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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

DFT and microkinetic comparison of Pt, Pd and Rh-catalyzed ammonia oxidation

Ammonia oxidation is the heart of the Ostwald process and is important in emissions control. Catalytic behaviors are a function of conditions and are observed to vary across the platinum group metals (PGMs) Pt, Pd, Rh. Here, we combine density functional theory computations and microkinetic modeling to rationalize these dependencies. We compute reactions over model (2 1 1) and (1 1 1) surfaces of PGMs. Binding energies are similar on Pd and Pt and generally greater on Rh, while activation energies vary across all metals. Rates on (2 1 1) surfaces are greater than (1 1 1) surfaces. Additionally, the stepped Pt is most active and stepped Rh most selective to N 2 at ammonia slip conditions, while at Ostwald process conditions, stepped Pd is most active and stepped Pt most selective to NO. Degree of rate and selectivity control analysis provides insights into the reactions limiting performance of PGMs. Both activation barriers and surface coverages influence rates and selectivities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons

Neural networks (NNs) are currently changing the computational paradigm on how to combine data with mathematical laws in physics and engineering in a profound way, tackling challenging inverse and ill-posed problems not solvable with traditional methods. However, quantifying errors and uncertainties in NN-based inference is more complicated than in traditional methods. This is because in addition to aleatoric uncertainty associated with noisy data, there is also uncertainty due to limited data, but also due to NN hyperparameters, overparametrization, optimization and sampling errors as well as model misspecification. Although there are some recent works on uncertainty quantification (UQ) in NNs, there is no systematic investigation of suitable methods towards quantifying the total uncertainty effectively and efficiently even for function approximation, and there is even less work on solving partial differential equations and learning operator mappings between infinite-dimensional function spaces using NNs. In this work, we present a comprehensive framework that includes uncertainty modeling, new and existing solution methods, as well as evaluation metrics and post-hoc improvement approaches. Further, to demonstrate the applicability and reliability of our framework, we present an extensive comparative study in which various methods are tested on prototype problems, including problems with mixed input-output data, and stochastic problems in high dimensions. In the Appendix, we include a comprehensive description of all the UQ methods employed. Further, to help facilitate the deployment of UQ in Scientific Machine Learning research and practice, we present and develop in [1] an open-source Python library (github.com/Crunch-UQ4MI/neuraluq), termed NeuralUQ, that is accompanied by an educational tutorial and additional computational experiments.

11 physics-informed neural networks↗
DOE OSTI2024

Comparison of atmospheric radionuclide dispersion models for a risk-informed consequence-driven advanced reactor licensing framework

Current nuclear facility emergency planning zones (EPZs) are based on outdated distance-based criteria, predating comprehensive dose and risk-informed frameworks. Recent advancements in simulation tools have permitted the development of site-specific, dose, and risk-based consequence-driven assessment frameworks. This study investigated the computation of advanced reactor (AR) EPZs using two atmospheric dispersion models: a straight-line Gaussian plume model (GPM) and a semi-Lagrangian Particle in Cell (PIC). Two case studies were conducted: (1) benchmarking the NRC SOARCA study for the Peach Bottom Nuclear Generating Station and (2) analyzing an advanced INL Heat Pipe Design A microreactor's end-of-cycle inventory. The dose criteria for both cases were 10 mSv at mean weather conditions and 50 mSv at 95th percentile weather conditions at 96 h post-release. Results demonstrated that GPM and PIC estimated similar mean peak dose levels for large boiling water reactors in the farfield case, placing EPZ limits beyond current regulations. For ARs with source terms remaining in the nearfield, PIC modeling without specific nearfield considerations could result in excessively high doses and inaccurate EPZ designations. PIC dispersion demonstrated an order of magnitude higher estimate of nearfield inhalation dose contribution when compared to GPM results. Furthermore, both models significantly reduced EPZ sizing within the nearfield. Thus, reductions in the AR source term may eliminate the need for a separate EPZ.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2024

