Search NASA⌕ Search

SEARCH · Search NASA

Results for “Probability Distribution Function”

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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

137 Ba Double Gamma Decay Measurement with GAMMASPHERE

The study of the electromagnetic moments (EM), and decay probability, provides detailed information about nuclear wave functions. The well-know properties of EM interactions are good for extracting information about the motion of nucleons. Higher order EM processes always occur, but are usually too weak to be measured. In the case of a 0 + → 0 + transitions, where a single gamma transition is forbidden, the simultaneous emission of two γ-rays has been studied. An interesting opportunity to further investigate 2-photon emission phenomena is by using a standard 137 Cs source populating, via β-decay, the J π = 11/2 - isomeric state at 662 keV in 137 Ba. In this case, two photon process can have contributions from quadrupole-quadrupole or dipole-octupole multipolarities in direct competition with the high multipolarity M4 decay. Since the yield of the double gamma decay is around six orders of magnitude less than the first order transition, very good statistics are needed in order to observe the phenomena and great care must be taken to suppress the first-order decay. The Gammasphere array is ideal since its configuration allows a good coverage of the angular distribution and the Compton events can be suppressed. Nevertheless the process to understand and eliminate the Compton background is a challenge. Geant4 simulations were carried out to help understand and correct for those factors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

PS1-12sk IS A PECULIAR SUPERNOVA FROM A He-RICH PROGENITOR SYSTEM IN A BRIGHTEST CLUSTER GALAXY ENVIRONMENT

We report on our discovery and observations of the Pan-STARRS1 supernova (SN) PS1-12sk, a transient with properties that indicate atypical star formation in its host galaxy cluster or pose a challenge to popular progenitor system models for this class of explosion. The optical spectra of PS1-12sk classify it as a Type Ibn SN (SN Ibn; cf. SN 2006jc), dominated by intermediate-width (3 Multiplication-Sign 10{sup 3} km s{sup -1}) and time variable He I emission. Our multi-wavelength monitoring establishes the rise time dt {approx} 9-23 days and shows an NUV-NIR spectral energy distribution with temperature {approx}> 17 Multiplication-Sign 10{sup 3} K and a peak magnitude of M{sub z} = -18.88 {+-} 0.02 mag. SN Ibn spectroscopic properties are commonly interpreted as the signature of a massive star (17-100 M{sub Sun }) explosion within an He-enriched circumstellar medium. However, unlike previous SNe Ibn, PS1-12sk is associated with an elliptical brightest cluster galaxy, CGCG 208-042 (z = 0.054) in cluster RXC J0844.9+4258. The expected probability of an event like PS1-12sk in such environments is low given the measured infrequency of core-collapse SNe in red-sequence galaxies compounded by the low volumetric rate of SN Ibn. Furthermore, we find no evidence of star formation at the explosion site to sensitive limits ({Sigma}{sub H{alpha}} {approx}< 2 Multiplication-Sign 10{sup -3} M{sub Sun} yr{sup -1} kpc{sup -2}). We therefore discuss white dwarf binary systems as a possible progenitor channel for SNe Ibn. We conclude that PS1-12sk represents either a fortuitous and statistically unlikely discovery, evidence for a top-heavy initial mass function in galaxy cluster cooling flow filaments, or the first clue suggesting an alternate progenitor channel for SNe Ibn.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Constraining Galaxy-Halo connection using machine learning

