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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Validation of semi-analytical, semi-empirical covariance matrices for two-point correlation function for early DESI data

ABSTRACT We present an extended validation of semi-analytical, semi-empirical covariance matrices for the two-point correlation function (2PCF) on simulated catalogs representative of luminous red galaxies (LRGs) data collected during the initial 2 months of operations of the Stage-IV ground-based Dark Energy Spectroscopic Instrument (DESI). We run the pipeline on multiple effective Zel’dovich (EZ) mock galaxy catalogs with the corresponding cuts applied and compare the results with the mock sample covariance to assess the accuracy and its fluctuations. We propose an extension of the previously developed formalism for catalogs processed with standard reconstruction algorithms. We consider methods for comparing covariance matrices in detail, highlighting their interpretation and statistical properties caused by sample variance, in particular, non-trivial expectation values of certain metrics even when the external covariance estimate is perfect. With improved mocks and validation techniques, we confirm a good agreement between our predictions and sample covariance. This allows one to generate covariance matrices for comparable data sets without the need to create numerous mock galaxy catalogs with matching clustering, only requiring 2PCF measurements from the data itself. The code used in this paper is publicly available at https://github.com/oliverphilcox/RascalC.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Robustness analysis of an air heating plant and control law by using polynomial chaos

This paper presents a robustness analysis of an air heating plant with a multivariable closed-loop control law by using the polynomial chaos methodology (MPC). The plant consists of a PVC tube with a fan in the air input (that forces the air through the tube) and a mass flux sensor in the output. A heating resistance warms the air as it flows inside the tube, and a thermo-couple sensor measures the air temperature. The plant has thus two inputs (the fan's rotation intensity and heat generated by the resistance, both measured in percent of the maximum value) and two outputs (air temperature and air mass flux, also in percent of the maximal value). The mathematical model is obtained by System Identification techniques. The mass flux sensor, which is nonlinear, is linearized and the delays in the transfer functions are properly approximated by non-minimum phase transfer functions. The resulting model is transformed to a state-space model, which is used for control design purposes. The multivariable robust control design techniques used is the LQG/LTR, and the controllers are validated in simulation software and in the real plant. Finally, the MPC is applied by considering some of the system's parameters as random variables (one at a time, and the system's stochastic differential equations are solved by expanding the solution (a stochastic process) in an orthogonal basis of polynomial functions of the basic random variables. This method transforms the stochastic equations in a set of deterministic differential equations, which can be solved by traditional numerical methods (That is the MPC). Statistical data for the system (like expected values and variances) are then calculated. The effects of randomness in the parameters are evaluated in the open-loop and closed-loop pole's positions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

IAEA Coordinated Research Project on HTGR Physics, Thermal Hydraulics, and Depletion Uncertainty Analysis: PHISICS/RELAP5-3D Results for the Phase III Coupled Core Exercises

