measurements and time traces over a suite of physical and emulated 10 Gbps connections with 0-366 ms round-trip times (RTTs) show significant statistical and temporal variations. Consequently, parameter selection and optimization for transport methods require data analytics to complement analytical throughput models. We present analytics based on the concavity-convexity of throughput profiles which provide insights into peak throughput and superior/inferior trend compared to linear interpolations based on RTT. In particular, we propose the utilization-concavity coefficient, a scalar metric that incorporates both utilization and concavity profile to characterize the overall performance of a transport protocol. These measurements-based anaytics enable us to select a transport protocol and its parameters for a given host and connection configuration to achieve high throughput with statistical guarantees.

Rao, Nageswara↗

Evaluating Optical Classification for Fermi Blazar Candidates with a Statistical Method Using Broadband Spectral Indices

We aim to test whether a blazar candidate of uncertain type (BCU) in the third Fermi catalog of active galactic nuclei (3LAC) can be potentially classified as a BL Lac object or a flat-spectrum radio quasar (FSRQ) by performing a statistical analysis of its broadband spectral properties. We find that 34% of the radio-selected BCUs (583 BCUs) are BL Lac-like and 20% are FSRQ-like, at a 90% level of confidence. Similarly, 77.3% of the X-ray-selected BCUs (176 BCUs) are evaluated as BL Lac-like and 6.8% may be FSRQ-like sources. And 88.7% of the BL Lac-like BCUs that have synchrotron peak frequencies available are high synchrotron peaked BL Lacs in the X-ray-selected BCUs. The percentages are accordingly 62% and 7.3% in the sample of 124 optically selected BCUs. The high ratio of the number of BL Lac-like sources to the number of FSRQ-like BCUs in the X-ray-selected and optically selected BCU samples is due to selection effects. Examining the consistency between our evaluation and spectroscopic identification case by case with a sample of 78 radio-selected BCUs, it is found that the statistical analysis and its resulting classifications agree with the results of the optical follow-up spectroscopic observations. Our observation campaign for high-|ρ{sub s}| BCUs selected with our method, i.e., |ρ{sub s}|>0.8, is ongoing.

79 ASTRONOMY AND ASTROPHYSICS↗

National Climate Database (NCDB)

The National Climate Database (NCDB) is a high resolution, bias-corrected climate dataset consisting of the three most widely used variables of solar radiation- global horizontal (GHI), direct normal (DNI), and diffuse horizontal irradiance (DHI)- as well as other meteorological data. The goal of the NCDB is to provide unbiased high temporal and spatial resolution climate data needed for renewable energy modeling. The NCDB is modeled using a statistical downscaling approach with Regional Climate Model (RCM)-based climate projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX; linked below). Daily climate projections simulated by the Canadian Regional Climate Model 4 (CanRCM4) forced by the second-generation Canadian Earth System Model (CanESM2) for two Representative Concentration Pathways (RCP4.5 or moderate emissions scenario and RCP8.5 or highest baseline emission scenario) are selected as inputs to the statistical downscaling models. The National Solar Radiation Database (NSRDB) is used to build and calibrate statistical models.

Array↗

Microfluidic-based mini-metagenomics enables discovery of novel microbial lineages from complex environmental samples

Metagenomics and single-cell genomics have enabled genome discovery from unknown branches of life. However, extracting novel genomes from complex mixtures of metagenomic data can still be challenging and represents an ill-posed problem which is generally approached with ad hoc methods. Here we present a microfluidic-based mini-metagenomic method which offers a statistically rigorous approach to extract novel microbial genomes while preserving single-cell resolution. We used this approach to analyze two hot spring samples from Yellowstone National Park and extracted 29 new genomes, including three deeply branching lineages. The single-cell resolution enabled accurate quantification of genome function and abundance, down to 1% in relative abundance. Our analyses of genome level SNP distributions also revealed low to moderate environmental selection. The scale, resolution, and statistical power of microfluidic-based mini-metagenomics make it a powerful tool to dissect the genomic structure of microbial communities while effectively preserving the fundamental unit of biology, the single cell.

