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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Tropospheric monitoring technology for gravity wave experiments

Tropospheric refractivity fluctuations are an important error source for gravity wave detection by Doppler tracking in that they alter the phase and phase rate of electromagnetic signals. Estimates are presented of the effect of tropospheric fluctuations on the Doppler signal and some examples are suggested of methods which minimize the effect. A model of the fluctuations is utilized to achieve those goals. Four possible methods for reducing the fluctuation effect are suggested: (1) observation and analysis strategies, which separate the atmospheric and gravity wave signatures; (2) water vapor radiometry for the wet component; (3) calibration using Global Positioning System (GPS) satellites; and (4) Doppler observations from multiple antennas to average fluctuation effects. The last two techniques could be used to calibrate both wet and dry fluctuations, or could be used in conjunction with water vapor radiometry to calibrate only the dry component.

Treuhaft, R. N.↗
NASA NTRS1991

Program Analyzes Errors In STAGS

EAC computer program designed for analysis of errors in results of STAGS computer program (COSMIC Program HQN-10967). Requires input data for geometry of plate, properties of material, and set of boundary conditions. These input data come from STAGS code. (The specific link between input and output data from STAGS and input data for EAC is POSTP, postprocessor program in STAGS processors.) EAC computes continuous solution from discrete results of STAGS in order to estimate error of results of STAGS. Written in FORTRAN 77.

Thurston, Gaylen A.↗
NASA NTRS1992

Modified optimal control pilot model for computer-aided design and analysis

This paper presents the theoretical development of a modified optimal control pilot model based upon the optimal control model (OCM) of the human operator developed by Kleinman, Baron, and Levison. This model is input compatible with the OCM and retains other key aspects of the OCM, such as a linear quadratic solution for the pilot gains with inclusion of control rate in the cost function, a Kalman estimator, and the ability to account for attention allocation and perception threshold effects. An algorithm designed for each implementation in current dynamic systems analysis and design software is presented. Example results based upon the analysis of a tracking task using three basic dynamic systems are compared with measured results and with similar analyses performed with the OCM and two previously proposed simplified optimal pilot models. The pilot frequency responses and error statistics obtained with this modified optimal control model are shown to compare more favorably to the measured experimental results than the other previously proposed simplified models evaluated.

Davidson, John B.↗
NASA NTRS1996

Determination of Small Animal Long Bone Properties Using Densitometry

Assessment of bone structural property changes due to loading regimens or pharmacological treatment typically requires destructive mechanical testing and sectioning. Our group has accurately and non-destructively estimated three dimensional cross-sectional areal properties (principal moments of inertia, Imax and Imin, and principal angle, Theta) of human cadaver long bones from pixel-by-pixel analysis of three non-coplanar densitometry scans. Because the scanner beam width is on the order of typical small animal diapbyseal diameters, applying this technique to high-resolution scans of rat long bones necessitates additional processing to minimize errors induced by beam smearing, such as dependence on sample orientation and overestimation of Imax and Imin. We hypothesized that these errors are correctable by digital image processing of the raw scan data. In all cases, four scans, using only the low energy data (Hologic QDR-1000W, small animal mode), are averaged to increase image signal-to-noise ratio. Raw scans are additionally processed by interpolation, deconvolution by a filter derived from scanner beam characteristics, and masking using a variable threshold based on image dynamic range. To assess accuracy, we scanned an aluminum step phantom at 12 orientations over a range of 180 deg about the longitudinal axis, in 15 deg increments. The phantom dimensions (2.5, 3.1, 3.8 mm x 4.4 mm; Imin/Imax: 0.33-0.74) were comparable to the dimensions of a rat femur which was also scanned. Cross-sectional properties were determined at 0.25 mm increments along the length of the phantom and femur. The table shows average error (+/- SD) from theory of Imax, Imin, and Theta) over the 12 orientations, calculated from raw and fully processed phantom images, as well as standard deviations about the mean for the femur scans. Processing of phantom scans increased agreement with theory, indicating improved accuracy. Smaller standard deviations with processing indicate increased precision and repeatability. Standard deviations for the femur are consistent with those of the phantom. We conclude that in conjunction with digital image enhancement, densitometry scans are suitable for non-destructive determination of areal properties of small animal bones of comparable size to our phantom, allowing prediction of Imax and Imin within 2.5% and Theta within a fraction of a degree. This method represents a considerable extension of current methods of analyzing bone tissue distribution in small animal bones.

