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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
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↗
NASA NTRS1992

A structured data transfer protocol

The transfer of data between different computers and programs can be a major obstacle during data analysis. We present a new data transfer protocol which is based on a simple structure containing a value, an error, and a unit. Each of these members can be arrays or another structure. The ability to nest structures allows for the concept of objects. When using an object-oriented language such as C++, reference can be made to the object name instead of each element explicitly. Prototype code has been written which implements the basic design with enhancements planned for the future.

Barrett, P.↗
DOE OSTI2022

Revisiting Multi-Material Composite Structures with Homogenized Composite Properties

Composite structures inherently develop residual stresses during their curing process. Driven predominately by mismatched thermal strains between differing materials or ply orientations, but also affected by curing process phenomena like polymer shrinkage, these residual stresses can lead to failure within composite structures. There are several methods varying in complexity that can be used to model the development of residual stresses, all of which are capable of capturing sufficient detail to understand the residual stress state at the ply level. However, explicitly modeling all plies of a layup in a composite structure can be prohibitively expensive based on the number of plies, structure size, and required element size. The computational cost can be reduced through the homogenization of the composite layup without losing much fidelity of the overall response of the structure. The homogenization process reduces the many plies of a laminate to a single lamina that reduces complexity and increases the mesh size where a single element can span multiple plies. This report focuses on verification and validation efforts for a homogenization process using a suite of finite element simulations rather than an analytic solution derived from classical laminate theory. Initial verification using representative element volumes indicated there was minimal error in the homogenization process; however, this compounded to a small, but acceptable error in strip and split ring experimental composite structures. The error does under predict the residual stress state in the strip and split ring and should be accounted for when simulating composite structures with homogenized properties.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Classification and reduction of pilot error

Human error is a primary or contributing factor in about two-thirds of commercial aviation accidents worldwide. With the ultimate goal of reducing pilot error accidents, this contract effort is aimed at understanding the factors underlying error events and reducing the probability of certain types of errors by modifying underlying factors such as flight deck design and procedures. A review of the literature relevant to error classification was conducted. Classification includes categorizing types of errors, the information processing mechanisms and factors underlying them, and identifying factor-mechanism-error relationships. The classification scheme developed by Jens Rasmussen was adopted because it provided a comprehensive yet basic error classification shell or structure that could easily accommodate addition of details on domain-specific factors. For these purposes, factors specific to the aviation environment were incorporated. Hypotheses concerning the relationship of a small number of underlying factors, information processing mechanisms, and error types types identified in the classification scheme were formulated. ASRS data were reviewed and a simulation experiment was performed to evaluate and quantify the hypotheses.

Rogers, W. H.↗
NASA NTRS2007

Using MODIS and GLAS Data to Develop Timber Volume Estimates in Central Siberia

The boreal forest is the Earth's largest terrestrial biome, covering some 12 million km2 and accounting for about one third of this planet's total forest area. Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. Ground based forest inventories, have much uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse and/or lacking. In addition, many of the forest inventories that do exist for Siberia are now a decade or more old. Thus, available forest inventories fail to capture the current conditions. Changes in forest structure in a particular forest-type and region can change significantly due to changing environment conditions, and natural and anthropogenic disturbance. Remote sensing methods can potentially overcome these problems. Multispectral sensors can be used to provide vegetation cover maps that show a timely and accurate geographic distribution of vegetation types rather than decade old ground based maps. Lidar sensors can be used to directly obtain measurements that can be used to derive critical forest structure information (e.g., height, density, and volume). These in turn can used to estimate biomass components using allometric equations without having to use out dated forest inventory. Finally, remote sensing data is ideally suited to provide a sampling basis for a rigorous statistical estimate of the variance and error bound on forest structure measures. In this study, new remote sensing methods were applied to develop estimates timber volume using NASA's MODerate resolution Imaging Spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) for a 10 deg x 10 deg area in central Siberia. Using MODIS and GLAS data, maps were produced for cover type and timber volume for 2003, and a realistic variance (error bound) for timber volume was calculated for the study area. In this 'study we used only GLAS footprints that had a slope value of less than 10 deg. This was done to avoid large errors due to the effect of slope on the GLAS models. The method requires the integration of new remote sensing methods with available ground studies of forest timber volume conducted in Russian forests. The results were compared to traditional ground forest inventory methods reported in the literature and to ground truth collected in the study area.

Ranson, K. Jon↗
NASA NTRS2005

Handling Trajectory Uncertainties for Airborne Conflict Management

Airborne conflict management is an enabling capability for NASA's Distributed Air-Ground Traffic Management (DAG-TM) concept. DAGTM has the goal of significantly increasing capacity within the National Airspace System, while maintaining or improving safety. Under DAG-TM, autonomous aircraft maintain separation from each other and from managed aircraft unequipped for autonomous flight. NASA Langley Research Center has developed the Autonomous Operations Planner (AOP), an onboard decision support system that provides airborne conflict management (ACM) and strategic flight planning support for autonomous aircraft pilots. The AOP performs conflict detection, prevention, and resolution from nearby traffic aircraft and area hazards. Traffic trajectory information is assumed to be provided by Automatic Dependent Surveillance Broadcast (ADS-B). Reliable trajectory prediction is a key capability for providing effective ACM functions. Trajectory uncertainties due to environmental effects, differences in aircraft systems and performance, and unknown intent information lead to prediction errors that can adversely affect AOP performance. To accommodate these uncertainties, the AOP has been enhanced to create cross-track, vertical, and along-track buffers along the predicted trajectories of both ownship and traffic aircraft. These buffers will be structured based on prediction errors noted from previous simulations such as a recent Joint Experiment between NASA Ames and Langley Research Centers and from other outside studies. Currently defined ADS-B parameters related to navigation capability, trajectory type, and path conformance will be used to support the algorithms that generate the buffers.

Barhydt, Richard↗