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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Wall heating by subcritical energetic electrons generated by the runaway electron avalanche source *

Abstract Subcritical energetic electrons (SEEs) produced by the runaway electron (RE) avalanche source at energies below the runaway threshold are found to be the primary contributor to surface heating of plasma-facing components (PFCs) during final loss events. This finding is supported by theoretical analysis, computational modeling with the Kinetic Orbit Runaway electrons Code (KORC), and qualitative agreement with DIII-D experimental observations. The avalanche source generates significantly more secondary electrons below the runaway threshold, which thermalize rapidly when well-confined. However, during a final loss event, the RE beam impacts the first wall, and SEEs are deconfined before they can thermalize. Additionally, because the energy deposition length decreases faster than energy, the deposited energy density, and thus the maximum PFC surface temperature change, is larger for SEEs than REs. KORC simulations employ an analytic first wall to model particle deconfinement onto a non-axisymmetric wall composed of individual tiles. PFC surface heating is calculated using a 1D model extended to include an energy-dependent deposition length scale. Simulations of DIII-D qualitatively agree with infrared (IR) imaging only when SEEs from the avalanche source are included. These results demonstrate that SEEs are the dominant contributor to PFC surface heating and indicate that the avalanche source plays a critical role in the PFC damage caused during final loss events. The prominence of SEEs also has important implications for interpreting IR imaging, one of the primary diagnostics for RE-wall interaction diagnosis, despite REs dominating the energy and current density. This result improves predictions of wall damage due to post-disruption REs to estimate material lifetime and design RE mitigation systems for ITER and future reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Denudation, solute export, landscape evolution modeling, and geographic information system data for the East River watershed, Colorado, USA (2020-2024)

This data package contains geographic information system (GIS) layers and tabular datasets associated with the study of lithologic controls on denudation, solute export, carbon-scaling relationships, and transient landscape evolution in the East River watershed near Crested Butte, Colorado, USA. The package includes GIS layers used to produce the Figure 2 map, including drainage, hillshade, lithology, sample locations, and basin polygons, together with comma-separated value (CSV) tables and matching CSV data dictionaries. One group of tables reports sample-level and catchment-level information for river-sediment samples analyzed for in situ-produced cosmogenic beryllium-10 (10Be), including sample names, outlet elevations, geographic coordinates, upstream drainage area, rock-type classes, production-rate scaling scheme, analyzed nuclide, catchment-averaged denudation rates, and associated lower and upper analytical uncertainties. Sample and catchment attributes provide the basis for comparing denudation rates across intrusive, shale, sedimentary, and mixed-lithology settings. A second group of tables reports supporting information for landscape-evolution modeling and the mapped geologic framework of the study area. Included files list parameter values and definitions for the two-phase landscape-evolution simulations, summarize full-domain model erosion fluxes and topographic metrics for different simulation configurations, provide a fixed-area carbon-model scaling table, and summarize mapped geologic units within the East River study domain, including geologic code, formation name, lithologic description, mapped area, and lithologic class grouping. Model outputs and geologic summaries support interpretation of transient landscape behavior and its relation to the mapped distribution of shale, intrusive, sedimentary, and surficial units. A third group of tables reports hydrologic and hydrochemical information used to quantify dissolved export from the watershed. Included files provide site-level values for drainage area, mean annual solute export, standard error of annual export, area-normalized solute yield, and equivalent weathering rate for five East River monitoring sites, along with metadata describing the number, sampling cadence, and date range of discharge records and partial and full total dissolved solids observations used in the solute-yield analyses. The package also contains a supplementary daily ion-load time series with daily mean discharge, discharge observation counts, dissolved concentrations, and daily loads for calcium, magnesium, sodium, potassium, chloride, sulfate, nitrate, fluoride, dissolved silica, charge-balance bicarbonate, and total dissolved solids. The package contains GIS files, comma-separated value files (.csv), CSV data dictionaries, a file-level metadata table, a package-tree text file, and a readme text file.

