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Results for “sample complexity analysis”

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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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Fantastic Fits with fantasy of Active Galactic Nuclei Spectra: Exploring the Fe II Emission near the Hα Line

In this study, a refined approach for multicomponent fitting of active galactic nuclei (AGNs) spectra is presented utilizing the newly developed Python code Fully Automated pythoN Tool for AGN Spectra analYsis (fantasy). AGN spectra are modeled by simultaneously considering the underlying broken power-law continuum, predefined emission line lists, and an Fe II model, which is here extended to cover the wavelength range 3700–11000 Å. The Fe II model, founded solely on atomic data, effectively describes the extensive emission of the complex iron ion in the vicinity of the Hγ and Hβ lines, as well as near the Hα line, which was previously rarely studied. The proposed spectral fitting approach is tested on a sample of high-quality AGN spectra from the Sloan Digital Sky Survey Data Release 17. The results indicate that when Fe II emission is present near Hβ, it is also detected redward from Hα, potentially contaminating the broad Hα line wings and thus affecting the measurements of its flux and width. The production of Fe II emission is found to be strongly correlated with Eddington luminosity and appears to be controlled by a similar mechanism as the hydrogen Balmer lines. The study highlights the benefits of fitting type 1 AGN spectra with the fantasy code, pointing that it may be used as a robust tool for analyzing a large number of AGN spectra in the coming spectral surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Performance evaluation of the ORNL multi-elemental XRF analysis algorithms

Hybrid K-Edge Densitometer (HKED) systems integrate both K-Edge Densitometry (KED) and X-Ray Fluorescence (XRF) analyses to provide accurate rapid, assay results of the uranium and plutonium content of dissolver solution samples from nuclear fuel reprocessing facilities. Introduced for international safeguards applications in the late 1980s, the XRF component of the hybrid analyses is limited to quantification of U and Pu over a narrow range of U:Pu concentration ratios in the vicinity of ≈100. The analysis was further limited regarding the presence of minor actinide components where only a single minor actinide (typically Am) is included in the analysis and then only treated as an interference. The evolving nuclear fuel cycle has created the need to assay more complex dissolver solutions where uranium may no longer be the dominant actinide in the solution and the concentrations of the so called minor actinides (e.g., Th, Np, Am, and Cm) are sufficiently high that they can no longer be treated as impurities and ignored. Extension of the traditional HKED Region of Interest (ROI) based analysis to include these additional actinides is not possible due to the increased complexity of the XRF spectra. Oak Ridge National Laboratory (ORNL) has developed a spectral fitting approach to the HKED XRF measurement with an enhanced algorithm set to accommodate these complex XRF spectra. This report provides a summary of the spectral fitting methodology and examines the performance of these algorithms using data obtained from the ORNL HKED system, as well as data provided by the International Atomic Energy Agency (IAEA) on actual dissolver solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

ℤ2 × ℤ2 Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks

This paper presents a comparative analysis of the performance of Equivariant Quantum Neural Networks (EQNNs) and Quantum Neural Networks (QNNs), juxtaposed against their classical counterparts: Equivariant Neural Networks (ENNs) and Deep Neural Networks (DNNs). We evaluate the performance of each network with three two-dimensional toy examples for a binary classification task, focusing on model complexity (measured by the number of parameters) and the size of the training dataset. Our results show that the Z2×Z2 EQNN and the QNN provide superior performance for smaller parameter sets and modest training data samples.

