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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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DOE OSTI2014

Motion as perturbation. II. Development of the method for dosimetric analysis of motion effects with fixed-gantry IMRT

Purpose: In this work, the feasibility of implementing a motion-perturbation approach to accurately estimate volumetric dose in the presence of organ motion—previously demonstrated for VMAT-–is studied for static gantry IMRT. The method's accuracy is improved for the voxels that have very low planned dose but acquire appreciable dose due to motion. The study describes the modified algorithm and its experimental validation and provides an example of a clinical application. Methods: A contoured region-of-interest is propagated according to the predefined motion kernel throughout time-resolved 4D phantom dose grids. This timed series of 3D dose grids is produced by the measurement-guided dose reconstruction algorithm, based on an irradiation of a staticARCCHECK (AC) helical dosimeter array (Sun Nuclear Corp., Melbourne, FL). Each moving voxel collects dose over the dynamic simulation. The difference in dose-to-moving voxel vs dose-to-static voxel in-phantom forms the basis of a motion perturbation correction that is applied to the corresponding voxel in the patient dataset. A new method to synchronize the accelerator and dosimeter clocks, applicable to fixed-gantry IMRT, was developed. Refinements to the algorithm account for the excursion of low dose voxels into high dose regions, causing appreciable dose increase due to motion (LDVE correction). For experimental validation, four plans using TG-119 structure sets and objectives were produced using segmented IMRT direct machine parameters optimization in Pinnacle treatment planning system (v. 9.6, Philips Radiation Oncology Systems, Fitchburg, WI). All beams were delivered with the gantry angle of 0°. Each beam was delivered three times: (1) to the static AC centered on the room lasers; (2) to a static phantom containing a MAPCHECK2 (MC2) planar diode array dosimeter (Sun Nuclear); and (3) to the moving MC2 phantom. The motion trajectory was an ellipse in the IEC XY plane, with 3 and 1.5 cm axes. The period was 5 s, with the resulting average motion speed of 1.45 cm/s. The motion-perturbed high resolution (2 mm voxel) volumetric dose grids on the MC2 phantom were generated for each beam. From each grid, a coronal dose plane at the detector level was extracted and compared to the corresponding moving MC2 measurement, using gamma analysis with both global (G) and local (L) dose-error normalization. Results: Using the TG-119 criteria of (3%G/3 mm), per beam average gamma analysis passing rates exceeded 95% in all cases. No individual beam had a passing rate below 91%. LDVE correction eliminated systematic disagreement patterns at the beams’ aperture edges. In a representative example, application of LDVE correction improved (2%L/2 mm) gamma analysis passing rate for an IMRT beam from 74% to 98%. Conclusions: The effect of motion on the moving region-of-interest IMRT dose can be estimated with a standard, static phantom QA measurement, provided the motion characteristics are independently known from 4D CT or otherwise. The motion-perturbed absolute dose estimates were validated by the direct planar diode array measurements, and were found to reliably agree with them in a homogeneous phantom.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Implications of inertial subrange scaling for stably stratified mixing

In this work, we investigate the effects of the turbulent dynamic range on active scalar mixing in stably stratified turbulence by adapting the theoretical passive scalar modelling and demonstrating their usefulness through consideration of the results of direct numerical simulations of statistically stationary homogeneous stratified and sheared turbulence. By analysis of inertial and inertial–convective subrange scalings, we show that the relationship between the active scalar and turbulence time scales is predicted by the ratio of the Kolmogorov and Obukhov–Corrsin constants, provided mean flow parameters permit the two subrange scalings to be appropriate approximations. We use the resulting relationship between time scales to parameterise an appropriate turbulent mixing coefficient $\varGamma \equiv \chi /\epsilon$, defined here as the ratio of available potential energy ($E_p$) and turbulent kinetic energy ($E_k$) dissipation rates. With the analysis presented here, we show that $\varGamma$ can be estimated by $E_p,E_k$ and a universal constant provided an appropriate Reynolds number is sufficiently high. This large Reynolds number regime appears here to occur at $ {{Re_b}} \equiv \epsilon / \nu N^{2} \gtrapprox 300$ where $\nu$ is the kinematic viscosity and $N$ is the characteristic buoyancy frequency. We propose a model framework for irreversible diapycnal mixing with robust theoretical parametrisation and asymptotic behaviour in this high-$ {{Re_b}}$ limit.