10Be↗
DOE OSTI2017

Ceramic Plugs for Deep Borehole Seals - 17316

In the deep borehole nuclear waste disposal concept, waste packages are emplaced deep in crystalline rock formations under conditions of high pressures, high mineral content water, and elevated temperatures. Well seals and plugs must perform for thousands of years. A novel ceramic plug system under development capitalizes on the thermal energy of thermite mixtures and engineered additives to react and form ceramic-like plugs in place with favorable structural, flow, and geochemical properties. Depending on the ingredients, the reaction can produce aluminosilicates, plagioclase feldspars, or other combinations in crystalline or amorphous forms. Normative mineralogy techniques were applied to predict product mineralogy and evaluate compatibility with host rocks, and showed they are comparable to igneous rock analogs. The results support a tentative geochemical compatibility between these formulations and granitic host rock. Because the reaction produces a significant amount of thermal energy, the thermal/structural/fluid response of the plug and surrounding media was evaluated with the FEHM code. Temperatures near the plug/rock interface are estimated to peak at less than 600 deg. C and cool to near ambient temperature within a day. Rock stresses resulting from the thermal pulse are predicted to be similar to the unconfined compressive strength of granites, and generally lower than triaxial test results. Entrained fluid expansion due to heating was shown to be lower than failure stresses. Little or no failure in the surrounding media would be expected due to the plug formation process. The present efforts are focused on refining the material formulations, evaluating the geochemical and mechanical interactions between the plug and host rock, and testing the plug formation process in scaled granite and basalt masses. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fuid-fow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fuid-fow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes. This submission includes the published journal article detailing this work, the published 3D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using the GeoThermalCloud framework, which is part of SmartTensors (both are linked below).

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Progress on Optimizing Wind Farms and Rotor Designs Using Adjoints

Modern wind plants are increasingly tasked with multiple performance objectives. In addition to designing plants that maximize power output and minimize the levelized cost of energy (LCOE), the design and operation of wind plants is increasingly influenced by challenges regarding grid integration of variable generation renewables. This places a growing emphasis on making wind plants more controllable and predictable. WindSE is a Reynolds-averaged Navier-Stokes (RANS) model designed around analytical gradient and adjoint methods, with the ability to capture terrain-induced effects, as shown in Figure 1. The recent addition of an unsteady solver with an actuator line method (ALM) and ongoing work to enable massively parallel optimizations gives it a unique niche to explore coupled plant-level controls and design problems. This code is an open source python package built on the FEniCS framework that utilizes fast, parallel PETSc solvers to model fluid flow throughout wind-farm scale domains. Two recent studies performed using WindSE demonstrate the capability to optimize under a wide variety of flow conditions and objective functions. In the first, we present an optimization focused on modifying the layout of a wind farm with a fixed number of turbines for maximum total power output [1]. This study highlights the ability to quickly perform simulations using the steady Navier-Stokes solver combined with rotors represented as actuator disks while also stressing the importance of capturing terrain-induced effects. Gradient-based optimization using the RANS equations is viable due to the inclusion of efficiently computed adjoint derivatives. We interpret the physical results of the optimal layout and also discuss the computational cost of scaling to larger problems. In the second study, we present the capabilities of the unsteady Navier-Stokes solver, where rotor-blade profiles represented by actuator lines are optimized to enhance wake steering effects and overall power production [2]. We quantify the wind plant performance gains obtained from this type of simultaneous control co-design optimization as compared to optimizing the blade design and yaw independently. Figure 2 shows the differences between a baseline two-turbine system and an optimized system where we fine-tune the blade chord profile. Results and challenges from each study are quickly summarized and used to motivate the current development efforts within WindSE. Current and future work is focused on enabling higher-resolution studies with more degrees of freedom through parallelization of both the simulation and optimization algorithms. We present benchmarking results to show that WindSE performs well in both weak- and strong-scaling tests and further demonstrate that the optimizer obtains the same convergence rates in both shared- and distributed-memory environments. Using larger wind farms, we can study deep-array effects within an optimization context, allowing the use of objective functions that have been previously unstudied. As an example, we present ongoing work on a blockage metric which characterizes the loss of available kinetic energy due to wake effects from multiple upstream turbines.

adjoint optimization↗
DOE OSTI2018

Deep reinforcement learning of cell movement in the early stage of C.elegans embryogenesis

