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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Figure correction of a metallic ellipsoidal neutron focusing mirror

An increasing number of neutron focusing mirrors is being adopted in neutron scattering experiments in order to provide high fluxes at sample positions, reduce measurement time, and/or increase statistical reliability. To realize a small focusing spot and high beam intensity, mirrors with both high form accuracy and low surface roughness are required. To achieve this, we propose a new figure correction technique to fabricate a two-dimensional neutron focusing mirror made with electroless nickel-phosphorus (NiP) by effectively combining ultraprecision shaper cutting and fine polishing. An arc envelope shaper cutting method is introduced to generate high form accuracy, while a fine polishing method, in which the material is removed effectively without losing profile accuracy, is developed to reduce the surface roughness of the mirror. High form accuracy in the minor-axis and the major-axis is obtained through tool profile error compensation and corrective polishing, respectively, and low surface roughness is acquired under a low polishing load. As a result, an ellipsoidal neutron focusing mirror is successfully fabricated with high form accuracy of 0.5 μm peak-to-valley and low surface roughness of 0.2 nm root-mean-square.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Traceable micro-CT scaling accuracy phantom for applications requiring exact measurement of distances or volumes

Purpose: Volumetric x-ray microcomputed tomography (CT) can be employed in a variety of quantitative research applications such as image-guided interventions or characterization of medical devices. To ensure the highest geometric fidelity of images for these applications, a phantom and image processing algorithm have been developed to calibrate the scaling accuracy of micro-CT scanners to a traceable standard and provide corrections to image voxel sizing. Methods: The calibration phantom contains six borosilicate beads whose separations have been measured to a traceable standard. An image processing algorithm compares the known separations of the beads to their separations in micro-CT images. A least-squares solution is used to determine linear scaling correction factors along each of the three scanner axes to minimize errors in the bead separations within the images by correcting the image voxel size. The correction factors were applied to images of a similar phantom with beads at different positions to evaluate the ability of the correction factors to reduce errors at points independent of the fiducial locations in the calibration phantom. The calibration phantom was used to evaluate the scaling accuracy of five different micro-CT scanners representing four different scanner models. Results: In two of the five scanners evaluated, the correction factors significantly reduced the mean error in bead separations in the images from 0.17% to 0.05% and from 0.37% to 0.07% of the actual bead separations, respectively. Scanners yielding similar voxel sizes possessed comparable geometric errors after correction using the phantom. Conclusions: Although the magnitude of the corrections is small, such corrections can be important for demanding micro-CT applications. Even if no voxel size correction is required, the phantom provides an easily implemented method to verify the geometric fidelity of micro-CT scanners to a traceable standard of measurement.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

ATTNChecker: Highly-Optimized Fault Tolerant Attention for Large Language Model Training

Large Language Models (LLMs) have demonstrated remarkable performance in various natural language processing tasks. However, the training of these models is computationally intensive and susceptible to faults, particularly in the attention mechanism, which is a critical component of transformer-based LLMs. In this paper, we investigate the impact of faults on LLM training, focusing on INF, NaN, and near-INF values in the computation results with systematic fault injection experiments. We observe the propagation patterns of these errors, which can trigger non-trainable states in the model and disrupt training, forcing the procedure to load from checkpoints. To mitigate the impact of these faults, we propose ATTNChecker, the first Algorithm-Based Fault Tolerance (ABFT) technique tailored for the attention mechanism in LLMs. ATTNChecker is designed based on fault propagation patterns of LLM and incorporates performance optimization to adapt to both system reliability and model vulnerability while providing lightweight protection for fast LLM training. Evaluations on four LLMs show that ATTNChecker on average incurs on average 7% overhead on training while detecting and correcting all extreme errors. Compared with the state-of-the-art checkpoint/restore approach, ATTNChecker reduces recovery overhead by up to 49×.

