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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

WE-AB-207A-01: BEST IN PHYSICS (IMAGING): High-Resolution Cone-Beam CT of the Extremities and Cancellous Bone Architecture with a CMOS Detector

Purpose: Extremity cone-beam CT (CBCT) with an amorphous silicon (aSi) flat-panel detector (FPD) provides low-dose volumetric imaging with high spatial resolution. We investigate the performance of the newer complementary metal-oxide semiconductor (CMOS) detectors to enhance resolution of extremities CBCT to ∼0.1 mm, enabling morphological analysis of trabecular bone. Quantitative in-vivo imaging of bone microarchitecture could present an important advance for osteoporosis and osteoarthritis diagnosis and therapy assessment. Methods: Cascaded systems models of CMOS- and FPD-based extremities CBCT were implemented. Performance was compared for a range of pixel sizes (0.05–0.4 mm), focal spot sizes (0.3–0.6 FS), and x-ray techniques (0.05–0.8 mAs/projection) using detectability of high-, low-, and all-frequency tasks for a nonprewhitening observer. Test-bench implementation of CMOS-based extremity CBCT involved a Teledyne DALSA Xineos3030HR detector with 0.099 mm pixels and a compact rotating anode x-ray source with 0.3 FS (IMD RTM37). Metrics of bone morphology obtained using CMOS-based CBCT were compared in cadaveric specimens to FPD-based system using a Varian PaxScan4030 (0.194 mm pixels). Results: Finer pixel size and reduced electronic noise for CMOS (136 e compared to 2000 e for FPD) resulted in ∼1.9× increase in detectability for high-frequency tasks and ∼1.1× increase for all-frequency tasks. Incorporation of the new x-ray source with reduced focal spot size (0.3 FS vs. 0.5 FS used on current extremities CBCT) improved detectability for CMOS-based CBCT by ∼1.7× for high-frequency tasks. Compared to FPD CBCT, the CMOS detector yielded improved agreement with micro-CT in measurements of trabecular thickness (∼1.7× reduction in relative error), bone volume (∼1.5× reduction), and trabecular spacing (∼3.5× reduction). Conclusion: Imaging performance modelling and experimentation indicate substantial improvements for high-frequency imaging tasks through adoption of the CMOS detector and small FS x-ray source, motivating the use of these components in a new system for quantitative in-vivo imaging of trabecular bone. Financial Support: US NIH grant R01EB018896. Qian Cao is a Howard Hughes Medical Institute International Student Research Fellow. Disclosures: W Zbijewski, J Siewerdsen and A Sisniega receive research funding from Carestream Health.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

X-Ray Stereo Digital Image Correlation

Digital Image Correlation (DIC) is a well-established, non-contact diagnostic technique used to measure shape, displacement and strain of a solid specimen subjected to loading or deformation. Yet, measurements using standard DIC can have significant errors or be completely infeasible in challenging experiments, such as explosive, combustion, or fluid-structure interaction applications, where beam-steering due to index of refraction variation biases measurements or where the sample is engulfed in flames or soot. To address these challenges, we propose using X-ray imaging instead of visible light imaging for stereo-DIC, since refraction of X-rays is negligible in many situations, and X-rays can penetrate occluding material. Two techniques of creating an appropriate pattern for X-ray DIC are presented, both based on adding a dense material in a random speckle pattern on top of a less-dense specimen. A standard dot-calibration target is adapted for X-ray imaging, allowing the common bundle-adjustment calibration process in commercial stereo-DIC software to be used. High-quality X-ray images with sufficient signal-to-noise ratios for DIC are obtained for aluminum specimens with thickness up to 22.2 mm, with a speckle pattern thickness of only 80 μm of tantalum. The accuracy and precision of X-ray DIC measurements are verified through simultaneous optical and X-ray stereo-DIC measurements during rigid in-plane and out-of-plane translations, where errors in the X-ray DIC displacements were approximately 2–10 μm for applied displacements up to 20 mm. Finally, a vast reduction in measurement error—5–20 times reduction of displacement error and 2–3 times reduction of strain error—is demonstrated, by comparing X-ray and optical DIC when a hot plate induced a heterogeneous index of refraction field in the air between the specimen and the imaging systems. Subsequently, these findings show the feasibility of using X-ray-based stereo-DIC for non-contact measurements in exacting experimental conditions, where optical DIC cannot be used.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

