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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

CFDverify

Estimating the discretization error of computational fluid dynamics (CFD) or other scientific codes as part of solution verification is often a non-trivial part of the analysis process. Methods can be complicated and may include assumptions/qualifications that need to be checked during analysis. CFD analysts, therefore, are likely to make errors when trying to conduct this necessary analysis on their own in not knowing about the best method for their problem, not correctly implementing a method, or in not have diagnostic tools to determine if the method was correctly applied.

Weinmeister, Justin [Oak Ridge National Laboratory↗
DOE OSTI2022

RNAseq-based transcriptome assembly of Clostridium acetobutylicum for functional genome annotation and discovery

Accurate genome annotations are essential in modern biology and biotechnology, yet they are still largely based on genome sequencing and comparative analyses. We show that the Clostridium acetobutylicum genome annotation can be markedly improved by integrating bioinformatic predictions with RNA sequencing (RNAseq) data. Samples were acquired under butanol, butyrate, and unstressed treatments across various growth conditions. Analysis of an initial assembly revealed errors due to background signals and limitations of assembly algorithms. Hurdles for RNAseq transcriptome mapping include optimizing library complexity and sequencing depth, yet most studies report low sequencing depth and ignore the effect of ribosomal RNA abundance. An integrative analysis was developed to combine motif predictions, single-nucleotide resolution sequencing depth, and library complexity to resolve difficulties in assembly curation. This minimized false positive error and determined gene boundaries, in some cases, to the exact base-pair of prior studies. This will be the first strand-specific transcriptome assembly in a Clostridium organism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Layer-Dependent Bit Error Variation in 3-D NAND Flash Under Ionizing Radiation

In this paper, we studied the total ionization dose (TID) effects on the multilevel-cell (MLC) 3-D NAND flash memory using Co-60 gamma radiation. We found a significant page-to-page bit error variation within a physical memory block of the irradiated memory chip. Our analysis showed that the origin of the bit error variation is the unique vertical layer-dependent TID response of the 3-D NAND. We found that the memory pages located at the upper and lower layers of the 3-D stack show higher fails compared to the middle-layer pages of a given memory block. We confirmed our findings by comparing radiation response of four different chips of the same specification. In addition, we compared the TID response of the MLC 3-D NAND with that of the 2-D NAND chip, which showed less page-to-page variation in bit error within a given memory block. We discuss the possible application of our findings for the radiation-tolerant smart memory controller design.

3-D NAND flash↗
DOE OSTI2022

Region-adaptive, Error-controlled Scientific Data Compression using Multilevel Decomposition

The increase of computer processing speed is significantly outpacing improvements in network and storage bandwidth, leading to the big data challenge in modern science, where scientific applications can quickly generate much more data than that can be transferred and stored. As a result, big scientific data must be reduced by a few orders of magnitude while the accuracy of the reduced data needs to be guaranteed for further scientific explorations. Moreover, scientists are often interested in some specific spatial/temporal regions in their data, where higher accuracy is required. The locations of the regions requiring high accuracy can sometimes be prescribed based on application knowledge, while other times they must be estimated based on general spatial/temporal variation. In this paper, we develop a novel multilevel approach which allows users to impose region-wise compression error bounds. Our method utilizes the byproduct of a multilevel compressor to detect regions where details are rich and we provide the theoretical underpinning for region-wise error control. With spatially varying precision preservation, our approach can achieve significantly higher compression ratios than single-error bounded compression approaches and control errors in the regions of interest.We conduct the evaluations on two climate use cases – one targeting small-scale, node features and the other focusing on long, areal features. For both use cases, the locations of the features were unknown ahead of the compression. By selecting approximately 16% of the data based on multi-scale spatial variations and compressing those regions with smaller error tolerances than the rest, our approach improves the accuracy of post-analysis by approximately 2 × compared to single-error-bounded compression at the same compression ratio. Using the same error bound for the region of interest, our approach can achieve an increase of more than 50% in overall compression ratio.