Motivation: Cell movement in the early phase of Caenorhabditis elegans development is regulated by a highly complex process in which a set of rules and connections are formulated at distinct scales. Previous efforts have demonstrated that agent-based, multi-scale modeling systems can integrate physical and biological rules and provide new avenues to study developmental systems. However, the application of these systems to model cell movement is still challenging and requires a comprehensive understanding of regulatory networks at the right scales. Recent developments in deep learning and reinforcement learning provide an unprecedented opportunity to explore cell movement using 3D time-lapse microscopy images. Results: We present a deep reinforcement learning approach within an agent-based modeling system to characterize cell movement in the embryonic development of C.elegans. Our modeling system captures the complexity of cell movement patterns in the embryo and overcomes the local optimization problem encountered by traditional rule-based, agent-based modeling that uses greedy algorithms. Here, we tested our model with two real developmental processes: the anterior movement of the Cpaaa cell via intercalation and the rearrangement of the superficial left-right asymmetry. In the first case, the model results suggested that Cpaaa’s intercalation is an active directional cell movement caused by the continuous effects from a longer distance (farther than the length of two adjacent cells), as opposed to a passive movement caused by neighbor cell movements. In the second case, a leader-follower mechanism well explained the collective cell movement pattern in the asymmetry rearrangement. These results showed that our approach to introduce deep reinforcement learning into agent-based modeling can test regulatory mechanisms by exploring cell migration paths in a reverse engineering perspective. Lastly, this model opens new doors to explore the large datasets generated by live imaging. Availability and implementation: Source code is available at https://github.com/zwang84/drl4cellmovement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Modeling and Validation of Irradiation Damage in Ni-based Alloys for Long-Term LWR Applications (Final Report)

As light water reactor (LWR) plant lives are extended, the need for predictive modeling tools for materials degradation increase in order to ensure safe operation and plan for component replacements. The Grizzly code, which is built on the MOOSE multi-physics simulation environment, is being developed for exactly this purpose. To extend Grizzly to include capabilities for modeling Ni-based alloys, we propose a US/UK integrated program to address thermal and irradiation-induced transformations mechanisms of Alloys 690 and 625. Alloy 690 is widely used in existing LWR plants due to its superior stress corrosion cracking (SCC) resistance compared to Alloy 600. Alloy 625 is used in more limited applications but offers the benefits of both high strength (in the aged condition) and corrosion/SCC resistance. Research has shown that both alloys can undergo phase changes due to thermal or irradiation exposure. In the precipitation-hardened condition, Alloy 625 “softens” during neutron irradiation as the strengthening precipitates decompose and metastable precipitates form. However, the nature and rates of these transformations as a function of exposure conditions are not well understood. Similarly, the effects of these thermal and irradiation-induced microstructural changes on mechanical properties require evaluation. The proposed program combines thermal and irradiation experiments, mechanical testing, microstructural characterization using state-of-the art analytical techniques, atomistic modeling, micro-and macro-scale modeling via Grizzly. This multi-pronged approach yields several benefits: 1) atomistic scale models capture the physics of the mechanisms of phase transformations, which can be generalized to other systems, 2) the modeling results (from atomistic to continuum) will be validated experimentally to ensure the predictive aspect, 3) the microstructure/property relationships captured with mechanical testing provides information at the engineering scale that is needed to validate the integration of the proposed new capability into Grizzly

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Visual Data-Analytics of Large-Scale Parallel Discrete-Event Simulations

Parallel discrete-event simulation (PDES) is an important tool in the codesign of extreme-scale systems because PDES provides a cost-effective way to evaluate designs of highperformance computing systems. Optimistic synchronization algorithms for PDES, such as Time Warp, allow events to be processed without global synchronization among the processing elements. A rollback mechanism is provided when events are processed out of timestamp order. Although optimistic synchronization protocols enable the scalability of large-scale PDES, the performance of the simulations must be tuned to reduce the number of rollbacks and provide an improved simulation runtime. To enable efficient large-scale optimistic simulations, one has to gain insight into the factors that affect the rollback behavior and simulation performance. We developed a tool for ROSS model developers that gives them detailed metrics on the performance of their large-scale optimistic simulations at varying levels of simulation granularity. Model developers can use this information for parameter tuning of optimistic simulations in order to achieve better runtime and fewer rollbacks. In this work, we instrument the ROSS optimistic PDES framework to gather detailed statistics about the simulation engine. We have also developed an interactive visualization interface that uses the data collected by the ROSS instrumentation to understand the underlying behavior of the simulation engine. The interface connects real time to virtual time in the simulation and provides the ability to view simulation data at different granularities. We demonstrate the usefulness of our framework by performing a visual analysis of the dragonfly network topology model provided by the CODES simulation framework built on top of ROSS. The instrumentation needs to minimize overhead in order to accurately collect data about the simulation performance. To ensure that the instrumentation does not introduce unnecessary overhead, we perform a scaling study that compares instrumented ROSS simulations with their noninstrumented counterparts in order to determine the amount of perturbation when running at different simulation scales.

