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DOE OSTI2021

Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part I: The retrieval algorithms

Following the release of the version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version (version 4; V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter and ice or liquid water path estimates. Dedicated retrievals for water clouds were added in V4, taking advantage of the high sensitivity of the IIR retrieval technique to small particle sizes. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results will be presented in a companion (Part II) paper. The IIR Level 2 algorithm has been modified in the V4 data release to improve the accuracy of the retrievals in clouds of very small (close to 0) and very large (close to 1) effective emissivities. To reduce biases at very small emissivities that were made evident in V3, the radiative transfer model used to compute clear-sky brightness temperatures over oceans has been updated and tuned for the simulations using Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data to match IIR observations in clear-sky conditions. Furthermore, the clear-sky mask has been refined compared to V3 by taking advantage of additional information now available in the V4 CALIOP 5 km layer products used as an input to the IIR algorithm. After sea surface emissivity adjustments, observed and computed brightness temperatures differ by less than ±0.2 K at night for the three IIR channels centered at 08.65, 10.6, and 12.05 µm, and inter-channel biases are reduced from several tens of Kelvin in V3 to less than 0.1 K in V4. We have also improved retrievals in ice clouds having large emissivity by refining the determination of the radiative temperature needed for emissivity computation. The initial V3 estimate, namely the cloud centroid temperature derived from CALIOP, is corrected using a parameterized function of temperature difference between cloud base and top altitudes, cloud absorption optical depth, and CALIOP multiple scattering correction factor. As shown in Part II, this improvement reduces the low biases at large optical depths that were seen in V3 and increases the number of retrievals. As in V3, the IIR microphysical retrievals use the concept of microphysical indices applied to the pairs of IIR channels at 12.05 and 10.6 µm and at 12.05 and 08.65 µm. The V4 algorithm uses ice look-up tables (LUTs) built using two ice habit models from the recent “TAMUice2016” database, namely the single-hexagonal-column model and the eight-element column aggregate model, from which bulk properties are synthesized using a gamma size distribution. Four sets of effective diameters derived from a second approach are also reported in V4. Here, the LUTs are analytical functions relating microphysical index applied to IIR channels 12.05 and 10.6 µm and effective diameter as derived from in situ measurements at tropical and midlatitudes during the Tropical Composition, Cloud, and Climate Coupling (TC4) and Small Particles in Cirrus Science and Operations Plan (SPARTICUS) field experiments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling

Abstract. Organic matter (OM) composition plays a central role in microbial respiration of dissolved organic matter and subsequent biogeochemical reactions. Here, a direct connection of organic matter chemistry and thermodynamics to reactive transport simulators has been achieved through the newly developed Lambda-PFLOTRAN workflow tool that succinctly incorporates carbon chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate organic matter degradation and the resulting biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow, executed through a Jupyter notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow and transport code PFLOTRAN. The workflow consists of the following five steps: configuration, thermodynamic (lambda) analysis, sensitivity analysis, parameter estimation, and simulation output and visualization. Two test cases are provided to demonstrate the functionality of the Lambda-PFLOTRAN workflow. The first test case uses laboratory incubation data of temporal oxygen depletion to fit lambda parameters (i.e., maximum utilization rate and microbial carrying capacity). A slightly more complex second test case fits multiple lambda formulation and soil organic matter release parameters to temporal greenhouse gas generation measured during a soil incubation. Overall, the Lambda-PFLOTRAN workflow facilitates upscaling by using molecular-scale characterization to inform biogeochemical processes occurring at larger scales.

58 GEOSCIENCES↗

DOE OSTI2025

An efficient hybrid downscaling framework to estimate high-resolution river hydrodynamics

Flow depth and velocity are the most important hydrodynamic variables that govern various river functions, including water resources, navigation, sediment transport, and biogeochemical cycling. Existing high-resolution flow depth simulations rely on either computationally expensive river hydrodynamic models (RHMs) or data-driven models with formidable training costs, whereas data-driven modeling of flow velocity has rarely been explored. Here, using the hybrid Low-fidelity, Spatial analysis, and Gaussian process learning (LSG) model, we developed a downscaling approach to construct high-resolution flow depth and velocity from a two-dimensional (2-D) RHM simulation at coarse resolution. The LSG models were trained and tested in an urban watershed in Houston using two different hurricane-driven flood events. The high-resolution (as fine as 30 m resolution) and low-resolution (mostly 1000 m resolution) meshes include 664 724 and 14 536 grid cells, respectively. The results showed that through downscaling, the simulation errors were reduced to less than one-fourth and one-third of the errors of the low-resolution 2-D RHM for flow depth and velocity, respectively. Our analysis further revealed that the dominant uncertainty sources of the downscaled hydrodynamics are different, with flow velocity dominated by the dimensionality reduction error, which we reduced by using a regionalized training procedure. The downscaling approach achieves an 84-fold acceleration in computational time compared to the high-resolution 2-D RHM, making high-fidelity ensemble flood modeling feasible. More importantly, the developed method provides an opportunity to couple large-scale hydrodynamical processes with local physical, chemical, and biological processes in river models.

