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DOE OSTI2022

XRF-ROI Finder: Machine Learning to Guide Region-of-Interest Scanning for X-ray Fluorescence Microscopy

The ROI-finder software is being developed for use by several Microscopy Group beamlines at Argonne National Laboratory, including 2-ID microprobes and 9-ID-B Bionanoprobe which use multi-scale scanning fluorescence microscopy to acquire elemental maps (multi-modal image data). Microscopy experiments require scan of samples at a coarse resolution followed by ROI identification using feature detection based on domain expertise. Finer resolution scans are then conducted based on identified ROI. The decision-making process based on domain expertise will be difficult to perform for faster data rates and much larger sampling volumes anticipated after APS-U necessitating the need for the ROI-finder software. The ROI- finder detects regions of interest through a continuous learning process, starting with a unsupervised representation learning and improving its recommendations through supervised learning and an interactive tool for user annotation. The scope of ongoing development efforts includes the integration of image registration module to correlate optical and X-ray images, extraction of feature morphology as well as elemental signatures in the image space and incorporation of beamtime streaming data by the scanning probe via EPICS.

CHOWDHURY, M. ARSHAD ZAHANGIR↗

DOE OSTI2022

VPIC-Kokkos

VPIC is a particle-in-cell (PIC) code that solves the Maxwell-Boltzmann system of equations and can be used to simulate a wide variety of plasmas, including those that are fully kinetic and relativistic. Utilizing the Kokkos performance-portable framework, VPIC achieves high performance on multiple CPU and GPU architectures and is adaptable to future platforms with minimal developer effort. VPIC features very powerful input decks, allowing insertion of arbitrary C++ code for custom diagnostics, boundary conditions, and additional physics models.

Luedtke, Scott↗

DOE OSTI2020

kynema-sgf [SWR-20-85]

Kynema-SGF (formerly AMR-Wind), wherein SGF stands for structured-grid fluid dynamics, is a massively parallel, block-structured adaptive-mesh, incompressible flow solver. The codebase was initiated in 2019 from incflo. The solver is built on top of the AMReX library. AMReX library provides the mesh data structures, mesh adaptivity, as well as the linear solvers used for solving the governing equations. Kynema-SGF is actively developed and maintained by a dedicated multi-institutional team from Lawrence Berkeley National Laboratory, National Laboratory of the Rockies, and Sandia National Laboratories. The primary applications for Kynema-SGF are: performing large-eddy simulations (LES) of atmospheric boundary layer (ABL) flows, simulating wind farm turbine-wake interactions using actuator disk or actuator line models for turbines, and as a background solver when coupled with a near-body solver (e.g., Kynema-UGF) with overset methodology to perform blade-resolved simulations of multiple wind turbines within a wind farm. For offshore applications, the ability to model the air-sea interaction effects and its impact on the ABL characteristics is another focus for the code development effort. As with other codes in the Kynema ecosystem, Kynema-SGF shares the following objectives: *an open, well-documented implementation of the state-of-the-art computational models for modeling wind farm flow physics at various fidelities that are backed by a comprehensive verification and validation (V&V) process; *be capable of performing the highest-fidelity simulations of flow fields within wind farms; and *be able to leverage the high-performance leadership class computing facilities available at DOE national laboratories.

Ananthan, Shreyas↗

DOE OSTI2024

Are Atmospheric Models Too Cold in the Mountains? The State of Science and Insights from the SAIL Field Campaign