42 ENGINEERING↗
DOE OSTI2024

FARM User Guidance and Instructions

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, the general workflow and the software requirements of FARM module are summarized, and the detailed instructions for installing FARM software, running built-in example cases, deriving Linear Parameter-Varying (LPV) state-space models, and using FARM for user-defined power dispatch problems are provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

A Review of Modeling Approaches for Predicting Frost Growth and Defrosting on Tube-Fin Heat Exchangers: Preprint

Frost formation and growth on the evaporator surface is a common process that deteriorates the air-refrigerant heat transfer and restricts airflow. This degrades the performance of the vapor compression system by increasing temperature lift and air-side pressure drop. To accurately predict these effects during coil frosting, as well as the energy use and duration of the defrost process, there is a need to estimate the heat and mass transfer, momentum transport, and solid-liquid and liquid-vapor phase change. Therefore, in the past few decades, continuous effort has been made to model frosting and defrosting processes using approaches ranging from empirical correlations to computational fluid dynamic models. To provide a clearer overview for researchers, engineers, and manufacturers in this field, this paper provides a comprehensive literature review for frosting and defrosting models. The paper begins with theoretical background of frost formation and defrost processes, and then reviews the common modeling approaches in literature and their underlying assumptions when trying to account for various physical phenomenon. Based on the literature review, the most critical modeling effort for frost formation is the determination of frost densification rate and frost growth rate. Various methods to predict these two parameters are reviewed. Empirical correlations commonly used for frost density and thermal conductivity are presented and compared. For the defrost process, various multi-stage models have been proposed with different assumptions. Some assume the presence of air gap between the tube wall and the frost, while others consider the melted frost flow due to gravity. We also review physics-based and empirical approaches to integrate defrost models into heat pump models. We conclude by identifying research gaps and providing recommendations.

defrost↗
DOE OSTI2015

Chaos in an imperfectly premixed model combustor

This article reports nonlinear bifurcations observed in a laboratory scale, turbulent combustor operating under imperfectly premixed mode with global equivalence ratio as the control parameter. The results indicate that the dynamics of thermoacoustic instability correspond to quasi-periodic bifurcation to low-dimensional, deterministic chaos, a route that is common to a variety of dissipative nonlinear systems. The results support the recent identification of bifurcation scenarios in a laminar premixed flame combustor (Kabiraj et al., Chaos: Interdiscip. J. Nonlinear Sci. 22, 023129 (2012)) and extend the observation to a practically relevant combustor configuration.

42 ENGINEERING↗
DOE OSTI2015

Developing and Implementing the Data Mining Algorithms in RAVEN

The RAVEN code is becoming a comprehensive tool to perform probabilistic risk assessment, uncertainty quantification, and verification and validation. The RAVEN code is being developed to support many programs and to provide a set of methodologies and algorithms for advanced analysis. Scientific computer codes can generate enormous amounts of data. To post-process and analyze such data might, in some cases, take longer than the initial software runtime. Data mining algorithms/methods help in recognizing and understanding patterns in the data, and thus discover knowledge in databases. The methodologies used in the dynamic probabilistic risk assessment or in uncertainty and error quantification analysis couple system/physics codes with simulation controller codes, such as RAVEN. RAVEN introduces both deterministic and stochastic elements into the simulation while the system/physics code model the dynamics deterministically. A typical analysis is performed by sampling values of a set of parameter values. A major challenge in using dynamic probabilistic risk assessment or uncertainty and error quantification analysis for a complex system is to analyze the large number of scenarios generated. Data mining techniques are typically used to better organize and understand data, i.e. recognizing patterns in the data. This report focuses on development and implementation of Application Programming Interfaces (APIs) for different data mining algorithms, and the application of these algorithms to different databases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Influence of Nd(II) and Nd(III) Ions on the Speciation and Kinetic Dynamics of Radiolytic Transients in Molten LiCl-KCl Eutectic Salt Mixtures

