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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 901 records · Page 50

Scoreboard

Emerging HPC machines have given rise to enhanced compute power that far outstrips the machine's ability to save large scale results for post-processing. To combat this, in situ data analysis techniques are slowly being adopted. With in situ data management favoring workflows composed of multiple simulations and analyses connected in transit on heterogeneous machines, scientists and engineers need a tool that enables them to create data extracts, visualizations, and interactively monitor and steer their simulations. Scoreboard Phase II is a next generation analysis software that supports composite in transit workflows on heterogeneous architectures and restores interactivity to in situ data analysis through simulation monitoring and computational steering. Scoreboard provides a simulation dashboard with graphs of metrics over time, controls for setting custom simulation steering parameters, controls for managing the set of data extracts being produced in the simulation, as well as the ability to explore data extracts, all from a web browser. Realizing the vision outlined in this project required research into making a system that integrates end to end from simulations all the way to the user. In situ tools generally suffer from complexity and excessive software dependencies. Scoreboard, by contrast, is easy to build and integrate into simulation codes and it provides first class FORTRAN support. The Scoreboard library is capable of in situ and in transit data analysis that can produce data extracts commonly needed for Computational Fluid Dynamics (CFD) analysis. Simulations can transparently stage data in transit to a Scoreboard Endpoint program, which can accept their data and produce the requested data extracts. This lets simulations return to their work while the Endpoint works on the analysis. Efficiently staging the data at scale was a topic of this research. Scoreboard provides the means to let the user manage data extracts and monitor/steer many simulations from a web browser. This area of the research focused on discovery of in transit network components to expose and control their steering parameters within an interactive browser-based user interface that includes: system topology, gathered metrics, notifications, dynamically-generated steering controls, and exploration of visualization data products.

Whitlock, BradJoseph [Intelligent Light] (00000001↗

Neural Network Export Package (nexport) v0.1.0

nexport is a lightweight python 3 package which enables neural network developers to export the weights and biases of trained networks to useful file types. It provides I/O support for applications which require specific data types for instantiating neural networks in various inference environments. It was initially developed to support exporting to the data structure used by 'inference-engine', a Fortran inference package.

Welsman, Jordan↗

SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training) v1

SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training) is a comprehensive data visualization and analysis application focused on working with COLTRIMS (COLd Target Recoil Ion Momentum Spectroscopy) data, which is used in atomic and molecular physics experiments. The application offers several powerful features: - Data uploading and processing capabilities for COLTRIMS files - Multiple visualization methods using UMAP (Uniform Manifold Approximation and Projection) for dimensionality reduction - Interactive selection of data points across multiple views - Feature engineering through various methods: - Manual feature selection from calculated physics parameters - Deep autoencoder for dimension reduction - Genetic programming for discovering meaningful features - Mutual information-based feature selection - Multiple clustering approaches (DBSCAN, KMeans, Agglomerative) - Quality metrics for evaluating clustering results - Export capabilities for selections and generated features

Daoud, Hazem [Lawrence Berkeley National Laborator↗

Vibration of a cryomodule’s coupler during road transportation: Multibody analysis and experimental validation

The road transportation of critical components for cryogenic cryomodules is a challenging task. Indeed, the shipping and the handling of fundamental sub-assemblies can expose these components to harmful dynamic loads that can jeopardize their structural integrity. This article has the purpose of developing a finite element multibody model capable of assessing the acceleration on a test coupler for a cavity of the Single Spoke Resonator 1 subjected to a typical road transportation trip. A multibody model consisting of rigid bodies and finite element–imported flexible bodies has been created allowing a comparison of the simulated and experimental acceleration. Afterwards, an experimental on-road test, whose set-up is described in this article, has been carried out at Fermilab with instrumented components. Being able to effectively simulate and validate the dynamic effects on such sub-assemblies makes it possible, for the future, to simulate more complex structures subject to dynamic loadings, such as the entire cryomodules during shipping. Furthermore, the results from the simulations can be used to guide the design of new suspension systems suitable for the reduction mitigation of structural vibration during the road transportation of cryomodules.

42 ENGINEERING↗

Illite Dissolution Rates and Equation (100 to 280 dec C)

The objective of this suite of experiments was to develop a useful kinetic dissolution expression for illite applicable over an expanded range of solution pH and temperature conditions representative of subsurface conditions in natural and/or engineered geothermal reservoirs. Using our new data, the resulting rate equation is dependent on both pH and temperature and utilizes two specific dissolution mechanisms (a “neutral” and a “basic” mechanism). The form of this rate equation should be easily incorporated into most existing reactive transport codes for to predict rock-water interactions in EGS shear zones.

