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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
NASA NTRS1982

Dynamics and control of a large space antenna

It is pointed out that large space antennae and other large space structures will play an important role in the coming decades as commercial applications of space become feasible. A investigation is conducted of the structural dynamics and the control properties for a 64-meter diameter center fed antenna. Attention is given to antenna configuration and structural dynamic porperties, the attitude and structural control system, disturbance assessment, hardware sizing, the construction of weighting matrices, and numerical results. It is found that structural uncertainties and model error can cause serious performance deterioration and can even destabilize the controllers. Flight test and in-orbit system identification of critical structural modes will insure performance and reduce risk for large space antenna missions.

Wang, S. J.↗
NASA NTRS2018

Discrete Assemblers Utilizing Conventional Motion Systems

An alternative to additive manufacturing is disclosed, introducing an end-to-end workflow in which discrete building blocks are reversibly joined to produce assemblies called digital materials. Described is the design of the bulk-material building blocks and the devices that are assembled from them. Detailed is the design and implementation of an automated assembler, which takes advantage of the digital material structure to avoid positioning errors within a large tolerance. To generate assembly sequences, a novel CAD/CAM workflow is described for designing, simulating, and assembling digital materials. The structures assembled using this process have been evaluated, showing that the joints perform well under varying conditions and that the assembled structures are functionally precise.

Langford, William Kai↗
DOE OSTI2025

Introducing a multiscale feature integration network for inpainting with applications to enhanced CMB map reconstruction

We introduce a novel neural network, SkyReconNet, which combines the expanded receptive fields of dilated convolutional layers along with standard convolutions, to capture both the global and local features for reconstructing the missing information in an image. We implement our network to inpaint the masked regions in a full-sky cosmic microwave background (CMB) map. Inpainting CMB maps is a particularly formidable challenge when dealing with extensive and irregular masks, such as galactic masks which can obscure substantial fractions of the sky. The hybrid design of SkyReconNet leverages the strengths of standard and dilated convolutions to accurately predict CMB fluctuations in the masked regions by effectively utilizing the information from surrounding unmasked areas. During training, the network optimizes its weights by minimizing a composite loss function that combines the structural similarity index measure (SSIM) and mean squared error (MSE). SSIM preserves the essential structural features of the CMB, ensuring an accurate and coherent reconstruction of the missing CMB fluctuations, while MSE minimizes the pixelwise deviations, thus enhancing the overall accuracy of the predictions. The predicted CMB maps and their corresponding angular power spectra align closely with the targets, achieving the performance limited only by the fundamental uncertainty of cosmic variance. The network’s generic architecture enables application to other physics-based challenges involving data with missing or defective pixels, systematic artifacts, etc. In conclusion, our results demonstrate its effectiveness in addressing the challenges posed by large irregular masks, offering a significant inpainting tool not only for CMB analyses but also for image-based experiments across disciplines where such data imperfections are prevalent.

Cosmic microwave background↗
DOE OSTI2022

Distant Observer™ [SWR-12-09]

Distant Observer™ (DO) is an optical measurement tool, designed for parabolic trough solar collectors, that determines reflector slope error, absorber position error, and the combined errors based on images of the receiver-tube reflection taken from different angles. We have demonstrated that DO can provide a measurement accuracy of 0.25 mrad for the slope and receiver position errors. DO has two implementation versions: ground-based and drone-driven. As we pursue efforts to lower the capital and installation costs of parabolic trough solar collectors, it is essential to maintain high optical performance. The Distant Observer™ (DO) tool, developed by engineers at NREL, is a fast and highly accurate tool that provides complete characterization of the performance of the optical components which include the mirror panels and thermal receiver. This tool is very useful for testing both prototype and operational modules. The Distant Observer™ is an optical measurement tool for parabolic solar collectors that measures reflector slope error, absorber position error and the combined errors. Reflector slope errors occur for many reasons including imperfection in structural frame design, manufacturing and assembly. Absorber position error can be caused by poor structural design, poor installation, sag from the absorber weight, or change in the structure over time.