Mountains play an outsized role in water resource availability, and the amount and timing of water they provide depend strongly on temperature. To that end, we ask the question: How well are atmospheric models capturing mountain temperatures? We synthesize results showing that high-resolution, regionally relevant climate models produce 2-m air temperature (T2m) measurements colder than what is observed (a “cold bias”), particularly in snow-covered midlatitude mountain ranges during winter. We find common cold biases in 44 studies across global mountain ranges, including single-model and multimodel ensembles. We explore the factors driving these biases and examine the physical mechanisms, data limitations, and observational uncertainties behind T2m. Our analysis suggests that the biases are genuine and not due to observation sparsity or resolution mismatches. Cold biases occur primarily on mountain peaks and ridges, whereas valleys are often warm biased. Our literature review suggests that increasing model resolution does not clearly mitigate the bias. By analyzing data from the Surface Atmosphere Integrated Field Laboratory (SAIL) field campaign in the Colorado Rocky Mountains, we test various hypotheses related to cold biases and find that local wind circulations, longwave (LW) radiation, and surface-layer parameterizations contribute to the T2m biases in this particular location. We conclude by emphasizing the value of coordinated model evaluation and development efforts in heavily instrumented mountain locations for addressing the root cause(s) of T2m biases and improving predictive understanding of mountain climates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Are Atmospheric Models Too Cold in the Mountains? The State of Science and Insights from the SAIL Field Campaign

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

PeleC: An adaptive mesh refinement solver for compressible reacting flows

Reacting flow simulations for combustion applications require extensive computing capabilities. Leveraging the AMReX library, the Pele suite of combustion simulation tools targets the largest supercomputers available and future exascale machines. We introduce PeleC, the compressible solver in the Pele suite, and detail its capabilities, including complex geometry representation, chemistry integration, and discretization. We present a comparison of development efforts using both OpenACC and AMReX’s C++ performance portability framework for execution on multiple GPU architectures. We discuss relevant details that have allowed PeleC to achieve high performance and scalability. PeleC’s performance characteristics are measured through relevant simulations on multiple supercomputers. The success of PeleC’s design for exascale is exhibited through demonstration of a 160 billion cell simulation and weak scaling onto 100% of Summit, an NVIDIA-based GPU supercomputer at Oak Ridge National Laboratory. Our results provide confidence that PeleC will enable future combustion science simulations with unprecedented fidelity.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Spectroelectrochemical insights into the intrinsic nature of lead halide perovskites

Abstract Lead halide perovskites have emerged as a new class of semiconductor materials with exceptional optoelectronic properties, sparking significant research interest in photovoltaics and light-emitting diodes. However, achieving long-term operational stability remains a critical hurdle. The soft, ionic nature of the halide perovskite lattice renders them vulnerable to various instabilities. These instabilities can be triggered by factors such as photoexcitation, electrical bias, and the surrounding electrolyte/solvent or atmosphere under operating conditions. Spectroelectrochemistry offers a powerful approach to bridge the gap between electrochemistry and photochemistry (or spectroscopy), by providing a comprehensive understanding of the band structure and excited-state dynamics of halide perovskites. This review summarizes recent advances that highlight the fundamental principles, the electronic band structure of halide perovskite materials, and the photoelectrochemical phenomena observed upon photo- and electro-chemical charge injections. Further, we discuss halide instability, encompassing halide oxidation, vacancy formation, ion migration, degradation, and sequential expulsion under electrical bias. Spectroelectrochemical studies that provide a deeper understanding of interfacial processes and halide mobility can pave the way for the design of more robust perovskites, accelerating future research and development efforts. Graphical Abstract

Min, Seonhong↗

DOE OSTI2023

Anomaly Detection and Identification Using a Leave-One-Variable-Out Method

At nuclear power plants (NPPs), anomaly detection and identification (i.e., determining the causes of anomalies) are important tasks for ensuring the safe and efficient operation of NPPs. These tasks are currently labor-intensive and costly, and are made more difficult by the size and complexity of NPP systems. An alternative approach to conducting these tasks is to automate them, such as via the reconstruction-based contribution method, which is a well-researched unsupervised machine learning method that uses a data-driven model of anomaly-free behavior to detect events and then identify each variable’s contributions to those events. The present effort developed a novel contribution approach that utilized a leave-one-variable-out (LOVO) model, with which each variable is predicted using all the other variables. The novelty lay in transforming this model into a reconstruction model and modifying the identification algorithm to work with the new reconstruction model. To evaluate this method in a controlled environment, a synthetic dataset based on spring-mass-damper (SMD) systems (commonly found in mechanical engineering references) was used, with known anomalies introduced into the system. The proposed method successfully detected the anomalies and afforded insights into their causes, thus enabling the appropriate identifications to be made.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Age at release affects developmental physiology and sex-specific phenotypic diversity of hatchery steelhead trout (Oncorhynchus mykiss)