Gong, Qian↗
DOE OSTI2016

TH-CD-207A-11: Sensitivity Analysis of Action Limits for Real-Time EPID-Based Delivery Verification System Using Artificial Clinical Relevant Error Simulations

Purpose: A real-time patient treatment delivery verification system using EPID (Watchdog) has been developed as an advanced patient safety tool. In a pilot study data was acquired for 119 prostate and head and neck (HN) IMRT patient deliveries to generate body-site specific action limits using statistical process control. The purpose of this study is to determine the sensitivity of Watchdog to detect clinically significant errors during treatment delivery. Methods: Watchdog utilizes a physics-based model to generate a series of predicted transit cine EPID images as a reference data set, and compares these in real-time to measured transit cine-EPID images acquired during treatment using chi comparison (4%, 4mm criteria) after the initial 2s of treatment to allow for dose ramp-up. Four study cases were used; dosimetric (monitor unit) errors in prostate (7 fields) and HN (9 fields) IMRT treatments of (5%, 7%, 10%) and positioning (systematic displacement) errors in the same treatments of (5mm, 7mm, 10mm). These errors were introduced by modifying the patient CT scan and re-calculating the predicted EPID data set. The error embedded predicted EPID data sets were compared to the measured EPID data acquired during patient treatment. The treatment delivery percentage (measured from 2s) where Watchdog detected the error was determined. Results: Watchdog detected all simulated errors for all fields during delivery. The dosimetric errors were detected at average treatment delivery percentage of (4%, 0%, 0%) and (7%, 0%, 0%) for prostate and HN respectively. For patient positional errors, the average treatment delivery percentage was (52%, 43%, 25%) and (39%, 16%, 6%). Conclusion: These results suggest that Watchdog can detect significant dosimetric and positioning errors in prostate and HN IMRT treatments in real-time allowing for treatment interruption. Displacements of the patient require longer to detect however incorrect body site or very large geographic misses will be detected rapidly.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-334: Dosimetric Impacts of Organ at Risk (OAR) Contour Errors in Prostate Volumetric Modulated Arc Therapy (VMAT) Planning: A Sensitivity Study

Purpose: To investigate the dosimetric impacts of OAR contour errors in prostate VMAT planning with a sensitivity analysis method. Methods: Ten randomly selected prostate VMAT patients were used to simulate OAR contour error in rectum and bladder. For each OAR 12 even spaced contour control points were selected in every three slices. For each simulation, only one of the control points was simulated to move inwards or outwards by up to 6 voxels and coordinates of adjacent voxels to that moving control point were moved accordingly with a 3D-spline smooth function. An in-house software was used to predict OARs dosimetric endpoints based on geometric relationship between PTV and OAR. In this study, the V75, V70, V65, V60 of rectum and V80, V75, V70, V65 of bladder with and without perturbed contours were calculated and compared. Results: The percentage of OAR dose volume difference around the reference OAR contours were plotted as iso-error lines overlaid on CT images. The significant difference was shown in OAR contours adjacent to the PTV where high dose gradient exists. When one of the 12 points adjacent to the PTV moved up to 6 voxels, maximum errors of 1.99%, 2.46%, 2.89%, and 3.19% were found in V75, V70, V65, and V60 of the rectum, and 1.59%, 1.67%, 1.87%, and 1.90% were found in V80, V75, V70, and V65 of the bladder, respectively. Conclusion: We can quantify the dosimetric impact of OAR contouring error by evaluating the percentage of OAR dose volume changes in prostate VMAT planning. For the adaptive radiation therapy, the iso-error lines can provide the planner a guideline that which portion of contour needed to be checked carefully because dosimetric sensitivity of contour errors are different for different part of contours.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Determination of Main Components of Glass-Forming Cu–Zr Alloys

A rapid procedure is developed for determination of copper and zirconium in their binary alloys Cu{sub 100–x}Zr{sub x} in the content ranges corresponding to the region of bulk amorphization (x = 30–70) using inductively coupled plasma atomic emission spectroscopy (ICP-AES). The spectrometer operating conditions are optimized, and the analytical spectral lines (Cu II 224.700 nm and Zr II 354.262 nm) are selected, as well as calibration method and sampling procedure: dissolution in the mixture of HNO{sub 3} and HF with addition of HCl, providing for the minimum standard deviation of the analytical signal. A procedure of oxygen determination by inert gas fusion technique and a procedure for determination of copper by spectrophotometry and zirconium by gravimetric analysis in a single sample together with quality control of ICP-AES are developed for the considered alloys. The results of analysis of Cu{sub 100–x}Zr{sub x} alloys according to the developed procedures agree well between themselves and accounting for adjustment of oxygen content agree within the error limits (not more than 0.5 wt %) with the added content of copper and zirconium upon synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Droplet size distributions in turbulent clouds: experimental evaluation of theoretical distributions