Dong, Zhongtian (ORCID:0000000210003454)↗
DOE OSTI2017

DIFFERENT ORIGINS OR DIFFERENT EVOLUTIONS? DECODING THE SPECTRAL DIVERSITY AMONG C-TYPE ASTEROIDS

Anhydrous pyroxene-rich interplanetary dust particles (IDPs) have been proposed as surface analogs for about two-thirds of all C-complex asteroids. However, this suggestion appears to be inconsistent with the presence of hydrated silicates on the surfaces of some of these asteroids, including Ceres. Here, we report the presence of enstatite (pyroxene) on the surface of two C-type asteroids (Ceres and Eugenia) based on their spectral properties in the mid-infrared range. The presence of this component is particularly unexpected in the case of Ceres, because most thermal evolution models predict a surface consisting of hydrated compounds only. The most plausible scenario is that Ceres’ surface has been partially contaminated by exogenous enstatite-rich material, possibly coming from the Beagle asteroid family. This scenario questions a similar origin for Ceres and the remaining C-types, and it possibly supports recent results obtained by the Dawn mission (NASA) that Ceres may have formed in the very outer solar system. Concerning the smaller D ∼ 200 km C-types such as Eugenia, both their derived surface composition (enstatite and amorphous silicates) and low density (<1.5 g cm{sup −3}) suggest that these bodies accreted from the same building blocks, namely chondritic porous, pyroxene-rich IDPs and volatiles (mostly water ice), and that a significant volume fraction of these bodies has remained unaffected by hydrothermal activity likely implying a late accretion. In addition, their current heliocentric distance may best explain the presence or absence of water ice at their surfaces. Finally, we raise the possibility that CI chondrites, Tagish-Lake-like material, or hydrated IDPs may be representative samples of the cores of these bodies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 1. Characterizing Thermal–Hydrological–Mechanical Processes

Abstract Bentonite clay is widely used in engineered barrier systems for the permanent disposal of high‐level radioactive waste due to its low permeability, high swelling capacity, and thermal stability. However, the complex thermal‐hydrological‐mechanical (THM) processes induced by heating from decaying radioactive waste and hydration from surrounding rock can lead to heterogeneous changes that are difficult to measure and predict. This study develops an Electrical Resistivity Tomography (ERT)‐based framework for monitoring THM processes, progressing from sample‐scale to bench‐scale tests, to inform field‐scale applications. Sample‐scale tests analyzed small bentonite samples under controlled variations in water content, temperature, and porosity to establish fundamental resistivity relationships. Bench‐scale tests involved larger bentonite columns subjected to heating (up to 200°C) and hydration under controlled pressure, simulating repository conditions. ERT measurements, complemented by X‐ray CT imaging, temperature monitoring, and tracing sensors, revealed coupled THM processes, such as hydration‐induced compression, swelling, and thermal gradients, leading to complex resistivity patterns. The results demonstrate the potential of ERT for capturing THM‐induced resistivity changes, though challenges remain in upscaling and quantitative analysis. This study evaluates laboratory test capabilities and proposes future improvements for understanding THM‐induced resistivity responses. A conceptual framework for ERT implementation in field‐scale monitoring is presented, synthesizing findings from both scales and exploring how ERT data can inform long‐term modeling and reduce prediction uncertainties. Overall, this ERT‐based framework offers a robust method for monitoring bentonite buffers, aiding in early issue detection and supporting the safe long‐term disposal of radioactive waste in geological repositories, while highlighting the need for future development. Plain Language Summary Bentonite clay is crucial in engineered barrier systems (EBS) for containing high‐level radioactive waste due to its ability to absorb water, swell, seal and remain stable under high temperatures. When bentonite absorbs water and heats up from radioactive decay, it experiences complex changes in its physical and mechanical properties. Understanding these changes is important for ensuring the long‐term safety and effectiveness of EBS. This study used Electrical Resistivity Tomography (ERT), a non‐invasive method that measures electrical conductivity to monitor these changes during laboratory experiments. The ERT data revealed significant variations in resistivity corresponding to changes in water content, temperature, and density, providing detailed spatial and temporal insights into the behavior of bentonite. These findings enhance our ability to predict the long‐term performance of bentonite barriers, ensuring the safe containment of radioactive waste. By improving our understanding of bentonite's behavior, this research supports the development of more reliable and effective barrier systems for radioactive waste disposal, protecting the environment and public health. Key Points ERT monitoring was employed to capture resistivity changes in bentonite during controlled heating and hydration experiments, providing insights into THM processes ERT data reveal significant resistivity changes correlated with water content, temperature, and mechanical effects, enhancing the understanding of THM dynamics in bentonite This study explores the potential of the framework for application in field‐scale EBS monitoring, emphasizing the need for integrating additional geophysical methods for comprehensive subsurface imaging