Ross, Caitlin↗
DOE OSTI2022

Diagnosing the DARHT Electron Beam-Target Interaction and Hydrodynamic Expansion [Dissertation]

Quantitative electron beam-target interaction studies on the Dual-Axis Radiographic Hydrodynamic Test (DARHT) electron linear induction accelerators have only been performed recently. This includes characterization of the temperature, density, pressure, extent, and expansion velocity of the plasma plume. The results presented in this dissertation present a detailed and unified overview of the accelerator systems, target heating physics, beam transport, and diagnostic tools. Additional information includes calibration sources, radiation hydrodynamics, spectroscopic-quality radiation transport modeling, experimental measurements, and analyses of electron beam driven aluminum experiments. The first set of spatially and temporally resolved spectroscopic measurements of electron beam driven aluminum are presented. Contamination quantification analyses are used to understand the origin of the strong Na-I 3p-3s lines that are observed in absorption within the aluminum plasma continuum. These results inform the creation of the first spectroscopic-quality radiation transport model that links several atomic physics codes to interpret the conditions from which the Na-I lines originate. A good agreement is found between the surface analysis results and the model which confirms the concentration of the sodium present within the aluminum alloy foil material. It also demonstrates, for the first time on electron beam-driven target experiments, the ability to interpret plasma conditions from measured absorption lines. In a second experimental campaign which focuses on pure aluminum, the Al-I 3p-4s and 3p3d doublets are both measured in emission. A detailed analysis of the Al-I 3p-4s doublet reveals that the lines undergo moderate self-absorption. A simple model of the self-absorption effect is successfully used to match measured spectra at various temperature/density/plasma scale length combinations. These measurements led to the realization of the minimum density that can be resolved by the spectrometers for the Al-I 3p-4s lines due to the large slit width required to observe a signal on aluminum. These measurements also demonstrate the sensitivity of visible and long wave UV spectroscopy to minor changes in both temperature and density. The simple self-absorption model will be useful for analysis of other beam-target interaction experiments with spectra exhibiting either self-absorption or full self-reversal. Substantial headway has been made on the modeling front by linking together several codes needed to model both the energy deposition, hydrodynamic motion, and atomic kinetics to produce synthetic spectral calculations that are compared with experimental measurements. There exists ample space for improvement, especially with benchmarking the hydrodynamics codes and equation-of-state tables with experimental measurements. The X-ray diagnostics required to make these new measurements along with the simulation capabilities required to interpret the results are under development and will be the subject of future studies.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

The Building ENergy Demand (BEND) Model: A Comprehensive Composite Building Energy Modeling Framework

The Building ENergy Demand (BEND) model was developed at Pacific Northwest National Laboratory (PNNL) to simulate climate-dependent hourly building energy demand with the ability to disaggregate down to or aggregate up to any geographic area of interest, including counties, states, electric utility service territories, and census regions. The BEND modeling framework is designed to study the effects of climate change, economics, technology advancement, and various mitigation policies on aggregate building energy demand. To make the process computationally feasible, BEND reduces granularity in building characteristics and weather forcing while maintaining enough detail to minimize systematic differences (biases) between BEND results and data from the Energy Information Administration (EIA). Based on the Commercial Building Energy Consumption Survey (CBECS) and Residential Energy Consumption Survey (RECS) databases, BEND establishes a set of representative buildings with predefined sets of building types, sizes, and vintages. These representative buildings are defined for each of the four U.S. census regions and the five climate zones used by the EIA for building surveys (hereafter “EIA climate zones”). BEND’s representative buildings are based on a statistical analysis of the CBECS and RECS databases that infers detailed parameters such as construction type, thermal properties, internal loads, equipment and mechanical systems, and operation schedules from the high-level descriptors in those databases (building type, vintage, size, and location). The representative buildings are simplified and consolidated into a set of prototype buildings for the purpose of simulating building energy demand. Combining the prototype buildings with weather files from selected locations and years, BEND creates a set of simulation-ready building models to be run using the EnergyPlus simulation engine (EnergyPlus). The base spatial unit of each BEND simulation is a subregion that is the intersection of an International Energy Conservation Code climate zone, a census region, and an EIA climate zone; analysis for each spatial unit is influenced by the weather file BEND selects to represent the climate-similar area. The major simulation outputs of interest to BEND are hourly energy consumption values for each simulated year, possibly for multiple fuel types. Based on building-stock weights derived from the CBECS/RECS data, the hourly output streams are aggregated to a single, 8760-hour load profile for each of the major building categories—residential and commercial—with the possibility of segregating by fuel types. To correct for biases inherent in the use of a limited suite of representative buildings, BEND is calibrated against observational targets of total annual building energy consumption and hourly load profiles (including peak demand) obtained for the decision-relevant geographic scales of interest (e.g., total electric load data for individual balancing authorities available from EIA). Based on available data such as population distribution, BEND is able to aggregate both up and down scales, allowing the study of building energy demand over a range of spatial scales (e.g., states or counties within the Western Electricity Coordinating Council, Eastern Interconnection, or the entire U.S.) and/or subsets of building types (e.g., office buildings with particular size ranges).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