In the pyrochemical reprocessing of used nuclear fuel, understanding the effects of ionizing radiation on the chemical behavior of fission products in molten chloride eutectic salt is crucial. Here, this study investigates the impact of radiation on the chemical and kinetic speciation of Nd ions in molten LiCl-KCl eutectic, which are challenging to separate due to their multivalent oxidation states and comproportionation reactions. Electron pulse radiolysis techniques were used to determine transient absorption spectra, chemical kinetics, and activation parameters for the reaction of Nd ions with the primary products of molten LiCl-KCl eutectic radiolysis: the solvated electron (e S - ) and dichlorine radical anion (Cl 2 •- ). Initially, Nd(III) reacted rapidly with e S - , forming Nd(II) with a second-order rate coefficient of k = (4.54 ± 0.07) × 10 10 M -1 s -1 at 673 K. The resulting Nd(II) ions then reacted slowly with Cl 2 •- , regenerating Nd(III) with an estimated rate of k = (1.72 ± 0.04) × 10 10 M -1 s -1 at 673 K. Additionally, the comproportionation reaction of Nd(III) and Nd(s) to form Nd(II) was monitored chemically and electrochemically. This work suggests that the comproportionation reaction of Nd(III) with Nd(s) to form Nd(II) is unstable in molten LiCl-KCl eutectic.

36 - MATERIALS SCIENCE↗
DOE OSTI2012

Report of Separate Effects Testing for Modeling of Metallic Fuel Casting Process

In order to give guidance regarding the best investment of time and effort in experimental determination of parameters defining the casting process, a Flow-3D model of the casting process was used to investigate the most influential parameters regarding void fraction of the solidified rods and solidification speed for fluid flow parameters, liquid heat transfer parameters, and solid heat transfer parameters. Table 1 summarizes the most significant variables for each of the situations studied. A primary, secondary, and tertiary effect is provided for fluid flow parameters (impacts void fraction) and liquid heat transfer parameters (impacts solidification). In Table 1, the wetting angle represents the angle between the liquid and mold surface as pictured in Figure 1. The viscosity is the dynamic viscosity of the liquid and the surface tension is the property of the surface of a liquid that allows it to resist an external force. When only considering solid heat transfer properties, the variations from case to case were very small. Details on this conclusion are provided in the section considering solid heat transfer properties. The primary recommendation of the study is to measure the fluid flow parameters, specifically the wetting angle, surface tension, and dynamic viscosity, in order of importance, as well as the heat transfer parameters latent heat and specific heat of the liquid alloy. The wetting angle and surface tension can be measured simultaneously using the sessile drop method. It is unclear whether there is a temperature dependency in these properties. Thus measurements for all three parameters are requested at 1340, 1420, and 1500 degrees Celsius, which correspond to the minimum, middle, and maximum temperatures of the liquid alloy during the process. In addition, the heat transfer coefficient between the mold and liquid metal, the latent heat of transformation, and the specific heat of the liquid metal all have strong influences on solidification. These parameters should be measured to achieve better simulation fidelity. Information on all the mentioned parameters is virtually nonexistent. Presently, all the parameters within the casting model are estimates based on pure U, or another alloy such as U-Ni.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Bayesian Cloud Property Retrievals from ARM Active and Passive Measurements

The optimum use of the continuous measurements of thermodynamics, radiation, aerosols, clouds and precipitation from the DOE Atmospheric Radiation Measurement (ARM) program is key to achieve the DOE Atmospheric System Research (ASR)’s objectives. One of the key mission requirements is to retrieve cloud and precipitation properties, as well as vertical motion parameters, along the vertical cross- section defined by the profiling active sensors. Such retrievals are challenging to perform continuously in the entire spectrum of cloud and precipitation conditions due to the large natural microphysical and dynamical variability, the often-limited information content in the measurements, and the lack of proper characterization of measurement quality and uncertainty. Today, the acquisition of new remote and in-situ sensors by the ARM program creates opportunities to address the microphysical retrieval problem by exploiting new, more robust retrieval techniques and integrating various scattered advancements in both sensor techniques and retrieval algorithms. During this project, we constructed a robust Bayesian Markov chain Monte Carlo (MCMC) cloud property retrieval algorithm that includes a state of the art radar forward model. Our MCMC-based retrieval produces both the best estimate of height-resolved cloud and precipitation properties in the radar profile, as well as an estimate of the in-cloud vertical motion and turbulence. In addition, the MCMC algorithm automatically produces robust and flexible estimates of retrieval uncertainty. We tested the algorithm on several synthetic cloud profiles obtained from large eddy simulation (LES) models with bin-resolved microphysics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Percheron Power Archimedes Screw Turbine Analysis (Abstract)