Tan, Zeli [Pacific Northwest National Laboratory (↗

DOE OSTI2017

Relaxation time estimation in surface NMR

NMR relaxation time estimation methods and corresponding apparatus generate two or more alternating current transmit pulses with arbitrary amplitudes, time delays, and relative phases; apply a surface NMR acquisition scheme in which initial preparatory pulses, the properties of which may be fixed across a set of multiple acquisition sequence, are transmitted at the start of each acquisition sequence and are followed by one or more depth sensitive pulses, the pulse moments of which are varied across the set of multiple acquisition sequences; and apply processing techniques in which recorded NMR response data are used to estimate NMR properties and the relaxation times T.sub.1 and T.sub.2* as a function of position as well as one-dimensional and two-dimension distributions of T.sub.1 versus T.sub.2* as a function of subsurface position.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

RISK-INFORMED EXTERNAL HAZARDS ANALYSIS BY EEVE TOOLKIT

Introducing risk-informed safety analyses for external events can bring sensible benefits to the nuclear power industry easing the regulatory burden introduced in the aftermath of the Fukushima accident. In the framework of the US-DOE Light-Water Reactor Sustainability program, Risk-Informed Margin Characterization project (LWRS-RISMC), research activities were conducted at INL for developing and applying a toolkit for performing risk-informed external hazards analysis. The “EEVE” (External EVEnts) toolkit, a chain of INL and state-of-the-art codes, was set-up and applied for simulating earthquake-induced transients with internal flooding in a PWR. This was done using methodology set-up for evaluating new data and determining critical areas that would benefit most from advanced analysis methods. The methodology is agnostic and it can be applied to other external hazards than just seismic and flooding (e.g., high winds, intense precipitation, etc.). The first step was the deterministic calculations for evaluating the propagation of a set of earthquakes and for determining the effects on a fire suppression system in an auxiliary building. These deterministic calculations were performed using the LS-DYNA and the OPENSEE structural mechanics codes. Probability failures and event trees of a generic 3-loops Westinghouse PWR were derived from a generic SAPHIRE model. Seismically induced Loss of Offsite Power, Station Blackout, and fire suppression piping failure events were considered. SAPHIRE code allowed a pre-screening of all possible branches of the event tree and a selection of those with the largest Core Damage Frequency increase for further analysis using dynamic PRA methods. INL's EMRALD code performed dynamic PRA calculations of the identified sequences, integrating risk analysis with on-line deterministic safety analysis results (seismically-induced internal flooding calculations by NEUTRINO code and system analysis by RELAP5-3D code). RELAP5-3D Best-Estimate calculations coupled with RAVEN statistical code were used for deriving limit surfaces as function of relevant transient parameters. This data was used by EMRALD for determining the final core status (core damage/core safe). Finally, the coupling of seismic, flooding, system thermal-hydraulic, uncertainty quantification and probabilistic risk analysis for an advanced risk-informed external hazards analysis was demonstrated. Results showed the sensible decrease in the level of conservatism achieved using the developed risk-informed methodology, which allowed also improving the evaluation of the failure modes and failure probabilities of different components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Analysis of Time of Arrival Measurement with Low-Gain-Avalanche-Diode

aAnalyzes of Time-of-Arrival measurements with Low-Gain-Avalanche-Diode sensors were carried out for the amplitude or time-over-threshold corrected Leading-Edge and for practical realizations of Constant-Fraction discrimination. The latter was based on subtraction of the scaled original signal from the delayed one, whereas the delay is an ideal delay element or RC-type low pass filter. Current waveforms from modeling of a sensor and varied conditioning of a signal in the front-end circuit, including varied transfer functions and their parameters, were considered for practically achievable signal-to-noise ratios. Estimation of the variations of the Time-of-Arrival measurements in practically built systems is targeted.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Computational optical physical unclonable function