Liang, Yuhang [University of Alabama - Birmingham]↗
DOE OSTI2015

SU-E-J-44: A Novel Approach to Quantify Patient Setup and Target Motion for Real-Time Image-Guided Radiotherapy (IGRT)

Purpose Isocenter shifts and rotations to correct patient setup errors and organ motion cannot remedy some shape changes of large targets. We are investigating new methods in quantification of target deformation for realtime IGRT of breast and chest wall cancer. Methods Ninety-five patients of breast or chest wall cancer were accrued in an IRB-approved clinical trial of IGRT using 3D surface images acquired at daily setup and beam-on time via an in-room camera. Shifts and rotations relating to the planned reference surface were determined using iterative-closest-point alignment. Local surface displacements and target deformation are measured via a ray-surface intersection and principal component analysis (PCA) of external surface, respectively. Isocenter shift, upper-abdominal displacement, and vectors of the surface projected onto the two principal components, PC1 and PC2, were evaluated for sensitivity and accuracy in detection of target deformation. Setup errors for some deformed targets were estimated by superlatively registering target volume, inner surface, or external surface in weekly CBCT or these outlines on weekly EPI. Results Setup difference according to the inner-surface, external surface, or target volume could be 1.5 cm. Video surface-guided setup agreed with EPI results to within < 0.5 cm while CBCT results were sometimes (∼20%) different from that of EPI (>0.5 cm) due to target deformation for some large breasts and some chest walls undergoing deep-breath-hold irradiation. Square root of PC1 and PC2 is very sensitive to external surface deformation and irregular breathing. Conclusion PCA of external surfaces is quick and simple way to detect target deformation in IGRT of breast and chest wall cancer. Setup corrections based on the target volume, inner surface, and external surface could be significant different. Thus, checking of target shape changes is essential for accurate image-guided patient setup and motion tracking of large deformable targets. NIH grant for the first author as cionsultant and the last author as the PI.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1981

Integrated and spectral energetics of the GLAS general circulation model

Integrated and spectral error energetics of the Goddard Laboratory for Atmospheric Sciences (GLAS) general circulation model are compared with observations for periods in January 1975, 1976, and 1977. For two cases the model shows significant skill in predicting integrated energetics quantities out to two weeks, and for all three cases, the integrated monthly mean energetics show qualitative improvements over previous versions of the model in eddy kinetic energy and barotropic conversions. Fundamental difficulties remain with leakage of energy to the stratospheric level. General circulation model spectral energetics predictions are compared with the corresponding observational spectra on a day by day basis. Eddy kinetic energy can be correct while significant errors occur in the kinetic energy of wavenumber three. Single wavenumber dominance in eddy kinetic energy and the correlation of spectral kinetic and potential energy are demonstrated.

Tenenbaum, J.↗
NASA NTRS1981

Pilot estimates of glidepath and aim point during simulated landing approaches

Pilot perceptions of glidepath angle and aim point were measured during simulated landings. A fixed-base cockpit simulator was used with video recordings of simulated landing approaches shown on a video projector. Pilots estimated the magnitudes of approach errors during observation without attempting to make corrections. Pilots estimated glidepath angular errors well, but had difficulty estimating aim-point errors. The data make plausible the hypothesis that pilots are little concerned with aim point during most of an approach, concentrating instead on keeping close to the nominal glidepath and trusting this technique to guide them to the proper touchdown point.

Acree, C. W., Jr.↗
NASA NTRS2008

Forward-looking Assimilation of MODIS-derived Snow Covered Area into a Land Surface Model

Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation SCA indicates only the presence or absence of snow, and not snow volume and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to non-physical artifacts in the local water balance. In this paper we present a novel assimilation algorithm that introduces MODIS SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm utilizes observations from up to 72 hours ahead of the model simulation in order to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes both during the snow season and, in some regions, on into the following spring.

Zaitchik, Benjamin F.↗
DOE OSTI2018

Error Analysis of the Thornado Supernova Simulation Code

The iron core collapse of a supernova throws 1.5 solar masses at speeds up to 35% the speed of light into a space with radius 50km, which creates a high density environment capable of generating neutrinos, producing gravitational waves, and driving chemical evolution of matter past iron. By designing a simulation of the process, we can better understand the origins and properties of these rare phenomena which are not seen anywhere else in the universe. Typically, supernovas are simulated with a finite volume method, but we want to incorporate a Nodal Discontinuous Galerkin Method to better utilize high performance computing because the DG method allows us to increase precision without increasing the number of computational elements. This project focuses on the fluid dynamics during collapse and the resulting shockwaves. To understand this, we improved on an existing simulation by comparing benchmark tests against published and theoretical results to identify and correct sources of error. The DG Method creates discontinuous functions across computational elements by solving the Euler fluid equations computed over Runge-Kutta time steps. The DG method allows for discontinuous functions to be built from polynomials defined in individual elements; however, it can lead to unphysical oscillation near discontinuities. We apply the characteristic slope limiter to reduce these affects, but when applied globally it leads to a 1% increase in absolute error. By introducing a Trouble Cell Indicator, which marks certain fluid elements based on the rate of change of observables, we can constrain the limiter to elements near shocks and manage the resulting absolute error. By constraining the limiter to discontinuous regions, we can remove what we know will be unrealistic without impacting naturally occurring oscillations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The effect of image-guided radiation therapy on the margin between the clinical target volume and planning target volume in lung cancer