Daily Orthogonal Kilovoltage Imaging Using a Gantry-Mounted On-Board Imaging System Results in a Reduction in Radiation Therapy Delivery Errors

Purpose: To determine whether the use of routine image guided radiation therapy (IGRT) using pretreatment on-board imaging (OBI) with orthogonal kilovoltage X-rays reduces treatment delivery errors. Methods and Materials: A retrospective review of documented treatment delivery errors from 2003 to 2009 was performed. Following implementation of IGRT in 2007, patients received daily OBI with orthogonal kV X-rays prior to treatment. The frequency of errors in the pre- and post-IGRT time frames was compared. Treatment errors (TEs) were classified as IGRT-preventable or non-IGRT-preventable. Results: A total of 71,260 treatment fractions were delivered to 2764 patients. A total of 135 (0.19%) TEs occurred in 39 (1.4%) patients (3.2% in 2003, 1.1% in 2004, 2.5% in 2005, 2% in 2006, 0.86% in 2007, 0.24% in 2008, and 0.22% in 2009). In 2007, the TE rate decreased by >50% and has remained low (P = .00007, compared to before 2007). Errors were classified as being potentially preventable with IGRT (e.g., incorrect site, patient, or isocenter) vs. not. No patients had any IGRT-preventable TEs from 2007 to 2009, whereas there were 9 from 2003 to 2006 (1 in 2003, 2 in 2004, 2 in 2005, and 4 in 2006; P = .0058) before the implementation of IGRT. Conclusions: IGRT implementation has a patient safety benefit with a significant reduction in treatment delivery errors. As such, we recommend the use of IGRT in routine practice to complement existing quality assurance measures.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1986

Correction function in the Lidar equation and the solution techniques for CO2 Lidar date reduction

For lidar systems with long laser pulses the unusual behavior of the near-range signals causes serious difficulties and large errors in reduction. The commonly used lidar equation is no longer applicable since the convolution of the laser pulse with the atmospheric parameter distributions should be taken into account. It is important to give more insight into this problem and find the solution techniques. Starting from the original equation, a general form is suggested for the single scattering lidar equation where a correction function Cr is introduced. The correction Function Cr(R) derived from the original equation indicates the departure from the normal lidar equation. Examples of Cr(R) for a coaxial CO2 lidar system are presented. The Differential Absorption Lidar (DIAL) errors caused by the differences of Cr(R) for H2O measurements are plotted against height.

Zhao, Y.↗
DOE OSTI2015

SU-E-T-186: Cloud-Based Quality Assurance Application for Linear Accelerator Commissioning

Purpose: To identify anomalies and safety issues during data collection and modeling for treatment planning systems Methods: A cloud-based quality assurance system (AQUIRE - Automated QUalIty REassurance) has been developed to allow the uploading and analysis of beam data aquired during the treatment planning system commissioning process. In addition to comparing and aggregating measured data, tools have also been developed to extract dose from the treatment planning system for end-to-end testing. A gamma index is perfomed on the data to give a dose difference and distance-to-agreement for validation that a beam model is generating plans consistent with the beam data collection. Results: Over 20 linear accelerators have been commissioning using this platform, and a variety of errors and potential saftey issues have been caught through the validation process. For example, the gamma index of 2% dose, 2mm DTA is quite sufficient to see curves not corrected for effective point of measurement. Also, data imported into the database is analyzed against an aggregate of similar linear accelerators to show data points that are outliers. The resulting curves in the database exhibit a very small standard deviation and imply that a preconfigured beam model based on aggregated linear accelerators will be sufficient in most cases. Conclusion: With the use of this new platform for beam data commissioning, errors in beam data collection and treatment planning system modeling are greatly reduced. With the reduction in errors during acquisition, the resulting beam models are quite similar, suggesting that a common beam model may be possible in the future. Development is ongoing to create routine quality assurance tools to compare back to the beam data acquired during commissioning. I am a medical physicist for Alzyen Medical Physics, and perform commissioning services.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1988