Chen, Hang↗
DOE OSTI2024

Realization of two-sublattice exchange physics in the triangular lattice compound Ba 3 Er(BO 3 ) 3

Geometric frustration commonly occurs in materials where magnetic rare-earth ions are arranged on a two-dimensional triangular lattice. These compounds have been gaining significant attention lately, as they hold the promise of revealing unique quantum states of matter. However, little attention has been devoted to cases where spin-$\frac{1}{2}$ rare-earth ions are substituted with ions exhibiting higher spin multiplicities. Here, we successfully synthesize high-quality single crystal samples of Ba 3 Er(BO 3 ) 3 , which is part of the family of triangular lattice compounds. In our experiments, conducted at extremely low temperatures (around 100 millikelvin), we observe two sublattice exchange interactions in Ba 3 Er(BO 3 ) 3 , resulting in the hexagonal lattice spins exhibiting a mixture of ferromagnetic and antiferromagnetic tendencies. Our theoretical analysis suggest that this behavior may be attributed to the distinct positions of magnetic ions within the crystal lattice. However, the presence of quantum effects adds an extra layer of complexity to our findings, calling for further exploration.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The H I absorption zoo: JVLA extension to z ~ 0.4

Here, we present an H I 21 cm absorption study of a sample of 26 radio-loud active galactic nuclei (AGN) at 0.25 < z < 0.4 carried out with the Karl G. Jansky Very Large Array. Our aim was to study the rate of incidence of H I in different classes of radio AGN, the morphology and kinematics of the detected H I, and the nature of the interaction between the H I and the radio source at these redshifts. Our sample consists of 14 sources with sizes of up to tens of kpc and 12 compact sources (< a few kpc) in the radio-power range 10 25.7 W Hz –1 –10 26.5 W Hz –1 . We detect H I in five sources, corresponding to a detection rate of ~19%. Within the error bars, this agrees with the detection rate found at lower redshifts. We find that the rest-frame UV luminosities of most of the sources in the sample, including all the detections, are below the proposed threshold above which the H I is supposed to have been ionised. An analysis of the optical emission-line spectra of the sources shows that despite their high radio powers, about one-third of the sample, including two detections, are low-ionisation sources. The radio continuum emission from the sources detected in H I is unresolved at ~5 to 10 kpc scales in our observations, but shows extended structure on parsec scales. We analysed the H I 21 cm absorption spectra of the detections to understand the morphology and kinematics of H I. The absorption profiles are mostly complex with widths between the nulls ranging from ~60 km s –1 to 700 km s –1 . These detections also exhibit remarkably high H I column densities in the range ~10 21 cm –2 –10 22 cm –2 for T spin = 100 K and unit covering factor. Our modelling of the H I 21 cm absorption profiles suggests that in two sources the gas appears to be disturbed, and in three cases, including one with disturbed H I, the majority of the absorption is consistent with it arising from an H I disc. Despite the high radio power of our sources, we do not detect fast outflows. However, the optical emission lines in these detections show the presence of significantly disturbed gas in the nuclear regions in the form of very wide and highly blueshifted emission-line components. Since some of our detections are also low-ionisation AGN, it is quite possible that this disturbance is caused by the radio jets. Overall, our findings point towards a continuation of the low-z trends in the H I detection rate and the incidence of H I in radio AGN up to z ~ 0.4.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