A system or method for encryption of data includes a light source, a random optical element and a light detection element. The light source is arranged to transmit an input data signal to the random optical element. The light source is incident on the random optical element such that the input data signal is randomly scattered by the random optical element to generate an image at on the detector disposed at an output of the random optical element. The image received by the detector is applied to a compressive sensing algorithm to generate a transfer function. The transfer function defines a relationship between the input data signal and the image to enable estimation and reconstruction of the input data signal.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Computational optical physical unclonable function

Birch, Gabriel Carlisle↗

DOE OSTI2022

Dynamic, resilient virtual sensing system and shadow controller for cyber-attack neutralization

An industrial asset may have monitoring nodes (e.g., sensor or actuator nodes) that generate current monitoring node values. An abnormality detection and localization computer may receive the series of current monitoring node values and output an indication of at least one abnormal monitoring node that is currently being attacked or experiencing a fault. An actor-critic platform may tune a dynamic, resilient state estimator for a sensor node and output tuning parameters for a controller that improve operation of the industrial asset during the current attack or fault. The actor-critic platform may include, for example, a dynamic, resilient state estimator, an actor model, and a critic model. According to some embodiments, a value function of the critic model is updated for each action of the actor model and each action of the actor model is evaluated by the critic model to update a policy of the actor-critic platform.

Roychowdhury, Subhrajit↗

DOE OSTI2020

Development of an In-Situ Leaching Technology for Extracting Residual Uranium from Remediated Soil - 20099

Site-specific chemical solutions for extracting uranium were developed and evaluated for treating previously remediated soil at a former thorium mill tailings site, known as the Former Rare Earths Facility (REF), in West Chicago, Illinois. Prior remediation efforts had resulted in residual sand and gravel aggregate that met the soil cleanup standards. The target soil contains residual levels of uranium, which continues to leach into the site groundwater at levels exceeding groundwater protection standards (GWPS). A series of bench-scale tests were conducted to evaluate the efficacy and viability of in-situ leaching (ISL) technology to treat the target soil for the purposes of attaining uranium GWPS at the REF. Specific objectives of the bench-scale tests entailed identification and selection of optimal leaching, quantification of the extent and rate of uranium released as a function of chemical composition, chemical concentrations, chemical residence times, and obtaining critical data to estimate treatment costs. A combination of sodium bicarbonate and sodium carbonate reagent was the most effective leaching solution. In general, leaching solutions containing a higher concentration of sodium carbonate demonstrated superior uranium leaching capabilities. Removal of 50% of the uranium mass from the soil matrix was adequate for achieving compliance with the site-specific GWPS. After six to seven pore volume flushes (PVFs), the uranium leaching effectiveness of all leaching solutions was similar. The amount of initial uranium removed with each subsequent PVF was minimal, suggesting limited solubility of the remaining mass of uranium. The effects of leaching duration were significant and persisted through at least the first five consecutive PVFs. Leaching of uranium also resulted in leaching of several non-uranium constituents, many of which exceeded applicable National Pollutant Discharge Elimination System (NPDES) standards. Given historical operations and waste disposal practices at the site, leaching of non-uranium constituents was expected. Hydrochloric acid was used to stabilize treated soil. Savings of approximately $148 million in direct and indirect remediation costs are expected with an ISL alternative compared to the excavation and landfill disposal remediation option. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Scalable/Secure Cooperative Algorithms and Framework for Extremely-high Penetration Solar Integration (SolarExPert) (Final Technical Report)

This SolarExPert project has developed a Sustainable Grid Platform (SGP) with scalable architecture of distributed control and optimization. The SGP consists of the following major functions: 1) an advanced grid architecture with hierarchical and distributed communication and control, combined with the OpenFMB standard and implemented on the Multi-Agent OpenDSS (MA-OpenDSS) platform; 2) an online distributed stochastic optimal power flow; 3) an online distributed system state estimation algorithm; 4) the distributed Volt/VAR optimization and frequency control algorithms; 5) the distributed distribution system restoration strategy. The developed SGP together with advanced functions are tested in 1 million (1M)-node distribution system on the MA-OpenDSS platform. Furthermore, the models and algorithms are tested in 100,000-node system HiL simulation, and also in P-HiL implementation with 100 physical devices. The developed functions haven been validated and tested on the selected actual distribution feeder with the data collected from the field of Maui Meadows in Hawaii. The distributed PV hosting capacities with cooperative Volt/VAR and Volt/VAR/Watt control are estimated and compared to provide recommendations for customers and the utility company.