Ihas, Benjamin↗
NASA NTRS1990

Accuracy analysis of the semi-analytical method for shape sensitivity calculation

The semianalytical method of design sensitivity analysis that is widely used for calculating derivatives of static response with respect to design variables for structures modeled by finite elements is studied. It is shown that the method can have serious accuracy problems for shape design variables in structures modeled by beam, plate, truss, frame, and solid elements. Errors are shown to be associated with an incompatibility of the sensitivity field with the structure. An error index is developed to test the accuracy of the semianalytical method. It characterizes the difference in errors between a general finite-difference method and the semianalytical method. A method for improving the accuracy of the semianalytical method (when possible) is provided. Examples are presented to demonstrate the use of the error index.

Barthelemy, Bruno↗
NASA NTRS1991

Active isolation of vibrations with adaptive structures

Vibration transmission in structures is controlled by means of a technique which employs distributed arrays of piezoelectric transducers bonded to the supporting structure. Distributed PVDF piezoelectric strips are employed as error sensors, and a two-channel feedforward adaptive LMS algorithm is used for minimizing error signals and thereby controlling the structure. A harmonic force input excites a thick plate, and a receiving plate is configured with three pairs of piezoelectric actuators. Modal analyses are performed to determine the resonant frequencies of the system, and a scanning laser vibrometer is used to study the shape of the response of the receiving plate during excitation with and without the control algorithm. Efficient active isolation of the vibrations is achieved with modal suppression, and good control is noted in the on-resonance cases in which increased numbers of PVDF sensors and piezoelectric actuators are employed.

Guigou, C.↗
NASA NTRS1984

Robustness and modeling error characterization

The results on robustness theory presented here are extensions of those given in Lehtomaki et al., (1981). The basic innovation in these new results is that they utilize minimal additional information about the structure of the modeling error, as well as its magnitude, to assess the robustness of feedback systems for which robustness tests based on the magnitude of modeling error alone are inconclusive.

Lehtomaki, N. A.↗
NASA NTRS1993

A degree scale anisotropy measurement of the cosmic microwave background near the star Gamma Ursae Minoris

Results from a search for anisotropy in the cosmic microwave background (CMB) are presented from the third flight of the Millimeter-wave Anisotropy experiment. The CMB observation occurred over 1.37 hours and covered a 6.24 sq deg area of the sky where very little foreground emission is expected. Significant correlated structure is observed at 6 and 9/cm. At 12/cm we place an upper limit on the structure. The relative amplitudes at 6, 9, and 12/cm are consistent with a CMB spectrum. The spectrum of the structure is inconsistent with thermal emission from known forms of interstellar dust. Synchrotron and free-free emission would both require unusually flat spectral indices at cm wavelengths in order to account for the amplitude of the observed structure. Although known systematic errors are not expected to contribute significantly to any of the three optical channels, excess sidelobe contamination cannot be definitively ruled out. If all the structure is attributed to CMB anisotropy, a value of the weighted rms of the 6 and 9/cm channels of Delta T/T(CMB) = 4.7 +/- 0.8 x 10 exp -5 (+/- 1 sigma) was measured. If the CMB anisotropy is assumed to have a Gaussian autocorrelation function with a coherence angle of 25 arcmin, then the most probable value is Delta T/T(CMB) = 4.2 +1.7 or -1.1 x 10 exp -5, where the +/- refers to the 95 percent confidence limits.

Gundersen, J. O.↗
NASA NTRS1992

User's manual for MacPASCO

A user's manual is presented for MacPASCO, which is an interactive, graphic, preprocessor for panel design. MacPASCO creates input for PASCO, an existing computer code for structural analysis and sizing of longitudinally stiffened composite panels. MacPASCO provides a graphical user interface which simplifies the specification of panel geometry and reduces user input errors. The user draws the initial structural geometry and reduces user input errors. The user draws the initial structural geometry on the computer screen, then uses a combination of graphic and text inputs to: refine the structural geometry; specify information required for analysis such as panel load and boundary conditions; and define design variables and constraints for minimum mass optimization. Only the use of MacPASCO is described, since the use of PASCO has been documented elsewhere.