Comparison of source-location algorithms for atmospheric samplers

Numerous algorithms have been developed to determine the source characteristics for an atmospheric release, e.g., (Bieringer et al., 2017). This study compares three models that have been applied to the data collected by the International Monitoring System operated by the Comprehensive Nuclear-Test-Ban Treaty Preparatory Commission to estimate source event parameters. Each model uses a different approach to estimate the parameters. A deterministic model uses a possible source region (PSR) approach (Ringbom et al., 2014) that is based on the correlation between predicted and measured sample values. An unnamed model developed at Pacific Northwest National Laboratory (herein called BAYEST) uses a Bayesian formulation (Eslinger et al., 2019; Eslinger et al., 2020; Eslinger and Schrom, 2016). The FREAR model uses a different Bayesian formulation (De Meutter and Hoffman, 2020; De Meutter et al., 2021; Pieter De Meutter, 2021). The performance of the three source-location models is evaluated with 100 synthetic release cases for the single xenon isotope, 133 Xe. The release cases resulted in detections in a fictitious network with 120 noble gas samplers. All three source-location models use the same sampling data. The two Bayesian models yield more accurate location estimates than the deterministic PSR model, with FREAR having slightly better location performance than BAYEST. Samplers with collection periods of 3, 6, 8, 12, and 24-h were used. Results from BAYEST show that location accuracy improves with each reduction in sample collection length. The BAYEST model is slightly better for estimating the start time of the release. The PSR model has about the same spread in start times as the FREAR model, but the PSR results have a better average start time. The Bayesian source-location algorithms give more accurate results than the PSR approach, and provide release magnitude estimates, while the base PSR model does not estimate the release magnitude. This investigation demonstrates that a reasonably dense sampling grid will sometimes yield poor location and time estimates regardless of the model. The poor estimates generally coincide with cases where there is a much larger distance between the release point and the first detecting sampler than the average sampler spacing.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Core-scale numerical simulation and comparison of breakdown of shale and resulting fractures using sc-CO 2 and water as injectants

Supercritical carbon dioxide (sc-CO 2 ) is an alternative to water for stimulation of low permeability systems such as shale gas and geothermal resources. Previously core-scale experimental studies have compared the behavior of CO 2 to water injection for sample breakdown. Due to differences in experimental setup and core sample preparation, inconsistent or even apparently contradictory conclusions have resulted. To reconcile this contradiction, a phase-field numerical model is applied to understand hydraulic fracturing experiments using Green River shale found in the literature. The finite element numerical model incorporates a rate-dependent phase-field fracture model developed separately to describe fracture initiation and growth. We investigate the impact of various material and fluid properties on the resulting fractures. Most importantly, we study the effect of fluid properties and boundary conditions on the breakdown pressure, including the direction of the resulting fracture plane. Model results predict that (1) sc-CO 2 injection in the laboratory may result in greater breakdown pressure than that of water under no-flow boundary conditions because lower viscosity sc-CO 2 may result in pressure build up at the core boundary that opposes fracture initiation and (2) lower viscosity sc-CO 2 also produces fast-propagating fractures that are less influenced by the bedding plane on their resulting fracture topology. Here our model offers a straightforward explanation and reconciliation of existing experimental observations, as well as a means to extrapolate to new conditions. Exploration of field-scale conditions suggests less pronounced or no elevation in breakdown pressure when sc-CO 2 is injected because the pressure build up effect at the system boundary is significantly less or absent at field length scales.