New Oxide Materials for an Ultra High Temperature Environment

In this project, a new oxide material, Hf 6 Ta 2 O 17 has been successfully synthesized by the controlled oxidization of Hf-Ta alloys. This oxide exhibits good oxidation resistance, high temperature phase stability up to more than 2000°C, low thermal conductivity and thus could serve as a component or a coating material in an ultrahigh temperature environment. We have examined the microstructure evolution and phase formation sequence during the oxidation exposure of Hf-Ta alloys at 1500°C and identified that the oxidation of a Hf-26.7atomic %Ta alloy leads to the formation of a single phase adherent Hf 6 Ta 2 O 17 with a complex atomic structure i.e. superstructure. The overall reactive diffusion pathway is consistent with the calculated Hf-Ta-O ternary phase diagram. Besides the synthesis of Hf 6 Ta 2 O 17 superstructure by oxidizing Hf-Ta alloys, we have also developed a synthesis method based upon the reactive sintering of the correct ratios of mixed powders of HfO 2 and Ta 2 O 5 and verified the low thermal conductivity of Hf 6 Ta 2 O 17 superstructure on these samples. We have completed a preliminary analysis of the oxidation kinetics for Hf 6 Ta 2 O 17 , which shows an initial parabolic oxidation kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Towards resolving protein structures at the atomic scale using atom probe tomography

In the field of Structural Biology, Atom Probe Tomography (APT) is in the nascent stages of development wherein coarse-grained visuals of proteins have been captured. The characterization of organic samples or biomolecules through the technique is currently limited to the detection of a few dominant signatures. The problem of indecipherable characterization can inherently be traced back to multiple forms of technique-specific responses to organic samples and consequent triggers leading to organic-sample and sample-medium interactions. While it is possible for captured manifestations of protein reconstructions to seemingly appear intact from a basic visual purview, the parameter-protein associative responses throughout the structure as a direct consequence of the inherent workings of the technique (until harmonized with organic sample complexity and behavior) and field evaporation-based factors make non-aberrative atomic associations infeasible. The work focused on identifying and theorizing the (above stated and other) fundamental mechanisms that stronghold the study of intricate atomic to higher order associations in proteins through APT. Attempts at structure elucidation of the cryogenic sample under study, through indirect associations (and methods) based on other imaging techniques, further revealed the distinct and highly distortive nature at the atomic scale deterring structural tunability and thus characterization of APT based cryogenic samples under analysis. As a direct counter to the atomic scale characterization problem, by taking the experiment-specific uncertainties, and probable APT-centric organic sample-based variabilities into account, a basic result is extracted and presented. Through mass-spectrometric and computational analysis, specific individual amino acids (Sulfur-containing protein-bound amino acids) in proteins and aspects of protein structure (probable backbone fragments, partial sequence - partial backbone portions) have been identified and characterized. Under analysis considerations, a few of the simplest known and easily inferable segments that favor structural deteriorations in the reconstructions are stated. Additionally, to overcome technique-specific deterrents to the characterization of biomolecules in cryogenic sample medium, the development of a protein-labeling strategy tailored to APT is suggested.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Respirator Cartridge Performance on Mixed Vapors from Hanford Tank Headspaces and Exhausters - 20427