Precipitation efficiency and optical properties of clouds, both central to determining Earth's weather and climate, depend on the size distribution of cloud particles. Here in this paper, theoretical expressions for cloud droplet size distribution shape are evaluated using measurements from controlled experiments in a convective-cloud chamber. The experiments are a unique opportunity to constrain theory because they are in steady-state and because the initial and boundary conditions are well characterized compared to typical atmospheric measurements. Three theoretical distributions obtained from a Langevin drift-diffusion approach to cloud formation via stochastic condensation are tested: (a) stochastic condensation with a constant removal time-scale; (b) stochastic condensation with a size-dependent removal time-scale; (c) droplet growth in a fixed supersaturation condition and with size-dependent removal. In addition, a similar Weibull distribution that can be obtained from the drift-diffusion approach, as well as from mechanism-independent probabilistic arguments (e.g., maximum entropy), is tested as a fourth hypothesis. Statistical techniques such as the χ2 test, sum of squared errors of prediction, and residual analysis are employed to judge relative success or failure of the theoretical distributions to describe the experimental data. An extensive set of cloud droplet size distributions are measured under different aerosol injection rates. Five different aerosol injection rates are run both for size-selected aerosol particles, and six aerosol injection rates are run for broad-distribution, polydisperse aerosol particles. In relative comparison, the most favourable comparison to the measurements is the expression for stochastic condensation with size-dependent droplet removal rate. However, even this optimal distribution breaks down for broad aerosol size distributions, primarily due to deviations from the measured large-droplet tail. Lastly, a possible explanation for the deviation is the Ostwald ripening effect coupled with deactivation/activation in polluted cloud conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mesh-based super-resolution of fluid flows with multiscale graph neural networks

A graph neural network (GNN) approach is introduced in this work which enables mesh-based three-dimensional super-resolution of fluid flows. In this framework, the GNN is designed to operate not on the full mesh-based field at once, but on localized meshes of elements (or cells) directly. To facilitate mesh-based GNN representations in a manner similar to spectral (or finite) element discretizations, a baseline GNN layer (termed a message passing layer, which updates local node properties) is modified to account for synchronization of coincident graph nodes, rendering compatibility with commonly used element-based mesh connectivities. Furthermore, the architecture is multiscale in nature, and is comprised of a combination of coarse-scale and fine-scale message passing layer sequences (termed processors) separated by a graph unpooling layer. The coarse-scale processor embeds a query element (alongside a set number of neighboring coarse elements) into a single latent graph representation using coarse-scale synchronized message passing over the element neighborhood, and the fine-scale processor leverages additional message passing operations on this latent graph to correct for interpolation errors. Demonstration studies are performed using hexahedral mesh-based data from Taylor–Green Vortex and backward-facing step flow simulations at Reynolds numbers of 1600 and 3200. Through analysis of both global and local errors, the results ultimately show how the GNN is able to produce accurate super-resolved fields compared to targets in both coarse-scale and multiscale model configurations. Reconstruction errors for fixed architectures were found to increase in proportion to the Reynolds number. Geometry extrapolation studies on a separate cavity flow configuration show promising cross-mesh capabilities of the super-resolution strategy.

Backward-facing step↗
DOE OSTI2021

An asymptotic-preserving 2D-2P relativistic Drift-Kinetic-Equation solver for runaway electron simulations in axisymmetric tokamaks

We propose an asymptotic-preserving (AP), uniformly convergent numerical scheme for the relativistic collisional Drift-Kinetic Equation (rDKE) to simulate runaway electrons in axisymmetric toroidal magnetic field geometries typical of tokamak devices. The approach is derived from an exact Green's function solution with numerical approximations of quantifiable impact, and results in a simple, two-step operator-split algorithm, consisting of a collisional Eulerian step, and a Lagrangian orbit-integration step with analytically prescribed kernels. The AP character of the approach is demonstrated by analysis of the dominant numerical errors, as well as by numerical experiments. We demonstrate the ability of the algorithm to provide accurate answers regardless of plasma collisionality on a circular axisymmetric tokamak geometry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Nondestructive hydrogen analysis of steam-oxidized Zircaloy-4 by wide-angle neutron scattering