Breit, Gregory A.↗
NASA NTRS2009

Astrometry With the Hubble Space Telescope: Trigonometric Parallaxes of Planetary Nebula Nuclei NGC 6853, NGC 7293, ABELL 31, and DeHt 5

We present absolute parallaxes and relative proper motions for the central stars of the planetary nebulae NGC 6853 (The Dumbbell), NGC 7293 (The Helix), Abell 31, and DeHt 5. This paper details our reduction and analysis using DeHt 5 as an example. We obtain these planetary nebula nuclei (PNNi) parallaxes with astrometric data from Fine Guidance Sensors FGS 1r and FGS 3, white-light interferometers on the Hubble Space Telescope. Proper motions, spectral classifications and VJHKT2M and DDO51 photometry of the stars comprising the astrometric reference frames provide spectrophotometric estimates of reference star absolute parallaxes. Introducing these into our model as observations with error, we determine absolute parallaxes for each PNN. Weighted averaging with previous independent parallax measurements yields an average parallax precision, sigma (sub pi)/ pi = 5%. Derived distances are: d(sub NGC6853) = 405(exp +28 sub -25) pc, d(sub NGC7293) = 216(exp +14 sub -12) pc, d(sub Abell31) = 621(exp +91 sub -70) pc, and d(sub DeHt5) = 345(exp +19 sub -17) pc. These PNNi distances are all smaller than previously derived from spectroscopic analyses of the central stars. To obtain absolute magnitudes from these distances requires estimates of interstellar extinction. We average extinction measurements culled from the literature, from reddening based on PNNi intrinsic colors derived from model SEDs, and an assumption that each PNN experiences the same rate of extinction as a function of distance as do the reference stars nearest (in angular separation) to each central star. We also apply Lutz-Kelker bias corrections. The absolute magnitudes and effective temperatures permit estimates of PNNi radii through both the Stefan-Boltzmann relation and Eddington fluxes. Comparing absolute magnitudes with post-AGB models provides mass estimates. Masses cluster around 0.57 solar Mass, close to the peak of the white dwarf mass distribution. Adding a few more PNNi with well-determined distances and masses, we compare all the PNNi with cooler white dwarfs of similar mass, and confirm, as expected, that PNNi have larger radii than white dwarfs that have reached their final cooling tracks.

STARS↗
NASA NTRS2013

Systems and methods for circuit lifetime evaluation

Systems and methods for estimating the lifetime of an electrical system in accordance with embodiments of the invention are disclosed. One embodiment of the invention includes iteratively performing Worst Case Analysis (WCA) on a system design with respect to different system lifetimes using a computer to determine the lifetime at which the worst case performance of the system indicates the system will pass with zero margin or fail within a predetermined margin for error given the environment experienced by the system during its lifetime. In addition, performing WCA on a system with respect to a specific system lifetime includes identifying subcircuits within the system, performing Extreme Value Analysis (EVA) with respect to each subcircuit to determine whether the subcircuit fails EVA for the specific system lifetime, when the subcircuit passes EVA, determining that the subcircuit does not fail WCA for the specified system lifetime, when a subcircuit fails EVA performing at least one additional WCA process that provides a tighter bound on the WCA than EVA to determine whether the subcircuit fails WCA for the specified system lifetime, determining that the system passes WCA with respect to the specific system lifetime when all subcircuits pass WCA, and determining that the system fails WCA when at least one subcircuit fails WCA.

Heaps, Timothy L.↗
NASA NTRS2013

Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This proposal describes an approach to validate the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft. The research described here is absolutely cutting edge. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional"validation by test only'' mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computationaf Fluid Dynamics can be used to veritY these requirements; however, the model must be validated by test data. The proposed research project includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT and OPEN FOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid . . . Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System /spacecraft system. Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. To date, the author is the only person to look at the uncertainty in the entire computational domain. For the flow regime being analyzed (turbulent, threedimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.

Groves, Curtis E.↗
NASA NTRS2014

Dissertation Defense Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional "validation by test only" mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System /spacecraft system. Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. For the flow regime being analyzed (turbulent, three-dimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.

CFD↗
NASA NTRS2014

Dissertation Defense: Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional validation by test only mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions.Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations. This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System spacecraft system.Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. For the flow regime being analyzed (turbulent, three-dimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.