We investigate the potential of machine learning (ML) methods to model small-scale galaxy clustering for constraining Halo Occupation Distribution (HOD) parameters. Our analysis reveals that while many ML algorithms report good statistical fits, they often yield likelihood contours that are significantly biased in both mean values and variances relative to the true model parameters. This highlights the importance of careful data processing and algorithm selection in ML applications for galaxy clustering, as even seemingly robust methods can lead to biased results if not applied correctly. ML tools offer a promising approach to exploring the HOD parameter space with significantly reduced computational costs compared to traditional brute-force methods if their robustness is established. Using our ANN-based pipeline, we successfully recreate some standard results from recent literature. Properly restricting the HOD parameter space, transforming the training data, and carefully selecting ML algorithms are essential for achieving unbiased and robust predictions. Among the methods tested, artificial neural networks (ANNs) outperform random forests (RF) and ridge regression in predicting clustering statistics, when the HOD prior space is appropriately restricted. We demonstrate these findings using the projected two-point correlation function (w p (r p )), angular multipoles of the correlation function (ξ ℓ (r)), and the void probability function (VPF) of Luminous Red Galaxies from Dark Energy Spectroscopic Instrument mocks. Our results show that while combining w p (r p ) and VPF improves parameter constraints, adding the multipoles ξ 0 , ξ 2 , and ξ 4 to w p (r p ) does not significantly improve the constraints.

cosmology↗
DOE OSTI2015

Genomic and experimental evidence for multiple metabolic functions in the RidA/YjgF/YER057c/UK114 (Rid) protein family

It is now recognized that enzymatic or chemical side-reactions can convert normal metabolites to useless or toxic ones and that a suite of enzymes exists to mitigate such metabolite damage. Examples are the reactive imine/enamine intermediates produced by threonine dehydratase, which damage the pyridoxal 5'-phosphate cofactor of various enzymes causing inactivation. This damage is pre-empted by RidA proteins, which hydrolyze the imines before they do harm. RidA proteins belong to the YjgF/YER057c/UK114 family (here renamed the Rid family). Most other members of this diverse and ubiquitous family lack defined functions. Phylogenetic analysis divided the Rid family into a widely distributed, apparently archetypal RidA subfamily and seven other subfamilies (Rid1 to Rid7) that are largely confined to bacteria and often co-occur in the same organism with RidA and each other. The Rid1 to Rid3 subfamilies, but not the Rid4 to Rid7 subfamilies, have a conserved arginine residue that, in RidA proteins, is essential for imine-hydrolyzing activity. Analysis of the chromosomal context of bacterial RidA genes revealed clustering with genes for threonine dehydratase and other pyridoxal 5'-phosphate-dependent enzymes, which fits with the known RidA imine hydrolase activity. Clustering was also evident between Rid family genes and genes specifying FAD-dependent amine oxidases or enzymes of carbamoyl phosphate metabolism. Biochemical assays showed that Salmonella enterica RidA and Rid2, but not Rid7, can hydrolyze imines generated by amino acid oxidase. Genetic tests indicated that carbamoyl phosphate overproduction is toxic to S. enterica cells lacking RidA, and metabolomic profiling of Rid knockout strains showed ten-fold accumulation of the carbamoyl phosphate-related metabolite dihydroorotate. Like the archetypal RidA subfamily, the Rid2, and probably the Rid1 and Rid3 subfamilies, have imine-hydrolyzing activity and can pre-empt damage from imines formed by amine oxidases as well as by pyridoxal 5'-phosphate enzymes. The RidA subfamily has an additional damage pre-emption role in carbamoyl phosphate metabolism that has yet to be biochemically defined. As a result, the Rid4 to Rid7 subfamilies appear not to hydrolyze imines and thus remain mysterious.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: measurement of the growth rate of structure from the small-scale clustering of the luminous red galaxy sample

ABSTRACT We measure the small-scale clustering of the Data Release 16 extended Baryon Oscillation Spectroscopic Survey Luminous Red Galaxy sample, corrected for fibre-collisions using Pairwise Inverse Probability weights, which give unbiased clustering measurements on all scales. We fit to the monopole and quadrupole moments and to the projected correlation function over the separation range $7-60\, h^{-1}{\rm Mpc}$ with a model based on the aemulus cosmological emulator to measure the growth rate of cosmic structure, parametrized by fσ8. We obtain a measurement of fσ8(z = 0.737) = 0.408 ± 0.038, which is 1.4σ lower than the value expected from 2018 Planck data for a flat ΛCDM model, and is more consistent with recent weak-lensing measurements. The level of precision achieved is 1.7 times better than more standard measurements made using only the large-scale modes of the same sample. We also fit to the data using the full range of scales $0.1\text{--}60\, h^{-1}{\rm Mpc}$ modelled by the aemulus cosmological emulator and find a 4.5σ tension in the amplitude of the halo velocity field with the Planck + ΛCDM model, driven by a mismatch on the non-linear scales. This may not be cosmological in origin, and could be due to a breakdown in the Halo Occupation Distribution model used in the emulator. Finally, we perform a robust analysis of possible sources of systematics, including the effects of redshift uncertainty and incompleteness due to target selection that were not included in previous analyses fitting to clustering measurements on small scales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