DYNAMICS OF CIRCUMSTELLAR DISKS. III. THE CASE OF GG Tau A

We present two-dimensional hydrodynamic simulations using the Smoothed Particle Hydrodynamic code, VINE, to model a self-gravitating binary system. We model configurations in which a circumbinary torus+disk surrounds a pair of stars in orbit around each other and a circumstellar disk surrounds each star, similar to that observed for the GG Tau A system. We assume that the disks cool as blackbodies, using rates determined independently at each location in the disk by the time dependent temperature of the photosphere there. We assume heating due to hydrodynamical processes and to radiation from the two stars, using rates approximated from a measure of the radiation intercepted by the disk at its photosphere. We simulate a suite of systems configured with semimajor axes of either a = 62 AU (“wide”) or a = 32 AU (“close”), and with assumed orbital eccentricity of either e = 0 or e = 0.3. Each simulation follows the evolution for ∼6500–7500 yr, corresponding to about three orbits of the torus around the center of mass. Our simulations show that strong, sharply defined spiral structures are generated from the stirring action of the binary and that, in some cases, these structures fragment into 1–2 massive clumps. The torus quickly fragments into several dozen such fragments in configurations in which either the binary is replaced by a single star of equal mass, or radiative heating is neglected. The spiral structures extend inwards to the circumstellar environment as large scale material streams for which most material is found on trajectories that return it to the torus on a timescale of 1–200 yr, with only a small fraction accreting into the circumstellar environment. The spiral structures also propagate outwards through the torus, generating net outwards mass flow, and eventually losing coherence at large distances from the stars. The torus becomes significantly eccentric in shape over most of its evolution. In all configurations, accretion onto the stars occurs at a steady rate of a few ×10{sup −8} M {sub ⊙} yr{sup −1}, with the net result that, without replenishment, the disk lifetimes would be shorter than ∼10{sup 4} yr. Our simulations show that only wide orbit configurations are able to retain circumstellar disks, by virtue of accretion driven from the robust material streams generated in wide configurations, which are very weak in close configurations. In wide, eccentric orbit configurations, accretion is episodic and occurs preferentially onto the secondary, with rates strongly peaked near the binary periapse. Based on our results, we conclude that the GG Tau A torus is strongly self gravitating and that a major contribution to its thermal energy input is the shock dissipation associated with spiral structures generated both by self gravitating disturbances and by the stirring action of the binary. We interpret the sharply defined features observed in the torus as manifestations of such spiral structures. We interpret the low density disk surrounding it as an excretion disk created by the outward mass flux generated by the spiral arms as they propagate outwards. Typical eccentricities calculated for the shape of the tori modeled in our simulations are large enough to account for the supposed ∼20° mutual inclination between the stellar orbit plane of GG Tau A and its surrounding torus through a degeneracy between the interpretation of inclination of the torus and its eccentricity. We therefore interpret the observations in favor of a coplanar system with an eccentric torus. Because accretion onto the disks occurs at rates sufficient to sustain them only in wide orbit configurations, we conclude that the gas currently resident in the circumstellar disks of the GG Tau A system has been accreted from the torus within the past few thousand years. Although circumstellar disks will persist over time spans long enough to permit planet formation, the overall environment remains unfavorable due to high temperatures and other conditions. Given the presence of circumstellar disks, robust accretion streams, and our interpretation of the GG Tau A stellar orbit plane as coplanar with the torus surrounding it, we conclude that the GG Tau A system is in an eccentric, a ∼ 62 AU orbit, resolving questions in the literature regarding its orbit parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Open Source Application of Fusing Aerosol Products from GEO and LEO Satellites