An alternative to Guyan reduction of finite-element models

Structural modeling is a key part of structural system identification for large space structures. Finite-element structural models are commonly used in practice because of their general applicability and availability. The initial models generated by using a standard computer program such as NASTRAN, ANSYS, SUPERB, STARDYNE, STRUDL, etc., generally contain tens of thousands of degrees of freedom. The models must be reduced for purposes of identification. Not only does the magnitude of the identification effort grow exponentially as a function of the number of degrees of freedom, but numerical procedures may also break down because of accumulated round-off errors. Guyan reduction is usually applied after a static condensation. Misapplication of Guyan reduction can lead to serious modeling errors. It is quite unfortunate and disappointing, since the accuracy of the original detailed finite-element model one tries very hard to achieve is lost by the reduction. First, why and how Guyan reduction always causes loss of accuracy is examined. An alternative approach is then introduced. The alternative can be thought of as an improvement of Guyan reduction, the Rayleigh-Ritz method, and in particular the recent algorithm of Wilson, Yuan, and Dickens. Unlike Guyan reduction, the use of the alternative does not need any special insight, experience, or skill for partitioning the structural degrees of freedom. In addition to model condensation, this alternative approach can also be used for predicting analytically, quickly, and economically, what are those structural modes that are excitable by a force actuator at a given trial location. That is, in the excitation of the structural modes for identification, it can be used for guiding the placement of the force actuators.

Lin, Jiguan Gene↗
NASA NTRS1987

Computational procedures for evaluating the sensitivity derivatives of vibration frequencies and Eigenmodes of framed structures

Computational procedures are presented for evaluating the sensitivity derivatives of the vibration frequencies and eigenmodes of framed structures. Both a displacement and a mixed formulation are used. The two key elements of the computational procedure are: (a) Use of dynamic reduction techniques to substantially reduce the number of degrees of freedom; and (b) Application of iterative techniques to improve the accuracy of the derivatives of the eigenmodes. The two reduction techniques considered are the static condensation and a generalized dynamic reduction technique. Error norms are introduced to assess the accuracy of the eigenvalue and eigenvector derivatives obtained by the reduction techniques. The effectiveness of the methods presented is demonstrated by three numerical examples.

Fetterman, Timothy L.↗
NASA NTRS1989

Effect of ephemeris errors on the accuracy of the computation of the tangent point altitude of a solar scanning ray as measured by the SAGE 1 and 2 instruments

An analysis was made of the error in the minimum altitude of a geometric ray from an orbiting spacecraft to the Sun. The sunrise and sunset errors are highly correlated and are opposite in sign. With the ephemeris generated for the SAGE 1 instrument data reduction, these errors can be as large as 200 to 350 meters (1 sigma) after 7 days of orbit propagation. The bulk of this error results from errors in the position of the orbiting spacecraft rather than errors in computing the position of the Sun. These errors, in turn, result from the discontinuities in the ephemeris tapes resulting from the orbital determination process. Data taken from the end of the definitive ephemeris tape are used to generate the predict data for the time interval covered by the next arc of the orbit determination process. The predicted data are then updated by using the tracking data. The growth of these errors is very nearly linear, with a slight nonlinearity caused by the beta angle. An approximate analytic method is given, which predicts the magnitude of the errors and their growth in time with reasonable fidelity.

