SEARCH · Search NASA

Results for “error indicators”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,423 records · Page 79

All sources NASA NTRS DOE OSTI

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 The commonly used lidar equation is no longer applicable since the convolution of the laser pulse with the atmospheric parameter distributions should be taken into account.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.↗

NASA NTRS1989

Raman intensity as a probe of concentration near a crystal growing in solution

The feasibility of using Raman spectral scattering signals for measurements of concentration profiles near a crystal interface during growth or dissolution is discussed. With KH2PO4 (KDP) as a test material, optical multichannel analyzer (OMA) detection of a solute Raman vibrational band provided direct quantification of solute concentration with band intensity. The intersection of incident laser and Raman collection optics provided 3-D selective point measurements of the solution concentration field. Unlike many other techniques, the Raman band intensity is not sensitive to the typical temperature variations. Precision calibration of Raman intensity versus KDP concentration with less than 1 pct standard deviation error levels was demonstrated. A fiber optic, which sampled incident laser intensity and coupled it to the OMA, provided a fully synchronized monitor of fluctuations in laser power to correlate with observed Raman signals. With 1 W of laser power at the sample, good data statistics required eight repeated data collections at approximately 2.5 min collection. The accumulated time represents the concentration measurement time at one spatial location. Photomicroscopy documented a 30 micrometer diameter by 200 micrometer of laser Raman scattering region in the solution near the crystal surface. The laser beam was able to approach up to 25 micrometer from the crystal surface. However, a crystal surface reflected intensity contribution was weakly detectable. Nucleated microcrystals were seen in the crystal-growing solution. These microcrystals convect right up to the crystal surface and indicate no quiet diffusion region under normal gravity conditions. Translation of the solution cell with respect to the optics caused systematic intensity errors.

Wilkinson, R. Allen↗

NASA NTRS1988

Novae as distance indicators

It is shown that nova shells are characteristically prolate with equatorial bands and polar caps. Failure to take this geometry into consideration can lead to large errors in expansion parallaxes for individual novae. Extinction in the bulge of M31 is investigated by projecting Arp's and Rosino's novae onto a composite B - 6200 A color map of the bulge. Of the 86 novae, 32 project onto a smooth background with no underlying structure due to the presence of a dust cloud along the line of sight. The distribution of maximum magnitudes versus fade rates for these 'unreddened' novae is indistinguishable from the distribution for the entire set of novae. It is concluded that novae suffer very little extinction from the filamentary and patchy distribution of dust seen in the bulge of M31.

Ford, Holland C.↗

DOE OSTI2021

An innovative digital image correlation technique for in-situ process monitoring of composite structures in large scale additive manufacturing

As additive manufacturing (AM) continues to develop and become a standardized manufacturing method, there will be a continued need to provide in-situ monitoring during the manufacturing of polymer composite printed components. Thermal residual stress is a primary cause of failures such as interlayer disbonds or delamination, micro cracking, and dimensional instability, which can occur during or after the build. Here, we report a novel digital image correlation (DIC) adaptation to monitor thermal residual stresses during the entire print process for large-scale AM. In this work, DIC has been investigated (a) by the natural speckle produced by the polymer surface for correlation, (b) to monitor AM build, and (c) to evaluate the effect of thermal residual stress on warpage of the printed component. The natural speckle pattern of the AM material resulted in a respectable 3.57% error compared to the traditional painted speckle pattern of 3.05% error. DIC measured a 190% increase in vertical displacement at the edge of the wall compared to the center, indicating warpage during AM. This work is a step towards a non-intrusive residual stress measuring technique using DIC for large-scale AM.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Predicting lake surface water phosphorus dynamics using process-guided machine learning