Fluid Dynamics↗
NASA NTRS2017

A Celestial Reference Frame Based on Kalman Filtering

In this study, we investigate a novel approach to the determination of celestial reference frames (CRF). Instead of a constant model for radio sources positions, we adopt a time series representation, which allows temporal variations of radio source coordinates to be taken into account. In particular, the added flexibility is beneficial for radio sources with extended structure. We compute our time series-based CRF solutions by Kalman filtering and smoothing radio source positions, which are initially obtained from single-session VLBI analysis. The temporal resolution of the estimated CRF coordinates is identical to that of the input data, i.e. usually 1-4 days. The magnitude of the coordinate variations is controlled by the amount of process noise applied in the filter, which is in turn derived from analyzing the Allan standard deviation of the corresponding radio source coordinate time series. Measures have been developed to reduce the impact of observation errors and datum effects on the noise model.

Soja, B.↗
DOE OSTI2024

A $C^1$-Conforming Arbitrary-Order Two-Dimensional Virtual Element Method for the Fourth-Order Phase-Field Equation

We present a two-dimensional conforming virtual element method for the fourth-order phase-field equation. Our proposed numerical approach to the solution of this high-order phase-field (HOPF) equation relies on the design of an arbitrary-order accurate, virtual element space with $C^1$ global regularity. Such regularity is guaranteed by taking the values of the virtual element functions and their full gradient at the mesh vertices as degrees of freedom. Attaining high-order accuracy requires also edge polynomial moments of the trace of the virtual element functions and their normal derivatives. In this work, we detail the scheme construction, and prove its convergence by deriving error estimates in different norms. A set of representative test cases allows us to assess the behavior of the method.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1981

NOSS/ALDCS analysis and system requirements definition

The results of system analyses and implementation studies of an advanced location and data collection system (ALDCS) , proposed for inclusion on the National Oceanic Satellite System (NOSS) spacecraft are reported. The system applies Doppler processing and radiofrequency interferometer position location technqiues both alone and in combination. Aspects analyzed include: the constraints imposed by random access to the system by platforms, the RF link parameters, geometric concepts of position and velocity estimation by the two techniques considered, and the effects of electrical measurement errors, spacecraft attitude errors, and geometric parameters on estimation accuracy. Hardware techniques and trade-offs for interferometric phase measurement, ambiguity resolution and calibration are considered. A combined Doppler-interferometer ALDCS intended to fulfill the NOSS data validation and oceanic research support mission is also described.

Reed, D. L.↗
DOE OSTI2026

Optimality of Gradient-MUSIC for Spectral Estimation

We introduce the Gradient-MUSIC algorithm for estimating the unknown frequencies and amplitudes of a nonharmonic signal from noisy time samples. While the classical MUSIC algorithm performs a computationally expensive search over a fine grid, Gradient-MUSIC is significantly more efficient and eliminates the need for discretization over a fine grid by using optimization techniques. It coarsely scans the 1D landscape to find initialization simultaneously for all frequencies followed by parallelizable local refinement via gradient descent. We also analyze its performance when the noise level is sufficiently small and the signal frequencies are separated by at least 8π/m, where π/m is the standard resolution of this problem. Even though the 1D landscape is nonconvex, we prove a global convergence result for Gradient-MUSIC: coarse scanning provably finds suitable initialization and gradient descent converges at a linear rate. In addition to convergence results, we also upper bound the error between the true signal frequencies and amplitudes with those found by Gradient-MUSIC. For example, if the noise has $\ell^\infty$ norm at most ϵ, then the frequencies and amplitudes are recovered up to error at most Cϵ/m and Cϵ respectively, which are minimax optimal in m and ϵ. Our theory can also handle stochastic noise with performance guarantees under nonstationary independent Gaussian noise. Our main approach is a comprehensive geometric analysis of the landscape, a perspective that has not been explored before.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Grey-box and ANN-based building models for multistep-ahead prediction of indoor temperature to implement model predictive control

Model-based predictive control (MPC) strategies for heating, ventilation, and air-conditioning (HVAC) systems present an opportunity to lower building energy consumption and operational costs. Such approaches rely on the development of a model to precisely forecast building thermal dynamics, such as room air temperature or heating/cooling rate, and make control-related decisions. The control-oriented modeling of building energy systems should be accurate in predicting indoor conditions and present low computational complexity. These features are the key challenge of implementing advanced control methods such as MPC. Extant studies on building modeling for MPC have focused on step-ahead forecasting techniques to forecast building thermal dynamics, while multistep-ahead forecasting is essential. Moreover, machine learning model suitable in case of the domain-based engineering expertise are also not available. To this aim, we perform a comparative analysis of the grey-box model based on a resistance-capacitance (RC) thermal network and a machine learning model composed of an artificial neural network (ANN) for multistep-ahead prediction of building thermal dynamics using current and historical data. Actual experimental data obtained from the Flexible Research Platform (FRP) in Oak Ridge National Laboratory (US) are used for estimation and validation purposes. The average root mean squared error (RMSE) of the grey-box and ANN models are 0.89 °C and 1.02°C, respectively. Finally, the results indicate that the grey-box model outperforms the ANN model in the considered validation periods in terms of accuracy and prediction stability.