Between 2016 and 2018, the Hanford Tank Operations Contractor - Washington River Protection Solutions (WRPS) - conducted a series of tests of air-purifying respirator (APR) chemical cartridges commonly used at Hanford tank farms to determine the period of time for which the cartridges would provide adequate performance when used in APRs and powered-air-purifying respirators (PAPRs) to protect workers when exposed to a mixture of vapors exiting tank headspaces. Although cartridge manufacturers provide service life estimating tools for individual chemical compounds, the projected performance of these cartridges on complex vapor mixtures is not available, and the adequacy of APRs for tank farm applications represents an important workforce concern. The Occupational Safety and Health Administration identifies cartridge testing as a valid approach for establishing cartridge service life. The primary function of the WRPS Cartridge Test Program was to obtain objective data to determine service lives for the APR and PAPR cartridges used at Hanford tank farms. WRPS contracted with Pacific Northwest National Laboratory to analyze the test data and offer an independent analysis of and recommendations based on respirator cartridge performance. A total of 28 APR and 10 PAPR cartridge tests were conducted between 2016 and 2018 on 12 different tank headspaces and tank farm exhauster slipstreams. Two APR cartridges from SCOTT (now 3M) and two PAPR cartridges from MSA Safety, Inc. and 3M were evaluated using a cartridge testing system specifically designed to measure and monitor test conditions and sample cartridge inlet and outlet vapor streams for important chemical compounds. Testing focused on analysis of approximately 61 tank vapor chemicals of potential concern (COPCs) that have been previously detected in tank vapors at levels above 10% of their occupational exposure limits (OELs). Each test was conducted over 16 hours of run time. Evidence of chemical breakthrough was assessed by comparing inlet and outlet COPC concentrations over the duration of each test. The breakthrough threshold was normally defined as exceeding 10% of the compounds OEL at the cartridge outlet. Ammonia breakthrough was observed in a majority of the cartridge tests and occurred earlier than breakthrough of any other chemical compound. Several other COPCs did exhibit breakthrough behavior, including mercury, 1,3-butadiene, furan, 2,5 dihydrofuran, and N-nitrosodimethylamine (NDMA), but only in a very limited number of cartridge tests and only after ammonia breakthrough had occurred. In addition, tests results suggest that breakthrough of some of these COPCs may have been affected by competition with and breakthrough of other non-COPC organics, such as ethanol and acetone, with substantially lower toxicological hazard. Comparison of cartridge manufacturers' service life estimates with the experimentally derived breakthrough times indicates that manufacturers' estimates are generally conservative, even in the presence of the complex mixed vapor streams experienced in these tests. With consideration of appropriate safety margins, these results provide valuable insights on cartridge performance to inform industrial hygiene professionals in establishing appropriate cartridge change-out schedules for APR and PAPR use in the Hanford tank farms. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Experimental Investigation of Gas/Slag/Matte/Tridymite Equilibria in the Cu-Fe-O-S-Si System in Controlled Atmospheres: Development of Technique

The majority of primary pyrometallurgical copper making processes involve the formation of two immiscible liquid phases, i.e., matte product and the slag phase. There are significant gaps and discrepancies in the phase equilibria data of the slag and the matte systems due to issues and difficulties in performing the experiments and phase analysis. The present study aims to develop an improved experimental methodology for accurate characterisation of gas/slag/matte/tridymite equilibria in the Cu-Fe-O-S-Si system under controlled atmospheres. The experiments involve high-temperature equilibration of synthetic mixtures on silica substrates in CO/CO{sub 2}/SO{sub 2}/Ar atmospheres, rapid quenching of samples into water, and direct composition measurement of the equilibrium phases using Electron Probe X-ray Microanalysis (EPMA). A four-point-test procedure was applied to ensure the achievement of equilibrium, which included the following: (i) investigation of equilibration as a function of time, (ii) assessment of phase homogeneity, (iii) confirmation of equilibrium by approaching from different starting conditions, and (iv) systematic analysis of the reactions specific to the system. An iterative improved experimental methodology was developed using this four-point-test approach to characterize the complex multi-component, multi-phase equilibria with high accuracy and precision. The present study is a part of a broader overall research program on the characterisation of the multi-component (Cu-Fe-O-S-Si-Al-Ca-Mg), multi-phase (gas/slag/matte/metal/solids) systems with minor elements (Pb, Zn, As, Bi, Sn, Sb, Ag, and Au).

36 MATERIALS SCIENCE↗
DOE OSTI2025

A structured framework for predicting sustainable aviation fuel properties using liquid-phase FTIR and machine learning

Sustainable aviation fuels have the potential to improve efficiency, reduce emissions, and enhance energy security. To help identify viable sustainable aviation fuels and accelerate research, machine learning models have been developed to predict relevant physicochemical properties. However, many models have limited applicability, leverage data from complex analytical techniques with confined spectral ranges, or use feature decomposition methods that offer limited interpretability. Using liquid-phase Fourier Transform Infrared (FTIR) spectra, this study presents a structured method for creating accurate and interpretable property prediction models for neat molecules, aviation fuels, and blends. Liquid FTIR spectra can be collected quickly and consistently, offering high reliability, sensitivity, and component specificity using less than 2 ml of sample. The method first decomposes FTIR spectra into fundamental building blocks using non-negative matrix factorization (NMF) to enable scientific analysis of FTIR spectra attributes and fuel properties. The NMF features are then used to create five ensemble models for predicting final boiling point, flash point, freezing point, density at 15°C, and kinematic viscosity at -20°C. All models were trained using experimental property data from neat molecules, aviation fuels, and blends. The models accurately predict key properties across a broad range of neat molecules and representative fuels and blends, while enabling interpretation of relationships between compositional elements, such as functional groups or chemical classes, and their resulting properties. This demonstrates strong potential to support sustainable aviation fuel research and development. The models and data are available on an interactive web tool.