Phosphorus (P) loading to lakes is degrading the quality and usability of water globally. Accurate predictions of lake P dynamics are needed to understand whole-ecosystem P budgets, as well as the consequences of changing lake P concentrations for water quality. However, complex biophysical processes within lakes, along with limited observational data, challenge our capacity to reproduce short-term lake dynamics needed for water quality predictions, as well as long-term dynamics needed to understand broad scale controls over lake P. Here we use an emerging paradigm in modeling, process-guided machine learning (PGML), to produce a phosphorus budget for Lake Mendota (Wisconsin, USA) and to accurately predict epilimnetic phosphorus over a time range of days to decades. In our implementation of PGML, which we term a Process-Guided Recurrent Neural Network (PGRNN), we combine a process-based model for lake P with a recurrent neural network, and then constrain the predictions with ecological principles. We test independently the process-based model, the recurrent neural network, and the PGRNN to evaluate the overall approach. The process-based model accounted for most of the observed pattern in lake P; however it missed the long-term trend in lake P and had the worst performance in predicting winter and summer P in surface waters. The root mean square error (RMSE) for the process-based model, the recurrent neural network, and the PGRNN was 33.0 μg P L -1 , 22.7 μg P L -1 , and 20.7 μg P L -1 , respectively. All models performed better during summer, with RMSE values for the three models (same order) equal to 14.3 μg P L -1 , 10.9 μg P L -1 , and 10.7 μg P L -1 . Although the PGRNN had only marginally better RMSE during summer, it had lower bias and reproduced long-term decreases in lake P missed by the other two models. For all seasons and all years, the recurrent neural network had better predictions than process alone, with root mean square error (RMSE) of 23.8 μg P L -1 and 28.0 μg P L -1 , respectively. The output of PGRNN indicated that new processes related to water temperature, thermal stratification, and long term changes in external loads are needed to improve the process model. By using ecological knowledge, as well as the information content of complex data, PGML shows promise as a technique for accurate prediction in messy, real-world ecological dynamics, while providing valuable information that can improve our understanding of process.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Modeling of fluid injection-induced fault reactivation using coupled fluid flow and mechanical interface model

The present study is aimed at developing a numerical model to reproduce coupled hydro-mechanical processes associated with fault reactivation by fluid injection in low permeability rock, as part of the DECOVALEX-2019 project Task B. We proposed a modeling approach for simulating the processes using the TOUGH-FLAC simulator, and modeled a fault reactivation experiment conducted at Mont Terri Rock Laboratory in Switzerland. The first step of the study involved benchmark calculations considering a simplified fault plane and geometry. Fluid flow along a fault was modeled using elements of aperture-sized thickness on the basis of Darcy's law and the cubic law in TOUGH2, whereas the mechanical behavior of a single fault was represented by zero-thickness interface elements in FLAC3D upon which a slip and/or separation is allowed. A methodology to connect a TOUGH2 volume element to a FLAC3D interface element was developed for handling the hydro-mechanical interactions on the fault during fluid injection. Two different fault models for describing the evolutions of hydraulic aperture by elastic fracture opening and failure-induced aperture increase were considered in the benchmark calculations. In the coupling process, the changes in geometrical features and hydrological properties induced by mechanical deformation were continuously updated. The transient responses of the fault and host rock to stepwise pressurization were examined during the simulation. The hydro-mechanical behavior, including the injection flow rate, pressure distribution around the borehole, stress conditions, and displacements in normal and shear directions were monitored in the surrounding rock and along the fault. The results of benchmark calculations suggest that the developed model reasonably represents the hydro-mechanical behavior of a fault and the surrounding rock. This modeling approach was applied to the fault reactivation experiment of the Mont Terri Rock Laboratory. In this interpretive modeling, a parametric study was conducted to examine the effects of input parameters regarding in situ stress and fault properties on the hydro-mechanical responses of the fault to water injection. Then, an optimal parameter set to reproduce the field experiment results was chosen by trial-and-error. The injection flow rate and pressure response during fault reactivation closely matched those obtained at the site, which indicates the capability of the model to appropriately capture the progressive pathway evolution during fault reactivation tests at the site. Finally, the anchor displacements were overestimated by the model, but a fair agreement was obtained in terms of the order of magnitude and the variation tendency.