In this study, a nondestructive neutron scattering method to precisely measure the hydrogen content in high-temperature steam-oxidized Zircaloy-4 cladding was developed. Zircaloy-4 cladding was used to produce hydrided specimens with hydrogen content up to ≈500 wppm. Following hydrogen charging, the hydrogen content of the hydrided specimens was measured using the vacuum hot extraction method, by which the samples with desired hydrogen concentrations were selected for the neutron study. The hydrided samples were then oxidized in steam up to ≈6.0wt. % at 1100°C. Optical microscopy shows that our hydriding procedure results in uniform distribution of circumferential hydrides across the wall thickness, and uniform oxide layers were formed on the sample surfaces by the steam oxidation. Small- and wide-angle neutron scattering were simultaneously performed to provide a quick (less than an hour per sample) measurement of the hydrogen content in various types of hydrided and oxidized Zircaloy-4. Our study demonstrates that the hydrogen in pre-oxidized Zircaloy-4 cladding can be measured very accurately by both small- and wide-angle neutron scattering. For steam-oxidized samples, the small-angle neutron scattering is contaminated with coherent scattering from additional structural features induced by the steam oxidation. However, the scattering intensity of the wide-angle neutron scattering increases proportionally with the hydrogen charged in the samples. The hydrogen content and wide-angle neutron scattering intensity are highly linearly correlated for the oxidized cladding samples examined in this work, and can be used to precisely determine the hydrogen content in steam-oxidized Zircaloy-4 samples. Hydrogen contents determined by neutron scattering of oxidation samples were also found to be consistent with the results of chemical analysis within acceptable margins for error.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Improved guided-wave acoustic defect detection and localization in pipes under varying temperature conditions using deep learning

Early defect detection in pipelines is critical across industries, particularly in the oil and gas sector, where failures result in significant maintenance costs and operational disruptions. Acoustic guided-wave techniques are widely used for nondestructive evaluation of pipeline defects due to their long-distance propagation capability. However, environmental variations, sensitivity limitations, and complex signal interpretation challenges limit the effectiveness of traditional signal processing approaches with guided-wave signals. Recent advances in deep learning methods have demonstrated remarkable success in solving complex real-world problems in many fields. In particular, deep-learning-based signal processing holds substantial promise to overcome limitations and challenges of conventional signal processing. This study presents a deep learning framework for pipeline inspection using acoustic guided-wave signals under temperature varying environments. The proposed framework employs a dual-path one-dimensional convolutional autoencoder that combines defect detection, localization, and temperature prediction functions. The proposed system utilizes multi-mode and broadband acoustic waves with an optimized number of sensors that provide high accuracy while retaining practical simplicity. Experimental validation is performed on a carbon steel pipe. The results indicate exceptional defect detection accuracy and precise defect localization with a mean absolute error of 66 mm. The proposed technique also predicts the effective average temperature of the pipe with a mean absolute error of 0.2°C. Comparative analysis shows superior performance of the proposed method over a traditional method previously developed by the authors' team. These results highlight the potential of integrating deep learning methods into guided-wave pipeline inspection systems to improve reliability under varying environmental conditions.

42 ENGINEERING↗
DOE OSTI2015

Data Covariances from R-Matrix Analyses of Light Nuclei

After first reviewing the parametric description of light-element reactions in multichannel systems using R-matrix theory and features of the general LANL R-matrix analysis code EDA, we describe how its chi-square minimization procedure gives parameter covariances. This information is used, together with analytically calculated sensitivity derivatives, to obtain cross section covariances for all reactions included in the analysis by first-order error propagation. Examples are given of the covariances obtained for systems with few resonances ({sup 5}He) and with many resonances ({sup 13}C ). We discuss the prevalent problem of this method leading to cross section uncertainty estimates that are unreasonably small for large data sets. The answer to this problem appears to be using parameter confidence intervals in place of standard errors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Use of Physics to Improve Solar Forecast: Physics-Informed Persistence Models for Simultaneously Forecasting GHI, DNI, and DHI