Buglia, James J.↗
DOE OSTI2016

Multi-Physics Surrogate Modeling with Dimensionality Reduction

This summary provides a new algorithm to construct surrogate models for multi-physics, nonlinear, high dimensional models which typically suffer from the curse of dimensionality. To deal with the high computational cost and difficult error estimation, we employ recent advances in reduced order modeling (ROM) techniques to do an error-preserving reduction for the number of influential model parameters, followed by a conventional surrogate construction process. To implement ROM for a multiphysics model, a range finding algorithm (RFA) is used to identify a linear transformation in which the number of influential parameters can be minimized and the errors resulting from the non-influential parameters can be upper-bounded. The proposed algorithm is applied to the MAMMOTH coupled code system developed at the Idaho National Laboratory. In particular, we investigate the reducibility of Rattlesnake and BISON codes and their multi-physics coupling. The most important result of this work is that the reduction obtained with coupled physics is more significant than that with individual physics models. This summary explores the application of ROM techniques on multi-physics coupling codes system. Concise methodology is provided and selected numerical results are provided to show that coupling system provides additional reduction at interfaces. Future work could be invested to determine the optimum surrogate model format. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Many-body expansion based machine learning models for octahedral transition metal complexes

Abstract Graph-based machine learning (ML) models for material properties show great potential to accelerate virtual high-throughput screening of large chemical spaces. However, in their simplest forms, graph-based models do not include any 3D information and are unable to distinguish stereoisomers such as those arising from different orderings of ligands around a metal center in coordination complexes. In this work we present a modification to revised autocorrelation descriptors, a molecular graph featurization method, for predicting spin state dependent properties of octahedral transition metal complexes (TMCs). Inspired by analytical semi-empirical models for TMCs, the new modeling strategy is based on the many-body expansion (MBE) and allows one to tune the captured stereoisomer information by changing the truncation order of the MBE. We present the necessary modifications to include this approach in two commonly used ML methods, kernel ridge regression and feed-forward neural networks. On a test set composed of all possible isomers of binary TMCs, the best MBE models achieve mean absolute errors (MAEs) of 2.75 kcal mol −1 on spin-splitting energies and 0.26 eV on frontier orbital energy gaps, a 30%–40% reduction in error compared to models based on our previous approach. We also observe improved generalization to previously unseen ligands where the best-performing models exhibit MAEs of 4.00 kcal mol −1 (i.e. a 0.73 kcal mol −1 reduction) on the spin-splitting energies and 0.53 eV (i.e. a 0.10 eV reduction) on the frontier orbital energy gaps. Because the new approach incorporates insights from electronic structure theory, such as ligand additivity relationships, these models exhibit systematic generalization from homoleptic to heteroleptic complexes, allowing for efficient screening of TMC search spaces.

Meyer, Ralf (ORCID:0000000322360261)↗
NASA NTRS2014

Carbon Monitoring System Flux Estimation and Attribution: Impact of ACOS-GOSAT X(CO2) Sampling on the Inference of Terrestrial Biospheric Sources and Sinks

Using an Observing System Simulation Experiment (OSSE), we investigate the impact of JAXA Greenhouse gases Observing SATellite 'IBUKI' (GOSAT) sampling on the estimation of terrestrial biospheric flux with the NASA Carbon Monitoring System Flux (CMS-Flux) estimation and attribution strategy. The simulated observations in the OSSE use the actual column carbon dioxide (X(CO2)) b2.9 retrieval sensitivity and quality control for the year 2010 processed through the Atmospheric CO2 Observations from Space algorithm. CMS-Flux is a variational inversion system that uses the GEOS-Chem forward and adjoint model forced by a suite of observationally constrained fluxes from ocean, land and anthropogenic models. We investigate the impact of GOSAT sampling on flux estimation in two aspects: 1) random error uncertainty reduction and 2) the global and regional bias in posterior flux resulted from the spatiotemporally biased GOSAT sampling. Based on Monte Carlo calculations, we find that global average flux uncertainty reduction ranges from 25% in September to 60% in July. When aggregated to the 11 land regions designated by the phase 3 of the Atmospheric Tracer Transport Model Intercomparison Project, the annual mean uncertainty reduction ranges from 10% over North American boreal to 38% over South American temperate, which is driven by observational coverage and the magnitude of prior flux uncertainty. The uncertainty reduction over the South American tropical region is 30%, even with sparse observation coverage. We show that this reduction results from the large prior flux uncertainty and the impact of non-local observations. Given the assumed prior error statistics, the degree of freedom for signal is approx.1132 for 1-yr of the 74 055 GOSAT X(CO2) observations, which indicates that GOSAT provides approx.1132 independent pieces of information about surface fluxes. We quantify the impact of GOSAT's spatiotemporally sampling on the posterior flux, and find that a 0.7 gigatons of carbon bias in the global annual posterior flux resulted from the seasonally and diurnally biased sampling when using a diagonal prior flux error covariance.