The development of the Percheron Power (Percheron) composite Archimedes screw turbine (AST) is based upon employing newly developed theoretical mathematical models for optimizing the water volume carried through the AST for a given diameter, combined with minimizing efficiency losses due to bypass flow and friction. The key feasibility issues associated with producing the composite blades will be to understand the strength, fatigue, and wear performance of the AST blades and associated components, and how these factors change along the length of the turbine. To get to this understanding of material property requirements, Percheron needs free-surface computational fluid dynamics (CFD) models of the AST designs and to perform interactive modeling between the turbine blade optimization and component design based on finite element method stress analysis (FEA). The workscope and analyses requested by Percheron in the Small Business Voucher (SBV) program are well aligned with PNNL capability and recent work experience in performing CFD and FEA analysis for hydropower and marine energy turbines. The CFD analysis will provide estimates of power, efficiency, and surface forces on the blades. The forces on the blade will be transferred to the FEA analysis that will be used to evaluate the material stresses. The CFD and FEA analyses will be repeated for different AST designs provided to PNNL by Percheron. The work conducted in this SBV project will complement the existing Percheron FOA project by providing better defined parameters for design and material selection for the turbine unit prior to manufacture of initial test units.

42 ENGINEERING↗
DOE OSTI2015

On the cluster physics of Sunyaev–Zel’dovich and X-ray surveys. IV. Characterizing density and pressure clumping due to infalling substructures

Understanding the outskirts of galaxy clusters at the virial radius (R{sub 200}) and beyond is critical for an accurate determination of cluster masses, structure growth, and to ensure unbiased cosmological parameter estimates from cluster surveys. This problem has drawn renewed interest due to recent determinations of gas mass fractions beyond R{sub 200}, which appear to be considerably larger than the cosmic mean. Here, we use a large suite of cosmological hydrodynamical simulations to study the inhomogeneity of the intra-cluster medium and employ different variants of simulated physics, including radiative gas physics and thermal feedback by active galactic nuclei. We find that density and pressure clumping closely trace each other as a function of radius, but the bias on density remains on average <20% within R{sub 200}. At larger radii, clumping increases steeply due to the continuous infall of coherent structures that have not yet passed the accretion shock. Density and pressure clumping increase with cluster mass and redshift, which probes on average dynamically younger objects that are still in the process of assembling. The angular power spectra of gas density and pressure show that the clumping signal is dominated by large-scale cosmic filaments that reach from the cosmic web into the clusters, signaling the presence of gravitationally driven “super clumping.” While the prolateness of the gravitational halo potential implies an approximate radial correlation of these gaseous large-scale structures, gas density and pressure lose coherence on small scales across different radii due to dissipative gas physics. In contrast, the angular power spectrum of dark matter shows an almost uniform size distribution due to unimpeded subhalos. We provide a synopsis of the radial dependence of the clusters’ non-equilibrium measures (kinetic pressure support, ellipticity, and clumping) that all increase sharply beyond R{sub 200}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Collective Effect Studies of a Beta Beam Decay Ring

The Beta Beam, the concept of generating a pure and intense (anti) neutrino beam by letting accelerated radioactive ions beta decay in a storage ring called the Decay Ring (DR), is the basis of one of the proposed next generation neutrino oscillation facilities, necessary for a complete study of the neutrino oscillation parameter space. Sensitivities of the unknown neutrino oscillation parameters depend on the DR's ion intensity and of its duty factor (the filled ratio of the ring). Different methods, including analytical calculations and multiparticle tracking simulations, were used to estimate the DR's potential to contain enough ions in as small a part of the ring as needed for the sensitivities. Studies of transverse blow up of the beams due to resonance wake fields show that a very challenging upper limit of the transverse broadband impedance is required to avoid instabilities and beam loss.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Design and Simulation of a Novel Mechanical Power Take-Off for a Two-Body Wave Energy Point Absorber

In this paper, a two-body self-react wave energy converter with a novel mechanical Power Take-off (PTO) is introduced. The PTO rectifies the mechanical motion and regulates the flow with a mechanism called Mechanical Motion Rectifier (MMR), which converts the reciprocating motion of the ocean wave into unidirectional rotation of the generator. The overall system is analyzed in both time and frequency domain. In time domain, the piecewise non-linear dynamic model of the MMR PTO is derived, and parameters that could significantly influence the MMR property is extracted. By building the model into WEC-Sim, a time domain wave energy converter (WEC) simulation tool, to simulate and evaluate the performance of the PTO. In addition, the system is modelled as a two-body vibration system for frequency domain analysis in order to further investigate and optimize the proposed wave energy converter. The tunable parameters within the system, including the equivalent mass, the equivalent damping coefficient, and the PTO stiffness, are discussed based on the criteria of maximization of the total output power. To verify the theoretical analysis, a bench test prototype is developed and tested on a hydraulic test machine. The experimental results in line with the derived model and can be used for reasonable estimation on the output power of the proposed system in real ocean conditions.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Modeling perennial bioenergy crops in the E3SM land model (ELMv2)