This report details the Parallel and Highly Innovative Simulation for INL Code System (PHISICS)/Reactor Excursions and Leak Analysis Program (RELAP5)-3D results obtained for the neutronics stand-alone core exercises defined for Phase II of the International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP) on high-temperature gas cooled reactor (HTGR) uncertainty analysis in modeling (UAM). The Phase II models and results are linked to the earlier Standardized Computer Analyses for Licensing Evaluation (SCALE)/Sampler/New ESC-based Weighting Transport (NEWT) data generated for the lattice physics (lattice) stage Phase I of the CRP. The focus of this report is the propagation of cross-section uncertainties from the lattice to the core calculation (core) phase of the prismatic 350 megawatt (MW) General Atomics (GA) Modular HTGR (MHTGR). The Phase II neutronics exercises consist of two sub-cases (II-2a and II-2b) specified for the fresh and mixed core loading of the MHTGR-350 prismatic high-temperature reactor design. Exercises II-2a and II-2b are performed without temperature feedback using isothermal temperature profiles. For the nominal lattice physics (i.e., best-estimate) model, a series of fresh and depleted single block and super cell SCALE/KENO and SCALE/NEWT models were developed at Idaho National Laboratory (INL) to assess the impact of spectral effects on the few-group cross sections. A combination of these lattice cells were used in a super cell calculation to construct 8-group cross-section libraries for use in the INL-developed PHISICS/RELAP5-3D code suite. The block-level homogenized libraries were assigned to the 220 fuel zones utilized in the MHTGR-350 PHISICS core model, according to the fresh and mixed fresh/depleted core loading pattern. In order to evaluate the effect of uncertainty propagation, several sets consisting of 1,000 perturbed NEWT lattice and PHISICS/RELAP5-3D core calculations were performed using the SCALE 6.2 ENDF/B-VII.1 cross-section co-variance data and the stochastic sampling module Sampler in SCALE 6.2.0. The Figures of Merit (FOM) investigated include the mean and standard deviation uncertainty values obtained for the eigenvalues, control rod worth values, block-averaged power profiles, power axial offsets, and isothermal temperature feedback coefficients. A sensitivity study on the main nuclide reaction contributors to the FOM uncertainties has not yet been performed since the SCALE/PHISICS/RAVEN coupling with ENDF/B-VII co-variance data is still being developed. It was found that uncertainties in the cross sections lead to uncertainties in the local power values of up to 1.5%. The variances between the fresh and mixed/depleted core models are not as large as the axial variations between the top and bottom within each core model. The core eigenvalue uncertainty is approximately 0.5%, which is significant in comparison to typical eigenvalue difference targets (less than ~0.1% for LWRs). The power peaking and axial offset uncertainties are smaller (0.10% – 0.15%) and probably below the level of significance in typical core design metrics. The use of an 8-group energy structure slightly under-estimates some of the uncertainties, but in absolute terms, the uncertainty results are reasonably close to the 26-group results. The 26- and 8-group mean and nominal results differ by a larger degree, and if it can be afforded in terms of calculation resources, the 26-group structure should be used for HTGR calculations. The 8-group structure can, however, still be useful for reasonably accurate uncertainty assessments of transient cases where computational time is important. It was furthermore found that the use of a super cell during the cross-section generation process for better representation of the spectral environment at the core periphery did not lead to significant changes in the core eigenvalues, axial offset, and power peaking uncertainties. The impact of the super cell cross sections on the nominal and mean eigenvalues is, however, important enough (0.6% – 1.1% lower) to justify the use of these super cells for HTGR core simulation to represent the softer spectral environment in the core peripheral regions for nominal best-estimate calculations. The use of super cells for HTGR uncertainty studies is, therefore, not strictly necessary, but the improvements in nominal results could justify their use.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Accurate determination of electronic transport properties of silicon wafers by nonlinear photocarrier radiometry with multiple pump beam sizes

In this paper, photocarrier radiometry (PCR) technique with multiple pump beam sizes is employed to determine simultaneously the electronic transport parameters (the carrier lifetime, the carrier diffusion coefficient, and the front surface recombination velocity) of silicon wafers. By employing the multiple pump beam sizes, the influence of instrumental frequency response on the multi-parameter estimation is totally eliminated. A nonlinear PCR model is developed to interpret the PCR signal. Theoretical simulations are performed to investigate the uncertainties of the estimated parameter values by investigating the dependence of a mean square variance on the corresponding transport parameters and compared to that obtained by the conventional frequency-scan method, in which only the frequency dependences of the PCR amplitude and phase are recorded at single pump beam size. Simulation results show that the proposed multiple-pump-beam-size method can improve significantly the accuracy of the determination of the electronic transport parameters. Comparative experiments with a p-type silicon wafer with resistivity 0.1–0.2 Ω·cm are performed, and the electronic transport properties are determined simultaneously. The estimated uncertainties of the carrier lifetime, diffusion coefficient, and front surface recombination velocity are approximately ±10.7%, ±8.6%, and ±35.4% by the proposed multiple-pump-beam-size method, which is much improved than ±15.9%, ±29.1%, and >±50% by the conventional frequency-scan method. The transport parameters determined by the proposed multiple-pump-beam-size PCR method are in good agreement with that obtained by a steady-state PCR imaging technique.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Measuring the scale dependence of intrinsic alignments using multiple shear estimates