Retrieving aerosol optical depths (AODs) from sun-synchronous polar orbiting (aka low earth orbit, LEO) satellites, such as MODISs, and VIIRSs, OMI, TROPOMI, etc, has become well-established as a tool for extracting information on particulate matter (PM) and related processes in the atmosphere. However, with recently launched geostationary satellites (GEO), such as GOES-16/17/18, and Himawari-8/9, and Meteosat Third Generation (MTG) they provide a much higher temporal resolution (order of 10 minutes), typically an image once or more per hour during daylight compared to LEO once per day. By combining these observations, we may be able to characterize the diurnal cycle of global AOD at the local, regional and global scale. While the science community is still exploring the new data from GEO observations, we have been thinking about how to properly combine/merge/fuse those data considering differences in their spatial and temporal resolutions. However, this poses a “Big Data” challenge. The big data challenge is not just about data storage, but also about data discoverability, and accessibility, and even more, about data migration/mirroring in the cloud-computing environment. This paper is merely showing some of the efforts and approaches we have attempted in fusing six satellites’ Level 2 aerosol data (three are from GEO (GOES-16/17 and Himawari-8), and the other three are from LEO (TERRA/MODIS, AQUA/MODIS, SNPP-VIIRS) from Dark Target (DT) aerosol retrieval algorithm. Having the on-demand capability of fusing remote sensing products onto the desired temporal and spatial domain enables researchers and application practitioners to better manipulate and work with satellite and sensor data. It is our hopeWe hope that by making such an open-source package, and the accompanying functionality, the scientific community will be granted easier access to aerosol data processing resources. The MEaSUREs Program (Making Earth System Data Records for Use in Research Environments) expands our understanding of the Earth's current system through atmospheric and surface measurements. In an effort to aid the scientific research component and improve open source methods, this project developed Python code for fusing six satellite Level 2 aerosol data (three are from geostationary satellites (GEO), and the other three are from low earth orbital satellites (LEO)) from Dark Target Aerosol Retrieval Algorithm.

Jennifer Wei↗
DOE OSTI2023

Performance portable ice-sheet modeling with MALI

High-resolution simulations of polar ice sheets play a crucial role in the ongoing effort to develop more accurate and reliable Earth system models for probabilistic sea-level projections. These simulations often require a massive amount of memory and computation from large supercomputing clusters to provide sufficient accuracy and resolution; therefore, it has become essential to ensure performance on these platforms. Many of today’s supercomputers contain a diverse set of computing architectures and require specific programming interfaces in order to obtain optimal efficiency. In an effort to avoid architecture-specific programming and maintain productivity across platforms, the ice-sheet modeling code known as MPAS-Albany Land Ice (MALI) uses high-level abstractions to integrate Trilinos libraries and the Kokkos programming model for performance portable code across a variety of different architectures. In this article, we analyze the performance portable features of MALI via a performance analysis on current CPU-based and GPU-based supercomputers. The analysis highlights not only the performance portable improvements made in finite element assembly and multigrid preconditioning within MALI with speedups between 1.26 and 1.82x across CPU and GPU architectures but also identifies the need to further improve performance in software coupling and preconditioning on GPUs. We perform a weak scalability study and show that simulations on GPU-based machines perform 1.24–1.92x faster when utilizing the GPUs. The best performance is found in finite element assembly, which achieved a speedup of up to 8.65x and a weak scaling efficiency of 82.6% with GPUs. We additionally describe an automated performance testing framework developed for this code base using a changepoint detection method. The framework is used to make actionable decisions about performance within MALI. We provide several concrete examples of scenarios in which the framework has identified performance regressions, improvements, and algorithm differences over the course of 2 years of development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Erasure conversion in a high-fidelity Rydberg quantum simulator