14 SOLAR ENERGY↗

DOE OSTI2018

Relationship Between Integrated Autocorrelation Parameters of Optical Spectra and Color Characteristics of Multicomponent Hydrocarbon Media

The relationship between the integrated autocorrelation parameters of optical spectra of multicomponent hydrocarbon solutions and their color characteristics is established. The obtained functions enable the color characteristics of solutions of nonideal multicomponent hydrocarbon media such as petroleum and high-boiling petroleum distillates to be estimated from their optical spectra.

02 PETROLEUM↗

DOE OSTI2016

Helium-like magnesium embedded in strongly coupled plasma

In recent days, with the advent of the x-ray free electron laser (FEL) with Linac coherent light source (LCLS) and the Orion laser, experimental studies on atomic systems within strongly coupled plasma environment with remarkable improvement in accuracy as compared to earlier experiments have become possible. In these kinds of experiments, hydrogen-like and helium-like spectral lines are used for determination of plasma parameters such as temperature, density. Accurate theoretical calculations are, therefore, necessary for such kind of studies within a dense plasma environment. In this work, ab initio calculations are carried out in the framework of the Rayleigh-Ritz variation principle to estimate the ground state energy of helium-like magnesium within strongly coupled plasma environment. Explicitly correlated wave functions in Hylleraas coordinates have been used to incorporate the effect of electron correlation. The ion-sphere model potential that confines the central positive ion in a finite domain filled with plasma electrons has been adopted to mimic the strongly coupled plasma environment. Thermodynamic pressure ’felt’ by the ion in the ground states due to the confinement inside the ion spheres is also estimated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

Efficient scatter distribution estimation and correction in CBCT using concurrent Monte Carlo fitting

Purpose: X-ray scatter is a significant impediment to image quality improvements in cone-beam CT (CBCT). The authors present and demonstrate a novel scatter correction algorithm using a scatter estimation method that simultaneously combines multiple Monte Carlo (MC) CBCT simulations through the use of a concurrently evaluated fitting function, referred to as concurrent MC fitting (CMCF). Methods: The CMCF method uses concurrently run MC CBCT scatter projection simulations that are a subset of the projection angles used in the projection set, P, to be corrected. The scattered photons reaching the detector in each MC simulation are simultaneously aggregated by an algorithm which computes the scatter detector response, S{sub MC}. S{sub MC} is fit to a function, S{sub F}, and if the fit of S{sub F} is within a specified goodness of fit (GOF), the simulations are terminated. The fit, S{sub F}, is then used to interpolate the scatter distribution over all pixel locations for every projection angle in the set P. The CMCF algorithm was tested using a frequency limited sum of sines and cosines as the fitting function on both simulated and measured data. The simulated data consisted of an anthropomorphic head and a pelvis phantom created from CT data, simulated with and without the use of a compensator. The measured data were a pelvis scan of a phantom and patient taken on an Elekta Synergy platform. The simulated data were used to evaluate various GOF metrics as well as determine a suitable fitness value. The simulated data were also used to quantitatively evaluate the image quality improvements provided by the CMCF method. A qualitative analysis was performed on the measured data by comparing the CMCF scatter corrected reconstruction to the original uncorrected and corrected by a constant scatter correction reconstruction, as well as a reconstruction created using a set of projections taken with a small cone angle. Results: Pearson’s correlation, r, proved to be a suitable GOF metric with strong correlation with the actual error of the scatter fit, S{sub F}. Fitting the scatter distribution to a limited sum of sine and cosine functions using a low-pass filtered fast Fourier transform provided a computationally efficient and accurate fit. The CMCF algorithm reduces the number of photon histories required by over four orders of magnitude. The simulated experiments showed that using a compensator reduced the computational time by a factor between 1.5 and 1.75. The scatter estimates for the simulated and measured data were computed between 35–93 s and 114–122 s, respectively, using 16 Intel Xeon cores (3.0 GHz). The CMCF scatter correction improved the contrast-to-noise ratio by 10%–50% and reduced the reconstruction error to under 3% for the simulated phantoms. Conclusions: The novel CMCF algorithm significantly reduces the computation time required to estimate the scatter distribution by reducing the statistical noise in the MC scatter estimate and limiting the number of projection angles that must be simulated. Using the scatter estimate provided by the CMCF algorithm to correct both simulated and real projection data showed improved reconstruction image quality.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