We present a new method for measuring the scale dependence of the intrinsic alignment (IA) contamination to the galaxy–galaxy lensing signal, which takes advantage of multiple shear estimation methods applied to the same source galaxy sample. By exploiting the resulting correlation of both shape noise and cosmic variance, our method can provide an increase in the signal-to-noise of the measured IA signal as compared to methods which rely on the difference of the lensing signal from multiple photometric redshift bins. For a galaxy–galaxy lensing measurement which uses LSST sources and DESI lenses, the signal-to-noise on the IA signal from our method is predicted to improve by a factor of ~2 relative to the method of Blazek et al. (2012), for pairs of shear estimates which yield substantially different measured IA amplitudes and highly correlated shape noise terms. We show that statistical error necessarily dominates the measurement of IAs using our method. We also consider a physically motivated extension of the Blazek et al. (2012) method which assumes that all nearby galaxy pairs, rather than only excess pairs, are subject to IA. In this case, the signal-to-noise of the method of Blazek et al. (2012) is improved.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

General Multifidelity Surrogate Models: Framework and Active-Learning Strategies for Efficient Rare Event Simulation

Estimating the probability of failure for complex real-world systems using high-fidelity computational models is often prohibitively expensive, especially when the probability is small. Exploiting low-fidelity models can make this process more feasible, but merging information from multiple low-fidelity and high-fidelity models poses several challenges. Here, this paper presents a robust multi-fidelity surrogate modeling strategy in which the multi-fidelity surrogate is assembled using an active learning strategy using an on-the-fly model adequacy assessment set within a subset simulation framework for efficient reliability analysis. The multi-fidelity surrogate is assembled by first applying a Gaussian process correction to each low-fidelity model and assigning a model probability based on the model's local predictive accuracy and cost. Three strategies are proposed to fuse these individual surrogates into an overall surrogate model based on model averaging and deterministic/stochastic model selection. The strategies also dictate which model evaluations are necessary. No assumptions are made about the relationships between low-fidelity models, while the high-fidelity model is assumed to be the most accurate and most computationally expensive model. Through two analytical and two numerical case studies, including a case study evaluating the failure probability of Tristructural isotropic-coated (TRISO) nuclear fuels, the algorithm is shown to be highly accurate while drastically reducing the number of high-fidelity model calls (and hence computational cost).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

ON MORE SENSITIVE PERIODOGRAM STATISTICS

Period searches in event data have traditionally used the Rayleigh statistic, R {sup 2}. For X-ray pulsars, the standard has been the Z {sup 2} statistic, which sums over more than one harmonic. For γ-rays, the H-test, which optimizes the number of harmonics to sum, is often used. These periodograms all suffer from the same problem, namely artifacts caused by correlations in the Fourier components that arise from testing frequencies with a non-integer number of cycles. This article addresses this problem. The modified Rayleigh statistic is discussed, its generalization to any harmonic, R{sub k}{sup 2}, is formulated, and from the latter, the modified Z {sup 2} statistic, Z{sup 2}, is constructed. Versions of these statistics for binned data and point measurements are derived, and it is shown that the variance in the uncertainties can have an important influence on the periodogram. It is shown how to combine the information about the signal frequency from the different harmonics to estimate its value with maximum accuracy. The methods are applied to an XMM-Newton observation of the Crab pulsar for which a decomposition of the pulse profile is presented, and shows that most of the power is in the second, third, and fifth harmonics. Statistical detection power of the R{sub k}{sup 2} statistic is superior to the FFT and equivalent to the Lomb--Scargle (LS). Response to gaps in the data is assessed, and it is shown that the LS does not protect against the distortions they cause. The main conclusion of this work is that the classical R {sup 2} and Z {sup 2} should be replaced by R{sub k}{sup 2} and Z{sup 2} in all applications with event data, and the LS should be replaced by the R{sub k}{sup 2} when the uncertainty varies from one point measurement to another.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