A GENERALIZED STOCHASTIC COLLOCATION APPROACH TO CONSTRAINED OPTIMIZATION FOR RANDOM DATA IDENTIFICATION PROBLEMS

We present a scalable, parallel mechanism for stochastic identification/control for problems constrained by partial differential equations with random input data. Several identification objectives will be discussed that either minimize the expectation of a tracking cost functional or minimize the difference of desired statistical quantities in the appropriate $L^p$ norm, and the distributed parameters/control can both deterministic or stochastic. Given an objective we prove the existence of an optimal solution, establish the validity of the Lagrange multiplier rule and obtain a stochastic optimality system of equations. The modeling process may describe the solution in terms of high dimensional spaces, particularly in the case when the input data (coefficients, forcing terms, boundary conditions, geometry, etc) are affected by a large amount of uncertainty. For higher accuracy, the computer simulation must increase the number of random variables (dimensions), and expend more effort approximating the quantity of interest in each individual dimension. Hence, we introduce a novel stochastic parameter identification algorithm that integrates an adjoint-based deterministic algorithm with the sparse grid stochastic collocation FEM approach. This allows for decoupled, moderately high dimensional, parameterized computations of the stochastic optimality system, where at each collocation point, deterministic analysis and techniques can be utilized. The advantage of our approach is that it allows for the optimal identification of statistical moments (mean value, variance, covariance, etc.) or even the whole probability distribution of the input random fields, given the probability distribution of some responses of the system (quantities of physical interest). Our rigorously derived error estimates, for the fully discrete problems, will be described and used to compare the efficiency of the method with several other techniques. Numerical examples illustrate the theoretical results and demonstrate the distinctions between the various stochastic identification objectives.

Webster, Clayton G↗
DOE OSTI2025

Reduced Order Modeling conditioned on monitored features for response and error bounds estimation in engineered systems

Reduced Order Models (ROMs) form essential tools across engineering domains by virtue of their function as surrogates for computationally intensive digital twinning simulators. Although purely data-driven methods are available for ROM construction, schemes that allow to retain a portion of the physics tend to enhance the interpretability and generalization of ROMs. However, physics-based techniques can adversely scale when dealing with nonlinear systems that feature parametric dependencies. This study introduces a generative physics-based ROM that is suited for nonlinear systems with parametric dependencies and is additionally able to provide numerical error bounds associated with the respective estimates. A main contribution of this work is the conditioning of these parametric ROMs to features that can be derived from monitoring measurements, feasibly in an online fashion. This is contrary to most existing ROM schemes, which remain restricted to the prescription of the physics-based, and usually a priori unknown, system parameters. Our work utilizes conditional Variational Autoencoders to continuously map the required reduction bases to a feature vector extracted from limited output measurements, while additionally allowing for a probabilistic assessment of the ROM-estimated Quantities of Interest. An auxiliary task using a neural network-based parametrization of suitable probability distributions is introduced to re-establish the link with physical model parameters. We verify the proposed scheme on a series of simulated case studies incorporating effects of geometric and material nonlinearity under parametric dependencies related to system properties and input load characteristics.