Minimizing and understanding errors is critical for quantum science, both in noisy intermediate scale quantum (NISQ) devices and for the quest towards fault-tolerant quantum computation. Rydberg arrays have emerged as a prominent platform in this context with impressive system sizes and proposals suggesting how error-correction thresholds could be significantly improved by detecting leakage errors with single-atom resolution, a form of erasure error conversion. However, two-qubit entanglement fidelities in Rydberg atom arrays have lagged behind competitors and this type of erasure conversion is yet to be realized for matter-based qubits in general. Here we demonstrate both erasure conversion and high-fidelity Bell state generation using a Rydberg quantum simulator. When excising data with erasure errors observed via fast imaging of alkaline-earth atoms, we achieve a Bell state fidelity of $\ge 0.997{1}_{-13}^{+10}$ , which improves to $\ge 0.998{5}_{-12}^{+7}$ when correcting for remaining state-preparation errors. We further apply erasure conversion in a quantum simulation experiment for quasi-adiabatic preparation of long-range order across a quantum phase transition, and reveal the otherwise hidden impact of these errors on the simulation outcome. Our work demonstrates the capability for Rydberg-based entanglement to reach fidelities in the 0.999 regime, with higher fidelities a question of technical improvements, and shows how erasure conversion can be utilized in NISQ devices. These techniques could be translated directly to quantum-error-correction codes with the addition of long-lived qubits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2012

Flowfield Analysis of a Small Entry Probe (SPRITE) Tested in an Arc Jet

A novel concept of small size (diameter less than 15 inches) entry probes named SPRITE (Small Probe Re-entry Investigation for TPS Engineering) has been developed at NASA Ames Research Center (ARC). These flight probes have on-board data acquisition systems that have also been developed in parallel at NASA ARC by Greg Swanson1. Flight probes of this size facilitate testing over a wide range of conditions in arc jets available at NASA ARC, thereby fulfilling a 'test what you fly' paradigm. As indicated by the acronym, these probes, with suitably tailored trajectories, are primarily meant to be robotic flight test beds for TPS materials, although the design is flexible enough to accommodate additional objectives of flight-testing other vehicle subsystems. A first step towards establishing the feasibility of the SPRITE concept is to arc-jet test fully instrumented models at flight scale. In a follow-on to the Large-Scale Article Tests (LSAT2) performed in the 60 MW Interaction Heating Facility (IHF) in late 2008/early 2009, a full-scale model of Deep Space-2 (DS23) made of red oak was tested in the 20 MW Aerodynamic Heating Facility (AHF). There were no issues with mass capture by the diffuser for blunt bodies of roughly 15 inches diameter tested in the 18-inch nozzle of the AHF. Building on this initial success, two identical test articles - SPRITE-T1-1 and SPRITE-T1-2 (T1 indicating the choice of back shell geometry) - were fabricated, and one of them, SPRITE-T1-1, was tested in the AHF recently. Both these test articles, 14 inches in diameter, have a 45deg sphere-cone (like DS2) made of PICA bonded on to a 1/8th inch thick aluminum shell using RTV. The aft portion of the test article is a conical frustum (15deg cone angle) with LI-2200 bonded on to the aluminum shell. Each model is fully instrumented with: (a) thermocouples imbedded in plugs in the heat shield, (b) thermocouples bonded to the aluminum substructure; the thermocouples are distributed over the entire shell, and (c) a few strain gages. Data from some of the thermocouples and gages are acquired by the on-board data acquisition system (DAS), while data from the others are routed to the facility-provided DAS, thereby enabling a cross check on the in situ measurement capability. as inputs to v2.6.1 of the in-house materials thermal response code, FIAT

atmospheric entry↗
DOE OSTI2023

Flexible visualization of a 3rd party Intrusion Prevention (Security) tool: A use case with the ELK stack