JOINT ANALYSIS OF CLUSTER OBSERVATIONS. II. CHANDRA/XMM-NEWTON X-RAY AND WEAK LENSING SCALING RELATIONS FOR A SAMPLE OF 50 RICH CLUSTERS OF GALAXIES

We present a study of multiwavelength X-ray and weak lensing scaling relations for a sample of 50 clusters of galaxies. Our analysis combines Chandra and XMM-Newton data using an energy-dependent cross-calibration. After considering a number of scaling relations, we find that gas mass is the most robust estimator of weak lensing mass, yielding 15% {+-} 6% intrinsic scatter at r{sub 500}{sup WL} (the pseudo-pressure Y{sub X} yields a consistent scatter of 22% {+-} 5%). The scatter does not change when measured within a fixed physical radius of 1 Mpc. Clusters with small brightest cluster galaxy (BCG) to X-ray peak offsets constitute a very regular population whose members have the same gas mass fractions and whose even smaller (<10%) deviations from regularity can be ascribed to line of sight geometrical effects alone. Cool-core clusters, while a somewhat different population, also show the same (<10%) scatter in the gas mass-lensing mass relation. There is a good correlation and a hint of bimodality in the plane defined by BCG offset and central entropy (or central cooling time). The pseudo-pressure Y{sub X} does not discriminate between the more relaxed and less relaxed populations, making it perhaps the more even-handed mass proxy for surveys. Overall, hydrostatic masses underestimate weak lensing masses by 10% on the average at r{sub 500}{sup WL}; but cool-core clusters are consistent with no bias, while non-cool-core clusters have a large and constant 15%-20% bias between r{sub 2500}{sup WL} and r{sub 500}{sup WL}, in agreement with N-body simulations incorporating unthermalized gas. For non-cool-core clusters, the bias correlates well with BCG ellipticity. We also examine centroid shift variance and power ratios to quantify substructure; these quantities do not correlate with residuals in the scaling relations. Individual clusters have for the most part forgotten the source of their departures from self-similarity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Spectral fluctuations in the Sachdev-Ye-Kitaev model

We present a detailed quantitative analysis of spectral correlations in the Sachdev-Ye-Kitaev (SYK) model. We find that the deviations from universal Random Matrix Theory (RMT) behavior are due to a small number of long-wavelength fluctuations (of the order of the number of Majorana fermions N ) from one realization of the ensemble to the next one. These modes can be parameterized effectively in terms of Q-Hermite orthogonal polynomials, the main contribution being due to scale fluctuations for which we give a simple analytical estimate. Our numerical results for N = 32 show that only the lowest eight polynomials are needed to eliminate the nonuniversal part of the spectral fluctuations. The covariance matrix of the coefficients of this expansion can be obtained analytically from low-order double-trace moments. We evaluate the covariance matrix of the first six moments and find that it agrees with the numerics. We also analyze the spectral correlations in terms of a nonlinear σ-model, which is derived through a Fierz transformation, and evaluate the one and two-point spectral correlation functions to two-loop order. The wide correlator is given by the sum of the universal RMT result and corrections whose lowest-order term corresponds to scale fluctuations. However, the loop expansion of the σ-model results in an ill-behaved expansion of the resolvent, and it gives universal RMT fluctuations not only for q= 4 or higher even q-body interactions, but also for the q= 2 SYK model albeit with a much smaller Thouless energy while the correct result in this case should have been Poisson statistics. In our numerical studies we analyze the number variance and spectral form factor for N = 32 and q = 4. We show that the quadratic deviation of the number variance for large energies appears as a peak for small times in the spectral form factor. After eliminating the long-wavelength fluctuations, we find quantitative agreement with RMT up to an exponentially large number of level spacings for the number variance or exponentially short times in the case of the spectral form factor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Analytical Framework for Identifying and Differentiating Recent Hitchhiking and Severe Bottleneck Effects from Multi-Locus DNA Sequence Data