Life Sciences & Biomedicine - Other Topics↗

Measuring representative volume elements from high-resolution grain-scale strain fields

Most crystalline materials present a highly heterogeneous response at the microscale, which can be affected by both internal factors (such as microstructural parameters) and external factors (such as loading). Relating microscale inhomogeneities to the macroscale response of a material requires the use of homogenisation techniques, usually based on the concept of a representative volume element (RVE)—the smallest volume of material that represents the global average response. Here, in this work, we present a new and robust experimental method of measuring the size of a strain-based RVE from high-resolution grain-scale strain fields obtained using digital image correlation (DIC). The proposed method is based on the statistical (stereological) nature of the RVE, which has been widely adopted in numerical studies, and involves dividing a strain field into randomly selected regions of varying sizes and statistically analysing the distributions of average strains within them. To validate the new method, we generate a large number of synthetic strain fields from a fractional Gaussian noise algorithm. The proposed stereological method is shown to be capable of producing reliable RVE measurements from a very large range of possible microscale strain fields while at the same time being robust in that it can produce RVE measurement results even in cases where other existing methods may be unable to do so. The proposed method has a low field-of-view requirement, only needing a field-of-view about 1.2 times as large as the RVE to produce reliable measurements. In addition, the stereological method offers significant flexibility since its statistical nature allows for control over how strict the RVE measurement should be in each case.

36 MATERIALS SCIENCE↗

Integrated Methane Monitoring Platform Extension, Volume I: Final Technical Report

The IMMPE project, DE-FE0032284, was to enhance methane monitoring technologies and their applications across various natural gas asset classes. The scope included deploying advanced methane detection and monitoring technologies to identify and mitigate fugitive methane emissions, measuring emission rates, and assessing impacts. The findings included the successful mitigation of identified emissions and quantification of emission rates. A key outcome was the development of a comprehensive template and summary of recommendations for methane emissions monitoring, which is replicable for both upstream and downstream applications. Furthermore, the project emphasized the importance of education by providing training opportunities for technicians and regulators, thereby fostering awareness and promoting the adoption of cost-effective methane emissions monitoring and management techniques.

02 PETROLEUM↗

Automated selection of the optimal cardiac phase for single-beat coronary CT angiography reconstruction

Purpose: Reconstructing a low-motion cardiac phase is expected to improve coronary artery visualization in coronary computed tomography angiography (CCTA) exams. This study developed an automated algorithm for selecting the optimal cardiac phase for CCTA reconstruction. The algorithm uses prospectively gated, single-beat, multiphase data made possible by wide cone-beam imaging. The proposed algorithm differs from previous approaches because the optimal phase is identified based on vessel image quality (IQ) directly, compared to previous approaches that included motion estimation and interphase processing. Because there is no processing of interphase information, the algorithm can be applied to any sampling of image phases, making it suited for prospectively gated studies where only a subset of phases are available. Methods: An automated algorithm was developed to select the optimal phase based on quantitative IQ metrics. For each reconstructed slice at each reconstructed phase, an image quality metric was calculated based on measures of circularity and edge strength of through-plane vessels. The image quality metric was aggregated across slices, while a metric of vessel-location consistency was used to ignore slices that did not contain through-plane vessels. The algorithm performance was evaluated using two observer studies. Fourteen single-beat cardiac CT exams (Revolution CT, GE Healthcare, Chalfont St. Giles, UK) reconstructed at 2% intervals were evaluated for best systolic (1), diastolic (6), or systolic and diastolic phases (7) by three readers and the algorithm. Pairwise inter-reader and reader-algorithm agreement was evaluated using the mean absolute difference (MAD) and concordance correlation coefficient (CCC) between the reader and algorithm-selected phases. A reader-consensus best phase was determined and compared to the algorithm selected phase. In cases where the algorithm and consensus best phases differed by more than 2%, IQ was scored by three readers using a five point Likert scale. Results: There was no statistically significant difference between inter-reader and reader-algorithm agreement for either MAD or CCC metrics (p > 0.1). The algorithm phase was within 2% of the consensus phase in 15/21 of cases. The average absolute difference between consensus and algorithm best phases was 2.29% ± 2.47%, with a maximum difference of 8%. Average image quality scores for the algorithm chosen best phase were 4.01 ± 0.65 overall, 3.33 ± 1.27 for right coronary artery (RCA), 4.50 ± 0.35 for left anterior descending (LAD) artery, and 4.50 ± 0.35 for left circumflex artery (LCX). Average image quality scores for the consensus best phase were 4.11 ± 0.54 overall, 3.44 ± 1.03 for RCA, 4.39 ± 0.39 for LAD, and 4.50 ± 0.18 for LCX. There was no statistically significant difference (p > 0.1) between the image quality scores of the algorithm phase and the consensus phase. Conclusions: The proposed algorithm was statistically equivalent to a reader in selecting an optimal cardiac phase for CCTA exams. When reader and algorithm phases differed by >2%, image quality as rated by blinded readers was statistically equivalent. By detecting the optimal phase for CCTA reconstruction, the proposed algorithm is expected to improve coronary artery visualization in CCTA exams.