Introduction: This study aimed to evaluate the effect of image-guided radiation therapy (IGRT) on the margin between the clinical target volume (CTV) and planning target volume (PTV) in lung cancer. Methods: The CTV and PTV margin were determined in three dimensions by four radiation oncologists using a standard method in 10 lung cancer patients, and compared to consensus values. Transfer error was measured using a rigid phantom containing gold markers. Systematic error and random error set up errors were calculated in three dimensions from pre-treatment and post-treatment cone beam CT scans. Finally, the margin between the CTV and PTV was corrected for set up error and calculated. Results: The margins between the CTV and PTV with IGRT (and without IGRT) were 0.88 cm (0.96 cm), 0.99 cm (1.08 cm) and 1.28 cm (1.82 cm) in the anterior and posterior (AP), left and right (LR) and superior and inferior (SI) directions, respectively. Images from two other patients verified the validity of the corrected margin. The target delineation errors of the radiation oncologists are considered to be the largest compared with the set up errors. The application of IGRT reduced the set up errors and the margins between CTV and PTV. Conclusions: The delineation errors of radiation oncologists are the most important factor to consider for the margin between CTV and PTV for lung cancer. IGRT can reduce the margins by reducing the set up errors, especially in the SI direction. Further research is required to assess whether the reduction in the margin is solely based on set up errors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Effects of sample design and landscape features on a measure of environmental heterogeneity

Environmental heterogeneity, an important influence on organisms and ecological processes, can be quantified by the variance of an environmental characteristic over all locations within a study extent. However on landscapes with autocorrelation and gradient patterns, estimating this variance from a sample of locations may lead to errors that cannot be corrected with statistical techniques. We analytically derived the relative expected sampling error of sample designs on landscapes with particular gradient pattern and autocorrelation features. We applied this closed-form approach to temperature observations from an existing study. The expected heterogeneity differed, both in magnitude and direction, amongst sample designs over the study site's likely range of autocorrelation and gradient features. We conducted a simulation study to understand the effects of (i) landscape variability and (ii) design variability on an average sampling error. On 10 000 simulated landscapes with varying gradient and autocorrelation features, we compared estimates of variance from a variety of structured and random sample designs. While gradient patterns and autocorrelation cause large errors for some designs, others yield near-zero average sampling error. Sample location spacing is a key factor in sample design performance. Random designs have larger range of possible sampling errors than structured designs due to the potential for sample arrangements that over- and under-sample certain areas of the landscape. Furthermore, when implementing a new sample design to quantify environmental heterogeneity via variance, we recommend using a simple structured design with appropriate sample spacing. For existing designs, we recommend calculating the relative expected sampling error via our analytical derivation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

A simulation of GPS and differential GPS sensors

The Global Positioning System (GPS) is a revolutionary advance in navigation. Users can determine latitude, longitude, and altitude by receiving range information from at least four satellites. The statistical accuracy of the user's position is directly proportional to the statistical accuracy of the range measurement. Range errors are caused by clock errors, ephemeris errors, atmospheric delays, multipath errors, and receiver noise. Selective Availability, which the military uses to intentionally degrade accuracy for non-authorized users, is a major error source. The proportionality constant relating position errors to range errors is the Dilution of Precision (DOP) which is a function of the satellite geometry. Receivers separated by relatively short distances have the same satellite and atmospheric errors. Differential GPS (DGPS) removes these errors by transmitting pseudorange corrections from a fixed receiver to a mobile receiver. The corrected pseudorange at the moving receiver is now corrupted only by errors from the receiver clock, multipath, and measurement noise. This paper describes a software package that models position errors for various GPS and DGPS systems. The error model is used in the Real-Time Simulator and Cockpit Technology workstation simulations at NASA-LaRC. The GPS/DGPS sensor can simulate enroute navigation, instrument approaches, or on-airport navigation.