Conditional VAEs↗
DOE OSTI2020

Probabilistic Solar Power Forecasting Using Bayesian Model Averaging

There is rising interest in probabilistic forecasting to mitigate risks from solar power uncertainty, but the numerical weather prediction (NWP) ensembles readily available to system operators are often biased and underdispersed. We propose a Bayesian model averaging (BMA) post-processing method suitable for forecasting power from utility-scale photovoltaic (PV) plants at multiple time horizons up to at least the day-ahead timescale. BMA is a kernel dressing technique for NWP ensembles in which the forecast is a weighted sum of member-specific probability density functions. We tailor BMA for utility-scale PV forecasting by modeling power clipping at the AC inverter rating and advance the theory of BMA with a new beta kernel parameterization that accommodates theoretical constraints not previously addressed. BMA is demonstrated for a case study of 11 utility-scale PV plants in Texas, forecasting at hourly resolution for the complete year 2018. BMA's mixture-model approach mitigates underdispersion of the raw ensemble to significantly improve forecast calibration, while consistently outperforming an ensemble model output statistics (EMOS) parametric approach from the literature. At 4-hour lead time, the BMA post-processing achieves continuous ranked probability skill scores of 2--36% over the raw ensemble, with consistent performance at multiple lead times suitable for power system operations.

14 SOLAR ENERGY↗
DOE OSTI2023

Social network structure and the spread of complex contagions from a population genetics perspective

Ideas, behaviors, and opinions spread through social networks. If the probability of spreading to a new individual is a non-linear function of the fraction of the individuals’ affected neighbors, such a spreading process becomes a “complex contagion”. This non-linearity does not typically appear with physically spreading infections, but instead can emerge when the concept that is spreading is subject to game theoretical considerations (e.g. for choices of strategy or behavior) or psychological effects such as social reinforcement and other forms of peer influence (e.g. for ideas, preferences, or opinions). Here we study how the stochastic dynamics of such complex contagions are affected by the underlying network structure. Motivated by simulations of complex contagions on real social networks, we present a framework for analyzing the statistics of contagions with arbitrary non-linear adoption probabilities based on the mathematical tools of population genetics. The central idea is to use an effective lower-dimensional diffusion process to approximate the statistics of the contagion. This leads to a tradeoff between the effects of ”selection” (microscopic tendencies for an idea to spread or die out), random drift, and network structure. Our framework illustrates intuitively several key properties of complex contagions: stronger community structure and network sparsity can significantly enhance the spread, while broad degree distributions dampen the effect of selection compared to random drift. Finally, we show that some structural features can exhibit critical values that demarcate regimes where global contagions become possible for networks of arbitrary size. Our results draw parallels between the competition of genes in a population and memes in a world of minds and ideas. Our tools provide insight into the spread of information, behaviors, and ideas via social influence, and highlight the role of macroscopic network structure in determining their fate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The completed SDSS-IV extended baryon oscillation spectroscopic survey: pairwise-inverse probability and angular correction for fibre collisions in clustering measurements

ABSTRACT The completed extended Baryon Oscillation Spectroscopic Survey (eBOSS) catalogues contain redshifts of 344 080 quasars at 0.8 < z < 2.2, 174 816 luminous red galaxies between 0.6 < z < 1.0, and 173 736 emission-line galaxies over 0.6 < z < 1.1 in order to constrain the expansion history of the Universe and the growth rate of structure through clustering measurements. Mechanical limitations of the fibre-fed spectrograph on the Sloan telescope prevent two fibres being placed closer than 62 arcsec in a single pass of the instrument. These ‘fibre collisions’ strongly correlate with the intrinsic clustering of targets and can bias measurements of the two-point correlation function resulting in a systematic error on the inferred values of the cosmological parameters. We combine the new techniques of pairwise-inverse probability and the angular upweighting (PIP+ANG) to correct the clustering measurements for the effect of fibre collisions. Using mock catalogues, we show that our corrections provide unbiased measurements, within data precision, of both the projected $\rm {\mathit{ w}_p}\left(\mathit{ r}_p\right)$ and the redshift-space multipole ξ(ℓ = 0, 2, 4)(s) correlation functions down to $0.1\, h^{-1}{\rm Mpc}$, regardless of the tracer type. We apply the corrections to the eBOSS DR16 catalogues. We find that, on scales $s\gtrsim 20\, h^{-1}{\rm Mpc}$ for ξℓ, as used to make baryon acoustic oscillation and large-scale redshift-space distortion measurements, approximate methods such as nearest-neighbour upweighting are sufficiently accurate given the statistical errors of the data. Using the PIP method, for the first time for a spectroscopic program of the Sloan Digital Sky Survey, we are able to successfully access the one-halo term in the clustering measurements down to $\sim 0.1\, h^{-1}{\rm Mpc}$ scales. Our results will therefore allow studies that use the small-scale clustering to strengthen the constraints on both cosmological parameters and the halo occupation distribution models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Vertical overlap of probability density functions of cloud and precipitation hydrometeors: CLOUD AND PRECIPITATION PDF OVERLAP