Observation-based statistical models have been widely used in forecasting solar energy; however, existing models often lack a clear relation to physics and are limited largely to global horizontal irradiance (GHI) forecasts over relatively short time horizons (< 1 hour). Incorporating physics into observation-based models, increasing forecast time horizons and developing a model system for forecasting not only GHI but also direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI) remain challenging, especially under cloudy conditions because of complex cloud-radiation interactions. This work attempts to address these challenges by developing a hierarchy of four new physics-informed persistence models that can be used to simultaneously forecast GHI, DNI and DHI. The decade-long measurements (1998 to 2014) at the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM)'s Southern Great Plains (SGP) Central Facility site are used to evaluate the performance of the new models. Overall, the results show that the new physics-informed forecast models generally outperform the simple and smart persistence models, and improve the forecast accuracy at lead times from 1.25 hours up to 6 hours. Further analysis reveals that the forecast error is highly related to the error and temporal variability of the assumed cloud predictor. The best model for forecasting different radiative components can be explained by the relationship between solar irradiances and cloud properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Ab Initio Molecular Dynamics Spectra for Characterization of Hydrated Al 2 O 3 Supported MoO x

The structure of supported MoO x /Al 2 O 3 catalysts is investigated using ab initio molecular dynamics (AIMD) and density-functional theory (DFT). Phase diagrams were computed to understand the hydroxylation coverage as a function of the temperature, H 2 O partial pressure, and MoO x loading. We relate the shifts in experimental Raman vibrational frequencies under hydrated conditions to hydrogen bonding interactions and the MoO x anchoring location. We showcase that the use of AIMD as a benchmark for DFT can provide insight into how, under certain hydrated conditions, DFT excels as an inexpensive method for computing vibrational frequencies, while, under dehydrated conditions, it is susceptible to the largest errors. Additionally, to facilitate the analysis of the hydroxyl region of experimental infrared spectra, we compute the power spectra of individual hydroxyls and see a strong relationship between OH stretching frequencies and the surrounding coordination environment, which are also impacted by anchored MoO x . Here, we compare computational and experimental IR and Raman spectra of catalysts synthesized herein under the same conditions.

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

Inverse design of photonic surfaces via multi fidelity ensemble framework and femtosecond laser processing

We demonstrate a multi-fidelity (MF) machine learning ensemble framework for the inverse design of photonic surfaces, trained on a dataset of 11,759 samples that we fabricate using high throughput femtosecond laser processing. The MF ensemble combines an initial low fidelity model for generating design solutions, with a high fidelity model that refines these solutions through local optimization. The combined MF ensemble can generate multiple disparate sets of laser-processing parameters that can each produce the same target input spectral emissivity with high accuracy (root mean squared errors < 2%). SHapley Additive exPlanations analysis shows transparent model interpretability of the complex relationship between laser parameters and spectral emissivity. Finally, the MF ensemble is experimentally validated by fabricating and evaluating photonic surface designs that it generates for improved efficiency energy harvesting devices. Our approach provides a powerful tool for advancing the inverse design of photonic surfaces in energy harvesting applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Critical analysis and remedy of switching failures in straintronic logic using Bennett clocking in the presence of thermal fluctuations

Straintronic logic is a promising platform for beyond Moore's law computing. Using Bennett clocking mechanism, information can propagate through an array of strain-mediated multiferroic nanomagnets, exploiting the dipolar coupling between the magnets without having to physically interconnect them. Here, we perform a critical analysis of switching failures, i.e., error in information propagation due to thermal fluctuations through a chain of such straintronic devices. We solved stochastic Landau-Lifshitz-Gilbert equation considering room-temperature thermal perturbations and show that magnetization switching may fail due to inherent magnetization dynamics accompanied by thermally broadened switching delay distribution. Avenues available to circumvent such issue are proposed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Molecular electric moments calculated by using natural orbital functional theory

The molecular electric dipole, quadrupole, and octupole moments of a selected set of 21 spin-compensated molecules are determined employing the extended version of the Piris natural orbital functional 6 (PNOF6), using the triple-ζ Gaussian basis set with polarization functions developed by Sadlej, at the experimental geometries. The performance of the PNOF6 is established by carrying out a statistical analysis of the mean absolute errors with respect to the experiment. The calculated PNOF6 electric moments agree satisfactorily with the corresponding experimental data and are in good agreement with the values obtained by accurate ab initio methods, namely, the coupled-cluster single and doubles and multi-reference single and double excitation configuration interaction methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