42 ENGINEERING↗
DOE OSTI2020

Effects of surface runoff and infiltration partition methods on hydrological modeling: A comparison of four schemes in two watersheds in the Northeastern US

The ratio according to which the precipitation/snowmelt is divided into surface and subsurface water is of primary importance to watershed scale hydrological modeling. The present study compared four different surface runoff and infiltration partition methods in the Richards-equation-based SWAT model (RSWAT), i.e., daily curve number method (DC-RSWAT), hourly curve number method (HC-RSWAT), Green-Ampt method (GA-RSWAT), and effective infiltration capacity method (EIC-RSWAT). These four versions of RSWAT and a daily-curve-number-based SWAT (DC-SWAT) were used to simulate daily flow rate (from 2001 to 2015) at the outlets of the Tuckahoe Creek Watershed (TCW) and Greensboro Watershed (GW) of the Chesapeake Bay in Maryland. Parameter sensitivity analysis, calibration, and prediction uncertainty analysis were conducted. The results indicate that surface runoff and infiltration partition methods have pronounced impacts on model performance. Comparative analysis showed that DC-RSWAT outperformed other versions of RSWAT for both calibration (from 2001 to2007) and validation (from 2008 to 2015) periods in the two test watersheds. In general, DC-RSWAT achieved more accurate deterministic flow simulation and reliable uncertainty estimation than other versions. As such, daily-curve-number method is recommended for surface runoff and infiltration partition in RSWAT for simulating stream flow.

hydrology, modeling, streamflow↗
DOE OSTI2021

Comparison of fiber-optic distributed temperature sensing and high-sensitivity sensor spatial surveying of stream temperature

Measuring surface water temperature spatial variability is needed to estimate the interaction between surface water and groundwater, evaluate fish habitat and thermal inertia, and to estimate streamflow frequency and duration. Fiber optic distributed temperature sensing (FO-DTS) has been used in rivers and lakes, providing high-resolution and sensitive temperature monitoring over large temporal and spatial scales. However, in streams with cobbly or bedrock-lined streambeds and variable bathymetry, use of FO-DTS to measure temperature close to the surface water and groundwater interface can be challenging if even feasible. FO-DTS can also be costly, involve difficult installations, and require an advanced understanding of the technology, calibration, and data processing. In this study, we compared FO-DTS stream temperature survey results to an alternative temperature survey method employing a towed transect of high-resolution temperature loggers spaced at 1-m and transported in the stream along the study reach, to measure the spatial distribution of stream-water temperature in East Fork Poplar Creek near Oak Ridge, Tennessee, USA. We assessed the applicability and limitations of the two methods, and quantitatively compared in-situ temperature survey results measured simultaneously with each method. Regression results showed strong temporal and spatial correlation between the two methods. Differences were only elevated near the stream banks in areas that were coincident with correlation slope deviations from unity, which was attributed to shallower water and lower data density. Kriging standard errors were also low at channel center with minor increases near the stream banks. Furthermore, the results suggested that the array of the individual temperature sensors can provide a practical alternative to FO-DTS for thermal characterization of surface water, providing slightly lower spatial and temporal resolution, but with higher accuracy of temperature measurement, with greater simplicity, and with a broader range of conditions where it may be applied.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Machinability comparison of additively manufactured and traditionally wrought Ti-6Al-4V alloys using single-point cutting

Post-machining is often needed to provide high dimensional accuracy and fine surface finish for additively manufactured Ti-6Al-4V (Ti64). The material inhomogeneity, such as pores and microstructures, can affect the machining behavior of this already difficult-machine alloy. This study adopts a holistic approach to compare the machinability of additively manufactured and traditionally wrought Ti64 in terms of key machining factors, including forces, temperature, and vibration and the major machining outcomes including tool life, surface finish, and dimensional accuracy. Stress-relief annealing is applied to each of the part conditions as a secondary variable to observe the additional effects. The results show that AM is not particularly more difficult to machine in terms of cutting force and temperature, but it creates high cutting vibrations across a wide range of frequencies (to and over 5 kHz). The high vibrations do not lead to worse surface finish or dimensional accuracy but tend to worsen the tool life by chipping off the cutting edge. The vibration can be attributed to the brittle martensitic microstructure found in additively manufactured Ti64, which is also evidenced by the more serrated chips. Stress-relieving is found to change the microstructure and reduce the level of vibration to that of the wrought counterpart.

36 MATERIALS SCIENCE↗