Hitchhiking and severe bottleneck effects have impact on the dynamics of genetic diversity of a population by inducing homogenization at a single locus and at the genome-wide scale, respectively. As a result, identification and differentiation of the signatures of such events from DNA sequence data at a single locus is challenging. This study develops an analytical framework for identifying and differentiating recent homogenization events at multiple neutral loci in low recombination regions. The dynamics of genetic diversity at a locus after a recent homogenization event is modeled according to the infinite-sites mutation model and the Wright-Fisher model of reproduction with constant population size. In this setting, I derive analytical expressions for the distribution, mean, and variance of the number of polymorphic sites in a random sample of DNA sequences from a locus affected by a recent homogenization event. Based on this framework, three likelihood-ratio based tests are presented for identifying and differentiating recent homogenization events at multiple loci. Lastly, I apply the framework to two data sets. First, I consider human DNA sequences from four non-coding loci on different chromosomes for inferring evolutionary history of modern human populations. The results suggest, in particular, that recent homogenization events at the loci are identifiable when the effective human population size is 50000 or greater in contrast to 10000, and the estimates of the recent homogenization events are agree with the “Out of Africa” hypothesis. Second, I use HIV DNA sequences from HIV-1-infected patients to infer the times of HIV seroconversions. The estimates are contrasted with other estimates derived as the mid-time point between the last HIV-negative and first HIV-positive screening tests. Finally, the results show that significant discrepancies can exist between the estimates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Correction of confidence intervals in excess relative risk models using Monte Carlo dosimetry systems with shared errors

Introduction: Measurement errors are ubiquitous in epidemiological studies, especially for doses arising from environmental and occupational exposures, which are difficult to assess. Correction methods for independent measurement errors, have been comprehensively described elsewhere, including regression calibration, simulation extrapolation (SIMEX), etc. However, when exposure estimates are constructed using complicated physical and biological models, uncertainties in the dosimetry system can become very complex. In such systems, uncertainties in some parameters may affect a large group of study participants simultaneously, and hence are “shared” as opposed to independent dosimetric uncertainties. Representing the structure of the uncertainty in the dosimetry by providing multiple realizations of possible dose has been described for several studies. The goal of this paper is to implement, and explore the properties of, a generalized estimating equation-based approach to shared uncertainties based on principles described in an earlier paper. Methods: The effects of shared and unshared dosimetry error on parameter estimates and confidence intervals in a generalized excess relative risk model are examined. A post-hoc correction method is implemented that constructs corrected confidence intervals based on an underlying variance structure described in an earlier paper. In this correction method it is assumed that the estimated slope parameter in a linear excess relative risk model is distributed as a mixture of normal and lognormal components. A simulation study of the behavior of this correction was developed based on multiple realizations provided by the Monte Carlo dosimetry system used for the plutonium exposures in the Mayak Worker Cohort and a risk model with close similarity to that used in analyses of lung cancer data in that cohort. Results: In the simulation study we found that shared dose errors severely degraded the coverage probabilities of confidence limits for the slope parameter in the linear excess relative risk model relating uncertain exposure to lung cancer risk. Using our correction method to adjust the confidence intervals provided much improved coverage probabilities for this parameter. A smaller amount of degradation in confidence interval coverage for other parameters (e.g. those in the baseline and dose modification terms) was noted, and the proposed correction method also improved coverage for these parameters as well. Discussion: Compared to other recently described methods our proposed correction method relies on relatively familiar software to fit dose response models. The basic modeling philosophy described here first uses existing Poisson regression methods to estimate parameters in the excess relative risk model; in this first stage mean dose (computed from the multiple realizations) is used as the independent variable in the regression. Once the model is fit we then correct (widen) the standard errors for all parameters using the proposed correction method. The simulation studies indicate that the methods described here are an important contribution to the available tools for dealing with shared measurement errors in complex risk analysis.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2013