biased sampling↗
NASA NTRS1973

Delta modulation

The overshoot suppression algorithm has been more extensively studied. Computer generated test-pictures show a radical improvement due to the overshoot suppression algorithm. Considering the delta modulator link as a nonlinear digital filter, a formula that relates the minimum rise time that can be handled for given filter parameters and voltage swings has been developed. The settling time has been calculated for the case of overshoot suppression as well as when no suppression is employed. The results indicate a significant decrease in settling time when overshoot suppression is used. An algorithm for correcting channel errors has been developed. It is shown that pulse stuffing PCM words in the DM bit stream results in a significant reduction in error length.

Schilling, D. L.↗
DOE OSTI2012

IMPROVING CORRELATION FUNCTION FITTING WITH RIDGE REGRESSION: APPLICATION TO CROSS-CORRELATION RECONSTRUCTION

Cross-correlation techniques provide a promising avenue for calibrating photometric redshifts and determining redshift distributions using spectroscopy which is systematically incomplete (e.g., current deep spectroscopic surveys fail to obtain secure redshifts for 30%-50% or more of the galaxies targeted). In this paper, we improve on the redshift distribution reconstruction methods from our previous work by incorporating full covariance information into our correlation function fits. Correlation function measurements are strongly covariant between angular or spatial bins, and accounting for this in fitting can yield substantial reduction in errors. However, frequently the covariance matrices used in these calculations are determined from a relatively small set (dozens rather than hundreds) of subsamples or mock catalogs, resulting in noisy covariance matrices whose inversion is ill-conditioned and numerically unstable. We present here a method of conditioning the covariance matrix known as ridge regression which results in a more well behaved inversion than other techniques common in large-scale structure studies. We demonstrate that ridge regression significantly improves the determination of correlation function parameters. We then apply these improved techniques to the problem of reconstructing redshift distributions. By incorporating full covariance information, applying ridge regression, and changing the weighting of fields in obtaining average correlation functions, we obtain reductions in the mean redshift distribution reconstruction error of as much as {approx}40% compared to previous methods. We provide a description of POWERFIT, an IDL code for performing power-law fits to correlation functions with ridge regression conditioning that we are making publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Effect of Image-Guidance Frequency on Geometric Accuracy and Setup Margins in Radiotherapy for Locally Advanced Lung Cancer

Purpose: To assess the relative effectiveness of five image-guidance (IG) frequencies on reducing patient positioning inaccuracies and setup margins for locally advanced lung cancer patients. Methods and Materials: Daily cone-beam computed tomography data for 100 patients (4,237 scans) were analyzed. Subsequently, four less-than-daily IG protocols were simulated using these data (no IG, first 5-day IG, weekly IG, and alternate-day IG). The frequency and magnitude of residual setup error were determined. The less-than-daily IG protocols were compared against the daily IG, the assumed reference standard. Finally, the population-based setup margins were calculated. Results: With the less-than-daily IG protocols, 20-43% of fractions incurred residual setup errors {>=}5 mm; daily IG reduced this to 6%. With the exception of the first 5-day IG, reductions in systematic error ({Sigma}) occurred as the imaging frequency increased and only daily IG provided notable random error ({sigma}) reductions ({Sigma} = 1.5-2.2 mm, {sigma} = 2.5-3.7 mm; {Sigma} = 1.8-2.6 mm, {sigma} = 2.5-3.7 mm; and {Sigma} = 0.7-1.0 mm, {sigma} = 1.7-2.0 mm for no IG, first 5-day IG, and daily IG, respectively. An overall significant difference in the mean setup error was present between the first 5-day IG and daily IG (p < .0001). The derived setup margins were 5-9 mm for less-than-daily IG and were 3-4 mm with daily IG. Conclusion: Daily cone-beam computed tomography substantially reduced the setup error and could permit setup margin reduction and lead to a reduction in normal tissue toxicity for patients undergoing conventionally fractionated lung radiotherapy. Using first 5-day cone-beam computed tomography was suboptimal for lung patients, given the inability to reduce the random error and the potential for the systematic error to increase throughout the treatment course.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1988