Rankin, James M.↗
DOE OSTI2021

Design options for a superconducting ion linac

Following a review of the design options for a superconducting ion linac, we present here an alternative design for the pre-stripper section of the superconducting driver linac for the rare isotope science project (RISP) of the Institute for Basic Science in Korea. The proposed alternative design takes advantage of the recent accelerator developments at Argonne, namely for the recent ATLAS intensity and efficiency upgrade and the Fermilab proton improvement plan project (PIP-II). In particular, the state-of-the-art performance of quarter-wave (QWRs) and half-wave resonators (HWRs), the integrated steering correctors and cold beam position monitors (BPMs) for a compact cryomodule design. In order to simplify the design and avoid frequency transitions, we used two types of QWRs at 81.25 MHz while the baseline design has QWRs at 81.25 MHz and HWRs at 162.5 MHz. The new QWR types were optimized for β ~0.05 and ~0.11, respectively, and corrected for beam steering effects. Nine cryomodules are required to reach the stripping energy of 18.5 MeV/u for uranium beam. An alternative radio-frequency quadrupole (RFQ) design was also developed. It is optimized with the multi-harmonic buncher (MHB) to produce a much smaller longitudinal emittance, offering much needed flexibility for beam tuning and more tolerance to errors. Following the lattice design optimization, end-to-end beam dynamics simulations including most important sources of machine error were performed. The results showed that the design is robust and tolerant to errors with no beam loss observed for typical machine errors.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Evaluation of the Near-Surface Variables in the HRRR Weather Model Using Observations from the ARM SGP Site

Abstract The performance of version 4 of the NOAA High-Resolution Rapid Refresh (HRRR) numerical weather prediction model for near-surface variables, including wind, humidity, temperature, surface latent and sensible fluxes, and longwave and shortwave radiative fluxes, is examined over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) region. The study evaluated the model’s bias and bias-corrected mean absolute error relative to the observations on different time scales. Forecasts of near-surface geophysical variables at five SGP sites (HRRR at 3-km scale) were found to agree well with observations, but some consistent observation–forecast differences also occurred. Sensible and latent heat fluxes are the most challenging variables to be reproduced. The diurnal cycle is the main temporal scale affecting observation–forecast differences of the near-surface variables, and almost all of the variables showed different biases throughout the diurnal cycle. Results show that the overestimation of downward shortwave and the underestimation of downward longwave radiative flux are the two major biases found in this study. The timing and magnitude of downward longwave flux, wind speed, and sensible and latent heat fluxes are also different with contributions from model representations, data assimilation limitations, and differences in scales between HRRR and SGP sites. The positive bias in downward shortwave and negative bias in longwave radiation suggests that the model is underestimating cloud fraction in the study domain. The study concludes by showing a brief comparison with version 3 of the HRRR and shows that version 4 has better performance in almost all near-surface variables. Significance Statement A correct representation of the near-surface variables is important for numerical weather prediction models. This study investigates the capability of the latest NOAA High-Resolution Rapid Refresh (HRRRv4) model in simulating the near-surface variables by comparing against the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) in situ observations. Among others, we find that the surface heat fluxes, such as sensible and latent heat fluxes, are the most difficult variables to be reproduced. This study also shows that the diurnal cycle has the dominant impact on the model’s performance, which means the majority of the outputted near-surface variables have the strong diurnal cycle in their bias errors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

polishCLR: A Nextflow Workflow for Polishing PacBio CLR Genome Assemblies

Long-read sequencing has revolutionized genome assembly, yielding highly contiguous, chromosome-level contigs. However, assemblies from some third generation long read technologies, such as Pacific Biosciences (PacBio) continuous long reads (CLR), have a high error rate. Such errors can be corrected with short reads through a process called polishing. Although best practices for polishing non-model de novo genome assemblies were recently described by the Vertebrate Genome Project (VGP) Assembly community, there is a need for a publicly available, reproducible workflow that can be easily implemented and run on a conventional high performance computing environment. Here, we describe polishCLR (https://github.com/isugifNF/polishCLR), a reproducible Nextflow workflow that implements best practices for polishing assemblies made from CLR data. PolishCLR can be initiated from several input options that extend best practices to suboptimal cases. It also provides re-entry points throughout several key processes, including identifying duplicate haplotypes in purge_dups, allowing a break for scaffolding if data are available, and throughout multiple rounds of polishing and evaluation with Arrow and FreeBayes. PolishCLR is containerized and publicly available for the greater assembly community as a tool to complete assemblies from existing, error-prone long-read data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A bootstrapping approach to social media quantification