Coarse-resolution climate models increasingly rely on probability density functions (PDFs) to represent subgrid-scale variability of prognostic variables. While PDFs characterize the horizontal variability, a separate treatment is needed to account for the vertical structure of clouds and precipitation. When sub-columns are drawn from these PDFs for microphysics or radiation parameterizations, appropriate vertical correlations must be enforced via PDF overlap specifications. This study evaluates the representation of PDF overlap in the Subgrid Importance Latin Hypercube Sampler (SILHS) employed in the assumed PDF turbulence and cloud scheme called the Cloud Layers Unified By Binormals (CLUBB). PDF overlap in CLUBB-SILHS simulations of continental and tropical oceanic deep convection is compared with overlap of PDF of various microphysics variables in cloud-resolving model (CRM) simulations of the same cases that explicitly predict the 3D structure of cloud and precipitation fields. CRM results show that PDF overlap varies significantly between different hydrometeor types, as well as between PDFs of mass and number mixing ratios for each species, - a distinction that the current SILHS implementation does not make. In CRM simulations that explicitly resolve cloud and precipitation structures, faster falling species, such as rain and graupel, exhibit significantly higher coherence in their vertical distributions than slow falling cloud liquid and ice. These results suggest that to improve the overlap treatment in the sub-column generator, the PDF correlations need to depend on hydrometeor properties, such as fall speeds, in addition to the currently implemented dependency on the turbulent convective length scale.

58 GEOSCIENCES↗
DOE OSTI2013

GAS SURFACE DENSITY, STAR FORMATION RATE SURFACE DENSITY, AND THE MAXIMUM MASS OF YOUNG STAR CLUSTERS IN A DISK GALAXY. II. THE GRAND-DESIGN GALAXY M51

We analyze the relationship between maximum cluster mass and surface densities of total gas ({Sigma}{sub gas}), molecular gas ({Sigma}{sub H{sub 2}}), neutral gas ({Sigma}{sub H{sub I}}), and star formation rate ({Sigma}{sub SFR}) in the grand-design galaxy M51, using published gas data and a catalog of masses, ages, and reddenings of more than 1800 star clusters in its disk, of which 223 are above the cluster mass distribution function completeness limit. By comparing the two-dimensional distribution of cluster masses and gas surface densities, we find for clusters older than 25 Myr that M{sub 3rd}{proportional_to}{Sigma}{sub H{sub I}{sup 0.4{+-}0.2}}, whereM{sub 3rd} is the median of the five most massive clusters. There is no correlation with{Sigma}{sub gas},{Sigma}{sub H2}, or{Sigma}{sub SFR}. For clusters younger than 10 Myr, M{sub 3rd}{proportional_to}{Sigma}{sub H{sub I}{sup 0.6{+-}0.1}} and M{sub 3rd}{proportional_to}{Sigma}{sub gas}{sup 0.5{+-}0.2}; there is no correlation with either {Sigma}{sub H{sub 2}} or{Sigma}{sub SFR}. The results could hardly be more different from those found for clusters younger than 25 Myr in M33. For the flocculent galaxy M33, there is no correlation between maximum cluster mass and neutral gas, but we have determined M{sub 3rd}{proportional_to}{Sigma}{sub gas}{sup 3.8{+-}0.3}, M{sub 3rd}{proportional_to}{Sigma}{sub H{sub 2}{sup 1.2{+-}0.1}}, and M{sub 3rd}{proportional_to}{Sigma}{sub SFR}{sup 0.9{+-}0.1}. For the older sample in M51, the lack of tight correlations is probably due to the combination of strong azimuthal variations in the surface densities of gas and star formation rate, and the cluster ages. These two facts mean that neither the azimuthal average of the surface densities at a given radius nor the surface densities at the present-day location of a stellar cluster represent the true surface densities at the place and time of cluster formation. In the case of the younger sample, even if the clusters have not yet traveled too far from their birth sites, the poor resolution of the radio data compared to the physical sizes of the clusters results in measured{Sigma} that are likely quite diluted compared to the actual densities relevant for the formation of the clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