Fourier transform infrared spectroscopy↗
DOE OSTI2016

Full data acquisition in Kelvin Probe Force Microscopy: Mapping dynamic electric phenomena in real space

Kelvin probe force microscopy (KPFM) has provided deep insights into the role local electronic, ionic and electrochemical processes play on the global functionality of materials and devices, even down to the atomic scale. Conventional KPFM utilizes heterodyne detection and bias feedback to measure the contact potential difference (CPD) between tip and sample. This measurement paradigm, however, permits only partial recovery of the information encoded in bias- and time-dependent electrostatic interactions between the tip and sample and effectively down-samples the cantilever response to a single measurement of CPD per pixel. This level of detail is insufficient for electroactive materials, devices, or solid-liquid interfaces, where non-linear dielectrics are present or spurious electrostatic events are possible. Here, we simulate and experimentally validate a novel approach for spatially resolved KPFM capable of a full information transfer of the dynamic electric processes occurring between tip and sample. General acquisition mode, or G-Mode, adopts a big data approach utilising high speed detection, compression, and storage of the raw cantilever deflection signal in its entirety at high sampling rates (> 4 MHz), providing a permanent record of the tip trajectory. We develop a range of methodologies for analysing the resultant large multidimensional datasets involving classical, physics-based and information-based approaches. Physics-based analysis of G-Mode KPFM data recovers the parabolic bias dependence of the electrostatic force for each cycle of the excitation voltage, leading to a multidimensional dataset containing spatial and temporal dependence of the CPD and capacitance channels. We use multivariate statistical methods to reduce data volume and separate the complex multidimensional data sets into statistically significant components that can then be mapped onto separate physical mechanisms. Overall, G-Mode KPFM offers a new paradigm to study dynamic electric phenomena in electroactive interfaces as well as offer a promising approach to extend KPFM to solid-liquid interfaces.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Cluster decomposition of full configuration interaction wave functions: A tool for chemical interpretation of systems with strong correlation

Approximate full configuration interaction (FCI) calculations have recently become tractable for systems of unforeseen size, thanks to stochastic and adaptive approximations to the exponentially scaling FCI problem. The result of an FCI calculation is a weighted set of electronic configurations, which can also be expressed in terms of excitations from a reference configuration. The excitation amplitudes contain information on the complexity of the electronic wave function, but this information is contaminated by contributions from disconnected excitations, i.e., those excitations that are just products of independent lower-level excitations. The unwanted contributions can be removed via a cluster decomposition procedure, making it possible to examine the importance of connected excitations in complicated multireference molecules which are outside the reach of conventional algorithms. We present an implementation of the cluster decomposition analysis and apply it to both true FCI wave functions, as well as wave functions generated from the adaptive sampling CI algorithm. Furthermore, the cluster decomposition is useful for interpreting calculations in chemical studies, as a diagnostic for the convergence of various excitation manifolds, as well as as a guidepost for polynomially scaling electronic structure models. Applications are presented for (i) the double dissociation of water, (ii) the carbon dimer, (iii) the π space of polyacenes, and (iv) the chromium dimer. While the cluster amplitudes exhibit rapid decay with an increasing rank for the first three systems, even connected octuple excitations still appear important in Cr 2 , suggesting that spin-restricted single-reference coupled-cluster approaches may not be tractable for some problems in transition metal chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Dark Energy Survey year 6 results: Magnification modeling and its impact on galaxy clustering and galaxy-galaxy lensing cosmology