Perennial bioenergy crops are increasingly important for the production of ethanol and other renewable fuels, and as part of an agricultural system that alters the climate through its impact on biogeophysical and biogeochemical properties of the terrestrial ecosystem. Few earth system models (ESMs) represent such crops, however. In this study, we expand the Energy Exascale Earth System Model (E3SM) Land Model (ELMv2) to include perennial bioenergy crops with a high potential for mitigating climate change. We focus on high-productivity miscanthus and switchgrass, estimating various parameters associated with their different growth stages and performing a global sensitivity analysis to identify and optimize these parameters. The sensitivity analysis identifies five parameters associated with phenology, carbon/nitrogen allocation, stomatal conductance, and maintenance respiration as the most sensitive parameters for carbon and energy fluxes. We calibrated and validated the model against observations and found that the model closely captures the observed seasonality and the magnitude of carbon fluxes. The validated model represents the latent heat flux fairly well, but sensible heat flux for miscanthus is not well captured. Finally, we validated the model against observed leaf area index (LAI) and harvest amount and found modeled LAI captured observed seasonality , although the model underestimates LAI and harvest amount. This work provides a foundation for future ESM analyses of the interactions between perennial bioenergy crops and carbon, water, and energy dynamics in the larger earth system, and sets the stage for studying the impact of future biofuel expansion on climate and terrestrial systems.

09 BIOMASS FUELS↗
DOE OSTI2015

Resolve survey photometry and volume-limited calibration of the photometric gas fractions technique

We present custom-processed ultraviolet, optical, and near-infrared photometry for the REsolved Spectroscopy of a Local VolumE (RESOLVE) survey, a volume-limited census of stellar, gas, and dynamical mass within two subvolumes of the nearby universe (RESOLVE-A and RESOLVE-B). RESOLVE is complete down to baryonic mass ∼10{sup 9.1−9.3} M{sub ⊙}, probing the upper end of the dwarf galaxy regime. In contrast to standard pipeline photometry (e.g., SDSS), our photometry uses optimal background subtraction, avoids suppressing color gradients, and employs multiple flux extrapolation routines to estimate systematic errors. With these improvements, we measure brighter magnitudes, larger radii, bluer colors, and a real increase in scatter around the red sequence. Combining stellar mass estimates based on our optimized photometry with the nearly complete H i mass census for RESOLVE-A, we create new z = 0 volume-limited calibrations of the photometric gas fractions (PGF) technique, which predicts gas-to-stellar mass ratios (G/S) from galaxy colors and optional additional parameters. We analyze G/S-color residuals versus potential third parameters, finding that axial ratio is the best independent and physically meaningful third parameter. We define a “modified color” from planar fits to G/S as a function of both color and axial ratio. In the complete galaxy population, upper limits on G/S bias linear and planar fits. We therefore model the entire PGF probability density field, enabling iterative statistical modeling of upper limits and prediction of full G/S probability distributions for individual galaxies. These distributions have two-component structure in the red color regime. Finally, we use the RESOLVE-B 21 cm census to test several PGF calibrations, finding that most systematically under- or overestimate gas masses, but the full probability density method performs well.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Velocity Dispersion, Size, Sérsic Index, and D{sub n}4000: The Scaling of Stellar Mass with Dynamical Mass for Quiescent Galaxies