58 GEOSCIENCES↗

DOE OSTI2020

Fast dynamic aperture optimization with forward-reversal integration

A fast dynamic aperture (DA) optimization method for storage rings has been developed through the use of reversal integration. Even if dynamical systems have an exact reversal symmetry, a numerical forward integration differs from its reversal. For a chaotic trajectory, cumulative round-off errors are scaled, which results in an exponential growth on the difference. The exponential effect is a generic chaos indicator which represents the sensitivity of the chaotic motion to its initial condition. The chaos indicator of the charged particle motion can be obtained by comparing the forward integrations of particle trajectories with corresponding reversals, a.k.a. “backward integrations.” The indicator is observable even through short-term particle tracking simulations. Therefore, adopting it as an objective function could speed up optimization. Finally, the DA of the National Synchrotron Light Source II storage ring, and another test diffraction-limited light source ring, were optimized using this method for the purpose of demonstration.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Baseflow Identification via Explainable AI With Kolmogorov‐Arnold Networks

Abstract Hydrological models often involve constitutive laws that may not be optimal in every application. We propose to replace such laws with the Kolmogorov‐Arnold networks (KANs), a class of neural networks designed to identify symbolic expressions. We demonstrate KAN's potential on the problem of baseflow identification, a notoriously challenging task plagued by significant uncertainty. KAN‐derived functional dependencies of the baseflow components on the aridity index outperform their original counterparts; they demonstrate that water availability, rather than potential evapotranspiration, drives baseflow by constraining actual evapotranspiration under arid conditions. On a test set, they increase the Nash‐Sutcliffe efficiency (NSE) by 65%, decrease the root mean squared error by 29%, and increase the Kling‐Gupta efficiency by 34%. This superior performance is achieved while reducing the number of fitting parameters from three to two. Next, we use data from 378 catchments across the continental United States to refine the water‐balance equation at the mean‐annual scale. The KAN‐derived equations based on the refined water balance outperform both the current aridity index model, with up to a 105% increase in NSE, and the KAN‐derived equations based on the original water balance. While the performance of our model and tree‐based machine learning methods is similar, KANs offer the advantage of simplicity and transparency and require no specific software or computational tools. This case study focuses on the aridity index formulation, but the approach is flexible and transferable to other hydrological processes. Plain Language Summary Equations used in hydrologic model are often suboptimal, resulting in reduced prediction accuracy and efficiency. We implemented Kolmogorov‐Arnold networks (KAN), a machine learning algorithm for deriving symbolic formulations, to estimate groundwater recharge and showed that it outperforms an existing state‐of‐the‐art semi‐empirical formulation. In hydrology, Nash‐Sutcliffe efficiency (NSE), root mean squared error (RMSE), and Kling‐Gupta efficiency (KGE) are commonly used to evaluate model performance. Higher NSE and KGE values indicate better performance, while lower RMSE values are preferable. Our results show that NSE increased by 71%, RMSE decreased by 32%, and KGE improved by 25%. In addition, KAN identifies an optimal functional form and can be used to derive new analytical formulas using the prior knowledge. The KAN‐inspired equation outperformed the original formulation and reduced the fitting parameters. Furthermore, we refined the water‐balance equation at the mean‐annual scale and showed that, based on the new water‐balance equation, KAN can derive new formulations that are superior to the original aridity index formulations (up to 105% increase in NSE) and KAN‐derived equations based on the original water balance. These findings highlight the significant potential of KAN to advance the scientific understanding of a wide range of hydrologic processes. Key Points Kolmogorov‐Arnold networks (KANs) enhance interpretability of machine‐learned hydrological models KAN‐derived symbolic formulations outperform state‐of‐the‐art semi‐empirical aridity indices KAN‐identified functional form yields an analytical index with fewer fitting parameters and improved performance

baseflow↗

DOE OSTI2020

A Facile Approach to High Precision Detection of Cell-to-Cell Variation for Li-ion Batteries

Abstract Over the past decade, it has been repeatedly demonstrated that homogeneity in electrochemical performance of lithium-ion cells plays a major role in determining the life and safety of lithium-ion battery modules or packs. Generally, the homogeneity of a battery pack is evaluated by characterizing the cells individually in terms of capacity, mass, impedance. Particularly, high quality electrochemical data heavily relies on the availability of high precision current source to minimize the discrepancy induced by the channel-to-channel variation. Here, a facile and precise measurement method is reported for screening cell-to-cell variations, in which voltage is the only indicator parameter independent of high precision current source. In detail, by connecting the cells in series (CiS), the measurement error of electrochemical data caused by stability and discrepancy of current sources among different charge/discharge equipment can be effectively avoided. The findings of this work showed that the cell-to-cell variations can be simply and sensitively detected with CiS configuration. For example, the relative standard deviation, which is the evaluation criterion of battery homogeneity, was 2.14% based on CiS while it was 0.43% based on individual measurements. The simple and precise CiS measurement is promising for evaluation of cell quality or module integration quality. In addition, this work can also provide a solid foundation for the development of detection algorithms for battery management systems to rapidly monitor battery homogeneity.