Most steelhead trout hatcheries increase growth rate during rearing to produce and release yearling smolts for harvest augmentation, but natural steelhead exhibit variable age of smoltification, so this common rearing practice may not be ideal for programs focused on recovering imperiled wild stocks; therefore, it is important to investigate and compare alternative hatchery rearing methods that promote life history diversity. Over six consecutive years, the Winthrop National Fish Hatchery on the Methow River, WA reared and released paired groups of age-1 (S1) and age-2 (S2) steelhead smolts. To understand how the two rearing methods affected developmental ontogeny and life-history, fish were sampled prior to hatchery release for factors associated with smoltification (size, gill Na+/K+ ATPase activity, and a qualitative smolt phenotype) and sexual maturation (sex, pituitary and testis mRNA transcripts, gonadosomatic index, and plasma 11-ketotestosterone). Our objectives were to quantify levels of smoltification and male maturation during hatchery rearing, combine metrics to estimate residualism (failure to migrate upon release), and compare the treatments by sex. Overall, S2 rearing produced 7.8% more smolts and 44-fold (4.4 vs. 0.1%) more precociously mature males than S1 rearing. Conversely, S1 rearing produced 31.6% more residuals than S2 rearing. While the proportion of total male residuals was comparable between treatments, the S1 treatment produced approximately five-fold more female residuals (20.6 vs. 4.2%). Because residuals contribute minimally to adult returns and the number of returning adult females is critical to the success of salmonid supplementation efforts, developing rearing techniques that maximize migration in females is a management priority. Physiological assessments are useful for characterizing and quantifying the effects and risks of different hatchery rearing regimes on steelhead life-history, in addition to providing sex-specific guidance to inform and optimize conservation management goals in supplementation programs.

Middleton, Mollie A. (ORCID:0009000905577865)↗

DOE OSTI2016

Feeder Voltage Regulation with High-Penetration PV Using Advanced Inverters and a Distribution Management System: A Duke Energy Case Study

Duke Energy, Alstom Grid, and the National Renewable Energy Laboratory teamed up to better understand the impacts of solar photovoltaics (PV) on distribution system operations. The core goal of the project is to compare the operational - specifically, voltage regulation - impacts of three classes of PV inverter operations: 1.) Active power only (Baseline); 2.) Local inverter control (e.g., PF...not equal...1, Q(V), etc.); and 3.) Integrated volt-VAR control (centralized through the distribution management system). These comparisons were made using multiple approaches, each of which represents an important research-and-development effort on its own: a) Quasi-steady-state time-series modeling for approximately 1 year of operations using the Alstom eTerra (DOTS) system as a simulation engine, augmented by Python scripting for scenario and time-series control and using external models for an advanced inverter; b) Power-hardware-in-the-loop (PHIL) testing of a 500-kVA-class advanced inverter and traditional voltage regulating equipment. This PHIL testing used cosimulation to link full-scale feeder simulation using DOTS in real time to hardware testing; c) Advanced visualization to provide improved insights into time-series results and other PV operational impacts; and d) Cost-benefit analysis to compare the financial and business-model impacts of each integration approach.