15 GEOTHERMAL ENERGY↗

Pulse Tube Interference in Cryogenic Sensor Resonant Circuits (Final Paper)

Transition edge sensors (TES) are extremely sensitive superconducting sensors, operating at 100 mK, which can be used to detect X-rays and Cosmic Microwave Background. The goal of our project is to design the electronics to read out an array of 10000 of these sensors by using microwave signals. However, we noticed the pulse tube used to maintain cryogenic temperatures caused interference in our readout. To determine the cause of the signal distortions, we used a detector with a 370 MHz sampling rate to collect and analyze sensor data. Although this data provided little information towards the nature of the noise, it was determined through a maintenance procedure than the 0.3 mm stainless steel wires were being vibrated due to acoustic waves, which distorted the signal. Replacing this wire appeared to cease the interference from the sensor data.

42 ENGINEERING↗

SCC Aerosol Transport Model Summary Report

The purpose of the present work is to introduce a generic and reliable numerical model for prediction of aerosol transport, deposition, and plugging in leak paths similar to stress corrosion cracks while accounting for potential plugging formation. The model is dynamic (changing leak path geometry due to plugging) and it relies on the numerical solution of the aerosol transport equation in one dimension using finite differences. An extensive validation exercise (particle diameters: 0.01-10 μm and pressure difference up to 12 kPa) was conducted based on comparisons with experimental and theoretical data. The developed model is fairly general since it is based on a generic mechanistic description of the aerosol flow and particle deposition in the leak path, without requiring experimental fittings other than using the leak rate parameters commonly available in practical applications. Despite the approximate agreement of the model with the experimental data, the obtained predictions can be qualified as realistic. This is a major achievement of the model, which has been based on generic aerosol mechanics with no reference or adjustment to experimental data.

42 ENGINEERING↗

Technical Basis: SAVY-4000 Series, 2 qt Container

The 2 qt SAVY nuclear material storage container is the latest in the SAVY-4000 series. The 2 qt design is identical to the 1 qt container, with the exception of an extended, deep-drawn body. Here, a technical basis using engineering equivalency analysis, calculation, and test data is presented to establish that the 2 qt SAVY-4000 Container is a DOE Manual 441.1-1 compliant container and that a fifteen-year design life (as with the currently approved SAVY series) is justified.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

2018 Energy Storage Pricing Survey

Since grid energy storage is still a nascent industry, it is often difficult to obtain capital costs for various energy storage technologies. This type of information is required to perform an initial cost-benefit analysis related to a potential energy storage deployment, as well as to compare different energy storage technology options. The goal of this report is to summarize energy storage capital costs that were obtained from industry pricing surveys. The methodology breaks down the cost of an energy storage system into the following categories: the storage module; the balance of system; the power conversion system; the energy management system; and the engineering, procurement, and construction costs. Pricing data is presented for the following technologies: pumped hydro storage; compressed air energy storage; sodium battery storage; zinc battery storage; long duration flywheels; short duration flywheels; vanadium flow batteries; zinc bromide flow batteries; iron flow batteries; nickel batteries; lithium ion energy batteries; lithium ion power batteries; lead acid batteries; and advanced lead carbon batteries.