We examine the relation between stellar mass, velocity dispersion, size, Sérsic index, and D{sub n}4000 for a volume-limited sample of ∼40,000 quiescent galaxies in the SDSS. At a fixed stellar mass, galaxies with higher D{sub n}4000 have larger velocity dispersions and smaller sizes. D{sub n}4000 is a proxy for stellar population age, thus these trends suggest that older galaxies typically have larger velocity dispersions and smaller sizes. We combine velocity dispersion and size into a dynamical mass estimator, σ{sup 2}R. At a fixed stellar mass, σ{sup 2}R depends on D{sub n}4000. The Sérsic index is also correlated with D{sub n}4000. The dependence of σ{sup 2}R and Sérsic index on D{sub n}4000 suggests that quiescent galaxies are not structurally homologous systems. We derive an empirical correction for non-homology which is consistent with the analytical correction derived from the virial theorem. After accounting for non-homologous galactic structure, we measure M{sub ∗}∝M{sub d}{sup 0.998±0.004}, where M {sub *} is the stellar mass and M {sub d} is the dynamical mass derived from the velocity dispersion and size; stellar mass is directly proportional to dynamical mass. Quiescent galaxies appear to be in approximate virial equilibrium, and deviations of the fundamental plane parameters from the expected virial relation may result from mass-to-light ratio variations, selection effects, and the non-homology of quiescent galaxies. We infer the redshift evolution of velocity dispersion and size for galaxies in our sample assuming purely passive evolution. The inferred evolution is inconsistent with direct measurements at higher redshifts. Thus quiescent galaxies do not passively evolve. Quiescent galaxies have properties that are consistent with standard galaxy formation in ΛCDM. They form at different epochs and evolve modestly, increasing their size, velocity dispersion, and Sérsic index after they cease star formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A Bayesian Approach to Regional Decadal Predictability: Sparse Parameter Estimation in High-Dimensional Linear Inverse Models of High-Latitude Sea Surface Temperature Variability

Stochastic reduced models are an important tool in climate systems whose many spatial and temporal scales cannot be fully discretized or underlying physics may not be fully accounted for. One form of reduced model, the linear inverse model (LIM), has been widely used for regional climate predictability studies—typically focusing more on tropical or midlatitude studies. However, most LIM fitting techniques rely on point estimation techniques deriving from fluctuation–dissipation theory. In this methodological study we explore the use of Bayesian inference techniques for LIM parameter estimation of sea surface temperature (SST), to quantify the skillful decadal predictability of Bayesian LIM models at high latitudes. We show that Bayesian methods, when compared to traditional point estimation methods for LIM-type models, provide better calibrated probabilistic skill, while simultaneously providing better point estimates due to the regularization effect of the prior distribution in high-dimensional problems. We compare the effect of several priors, as well as maximum likelihood estimates, on 1) estimating parameter values on a perfect model experiment and 2) producing calibrated 1-yr SST anomaly forecast distributions using a preindustrial control run of the Community Earth System Model (CESM). Finally, we employ a host of probabilistic skill metrics to determine the extent to which an LIM can forecast SST anomalies at high latitudes. We find that the choice of prior distribution has an appreciable impact on estimation outcomes, and priors that emphasize physically relevant properties enhance the model’s ability to capture variability of SST anomalies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Estimates of the wavenumber wavelet power spectrum of magnetic fluctuations during magnetic reconnection

Fluctuation analyses of experimental observations generally lack high temporal resolution and are in frequency-space f, contrary to theoretical efforts in wavenumber-space k. This is due to the inherent limits of the Fourier transform, though it is prominent due to the ease of diagnostic implementation. Advances in wavelet-based analysis have provided relief due to its temporal resolution, but in its common use, is still hard to compare to theoretical models. By using the two-point correlation technique in conjunction with large data sets, a wavelet power spectrum in wavenumber-space can be created. Dubbed the wavenumber wavelet power spectrum, this spectrum relates wavenumber to power in time. Further, this analysis technique more closely connects characterizations of experimentally observed fluctuations with other system parameters and theoretical predictions. In this article, we develop the wavenumber wavelet power spectrum using magnetic fluctuations caused by tearing instability driven magnetic reconnection in reproducible, high temperature laboratory plasmas. These dynamic magnetic fluctuations generated in reversed field pinch plasmas are broadband, ranging from the low frequency, 10's of kHz, up to the ion gyroradii frequencies, 100's of kHz. The dominant fluctuations have poloidal and toroidal mode numbers (m,n)=(1,6−10) and can grow to 2%–3% of the mean magnetic field. During these reconnection events, ions, and electrons are energized, magnetic fluctuation amplitudes increase, plasma flow is halted, and the toroidal magnetic flux increases, all on a semi-periodic basis. The newly developed spectrum provides better temporal resolution of spectrum characteristics to correlate with these particle energization phenomena.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