25 ENERGY STORAGE↗

DOE OSTI2015

BEYOND THE MAIN SEQUENCE: TESTING THE ACCURACY OF STELLAR MASSES PREDICTED BY THE PARSEC EVOLUTIONARY TRACKS

Characterizing the physical properties of exoplanets and understanding their formation and orbital evolution requires precise and accurate knowledge of their host stars. Accurately measuring stellar masses is particularly important because they likely influence planet occurrence and the architectures of planetary systems. Single main-sequence stars typically have masses estimated from evolutionary tracks, which generally provide accurate results due to their extensive empirical calibration. However, the validity of this method for subgiants and giants has been called into question by recent studies, with suggestions that the masses of these evolved stars could have been overestimated. We investigate these concerns using a sample of 59 benchmark evolved stars with model-independent masses (from binary systems or asteroseismology) obtained from the literature. We find very good agreement between these benchmark masses and the ones estimated using evolutionary tracks. The average fractional difference in the mass interval ∼0.7–4.5 M{sub ⊙} is consistent with zero (−1.30 ± 2.42%), with no significant trends in the residuals relative to the input parameters. A good agreement between model-dependent and -independent radii (−4.81 ± 1.32%) and surface gravities (0.71 ± 0.51%) is also found. The consistency between independently determined ages for members of binary systems adds further support for the accuracy of the method employed to derive the stellar masses. Taken together, our results indicate that determination of masses of evolved stars using grids of evolutionary tracks is not significantly affected by systematic errors, and is thus valid for estimating the masses of isolated stars beyond the main sequence.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Quantitative Electroluminescence Imaging Analysis for Performance Estimation of PID-Influenced PV Modules

An empirical method for estimating relative power losses caused by potential-induced degradation (PID) for p-type solar cells and modules using quantitative electroluminescence (EL) analysis (QELA) is presented. First, EL images are corrected for camera- and perspective distortion. The relative power loss map is then calculated from the logarithmic ratio of two EL images, taken either before and after PID degradation or at different applied currents. Only the cell average of the resulting power loss map is evaluated. The highest power loss across each string is averaged to obtain the overall power loss. Consequently, for modules with three strings, three cells are averaged. The resulting power loss depends on the current applied. The conversion to equivalent irradiance allows for comparison of measured and estimated device performance. The analysis of roughly 2000 EL images and related current-voltage (I-V) curves indicates a good agreement between flash-test-measured and performance estimated using QELA. A relative root mean square error of 1-3% can be achieved.

14 SOLAR ENERGY↗

DOE OSTI2015

SU-D-BRB-02: Patient-Specific Rectal Toxicity Predictor Based Plan Quality Control for Prostate Stereotactic Body Radiation Therapy (SBRT)

Purpose: To develop a patient-specific rectal toxicity predictor guided plan quality control tool for prostate SBRT plans. Methods: For prostate SBRT cases, four segments of rectal walls including peri-prostatic anterior rectal wall, peri-prostatic lateral rectal walls, peri-prostatic posterior rectal wall and rectum superior to prostate are identified as organs at risk and the circumference of rectal wall receiving more than 39 Gy (CRW39) and 24 Gy (CRW24) are rectal toxicity predictors. In this new geometry-dosimetry model, a patient geometry descriptor, differential circumference of rectal wall (dCRW) is used as model input geometry parameters and plan dosimetric endpoints CRW39 and CRW24 are output dosimetric parameters. Linear models are built to correlate dCRW to both CRW39 and CRW24 and established with both a linear regression method and a modified bagging ensemble machine learning method. 27 SBRT prostate cases are retrospectively studied from a dose-escalated clinical trial research. 20 prescribed 50 Gy SBRT cases are recruited to train the model and the other rescaled 7 cases are used to evaluated model feasibility and accuracy. Results: Each solved linear coefficient sequence related to CRW39 or CRW24 is a one-dimensional decreasing function of the distance from the PTV boundary, indicating that the different locations of each rectal circumference have different contributions to each particular dosimetric endpoint. The fitting errors for those trained 20 prostate SBRT cases are small with mean values of 2.39%, 2.45% relative to the endpoint values for SBRT rectal toxicity predictor CRW39 and CRW24 respectively. 1 out of 7 evaluation plans is identified as poor quality plan. After re-planning, the CRW39 and CRW24 can be reduced by 3.34% and 3%, without sacrificing PTV coverage. Conclusion: The proposed patient geometry-plan toxicity predictor model for SBRT plans can be successfully applied to plan quality control for prostate SBRT cases.