14 SOLAR ENERGY↗

DOE OSTI2017

Groundwater Pathway Model for the Los Alamos National Laboratory Technical Area 21, Material Disposal Area T

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DOE OSTI2017

Groundwater Pathway Model for the Los Alamos National Laboratory Technical Area 54, Area G, Revision 1

This report consists of four major sections, including this introductory section. Section 2 provides an overview of previous investigations related to the development of the current sitescale model. The methods and data used to develop the 3-D groundwater model and the techniques used to distill that model into a form suitable for use in the GoldSim models are discussed in Section 3. Section 4 presents the results of the model development effort and discusses some of the uncertainties involved. Eight attachments that provide details about the components and data used in this groundwater pathway model are also included with this report. The groundwater modeling effort reported here is a revision of the work that was conducted in 2005 (Stauffer et al., 2005a) in support of the 2008 Area G performance assessment and composite analysis (LANL, 2008). The revision effort was undertaken primarily to incorporate new geologic information that has been collected since 2003 at, and in the vicinity of, Area G. The new data were used to create a more accurate geologic framework model (GFM) that forms the basis of the numerical modeling of the site’s long-term performance. The groundwater modeling uses mean hydrologic properties of the geologic strata underlying Area G; this revision includes an evaluation of the impacts that natural variability in these properties may have on the model projections.

58 GEOSCIENCES↗

DOE OSTI2017

Final Scientific Report: DE-SC0002194

We provide the final scientific report for DE-SC0002194. During the term of this grant, 28 publications spanning a variety of topics were addressed under the rubric of advanced x-ray methods and their application to extreme conditions of time-resolution or x-ray intensities. Notable accomplishments include a new observation of XANES features associated with f-shell reconfiguration in lanthanides, size-dependent x-ray heating effects under XFEL illumination conditions, theoretical development of improved treatments of inelastic x-ray scattering for 'warm dense matter' conditions, and several new instrument develop efforts for atomic, molecular, and condensed phase studies in the lab and at major facility lightsources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Sorbent-based Oxygen Production for Energy Systems

Project DE-FE0024075 deals with the development of a high-temperature sorbent-based oxygen production technology. Sorbent-based oxygen production process utilizes oxygen-storage properties of Perovskites to (1) adsorb oxygen from air in a solid sorbent, and (2) release the adsorbed oxygen into a sweep gas such as CO2 and/or steam for gasification systems or recycled flue gas for oxy-combustion systems. Pure oxygen can be produced by the use of vacuum instead of a sweep gas to affect the pressure swing. By developing more efficient and stable, higher sorption capacity, newer class of materials operating at lower temperatures this process represents a major advancement in air separation technology. Newly developed perovskite ceramic sorbent materials with order-disorder transition have a higher O 2 adsorption capacity, 200 ºC lower operating temperatures, and up to two orders of magnitude faster desorption rates than those used in earlier development efforts. The performance advancements afforded by the new materials lead to substantial savings in capital investment and operational costs. Cost of producing oxygen using sorbents could be as much as 60% lower than a cryogenic air separation unit.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2017

Sorbent-based Oxygen Production for Energy Systems

Project DE-FE0024075 deals with the development of a moderate-temperature sorbent-based oxygen production technology. Sorbent-based oxygen production process utilizes oxygen-storage properties of Perovskites to (1) adsorb oxygen from air in a solid sorbent, and (2) release the adsorbed oxygen into a sweep gas such as CO 2 and/or steam for gasification systems or recycled flue gas for oxy-combustion systems. Pure oxygen can be produced by the use of vacuum instead of a sweep gas to affect the pressure swing. By developing more efficient and stable, higher sorption capacity, newer class of materials operating at moderate temperatures this process represents a major advancement in air separation technology. Newly developed perovskite ceramic sorbent materials with order-disorder transition have a higher O 2 adsorption capacity, potentially 200 °C lower operating temperatures, and up to two orders of magnitude faster desorption rates than those used in earlier development efforts. The performance advancements afforded by the new materials lead to substantial savings in capital investment and operational costs. Cost of producing oxygen using sorbents could be as much as 26% lower than VPSA and about 13% lower than a large cryogenic air separation unit. Cost advantage against large cryogenic separation is limited because sorbent-based separation numbers up sorbent modules for achieving the larger capacity.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2017