The magnitude-redshift relation in a realistic inhomogeneous universe

The light rays from a source are subject to a local inhomogeneous geometry generated by inhomogeneous matter distribution as well as the existence of collapsed objects. In this paper we investigate the effect of inhomogeneities and the existence of collapsed objects on the propagation of light rays and evaluate changes in the magnitude-redshift relation from the standard relationship found in a homogeneous FRW universe. We give the expression of the correlation function and the variance for the perturbation of apparent magnitude, and calculate it numerically by using the non-linear matter power spectrum. We use the lognormal probability distribution function for the density contrast and spherical collapse model to truncate the power spectrum in order to estimate the blocking effect by collapsed objects. We find that the uncertainties in Ω{sub m} is ∼ 0.02, and that of w is ∼ 0.04 . We also discuss a possible method to extract these effects from real data which contains intrinsic ambiguities associated with the absolute magnitude.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Renormalized theory of ion temperature gradient instability of the magnetic-field-aligned plasma shear flow with hot ions

The developed kinetic theory for the stability of a magnetic-field-aligned (parallel) shear flow with inhomogeneous ion temperature [Mikhailenko et al., Phys. Plasmas 21, 072117 (2014)] predicted that a kinetic instability arises from the coupled reinforcing action of the flow velocity shear and ion temperature gradient in the cases where comparable ion and electron temperatures exist. In the present paper, the nonlinear theory was developed for the instability caused by the combined effects of ion-temperature-gradient and shear-flow (ITG–SF). The level of the electrostatic turbulence is determined for the saturation state of the instability on the basis of the nonlinear dispersion equation, which accounts for a nonlinear scattering of ions by the developed turbulence in a sheared flow. The renormalized quasilinear equation for the ion distribution function, which accounts for the turbulent scattering of ions by ITG–SF driven turbulence, was derived and employed for the estimation of the turbulent ion viscosity, the anomalous ion thermal conductivity, and anomalous ion heating rate at the saturation state of the instability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

Improved battery parameter estimation method considering operating scenarios for HEV/EV applications

This study presents an improved battery parameter estimation method based on typical operating scenarios in hybrid electric vehicles and pure electric vehicles. Compared with the conventional estimation methods, the proposed method takes both the constant-current charging and the dynamic driving scenarios into account, and two separate sets of model parameters are estimated through different parts of the pulse-rest test. The model parameters for the constant-charging scenario are estimated from the data in the pulse-charging periods, while the model parameters for the dynamic driving scenario are estimated from the data in the rest periods, and the length of the fitted dataset is determined by the spectrum analysis of the load current. In addition, the unsaturated phenomenon caused by the long-term resistor-capacitor (RC) network is analyzed, and the initial voltage expressions of the RC networks in the fitting functions are improved to ensure a higher model fidelity. Simulation and experiment results validated the feasibility of the developed estimation method.

25 ENERGY STORAGE↗

DOE OSTI2015

THE NEAR-ULTRAVIOLET LUMINOSITY FUNCTION OF YOUNG, EARLY M-TYPE DWARF STARS

Planets orbiting within the close-in habitable zones of M dwarf stars will be exposed to elevated high-energy radiation driven by strong magnetohydrodynamic dynamos during stellar youth. Near-ultraviolet (NUV) irradiation can erode and alter the chemistry of planetary atmospheres, and a quantitative description of the evolution of NUV emission from M dwarfs is needed when modeling these effects. We investigated the NUV luminosity evolution of early M-type dwarfs by cross-correlating the Lépine and Gaidos catalog of bright M dwarfs with the Galaxy Evolution Explorer (GALEX) catalog of NUV (1771-2831 Å) sources. Of the 4805 sources with GALEX counterparts, 797 have NUV emission significantly (>2.5σ) in excess of an empirical basal level. We inspected these candidate active stars using visible-wavelength spectra, high-resolution adaptive optics imaging, time-series photometry, and literature searches to identify cases where the elevated NUV emission is due to unresolved background sources or stellar companions; we estimated the overall occurrence of these ''false positives'' (FPs) as ∼16%. We constructed an NUV luminosity function that accounted for FPs, detection biases of the source catalogs, and GALEX upper limits. We found the NUV luminosity function to be inconsistent with predictions from a constant star-formation rate and simplified age-activity relation defined by a two-parameter power law.

79 ASTRONOMY AND ASTROPHYSICS↗