Encouraging Combined Heat and Power in California Buildings

Governor Brown’s research priorities include an additional 6.5 GW of combined heat and power (CHP) by 2030. As of 2009, roughly 0.25 GW of small natural gas and biogas fired CHP is documented by the Self-Generation Incentive Program (SGIP) database. The SGIP is set to expire, and the anticipated grid de-carbonization based on the development of 20 GW of renewable energy will influence the CHP adoption. Thus, an integrated optimization approach for this analysis was chosen that allows optimizing the adoption of distributed energy resources (DER) such as photovoltaics (PV), CHP, storage technologies, etc. in the California commercial sector from the building owners’ perspective. To solve this DER adoption problem the Distributed Energy Resources Customer Adoption Model (DER-CAM), developed by the Lawrence Berkeley National Laboratory and used extensively to address the problem of optimally investing and scheduling DER under multiple settings, has been used. The application of CHP at large industrial sites is well known, and much of its potential is already being realized. Conversely, commercial sector CHP, especially those above 50 to 100 kW peak electricity load, is widely overlooked. In order to analyze the role of DER in CO 2 reduction, 147 representative sites in different climate zones were selected from the California Commercial End Use Survey (CEUS). About 8000 individual optimization runs, with different assumptions for the electric tariffs, natural gas costs, marginal grid CO 2 emissions, and nitrogen oxide treatment costs, SGIP, fuel cell lifetime, fuel cell efficiency, PV installation costs, and payback periods for investments have been performed. The most optimistic CHP potential contribution in this sector in 2020 will be 2.7 GW. However, this result requires a SGIP in 2020, 46% average electric efficiency for fuel cells, a payback period for investments of 10 years, and a CO 2 focused approach of the building owners. In 2030 it will be only 2.5 GW due to the anticipated grid decarbonization. The 2030 result requires a 60% electric efficiency and 20 year life time for fuel cells, a payback period of 10 years, and a CO 2 minimization strategy of building owners. Finally, the possible CHP potential in 2030 shows a significant variance between 0.2 GW and 2.5 GW, demonstrating the complex interactions between technologies, policies, and customer objectives.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Relative Importance of Vital Rates to Population Dynamics of Wood Ducks

The wood duck (Aix sponsa) is a common and important cavity-nesting duck in North America; however, we know very little about how changes in vital rates influence population growth rate (λ). We used estimates of fertility and survival of female wood ducks from our nest-box studies in South Carolina, Alabama, and Georgia, USA, to create a stage-based matrix population model. We conducted perturbation analyses and ranked elasticity values to examine the relative importance of 17 component vital rates to λ. Female survival is influenced by nest success, so we recognized this female heterogeneity in our analyses. Four vital rates showed the greatest importance to λ. Analytic elasticities were greatest for breeding season and nonbreeding season survival of females that nested successfully, followed by nest success and female recruitment to the breeding population. Differences in female quality were important to λ. Next, we used process variation of vital rates and conducted life-stage simulation analyses (LSA) followed by variance decomposition to determine the amount of variation in λ explained by each vital rate. Female recruitment to the breeding population explained 57.7% of the variation in λ followed by nest success (11.4%), and breeding and nonbreeding season survival of females that nested successfully (9.3% and 9.4%, respectively). Together these 4 vital rates explained 88% of the variation in λ. Mean asymptotic population growth rate (λ = 0.80 ± 0.08 [SD]) from LSA revealed a declining population. Recruitment of females hatched from nest boxes was insufficient to sustain the nest-box population. Furthermore, including yearling (SY) females that were produced outside of nest boxes (i.e., immigrants) increased recruitment rates 1.5 to 2 times more than when only SY females recruited from nest boxes were included. Future research that examines how emigration and immigration interact with survival and reproduction to influence local population dynamics of wood ducks will be important for identifying the value of nest-box programs to wood duck conservation and management.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Accelerated statistical failure analysis of multifidelity TRISO fuel models