61 RADIATION PROTECTION AND DOSIMETRY↗

Uncertainty estimation of bifurcated solutions in the Rayleigh–Bénard problem for advanced nuclear reactors applications

Multiphysics models of nuclear reactors frequently comprise nonlinear systems of equations. The nonlinear nature of these models could lead to solution bifurcations, where a small change in a certain parameter, e.g., the thermophysical properties of the coolant, can lead to a sudden change in the system’s behavior. At the point in parameter space where this happens, called a critical point, the Jacobian matrix of the model’s nonlinear operator becomes singular potentially permitting multiple solutions to coexist. In this paper, we perform uncertainty estimation (UE) in a parameter range that includes bifurcated solutions within the context of Rayleigh–Bénard problem. We perform this analysis assuming uncertain temperature difference, and tilt angle for the iterative solution algorithm with a unit Prandtl number (Pr = 1). Also, we perform this analysis under uncertain thermophysical properties for both FLiBe molten salt and liquid sodium as working fluid. We deploy two approaches to compute statistical moments for the resulting distributions of selected flow-field variables. The first approach is the blind computation of the mean and the standard deviation without any consideration of solution bifurcation, while the second approach utilizes k-means clustering to cluster each branch’s solutions together and compute separate statistical moments for each branch. The statistical distributions are obtained by perturbing the selected parameters about nominal values that correspond to a solution on one of the valid branches, and that solution is used as initial guess for the iterative solution algorithm. We found that perturbation of any parameter when its nominal value is close to its critical point always leads to branch jumping, i.e., the iterations converge to a solution on a branch different from the branch of the initial guess. This produces a statistical ensemble comprised of fundamentally different solutions leading to wrong mean values and uncertainty estimates, whereas clustering provides an efficient way to deal with this type of computation. This work is important for developing Gen IV nuclear systems because many of these systems rely on natural convection for cooling especially in accident conditions.

97 - MATHEMATICS AND COMPUTING↗

Major cluster mergers and the location of the brightest cluster galaxy

Using a large N-body cosmological simulation combined with a subgrid treatment of galaxy formation, merging, and tidal destruction, we study the formation and evolution of the galaxy and cluster population in a comoving volume (100 Mpc){sup 3} in a ΛCDM universe. At z = 0, our computational volume contains 1788 clusters with mass M {sub cl} > 1.1 × 10{sup 12} M {sub ☉}, including 18 massive clusters with M {sub cl} > 10{sup 14} M {sub ☉}. It also contains 1, 088, 797 galaxies with mass M {sub gal} ≥ 2 × 10{sup 9} M {sub ☉} and luminosity L > 9.5 × 10{sup 5} L {sub ☉}. For each cluster, we identified the brightest cluster galaxy (BCG). We then computed two separate statistics: the fraction f {sub BNC} of clusters in which the BCG is not the closest galaxy to the center of the cluster in projection, and the ratio Δv/σ, where Δv is the difference in radial velocity between the BCG and the whole cluster and σ is the radial velocity dispersion of the cluster. We found that f {sub BNC} increases from 0.05 for low-mass clusters (M {sub cl} ∼ 10{sup 12} M {sub ☉}) to 0.5 for high-mass clusters (M {sub cl} > 10{sup 14} M {sub ☉}) with very little dependence on cluster redshift. Most of this result turns out to be a projection effect and when we consider three-dimensional distances instead of projected distances, f {sub BNC} increases only to 0.2 at high-cluster mass. The values of Δv/σ vary from 0 to 1.8, with median values in the range 0.03-0.15 when considering all clusters, and 0.12-0.31 when considering only massive clusters. These results are consistent with previous observational studies and indicate that the central galaxy paradigm, which states that the BCG should be at rest at the center of the cluster, is usually valid, but exceptions are too common to be ignored. We built merger trees for the 18 most massive clusters in the simulation. Analysis of these trees reveal that 16 of these clusters have experienced 1 or several major or semi-major mergers in the past. These mergers leave each cluster in a non-equilibrium state, but eventually the cluster settles into an equilibrium configuration, unless it is disturbed by another major or semi-major merger. We found evidence that these mergers are responsible for the off-center positions and peculiar velocities of some BCGs. Our results thus support the merging-group scenario, in which some clusters form by the merging of smaller groups in which the galaxies have already formed, including the galaxy destined to become the BCG. Finally, we argue that f {sub BNC} is not a very robust statistics, as it is very sensitive to projection and selection effects, but that Δv/σ is more robust. Still, both statistics exhibit a signature of major mergers between clusters of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantitative assessment of particle dispersion in polymeric composites and its effect on mechanical properties