42 ENGINEERING↗
DOE OSTI2025

Hyperspectral imaging for real-time waste materials characterization and recovery using endmember extraction and abundance detection

Hyperspectral imaging, combined with advanced spectral unmixing techniques and artificial intelligence, offers a powerful solution for improving material identification and classification. Here, this study evaluates the effectiveness of the pixel purity index and the sequential maximum angle convex cone algorithms in extracting and validating spectral signatures from pure samples of paper components (cellulose and lignin) and plastic (polypropylene). Principal-component analysis showed that both algorithms captured nearly all relevant variance for the tested materials. Spectral signatures were compared using the spectral angle mapper, revealing high similarity in the short-wave infrared region and greater variability in the visible near-infrared range. The methodology was then applied to a disposable coffee cup to detect and quantify mixed materials, accurately estimating material abundance and object area with less than 1% error. This approach enhances material classification, supporting product verification, quality control, and automated sorting for sustainable waste management and resource recovery.

36 MATERIALS SCIENCE↗
NASA NTRS1979

Evaluation Applied to Reliability Analysis of Reconfigurable, Highly Reliable, Fault-Tolerant, Computing Systems for Avionics

Emulation techniques are proposed as a solution to a difficulty arising in the analysis of the reliability of highly reliable computer systems for future commercial aircraft. The difficulty, viz., the lack of credible precision in reliability estimates obtained by analytical modeling techniques are established. The difficulty is shown to be an unavoidable consequence of: (1) a high reliability requirement so demanding as to make system evaluation by use testing infeasible, (2) a complex system design technique, fault tolerance, (3) system reliability dominated by errors due to flaws in the system definition, and (4) elaborate analytical modeling techniques whose precision outputs are quite sensitive to errors of approximation in their input data. The technique of emulation is described, indicating how its input is a simple description of the logical structure of a system and its output is the consequent behavior. The use of emulation techniques is discussed for pseudo-testing systems to evaluate bounds on the parameter values needed for the analytical techniques.

Migneault, G. E.↗
NASA NTRS1979

Emulation applied to reliability analysis of reconfigurable, highly reliable, fault-tolerant computing systems

Emulation techniques applied to the analysis of the reliability of highly reliable computer systems for future commercial aircraft are described. The lack of credible precision in reliability estimates obtained by analytical modeling techniques is first established. The difficulty is shown to be an unavoidable consequence of: (1) a high reliability requirement so demanding as to make system evaluation by use testing infeasible; (2) a complex system design technique, fault tolerance; (3) system reliability dominated by errors due to flaws in the system definition; and (4) elaborate analytical modeling techniques whose precision outputs are quite sensitive to errors of approximation in their input data. Next, the technique of emulation is described, indicating how its input is a simple description of the logical structure of a system and its output is the consequent behavior. Use of emulation techniques is discussed for pseudo-testing systems to evaluate bounds on the parameter values needed for the analytical techniques. Finally an illustrative example is presented to demonstrate from actual use the promise of the proposed application of emulation.

Migneault, G. E.↗
NASA NTRS2012

A Nonlinear Adaptive Filter for Gyro Thermal Bias Error Cancellation

Deterministic errors in angular rate gyros, such as thermal biases, can have a significant impact on spacecraft attitude knowledge. In particular, thermal biases are often the dominant error source in MEMS gyros after calibration. Filters, such as J\,fEKFs, are commonly used to mitigate the impact of gyro errors and gyro noise on spacecraft closed loop pointing accuracy, but often have difficulty in rapidly changing thermal environments and can be computationally expensive. In this report an existing nonlinear adaptive filter is used as the basis for a new nonlinear adaptive filter designed to estimate and cancel thermal bias effects. A description of the filter is presented along with an implementation suitable for discrete-time applications. A simulation analysis demonstrates the performance of the filter in the presence of noisy measurements and provides a comparison with existing techniques.

Galante, Joseph M.↗