Gravitational lensing magnification alters the observed spatial distribution of galaxies and must be accounted for to prevent biases in cosmological probes of the large-scale structure. We investigate its effects on the Dark Energy Survey Year 6 galaxy clustering and galaxy-galaxy lensing analyses using the fiducial lens (position tracer) sample M ag L im++. Magnification bias is parameterized by a coefficient that describes the response of the number of selected objects per unlensed area element to a change in the lensing convergence. We quantify this coefficient using the BALROG synthetic source injection catalog to account for the complexity of the selection function, and compare these results with simplified estimates. The resulting values of the magnification coefficients for each redshift bin are [3.16 ± 0.08, 2.76 ± 0.21, 4.09 ± 0.15, 4.42 ± 0.16, 4.90 ± 0.29, 4.83 ± 0.25]. Relative to Year 3, this analysis provides more precise and accurate magnification bias estimates through a larger BALROG area and reweighting to better match the data properties. Here, the cosmological results are robust when tested against various magnification parameter prior choices and also when adding cross-clustering between lens redshift bins. Neglecting magnification, however, introduces significant systematic shifts: relative to the fiducial analysis with Gaussian priors centered on the BALROG -derived estimates, we observe shifts of 1.37σ in S 8 and -0.84σ in Ω m (with cosmic shear included: -0.61σ in S 8 and -0.71σ in Ω m ), in agreement with findings from simulated data, demonstrating that magnification must be modeled to avoid biases. Freeing the magnification bias in lens bin 2 leads to unphysical negative values, further justifying its exclusion from the fiducial Year 6 analysis.

Cosmological parameters↗
DOE OSTI2018

Well Design, Operation and Maintenance and Proactive Rehabilitation to Optimize Remediation Well Performance - 18605

Optimizing performance of extraction, injection and monitoring wells, which are integral components of groundwater remediation systems, result in lower life cycle costs and a higher probability of meeting project objectives. These wells provide the means to extract contaminated groundwater, inject reagents, treated water and clean water to create groundwater reaction/flushing zones, and to provide groundwater level, contaminant concentration and geochemical data. Initial costs associated with well installation and associated pipelines and treatment systems are significant project expenditures related to site remediation. However, the life cycle costs for wells are dominated by the long-term operation and maintenance (O and M) expenditures. Remediation wells are particularly susceptible to various types of fouling that impact well performance and, therefore, drive up operating costs. Simply defined, fouling is the result of any biological, geochemical or physical process that negatively impacts the intended performance of a remediation well. Fouling decreases well performance by effectively reducing hydraulic communication between the well and the surrounding formation. Oftentimes this occurs via clogging screens and/or gravel pack/formation pore space by bacterial or chemical byproducts and gases, which can lead to corrosion of metal components and spreading fouling deposits to pipelines and surface treatment systems. Ultimately, this results in reduced hydraulic performance in extraction and injection wells and result in erroneous water level and chemical parameter concentration measurements in monitoring wells. Remediation well fouling cannot be eliminated, and natural fouling processes are exacerbated by the installation and operation of remedial systems. Steps required to extend the life of remediation wells and to lower life cycle costs are discussed in this paper in order to establish the required approach to effective system management. These optimization approaches have been developed through years of operation and maintenance of complex large-scale plume remediation systems utilizing a variety of subsurface in-situ and ex-situ technologies. Remediation well performance can be improved by: - careful site characterization, - appropriate well design, - proper well installation and development, - thoughtful and adaptable operation and maintenance, - well performance maintenance tracking and, - proactive well rehabilitation. Clear understanding of the site hydro-stratigraphy and geochemical settings places constraints on the compatibility of well materials and the configurations of well screens. Proper well design, including collection and analysis (sieve/grain-size) of screen zone formation samples, assures that wells can be optimally installed, developed and redeveloped during well rehabilitation. Design considerations should include proper sizing of filter packs and well screens, casing/screen diameter, well material selection/compatibility, expected life/use, and well head configuration to allow for future access. Applying appropriate and effective well installation and development methods are of paramount importance and rely on a good understanding of site characteristics (e.g., geologic setting) as well as local drilling company expertise and experience. Different approaches to operation and maintenance can greatly affect the degree of fouling, these include limiting reagent concentrations, maintaining submerged well screens and filtering injection water to prevent the introduction of fouling enhancing constituents. Tracking well performance by monitoring changes in system operation and metrics such as specific capacity or injectivity for extraction and injection wells, respectively, or turbidity and chemical analyses for monitoring wells is key to identifying well maintenance issues early when well rehabilitation can be most effective. Proactive well rehabilitation can include mechanical brushing, surging and jetting, chemical treatment or other specialized approaches; however, the approach needs to be based on a site-specific understanding of the predominant fouling mechanisms. Collection and analyses of fouling deposits can provide guidance for selection of rehabilitation methods and chemicals that will be most effective. Application of these approaches have led to extended operational life for reagent injection wells, which can foul quickly, from months to years. Additionally, proper maintenance will often lead to increased and extended productivity of the well. For extraction wells, this translates to a higher sustainable yield, which means shorter cleanup times. Similarly, for injection wells, proper maintenance allows for the introduction of a greater volume of reagents over a shorter period, thus, shorter cleanup times that reduce overall project costs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