Abstract This work considers the use of classifiers in a downstream aggregation task estimating class proportions, such as estimating the percentage of reviews for a movie with positive sentiment. We derive the bias and variance of the class proportion estimator when taking classification error into account to determine how to best trade off different error types when tuning a classifier for these tasks. Additionally, we propose a method for constructing confidence intervals that correctly adjusts for classification error when estimating these statistics. We conduct experiments on four document classification tasks comparing our methods to prior approaches across classifier thresholds, sample sizes, and label distributions. Prior approaches have focused on providing the most accurate point estimate while this work focuses on the creation of correct confidence intervals that appropriately account for classifier error. Compared to the prior approaches, our methods provide lower error and more accurate confidence intervals.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2015

MO-F-CAMPUS-J-05: Toward MRI-Only Radiotherapy: Novel Tissue Segmentation and Pseudo-CT Generation Techniques Based On T1 MRI Sequences

Purpose: To develop and validate a 4 class tissue segmentation approach (air cavities, background, bone and soft-tissue) on T1 -weighted brain MRI and to create a pseudo-CT for MRI-only radiation therapy verification. Methods: Contrast-enhanced T1-weighted fast-spin-echo sequences (TR = 756ms, TE= 7.152ms), acquired on a 1.5T GE MRI-Simulator, are used.MRIs are firstly pre-processed to correct for non uniformity using the non parametric, non uniformity intensity normalization algorithm. Subsequently, a logarithmic inverse scaling log(1/image) is applied, prior to segmentation, to better differentiate bone and air from soft-tissues. Finally, the following method is enrolled to classify intensities into air cavities, background, bone and soft-tissue:Thresholded region growing with seed points in image corners is applied to get a mask of Air+Bone+Background. The background is, afterward, separated by the scan-line filling algorithm. The air mask is extracted by morphological opening followed by a post-processing based on knowledge about air regions geometry. The remaining rough bone pre-segmentation is refined by applying 3D geodesic active contours; bone segmentation evolves by the sum of internal forces from contour geometry and external force derived from image gradient magnitude.Pseudo-CT is obtained by assigning −1000HU to air and background voxels, performing linear mapping of soft-tissue MR intensities in [-400HU, 200HU] and inverse linear mapping of bone MR intensities in [200HU, 1000HU]. Results: Three brain patients having registered MRI and CT are used for validation. CT intensities classification into 4 classes is performed by thresholding. Dice and misclassification errors are quantified. Correct classifications for soft-tissue, bone, and air are respectively 89.67%, 77.8%, and 64.5%. Dice indices are acceptable for bone (0.74) and soft-tissue (0.91) but low for air regions (0.48). Pseudo-CT produces DRRs with acceptable clinical visual agreement to CT-based DRR. Conclusion: The proposed approach makes it possible to use T1-weighted MRI to generate accurate pseudo-CT from 4-class segmentation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Author Correction: Informed-Proteomics: open-source software package for top-down proteomics

Correction to: Nature Methods 14, 909–914, https://doi.org/10.1038/nmeth.4388 (2017), published online 7 August 2017. In the version of this article initially published, the authors erroneously reported the search mode that was used for ProSightPC 3.0 in the Online Methods and in Supplementary Table 3. The results presented in Fig. 5 were obtained with ‘absolute mass’ search mode, not ‘biomarker discovery’ search mode. The ‘biomarker discovery’ search mode of ProSightPC 3.0 looks for subsequences of those contained in the annotated proteoform database (e.g., truncated forms from degradation and/or cleavage). This search mode is expected to generate similar numbers of identifications as Informed-Proteomics, but is also expected to take dramatically longer (~480 CPU hours). Unfortunately, because of these heavy computational requirements, the authors were unable to complete an analysis using this search mode. They chose to use ‘absolute mass’ mode to illustrate the effect of search mode and database choice on the results. ‘Absolute mass’ mode is the most restrictive of the search modes illustrated in Fig. 5, as it searches only for proteoforms explicitly listed in the proteoform database within a user-defined mass tolerance. In addition, in the supplementary information originally published online, Supplementary Table 3 incorrectly stated that ProSightPC v3.0 was used in ‘biomarker discovery’ mode. ‘Absolute mass’ mode was the mode actually used in this comparison. These errors have been corrected in the HTML and PDF versions of this article and in the associated supplementary information.

Park, Jungkap↗

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