Sorbent-based Oxygen Production for Energy Systems

Project DE-FE0024075 deals with the development of a moderate-temperature sorbent-based oxygen production technology. Sorbent-based oxygen production process utilizes oxygen-storage properties of Perovskites to (1) adsorb oxygen from air in a solid sorbent, and (2) release the adsorbed oxygen into a sweep gas such as CO 2 and/or steam for gasification systems or recycled flue gas for oxy-combustion systems. Pure oxygen can be produced by the use of vacuum instead of a sweep gas to affect the pressure swing. By developing more efficient and stable, higher sorption capacity, newer class of materials operating at moderate temperatures this process represents a major advancement in air separation technology. Newly developed perovskite ceramic sorbent materials with order-disorder transition have a higher O 2 adsorption capacity, potentially 200 ºC lower operating temperatures, and up to two orders of magnitude faster desorption rates than those used in earlier development efforts. The performance advancements afforded by the new materials lead to substantial savings in capital investment and operational costs. Cost of producing oxygen using sorbents could be as much as 26% lower than VPSA and about 13% lower than a large cryogenic air separation unit. Cost advantage against large cryogenic separation is limited because sorbent-based separation numbers up sorbent modules for achieving the larger capacity.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2017

Scoping assessments and review of sub-scale models in support of DuraMAT Predictive Simulation Capability Area #2

The goal of the DuraMAT Predictive Simulation Capability Area is to develop a suite of modeling and simulation tools to enhance understanding of module-level thermo-mechanical-electrical effects contributing to degradation of solar photovoltaic modules. Since these effects invoke multiple physical mechanisms and take place over greatly varied time- and length- scales, developing a module-level model of sufficient resolution to capture all geometries and physics of interest was expected to be near code capability and computational resource limits. A series of sub-models and workflows were developed to assess physics and material model maturity and the necessary computational capacity for resolving degradation mechanisms of interest. Knowledge gained from these activities help to better scope future development efforts, in line with available computational and code capabilities. This memo serves as the DuraMAT Quarterly Progress Indicator (QPI) for Quarter 3 of Fiscal Year 2017 (Project Quarter 1 / Month 3), and documents completion of Milestone Subtask 2.2.1.

14 SOLAR ENERGY↗

DOE OSTI2017

Updated Liquid Secondary Waste Grout Formulation and Preliminary Waste Form Qualification

This report describes the results from liquid secondary waste grout (LSWG) formulation and cementitious waste form qualification tests performed by Pacific Northwest National Laboratory (PNNL) for Washington River Protection Solutions, LLC (WRPS). New formulations for preparing a cementitious waste form from a high-sulfate liquid secondary waste stream simulant, developed for Effluent Management Facility (EMF) process condensates merged with low activity waste (LAW) caustic scrubber, and the release of key constituents (e.g. 99 Tc and 129 I) from these monoliths were evaluated. This work supports a technology development program to address the technology needs for Hanford Site Effluent Treatment Facility (ETF) liquid secondary waste (LSW) solidification and supports future Direct Feed Low-Activity Waste (DFLAW) operations. High-priority activities included simulant development, LSWG formulation, and waste form qualification. The work contained within this report relates to waste form development and testing and does not directly support the 2017 integrated disposal facility (IDF) performance assessment (PA). However, this work contains valuable information for use in PA maintenance past FY17, and for future waste form development efforts. The provided data should be used by (i) cementitious waste form scientists to further understanding of cementitious dissolution behavior, (ii) IDF PA modelers who use quantified constituent leachability, effective diffusivity, and partitioning coefficients to advance PA modeling efforts, and (iii) the U.S. Department of Energy (DOE) contractors and decision makers as they assess the IDF PA program. The results obtained help fill existing data gaps, support final selection of a LSWG waste form, and improve the technical defensibility of long-term waste form performance estimates.

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