Statistical nuclear fuel failure analysis is critical for the design and development of advanced reactor technologies. Although Monte Carlo Sampling (MCS) is a standard method of statistical failure analysis for fuels, the low failure probabilities of some advanced fuel forms and the correspondingly large number of required model evaluations limit its application to low-fidelity (e.g., 1-D) fuel models. In this paper, we present four other statistical methods for fuel failure analysis in Bison, considering tri-structural isotropic (TRISO)-coated particle fuel as a case study. The statistical methods considered are Latin hypercube sampling (LHS), adaptive importance sampling (AIS), subset simulation (SS), and the Weibull theory. Using these methods, we analyzed both 1-D and 2-D representations of TRISO models to compute failure probabilities and the distributions of fuel properties that result in failures. The results of these methods compare well across all TRISO models considered. Overall, SS and the Weibull theory were deemed the most efficient, and can be applied to both 1-D and 2-D TRISO models to compute failure probabilities. Moreover, since SS also characterizes the distribution of parameters that cause TRISO failures, and can consider failure modes not described by the Weibull criterion, it may be preferred over the other methods. Finally, a discussion on the efficacy of different statistical methods of assessing nuclear fuel safety is provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Measurement of gravitational lensing of the cosmic microwave background using SPT-3G 2018 data

We present a measurement of gravitational lensing over 1500 deg 2 of the Southern sky using SPT-3G temperature data at 95 GHz and 150 GHz taken in 2018. The lensing amplitude relative to a fiducial Planck 2018 Lambda cold dark matter ( Λ CDM ) cosmology is found to be 1.020 ± 0.060 , excluding instrumental and astrophysical systematic uncertainties. We conduct extensive systematic and null tests to check the robustness of the lensing measurements, and report a minimum-variance combined lensing power spectrum over angular multipoles of 50 < L < 2000 , which we use to constrain cosmological models. When analyzed alone and jointly with primary cosmic microwave background (CMB) spectra within the Λ CDM model, our lensing amplitude measurements are consistent with measurements from SPT-SZ, SPTpol, ACT, and Planck. Incorporating loose priors on the baryon density and other parameters including uncertainties on a foreground bias template, we obtain a 1 σ constraint on σ 8 Ω m 0.25 = 0.595 ± 0.026 using the SPT-3G 2018 lensing data alone, where σ 8 is a common measure of the amplitude of structure today and Ω m is the matter density parameter. Combining SPT-3G 2018 lensing measurements with baryon acoustic oscillation (BAO) data, we derive parameter constraints of σ 8 = 0.810 ± 0.033 , S 8 ≡ σ 8 ( Ω m / 0.3 ) 0.5 = 0.836 ± 0.039 , and Hubble constant H 0 = 68.8 - 1.6 + 1.3 km s - 1 Mpc - 1 . Our preferred S 8 value is higher by 1.6 to 1.8 σ compared to cosmic shear measurements from DES-Y3, HSC-Y3, and KiDS-1000 at lower redshift and smaller scales. We combine our lensing data with CMB anisotropy measurements from both SPT-3G and Planck to constrain extensions of Λ CDM . Using CMB anisotropy and lensing measurements from SPT-3G only, we provide independent constraints on the spatial curvature of Ω K = 0.01 4 - 0.026 + 0.023 (95% C.L.) and the dark energy density of Ω Λ = 0.72 2 - 0.026 + 0.031 (68% C.L.). When combining SPT-3G lensing data with SPT-3G CMB anisotropy and BAO data, we find an upper limit on the sum of the neutrino masses of ∑ m ν < 0.30 eV (95% C.L.). Due to the different combination of angular scales and sky area, this lensing analysis provides an independent check on lensing measurements by ACT and Planck.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