Lucas, S. H.↗
NASA NTRS2016

Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

model structure uncertainty↗
DOE OSTI2025

Online and Offline Data Quality Monitoring for the Mu2e Calorimeter

This thesis presents the design, implementation, and validation of a calorimeter Data Quality Monitoring (DQM) toolchain for the Mu2e experiment at Fermilab. Mu2e searches for charged lepton flavor violation via coherent muon-to-electron conversion in the field of an aluminum nucleus, $\mu^- Al \rightarrow e^-Al$, a process whose observation would constitute clear evidence of physics beyond the Standard Model. Achieving target sensitivity requires stringent control of detector performance and data integrity during acquisition, as subtle issues in readout configuration, data formatting, or electronics behavior can compromise reconstruction and bias downstream analyzes. To address these challenges, this work develops a multi-layer DQM approach spanning both raw data validation and reconstructed digi-level diagnostics. At the low level, a fragment analysis component performs word- and bit-field decoding of calorimeter readout blocks, enabling sanity checks of the expected structure and producing detailed error and integrity statistics useful for commissioning and troubleshooting. At the digi level, the CaloDigiDQM analyzer is implemented within the art framework and transforms each CaloDigiCollection into a structured hierarchy of ROOT histograms designed for fast drill-down diagnostics. The module generates coherent monitoring views at global, disk, board, and channel granularity, including occupancy, waveform-derived features (baseline, RMS, peak amplitude and position), and left-right sensor consistency metrics. Detector-aware channel-to-electronics mapping is performed through the conditions system (CaloDAQMap), ensuring that diagnostics remain aligned with hardware identifiers used in operations. For end-to-end testing without reliance on live DAQ data, a synthetic CaloDigi producer is developed to generate realistic waveforms with controlled noise and pulse shapes. The resulting system supports both offline ROOT-file production and online operation, including optional histogram streaming through otsdaq via ots::HistoSender. This toolchain provides a practical and scalable foundation for calorimeter commissioning and stable data collection, enabling early detection of anomalies and reducing operational risk for Mu2e.

Vakulenko, Mark [Drew U.] (ORCID:0009000276197818)↗
NASA NTRS2013

The Impact of Model and Rainfall Forcing Errors on Characterizing Soil Moisture Uncertainty in Land Surface Modeling

The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

Maggioni, V.↗
DOE OSTI2023

Likelihood-based signal and noise analysis for docking of models into cryo-EM maps

Fast, reliable docking of models into cryo-EM maps requires understanding of the errors in the maps and the models. Likelihood-based approaches to errors have proven to be powerful and adaptable in experimental structural biology, finding applications in both crystallography and cryo-EM. Indeed, previous crystallographic work on the errors in structural models is directly applicable to likelihood targets in cryo-EM. Likelihood targets in Fourier space are derived here to characterize, based on the comparison of half-maps, the direction- and resolution-dependent variation in the strength of both signal and noise in the data. Because the signal depends on local features, the signal and noise are analysed in local regions of the cryo-EM reconstruction. The likelihood analysis extends to prediction of the signal that will be achieved in any docking calculation for a model of specified quality and completeness. A related calculation generalizes a previous measure of the information gained by making the cryo-EM reconstruction.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1980

A computer program for determining truncation error coefficients for Runge-Kutta methods

The basic structure of a program to generate the truncation error coefficients for Runge-Kutta (RK) methods is reformulated to reduce storage requirements significantly and to accommodate variable dimensioning. This FORTRAN program, SUBROUTINE RKEQ, determines truncation error coefficients for RK algorithms for orders 1 through 10 and extends the order of coefficients through 12 with the 11th- and 12th-order terms determined following the patterns used to establish the lower order coefficients. Both subroutines (the original and RKEQ) are also written to treat RK m-fold methods which utilize m known derivatives of f to increase the order of the algorithm. Setting m = 0 gives the classical RK algorithm.

Horn, M. K.↗
NASA NTRS1993

The sensitivity of identified modal parameters to sensor placement errors and construction tolerances

This paper examines the sensitivity of experimentally measured modal frequencies and mode shapes to structural reassembly and sensor placement errors on a suspended three-bay truss. The statistical variations of identified mode shapes and frequencies are measured by repeated experiments. Both parameters are shown to vary measurably more with reassembly than sensor placement errors. Also, a directional stiffness in the truss joints was found to cause a parameter dependence on member orientation during reconstruction.

Hinkle, Jason↗