60 APPLIED LIFE SCIENCES↗

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↗

NASA NTRS1972

On the stability and pointing of an attached double-gimbal experiment package

The pointing capability of a double gimbal experiment isolation and control system of the Apollo telescope mount (ATM) type was investigated. Three composite structural models of an experiment package connected through frictionless gimbals to a carrier vehicle (including a rigid package-rigid carrier model, a rigid package-flexible carrier model, and a flexible package-flexible carrier model) were used, and a linear model of the nominal ATM gimbal control system is considered. A linear stability analysis was performed to verify stability of the control system with nominal gains. Transform techniques were used to compute pointing errors onboard the experiment package due to random crew motions input into the carrier vehicle. Results of the investigation indicate that there is no stability problem due to flexible coupling of the experiment package and the carrier, and that the ATM-type system is capable of pointing accuracies better than 0.1 arc second.

Groom, N. J.↗

NASA NTRS1972

Comparison of neutron spectra measured with three sizes of organic liquid scintillators using differentiation analysis

Proton recoil distributions were obtained by using organic liquid scintillators of different size. The measured distributions are converted to neutron spectra by differentiation analysis for comparison to the unfolded spectra of the largest scintillator. The approximations involved in the differentiation analysis are indicated to have small effects on the precision of neutron spectra measured with the smaller scintillators but introduce significant error for the largest scintillator. In the case of the smallest cylindrical scintillator, nominally 1.2 by 1.3 cm, the efficiency is shown to be insensitive to multiple scattering and to the angular distribution to the incident flux. These characteristics of the smaller scintillator make possible its use to measure scalar flux spectra within media high efficiency is not required.

Shook, D. F.↗

NASA NTRS1973

A reliability and comparative analysis of two standby system configurations.

Equations are derived which enable one to calculate the system reliability for parallel or triple modular redundant systems with standby spares. Software error detection is introduced into the TMR/Spares system configuration in order to utilize fully all of the units. An indication of the sensitivity of the system reliability to an increase in the number of spares, partitioning, switching, variations in the powered and unpowered failures rates, and time is presented. A comparison of the parallel and the TMR/Spares system configurations, under similar conditions, is given.

Taylor, D. S.↗

NASA NTRS1975

The use of back corrections in multistep methods of numerical integration

Generalized multistep methods for the numerical solution of nonlinear systems of ordinary differential equations are introduced which allow the correction of previously computed values of the solution at internal points of the grid. These methods are shown to possess enhanced numerical stability. Preliminary numerical results indicate that for some satellite orbit problems these methods also possess greater overall efficiency. A uniformly converging theory of error propagation is presented which is valid for nonasymptotic values of the step size. Experimental results are seen to conform with theory.

Beaudet, P.↗

NASA NTRS1976

Structure of the solar chromosphere. II - The underlying photosphere and temperature-minimum region

The paper presents a non-LTE empirical model of the quiet solar photosphere and the temperature-minimum region. The continuous spectrum computed from this model is in good overall agreement with available disk-center observations throughout the wavelength range from 0.125 to 500 microns. It is found that (1) absolute-intensity measurements are needed in the range between 1 and 2 microns to establish the structure of the deepest observable layers; (2) absolute-intensity or flux measurements are needed in the range between 20 and 200 microns to determine whether the minimum solar temperature occurring between the photosphere and the chromosphere is as low as indicated by present observations or much higher, as recent theoretical predictions indicate; (3) studies of the far-ultraviolet spectrum based on the assumption of LTE can be substantially in error; and (4) line opacity seems to account for the 'missing opacity' in the ultraviolet.

Vernazza, J. E.↗