High-Resolution Comonomer Sequencing of Blocky Brominated Syndiotactic Polystyrene Copolymers Using 13C NMR Spectroscopy and Computer Simulations

This work demonstrates the first high-resolution comonomer sequencing of Blocky brominated syndiotactic polystyrene (sPS-co-sPS-Br) copolymers based on pentad assign- ments of the quaternary carbon region of the nuclear magnetic resonance spectrum. Copolymers containing p-bromostyrene (Br-Sty) units were prepared in matched sets using postpolymerization bromination methods carried out in the heterogeneous gel state (Blocky) and homogeneous solution state (Random). Quantitative information from the quaternary carbon spectra, heteronuclear multiple bond correlation spectroscopy, electronic structure calculations, and simulated statistically random copolymers was correlated to confirm the carbon resonance assignments for all 20 possible pentad comonomer sequences. Using the experimental pentad sequence prevalences, a computer code was developed to simulate chains with microstructures typical of each sample as a means to visually represent the copolymer blockiness with quantitative precision. Based on the microstructure and distribution of run lengths in these chains, the simulations revealed that the Blocky copolymers contain a high degree of blockiness. By comparing the run lengths in the simulated chains to the average number of styrene units in a crystalline segment of sPS (found by small-angle X-ray scattering), copolymer crystallizability was predicted. For the simulated Blocky B-21% (21 mol % Br-Sty) chain, the probability of randomly selecting a styrene unit in a crystallizable block was 25.8%, while that in the simulated Random R-18% was zero, in excellent agreement with the experimental crystallization behavior measured by differential scanning calorimetry. Additionally, these predictions confirmed that the simulated chains accurately represent the ensemble of chains in their respective copolymer samples. Furthermore, each simulated Blocky chain contained one or more long sPS blocks that paralleled the measured 38-40 styrene units spanning a crystalline segment within the sPS/CCl4 gel. This finding affirmed that the long sPS segments originated from the precise lamellar structure within the heterogeneous gel morphology (i.e., block length is correlated with lamellar thickness). Overall, the ability to tailor the copolymer microstructure through control of the semicrystalline gel morphology opens the door to synthesizing ordered copolymers by postpolymerization functionalization processes with unprecedented levels of compositional control.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Seasonal Cost-Benefit Analysis of Automated Distribution Feeder Upgrades with Advanced Mitigation Technologies