Airborne radar technology for windshear detection

The objectives and accomplishments of the two-and-a-half year effort to describe how returns from on-board Doppler radar are to be used to detect the presence of a wind shear are reported. The problem is modeled as one of first passage in terms of state variables, the state estimates are generated by a bank of extended Kalman filters working in parallel, and the decision strategy involves the use of a voting algorithm for a series of likelihood ratio tests. The performance issue for filtering is addressed in terms of error-covariance reduction and filter divergence, and the performance issue for detection is addressed in terms of using a probability measure transformation to derive theoretical expressions for the error probabilities of a false alarm and a miss.

Hibey, Joseph L.↗
NASA NTRS1983

The effects of digitizing rate and phase distortion errors on the shock response spectrum

Some of the methods used for acquisition and digitization of high-frequency transients in the analysis of pyrotechnic events, such as explosive bolts for spacecraft separation, are discussed with respect to the reduction of errors in the computed shock response spectrum. Equations are given for maximum error as a function of the sampling rate, phase distortion, and slew rate, and the effects of the characteristics of the filter used are analyzed. A filter is noted to exhibit good passband amplitude, phase response, and response to a step function is a compromise between the flat passband of the elliptic filter and the phase response of the Bessel filter; it is suggested that it be used with a sampling rate of 10f (5 percent).

Wise, J. H.↗
DOE OSTI2026

How to Minimize Faradaic Efficiency Error in Electrochemical CO 2 Reduction for Gas Products

Faradaic efficiency (FE) is an important metric for evaluating electrochemical processes, such as carbon dioxide reduction, that is often used for performance comparisons. Although the equation to calculate FE is well-known, details needed to yield accurate values are often overlooked, potentially leading to errors exceeding 100%. Avoiding any errors is crucial for drawing correct conclusions, especially during a catalysis optimization process. Factors with high potential for FE errors include incorrect mass flow rates and temperature values, imprecise gas chromatography calibrations, and uncorrected gas viscosities, while factors with less potential are also identified. In conclusion, this manuscript presents FE calculation guidelines intended for both newcomers and experts in the field of electrochemical fuel production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

A Hybrid Global Ocean Data Assimilation System at NCEP

Seasonal forecasting with a coupled model requires accurate initial conditions for the ocean. A hybrid data assimilation has been implemented within the National Centers for Environmental Prediction (NCEP) Global Ocean Data Assimilation System (GODAS) as a future replacement of the operational three-dimensional variational data assimilation (3DVar) method. This Hybrid-GODAS provides improved representation of model uncertainties by using a combination of dynamic and static background error covariances, and by using an ensemble forced by different realizations of atmospheric surface conditions. An observing system simulation experiment (OSSE) is presented spanning January 1991 to January 1999, with a bias imposed on the surface forcing conditions to emulate an imperfect model. The OSSE compares the 3DVar used by the NCEP Climate Forecast System (CFSv2) with the new hybrid, using simulated in situ ocean observations corresponding to those used for the NCEP Climate Forecast System Reanalysis (CFSR). The Hybrid-GODAS reduces errors for all prognostic model variables over the majority of the experiment duration, both globally and regionally. Compared to an ensemble Kalman filter (EnKF) used alone, the hybrid further reduces errors in the tropical Pacific. The hybrid eliminates growth in biases of temperature and salinity present in the EnKF and 3DVar, respectively. A preliminary reanalysis using real data shows that reductions in errors and biases are qualitatively similar to the results from the OSSE. Finally, the Hybrid-GODAS is currently being implemented as the ocean component in a prototype next-generation CFSv3, and will be used in studies by the Climate Prediction Center to evaluate impacts on ENSO prediction.

54 ENVIRONMENTAL SCIENCES↗