High-throughput quantitative analysis of phytohormones in sorghum leaf and root tissue by ultra-performance liquid chromatography-mass spectrometry

Plant development, growth, and adaptation to stress are regulated by phytohormones, which can influence physiology even at low concentrations. Phytohormones are chemically grouped according to both structure and function as auxins, cytokinins, abscisic acid, jasmonates, salicylates, gibberellins, and brassinosteroids, among others. This chemical diversity and requirement for highly sensitive detection in complex matrices create unique challenges for comprehensive phytohormone analysis. Here, we present a robust and efficient quantitative UPLC-MS/MS assay for 17 phytohormones, including jasmonates, salicylates, abscisic acid, gibberellins, cytokinins, and auxins. Using this assay, 12 phytohormones were detected and quantified in sorghum plant tissue without the need for solid phase extraction (SPE) or liquid-liquid extraction. Variation of phytohormone profiles was explored in both root and leaf tissues between three genotypes, harvested at two different developmental time points. The results highlight the importance of tissue type, sampling time, and genetic factors when designing experiments that involve phytohormone analysis of sorghum. This research lays the groundwork for future studies, which can combine phytohormone profiling with other datasets such as transcriptome, soil microbiome, genome, and metabolome data, to provide important functional information about adaptation to stress and other environmental variables.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Automated Hybrid Variance Reduction on Advanced Architectures in the Shift Monte Carlo Code

Monte Carlo transport methods are the most accurate schemes for solving problems with complex energy and spatial features, but they come with a high computational cost. Although hybrid methods have enabled the use of Monte Carlo transport for a large class of problems, they still require significant computing resources. Modern multicore CPUs with large numbers of compute cores and graphical processing units (GPUs) provide opportunities to optimize the memory and run-time costs of hybrid Monte Carlo methods. This paper documents the development and analysis of three Monte Carlo transport algorithms that support hybrid transport using the consistent adjoint-driven importance sampling (CADIS) and forward-weighted CADIS methods in the Shift Monte Carlo code: history-based transport using static and dynamic threading on multicore CPUs and event-based transport enabling weight window tracking on GPUs. The results are shown for two challenging hybrid problems on the Frontier supercomputer at the Oak Ridge Leadership Computing Facility. The results show that all three methods yield good performance and enable solutions of difficult fixed-source transport problems in less than 2 min on 20 nodes of Frontier. Dynamic threading was observed to give up to 20% better scaling behavior than static threading. Moreover, the AMD Instinct 250X GPU was found to give 9 to 11 times greater throughput per graphics compute die than the best CPU performance. In conclusion, additional opportunities for optimization of hybrid transport on GPUs are discussed.

Denovo↗