In this work, an automated image analysis tool is developed to establish quantitative correlations between the particle/cluster size distribution and the mechanical properties of particle reinforced polymer composites (PRPC).This automated image analysis tool is developed within python programming software to process and analyze the microstructural images of the polymerbased composite materials. The spent coffee bean powder (SCBP) reinforced poly-propylene carbonate (PPC) polymer composite with differing wt.% of the filler is selected for the analysis. Detailed statistical analysis of the microstructural images reveals that ‘clustering of clusters’ is also presented in addition to the most commonly reported ‘clustering of particles’, and the distribution of particle/clusters is bimodal. Based on these findings, an effective volume fraction for the filler material is proposed to mainly capture the agglomeration effect. With this effective volume fraction, the standard rule-of-mixture model correctly captures the experimentally measured tensile strength and modulus as a function of filler wt.%. Further, the applicability of this effective volume fraction for other theoretical models is also analyzed. The detailed statistical analysis of the microstructure and the proposed effective volume fraction helps to develop a deeper quantitative understanding of the PRPC than the conventional qualitative correlation of microstructural features with the properties and failure processes.

36 MATERIALS SCIENCE↗

A reference-area-free strain mapping method using precession electron diffraction data

Here, in this work, we developed a method using precession electron diffraction data to map the residual elastic strain at the nano-scale. The diffraction pattern of each pixel was first collected and denoised. Template matching was then applied using the center spot as the mask to identify the positions of the diffraction disks. Statistics of distances between the selected diffracted disks enable the user to make an informed decision on the reference and to generate strain maps. Strain mapping on an unstrained single crystal sapphire shows the standard deviation of strain measurement is 0.5%. With this method, we were able to successfully measure and map the residual elastic strain in VO 2 on sapphire and martensite in a Ni 50.3 Ti 29.7 Hf 20 shape memory alloy. This approach does not require the user to select a “strain-free area” as a reference and can work on datasets even with the crystals oriented away from zone axes. This method is expected to provide a robust and more accessible alternative means of studying the residual strain of various material systems that complements the existing algorithms for strain mapping.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Protoplanetary disk masses in the young NGC 2024 cluster

We present the results from a Submillimeter Array survey of the 887 μm continuum emission from the protoplanetary disks around 95 young stars in the young cluster NGC 2024. Emission was detected from 22 infrared sources, with flux densities from ∼5 to 330 mJy; upper limits (at 3σ) for the other 73 sources range from 3 to 24 mJy. For standard assumptions, the corresponding disk masses range from ∼0.003 to 0.2 M{sub ⊙}, with upper limits at 0.002–0.01 M{sub ⊙}. The NGC 2024 sample has a slightly more populated tail at the high end of its disk mass distribution compared to other clusters, but without more information on the nature of the sample hosts it remains unclear if this difference is statistically significant or a superficial selection effect. Unlike in the Orion Trapezium, there is no evidence for a disk mass dependence on the (projected) separation from the massive star IRS 2b in the NGC 2024 cluster. We suggest that this is due to either the cluster youth or a comparatively weaker photoionizing radiation field.

79 ASTRONOMY AND ASTROPHYSICS↗