A difficult aspect of cyber security is the ability to achieve automated real time intrusion prevention across various sets of systems. To this extent, several companies are offering comprehensive solutions that leverage an "accuracy of scale" and moving much of the intelligence and detection on the Cloud, relying on an ever-growing set of data and analytics to increase decision accuracy. Often, they provide tools to visualize the decision workflows in attack prevention (as well as tune the algorithm) but those solutions are not always practical as companies see the problem as "global" that is, from a unified Cyber-security standpoint. However, a key to a successful Cyber-security program is transparency and trust: from an experimental team viewpoint, this specifically means having the ability to immediately see what and from where, who has been blocked and being able to inform the community in case of a revoked access without the need for filing a "ticket" (that may eventually be answered) – in other words, rapid response to their user-base is essential but solutions targeting "sub-groups" in an organization are not often available. We have come up with a versatile solution leveraging the ELK stack (Elasticsearch, Logstash, & Kibana) and an IPS (Intrusion Prevention System) based WAF (Web Application Firewall) from Signal Sciences. Signal Science allows the streaming of detailed logs in a Logstash format suitable for custom solutions for visualization. By combining these two tools, we have strengthened our security posture and enabled individual experiments to monitor their own traffic. Specifically, the IPS WAF provides unique data such as country of origin, protocol, response code, source IP, and paths accessed. In this contribution, we will show how we engineered a visualization solution so experiment groups could access a dashboard with predefined graphs but also, where they can create individual customizable dashboards used to display blocked traffic and troubleshoot latency issues. We will discuss the details and procedures for developing and configuring these tools and how it benefits cyber security postures across our scientific based environment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Details of the neutral energy distribution and ionization source using spectrally resolved Balmer-alpha measurements on DIII-D

Spectrally resolved passive Balmer- α (D- α, H- α) measurements from the DIII-D 16 channel edge main-ion charge exchange recombination system confirm the presence of higher energy neutrals (“thermal” neutrals) in addition to the cold neutrals that recycle off the walls in the edge region of DIII-D plasmas. Charge exchange between thermal ions and edge neutrals transfers energy and momentum between the populations giving rise to thermal neutrals with energies approximating the ions in the pedestal region. Multiple charge exchange events in succession allow an electron to effectively take a random walk, transferring from ion to ion, providing a pathway of increasing energy and velocity, permitting a neutral to get deeper into the plasma before a final ionization event that contributes to the ion and electron particle fueling. Spectrally resolved measurements provide information about the density and velocity distribution of these neutrals, which has been historically valuable for validating Monte Carlo neutral models, which include the multi stage charge exchange dynamics. Here, in this study, a multi-channel set of such measurements is used to specifically isolate the details of the thermal neutrals that are responsible for fueling inside the pedestal top. Being able to separate the thermal from the cold emission overcomes several challenges associated with optical filter-based neutral density measurements. The neutral dynamics, deeper fueling by the thermal neutrals, and spectral measurement are modeled with the FIDASIM Monte Carlo collisional radiative code, which also produces synthetic spectra with a shape that is in close agreement with the measurements. By scaling the number of neutrals in the simulation to match the intensity of the thermal emission, we show it is possible to obtain local neutral densities and ionization source rates.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2001

Textbook Multigrid Efficiency for Computational Fluid Dynamics Simulations

Considerable progress over the past thirty years has been made in the development of large-scale computational fluid dynamics (CFD) solvers for the Euler and Navier-Stokes equations. Computations are used routinely to design the cruise shapes of transport aircraft through complex-geometry simulations involving the solution of 25-100 million equations; in this arena the number of wind-tunnel tests for a new design has been substantially reduced. However, simulations of the entire flight envelope of the vehicle, including maximum lift, buffet onset, flutter, and control effectiveness have not been as successful in eliminating the reliance on wind-tunnel testing. These simulations involve unsteady flows with more separation and stronger shock waves than at cruise. The main reasons limiting further inroads of CFD into the design process are: (1) the reliability of turbulence models; and (2) the time and expense of the numerical simulation. Because of the prohibitive resolution requirements of direct simulations at high Reynolds numbers, transition and turbulence modeling is expected to remain an issue for the near term. The focus of this paper addresses the latter problem by attempting to attain optimal efficiencies in solving the governing equations. Typically current CFD codes based on the use of multigrid acceleration techniques and multistage Runge-Kutta time-stepping schemes are able to converge lift and drag values for cruise configurations within approximately 1000 residual evaluations. An optimally convergent method is defined as having textbook multigrid efficiency (TME), meaning the solutions to the governing system of equations are attained in a computational work which is a small (less than 10) multiple of the operation count in the discretized system of equations (residual equations). In this paper, a distributed relaxation approach to achieving TME for Reynolds-averaged Navier-Stokes (RNAS) equations are discussed along with the foundations that form the basis of this approach. Because the governing equations are a set of coupled nonlinear conservation equations with discontinuities (shocks, slip lines, etc.) and singularities (flow- or grid-induced), the difficulties are many. This paper summarizes recent progress towards the attainment of TME in basic CFD simulations.

Brandt, Achi↗