25 ENERGY STORAGE↗

Organic Iodide Sorption from Dilute Gas Streams

Reprocessing used nuclear fuel releases volatile radionuclides, including 129 iodine (I), into the off-gas of a processing plant. Volatile radioiodine could be present in several forms, depending on the chemistry of the process used and the off-gas stream. Inorganic I 2 is expected to be the predominant I species in the dissolver off-gas (DOG), with minor organic iodides present. The bulk of the I is expected to volatilize into the DOG in parts-per-million-level (ppm) concentrations. In contrast, in the vessel off-gas (VOG), most of the volatile I is expected to be found as organic iodides, such as CH 3 I, C 4 H 9 I, and C 12 H 25 I. These species are expected to be present in parts-per-billion-level (ppb) concentrations but require abatement, even at low expected concentrations, to meet regulatory emissions limits in the United States. Historically, studies of I abatement by Ag-functionalized sorbents have focused on inorganic I in the DOG, but in the last few years, more research attention has been given to organic iodides, especially longer chain species, such as C 4 H 9 I, and C 12 H 25 I. This report has three main goals: (1) to present new data generated at Oak Ridge National Laboratory (ORNL) in FY21 on the sorption behavior of organic iodides on AgZ, (2) to summarize and synthesize organic iodide data produced by ORNL and Idaho National Laboratory (INL) over the last 4 years to answer questions on organic iodides behavior outlined in the 2018 joint test plan (Jubin et al. 2018), and (3) to propose a VOG abatement system design that can provide the capture efficiencies required to meet I emission limits. The 2021 ORNL experimental campaign tested the effects of organic iodide speciation and concentration in the off-gas, superficial velocity of the off-gas, and effects of aging on AgZ sorbent capacity. These studies found that the sorption rate of organic iodides by AgZ depends on the hydrocarbon chain length and the concentration in the off-gas. Higher molecular weight organic iodides adsorb to AgZ more slowly than I. At a concentration of 50 ppm concentration in the off-gas, CH 3 I loads 8% slower, C 4 H 9 I loads 20% slower, and C 12 H 25 I loads 40% slower than I. The lowest concentration loading rates calculated were in 5 ppm organic iodide gas streams in which AgZ gained on average 0.14 mg I/g sorbent/hour in the bench scale test system. Thus, longer sorbent beds might be needed to accommodate slower loading rates onto AgZ in lower concentration gas streams. Although sorption rate varies as a function of hydrocarbon chain length, the saturation concentration of the sorbent for these I-bearing species does not vary. Aging AgZ in a humid air stream for 9 months drops the overall sorbent capacity by ~35% for CH 3 I, ~50% for C 4 H 9 I, and ~40% for C 12 H 25 I. This results in a saturation capacity between 35 and 70 mg I/g sorbent for the aged AgZ. In conjunction with recent data produced by INL, these data are used to estimate the mass transfer zone (MTZ) and decontamination factor (DF) for sorbent beds of AgZ. Sorption tests performed with iodide gas concentrations of about 1 ppm and higher at a superficial gas velocity of 10 m/min, indicate that MTZ depths for these conditions tend to range between about 8-20 cm. Tests performed at lower concentrations between 50-90 ppb and at gas superficial velocities of 1, 10, and 20 m/min indicate that the MTZ depth increases with increasing superficial gas velocity. The 20 m/min test indicates that the MTZ for those conditions was at least 22 cm, and doubling the superficial gas velocity from 10 to 20 m/min could roughly double or triple the MTZ depth. Doubling and tripling the bounding MTZ depth of 20 cm for the body of MTZ estimates made at with 10 m/min superficial velocity would extend the MTZ for a superficial velocity of 20 m/min to 40-60 cm. This bounding limit applies to all of the organic iodides that have been tested. These results also indicate that the sorption rate-limiting step is not sensitive to the superficial gas velocity; otherwise the MTZ depth would not have increased approximately in proportion to the increase in the gas superficial velocity. This further suggests that the rate limiting step is not associated with mass transfer of the sorbate to the sorbent surface, or mass transfer of the reaction byproducts from the sorbent surface, but is associated with sorption or chemical reactions on the sorbent surface or in sorbent pores. Deep bed testing at INL has established DFs of >2,000 for I, CH 3 I, and C 4 H 9 I under a range of conditions (Soelberg et al. 2021, Bruffey et al. 2019). DF does not seem to be affected by the concentration of the organic iodide in the gas stream over the range of 1 to 50 ppm. Thus, if the MTZ is accommodated in sorbent bed design for the DOG and VOG, then regulatory DFs will be met. To meet the third objective outlined in this report, these experimental data were used to update an engineering evaluation of the VOG first completed in 2016. The updated VOG design can be found in an accompanying document (Welty et al., 2021; INL- LTD-21-64587). This report finds that the VOG will decrease in both size and complexity, relative to previous designs, and will still meet regulatory requirements for all iodine forms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Assessment of Machine Learning for Ultrasonic Nondestructive Evaluation of Alkali–Silica Reaction in Concrete

Alkali–silica reaction (ASR) is a type of material degradation in concrete structures that leads to concrete cracking and rebar corrosion, thereby reducing the material’s structural integrity and the overall structure’s lifetime and raising safety concerns. Ultrasonic nondestructive evaluation (NDE) has been proven to be a valuable technique for assessing concrete properties and monitoring ASR progression in concrete. However, the deployment and analysis of ultrasonic NDE and its data requires specialized expertise, often relying on the engineer’s subjective interpretation. With the surge in computational power, artificial intelligence (AI) and machine learning (ML) algorithms have become popular in automating NDE data analysis. Various industrial sectors are increasingly adopting ML algorithms for NDE data analysis with a growing emphasis on AI–assisted automation. Regulatory agencies are also preparing for this technological shift, anticipating corresponding revisions in standards. Thus, there is an urgent need to identify the capabilities and limitations of current ML technologies for the evaluation of concrete material properties and damage status. Furthermore, the effects of various factors on ML model performance must be thoroughly investigated. The study summarized herein evaluated the effectiveness of two ML models (i.e., support vector regression (SVR) and deep neural network (DNN)) in predicting concrete material damage induced by ASR based on the long-term ultrasonic monitoring data. Four distinct concrete specimens were cast with artificially induced ASR, and over a period exceeding 500 days, ultrasonic signals and expansion data were continuously collected. For the SVR model, wave velocity and 12 other wave features were extracted from the ultrasonic signals, with 6 out of 13 features selected as input for the model. Different combinations of training and testing datasets were designed to explore factors influencing prediction performance, including the range of data within training and testing sets, in addition to various signal preprocessing methodologies. These findings suggest the importance of using a training dataset with a broader data range compared with testing datasets for improved model performance alongside consistent signal preprocessing across datasets.