THE DENSITY DISTRIBUTION IN TURBULENT BISTABLE FLOWS

We numerically study the volume density probability distribution function (n-PDF) and the column density probability distribution function ({Sigma}-PDF) resulting from thermally bistable turbulent flows. We analyze three-dimensional hydrodynamic models in periodic boxes of 100 pc by side, where turbulence is driven in the Fourier space at a wavenumber corresponding to 50 pc. At low densities (n {approx}< 0.6 cm{sup -3}), the n-PDF is well described by a lognormal distribution for an average local Mach number ranging from {approx}0.2 to {approx}5.5. As a consequence of the nonlinear development of thermal instability (TI), the logarithmic variance of the distribution of the diffuse gas increases with M faster than in the well-known isothermal case. The average local Mach number for the dense gas (n {approx}> 7.1 cm{sup -3}) goes from {approx}1.1 to {approx}16.9 and the shape of the high-density zone of the n-PDF changes from a power law at low Mach numbers to a lognormal at high M values. In the latter case, the width of the distribution is smaller than in the isothermal case and grows slower with M. At high column densities, the {Sigma}-PDF is well described by a lognormal for all of the Mach numbers we consider and, due to the presence of TI, the width of the distribution is systematically larger than in the isothermal case but follows a qualitatively similar behavior as M increases. Although a relationship between the width of the distribution and M can be found for each one of the cases mentioned above, these relations are different from those of the isothermal case.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Uncovering the Forced Climate Response from a Single Ensemble Member Using Statistical Learning

Internal atmospheric variability fundamentally limits predictability of climate and obscures evidence of anthropogenic climate change regionally and on time scales of up to a few decades. Dynamical adjustment techniques estimate and subsequently remove the influence of atmospheric circulation variability on temperature or precipitation. The residual component is expected to contain the thermodynamical signal of the externally forced response but with less circulation-induced noise. Existing techniques have led to important insights into recent trends in regional (hydro-) climate and their drivers, but the variance explained by circulation is often low. Here, we develop a novel dynamical adjustment technique by implementing principles from statistical learning. We demonstrate in an ensemble of Community Earth System Model (CESM) simulations that statistical learning methods, such as regularized linear models, establish a clearer relationship between circulation variability and atmospheric target variables, and need relatively short periods of record for training (around 30 years). The method accounts for, on average, 83% and 78% of European monthly winter temperature and precipitation variability at gridcell level, and around 80% of global mean temperature and hemispheric precipitation variability. We show that the residuals retain forced thermodynamical contributions to temperature and precipitation variability. Accurate estimates of the total forced response can thus be recovered assuming that forced circulation changes are gradual over time. Overall, forced climate response estimates can be extracted at regional or global scales from approximately 3–5 times fewer ensemble members, or even a single realization, using statistical learning techniques. We anticipate the technique will contribute to reducing uncertainties around internal variability and facilitating climate change detection and attribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Discovering strongly lensed quasar candidates with catalogue-based methods from DESI Legacy Surveys

The Hubble tension, revealed by a ~5σ discrepancy between measurements of the Hubble-Lemaitre constant among observations of the early and local Universe, is one of the most significant problems in modern cosmology. In order to better understand the origin of this mismatch, independent techniques to measure H 0 , such as strong lensing time delays, are required. Notably, the sample size of such systems is key to minimising the statistical uncertainties and cosmic variance, which can be improved by exploring the datasets of large-scale sky surveys such as Dark Energy Spectroscopic Instrument (DESI). We identify possible strong lensing time-delay systems within DESI by selecting candidate multiply imaged lensed quasars from a catalogue of 24 440 816 candidate QSOs contained in the ninth data release of the DESI Legacy Imaging Surveys (DESI-LS). Using a friend-of-friends-like algorithm on spatial co-ordinates, our method generates an initial list of compact quasar groups. This list is subsequently filtered using a measure of the similarity of colours among a group’s members and the likelihood that they are quasars. A visual inspection finally selects candidate strong lensing systems based on the spatial configuration of the group members. We identified 620 new candidate multiply imaged lensed quasars (101 grade-A, 214 grade-B, 305 grade-C). This number excludes 53 known spectroscopically confirmed systems and existing candidate systems identified in other similar catalogues. When available, these new candidates will be further checked by combining the spectroscopic and photometric data from DESI.

79 ASTRONOMY AND ASTROPHYSICS↗