The increasing deployment of distributed solar photovoltaics (DPV) to meet clean energy goals can trigger adverse grid operation issues, such as voltage excursions and the violation of thermal loading constraints of the power delivery elements (e.g., lines and transformers) on the evolving electricity infrastructure. Such integration issues would require distribution upgrades with associated costs to mitigate them and to maintain reliable and resilient grid operating conditions. Traditional distribution network upgrade approaches use a specific single snapshot analysis that is overly conservative. This study considers a multi-time point analysis to capture both moderate (probable bounds) and extreme grid operating conditions using time points such as minimum load with minimum photovoltaics (PV), maximum load with maximum PV, maximum load with minimum PV, and minimum load with maximum PV. Further, this study investigates seasonal variation impacts and associated distribution upgrade costs for a spring season case (March, representing a low load and high PV scenario) and a summer case (July, representing a high load and high PV scenario). Such seasonal analysis will allow system operators to characterize upgrade requirements and associated costs across various periods. Because the spatial distribution of DPV can impact upgrade and associated costs, this study investigates three common DPV deployment scenarios - randomly deployed, close to the substation, and far from the substation - at different penetration levels. Apart from spatial distribution impacts, this project evaluates the techno-economic impacts of the nodal photovoltaic penetration factor (NPPF) for generating the various DPV deployment scenarios at increasing penetration levels. This project investigates the impact of varying nodal PV-to-load ratios using conservative and extreme NPPF values of 3 and 10, respectively. This study investigates the deployment of traditional infrastructure upgrade strategies, such as installing new voltage regulating equipment, transformers and lines replacements, and the activation of advanced inverter functionality (e.g., autonomous volt/VAR) in expanding PV hosting capacity. Existing DPV systems are assumed to operate with the legacy unity power factor, and we considered the possibility of retrofitting such systems with the activation of volt/VAR control as integration standards and regulations continue to evolve to allow such functions. The cost-benefit analysis metrics used in study include distribution upgrade costs, average cost per watt of the upgrade cost, average marginal cost per watt of the upgrade cost, and power losses.

14 SOLAR ENERGY↗
DOE OSTI2023

Diverse Chemo-Dynamical Properties of Nitrogen-Rich Stars Identified from Low-Resolution Spectra

The second generation of stars in the globular clusters (GCs) of the Milky Way (MW) exhibit unusually high N, Na, or Al, compared to typical Galactic halo stars at similar metallicities. The halo field stars enhanced with such elements are believed to have originated in disrupted GCs or escaped from existing GCs. We identify such stars in the metallicity range –3.0 < [Fe/H] < 0.0 from a sample of ~ 36,800 giant stars observed in the Sloan Digital Sky Survey and Large Sky Area Multi-Object Fiber Spectroscopic Telescope survey, and present their dynamical properties. The N-rich population (NRP) and N-normal population (NNP) among our giant sample do not exhibit similarities in either in their metallicity distribution function (MDF) or dynamical properties. We find that, even though the MDF of the NRP looks similar to that of the MW’s GCs in the range of [Fe/H] < –1.0, our analysis of the dynamical properties does not indicate similarities between them in the same metallicity range, implying that the escaped members from existing GCs may account for a small fraction of our N-rich stars, or the orbits of the present GCs have been altered by the dynamical friction of the MW. We also find a significant increase in the fraction of N-rich stars in the halo field in the very metal-poor (VMP; [Fe/H] < –2.0) regime, comprising up to ~ 20% of the fraction of the N-rich stars below [Fe/H] = –2.5, hinting that partially or fully destroyed VMP GCs may have in some degree contributed to the Galactic halo. A more detailed dynamical analysis of the NRP reveals that our sample of N-rich stars do not share a single common origin. Although a substantial fraction of the N-rich stars seem to originate from the GCs formed in situ, more than 60% of them are not associated with those of typical Galactic populations, but probably have extragalactic origins associated with Gaia Sausage/Enceladus, Sequoia, and Sagittarius dwarf galaxies, as well as with presently unrecognized progenitors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Emergency core cooling system performance criteria for Multi-Layered Silicon Carbide nuclear fuel cladding