36 MATERIALS SCIENCE↗

Technical Basis SAVY-4000® Series, 5.5G Container (Rev. 1)

The 5.5 Gallon (5.5G) SAVY-4000® nuclear material storage container is the latest in the SAVY-4000® series. The 5.5G is similar to that of a 1or 2Qt container in functionality with the exception of a larger volume deep drawn and spun form body achieved through increases in the depth and diameter of the container. Here, a technical basis using engineering equivalency analysis, calculation, and test data is presented to establish that the 5.5G SAVY-4000® Container is a DOE Manual 441.1-1 compliant container at a drop height of 9 feet (rather than the typical 12 ft of the other SAVY-4000® containers) and that a twenty-five year design life (as with the currently approved SAVY-4000® series) is justified.

99 GENERAL AND MISCELLANEOUS↗

High Order Wall-Modeled Large-Eddy Simulation on Mixed Unstructured Meshes

In the present study, an algebraic equilibrium wall model previously developed for hexahedral elements is extended to handle mixed meshes including prismatic, tetrahedral, and pyramidal elements in the context of a discontinuous high-order method. This extension is needed for complex geometries, for which high-order mixed elements (e.g., tetrahedral and pyramidal elements) are often necessary near solid walls to avoid meshing challenges. Various design decisions are discussed to achieve the best performance on massively parallel CPU/GPU architectures for a production-level high-order large-eddy simulation solver based on the flux reconstruction/correction procedure via reconstruction method, hpMusic. The extension to other elements is first evaluated using a benchmark channel flow problem at various Reynolds numbers. After that, flow over the NASA high-lift Common Research Model (CRM-HL) from the 4th AIAA High-lift Prediction Workshop is computed to further test the new implementation. Computational results at the third- and fourth-order accuracies are compared with experimental data.

Engineering↗

Constraining Genome-Scale Models to Represent the Bow Tie Structure of Metabolism for 13 C Metabolic Flux Analysis

Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13 C Metabolic Flux Analysis ( 13 C MFA) and Two-Scale 13 C Metabolic Flux Analysis (2S- 13 C MFA) are two techniques used to determine such fluxes. Both operate on the simplifying approximation that metabolic flux from peripheral metabolism into central “core” carbon metabolism is minimal, and can be omitted when modeling isotopic labeling in core metabolism. The validity of this “two-scale” or “bow tie” approximation is supported both by the ability to accurately model experimental isotopic labeling data, and by experimentally verified metabolic engineering predictions using these methods. However, the boundaries of core metabolism that satisfy this approximation can vary across species, and across cell culture conditions. Here, we present a set of algorithms that (1) systematically calculate flux bounds for any specified “core” of a genome-scale model so as to satisfy the bow tie approximation and (2) automatically identify an updated set of core reactions that can satisfy this approximation more efficiently. First, we leverage linear programming to simultaneously identify the lowest fluxes from peripheral metabolism into core metabolism compatible with the observed growth rate and extracellular metabolite exchange fluxes. Second, we use Simulated Annealing to identify an updated set of core reactions that allow for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13 C MFA or 2S- 13 C MFA, as well as provide for a substantially lower set of flux bounds for fluxes into the core as compared with previous methods. We provide an open source Python implementation of these algorithms at https://github.com/JBEI/limitfluxtocore.

13C metabolic flux analysis↗

U.S. Solar Photovoltaic System Cost Benchmark Q1 2018

NREL has been modeling U.S. photovoltaic PV system costs since 2009. The U.S. Solar Photovoltaic System CostBenchmark Q1 2018 report benchmarks costs of U.S. solar PV for residential commercial and utility-scale systems built in the first quarter of 2018 Q1 2018. THE methodology includes bottom-up accounting for all system and project-development costs incurred when installing residential commercial and utility-scale systems and it models the capital costs for such systems.

14 SOLAR ENERGY↗