Multi-layered Silicon Carbide (SiC) cladding has been proposed to replace the current Zircaloy (Zr) cladding in existing nuclear power plants. Due to its ceramic property, SiC may have a different failure mechanism from that of metallic Zr clad. This characteristic should be considered in designing the plant’s safety system performance, such that the fuel’s integrity is reasonably assured during accident scenarios. This paper aims at optimizing the Emergency Core Cooling System (ECCS) performance criteria in mitigating LBLOCA accidents at a Pressurized Water Reactor (PWR) using the uranium dioxide fuel and duplex or triplex SiC cladding structures. Clad failures by brittle fractures and thermal degradation were modeled in a fuel analysis code. This fuel model was coupled with the RELAP5 plant model by adapting the fuel’s mesh configuration and formulating the effective heat transfer coefficients. A model to quantify the likelihood of clad functional failure as a combination of individual layer fractures at various axial positions was proposed. Updated SiC material properties were gathered from recent reference studies. Clad reliability estimates using the proposed model were compared with the estimates obtained using other models. The results were used to relax the criterion of required actuation timing of ECCS, such that the risk of the new plant design is less or equal to that of the initial plant configuration. Triplex clad was more reliable than duplex clad and Zr, reducing the conditional core damage probability by three orders of magnitude in the reference LBLOCA scenario. Compressive stresses due to irradiation swelling played the determining role in the vulnerabilities of each clad design. The duplex clad was vulnerable to pressure-loading stresses while triplex clad was prone to fail due to thermal shocks experienced during the LOCA reflood phase. Additionally, it was concluded that the most vulnerable axial fuel rod location in the reference LBLOCA scenario was located at the highest axial power peaking location. A sensitivity study on the ECCS timing density was conducted. The results showed that ECCS actuation timing could be extended from the initial technical specification, without increasing the fuel damage likelihood. The time extension was distributed in the order of several hundreds of seconds, which was comparable with time extensions offered by FeCrAl and Cr-coated-Zr clad designs in LBLOCA scenarios. This time extension may potentially reduce the failure probabilities of EDGs and pumps, hence improving the plant safety further.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Analysis, optimization, and implementation of a hybrid DS/FFH spread-spectrum technique for smart grid communications

In recent years, there has been great interest in using hybrid spread-spectrum (HSS) techniques for commercial applications, particularly in the Smart Grid, in addition to their inherent uses in military communications. This is because HSS can accommodate high data rates with high link integrity, even in the presence of significant multipath effects and interfering signals. A highly useful form of this transmission technique for many types of command, control, and sensing applications is the specific code-related combination of standard direct sequence modulation with fast frequency hopping, denoted hybrid DS/FFH, wherein multiple frequency hops occur within a single data-bit time. In this paper, error-probability analyses are performed for a hybrid DS/FFH system over standard Gaussian and fading-type channels, progressively including the effects from wide- and partial-band jamming, multi-user interference, and varying degrees of Rayleigh and Rician fading. In addition, an optimization approach is formulated that minimizes the bit-error performance of a hybrid DS/FFH communication system and solves for the resulting system design parameters. The optimization objective function is non-convex and can be solved by applying the Karush-Kuhn-Tucker conditions. We also present our efforts toward exploring the design, implementation, and evaluation of a hybrid DS/FFH radio transceiver using a single FPGA. Numerical and experimental results are presented under widely varying design parameters to demonstrate the adaptability of the waveform for varied harsh smart grid RF signal environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2010

Role of Radiation Dose in the Risk of Secondary Leukemia After a Solid Tumor in Childhood Treated Between 1980 and 1999

Purpose: The purpose of this study was to estimate the risk of secondary leukemia as a function of radiation dose, taking into account heterogeneous radiation dose distribution. Methods and Materials: We analyzed a case-control study that investigated the risk of secondary leukemia and myelodysplasia after a solid tumor in childhood; it included 61 patients with leukemia matched with 196 controls. Complete clinical, chemotherapy, and radiotherapy histories were recorded for each patient in the study. Average radiation dose to each of seven bone marrow components for each patient was incorporated into the models, and corresponding risks were summed up. Conditional maximum likelihood methods were used to estimate risk parameters. Results: Whatever the model, we failed to evidence a role for the radiation dose to active bone marrow in the risk of later leukemia, myelodysplasia, or myeloproliferative syndrome, when adjusting for epipodophyllotoxin and anthracycline doses. This result was confirmed when fitting models that included total dose of radiation delivered during radiotherapy, when fitting models taking into account dose per fraction, and when restricting the analysis to acute myeloid leukemia. Conclusions: In contrast to results found in similar studies that included children treated before the use of epipodophyllotoxins, this study failed to show a role for radiotherapy in the risk of secondary leukemia after childhood cancer in children treated between 1980 and 1999. This discrepancy was probably due to a competitive mechanism between these two carcinogens.

62 RADIOLOGY AND NUCLEAR MEDICINE↗