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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 415 records · Page 23

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NASA NTRS1985

Improved numerical methods for turbulent viscous recirculating flows

The hybrid-upwind finite difference schemes employed in generally available combustor codes possess excessive numerical diffusion errors which preclude accurate quantative calculations. The present study has as its primary objective the identification and assessment of an improved solution algorithm as well as discretization schemes applicable to analysis of turbulent viscous recirculating flows. The assessment is carried out primarily in two dimensional/axisymetric geometries with a view to identifying an appropriate technique to be incorporated in a three-dimensional code.

Turan, A.↗

NASA NTRS1988

Lidar windshear detection and avoidance: Performance and technical assessment

The objective of this study is to evaluate competing lidars for use in an airborne forward-looking system to enable aircraft to avoid the hazards of low altitude wind shear. Information is presented in vugraph form on lidar general requirements, tentative technical requirements, comparison of velocity errors and signal to noise ratios in clear weather for 2.1 and 10.6 micron lidars, a wind shear display, and preliminary results.

Targ, Russell↗

NASA NTRS1988

Computational aspects of sensitivity calculations in transient structural analysis

A key step in the application of formal automated design techniques to structures under transient loading is the calculation of sensitivities of response quantities to the design parameters. This paper considers structures with general forms of damping acted on by general transient loading and addresses issues of computational errors and computational efficiency. The equations of motion are reduced using the traditional basis of vibration modes and then integrated using a highly accurate, explicit integration technique. A critical point constraint formulation is used to place constraints on the magnitude of each response quantity as a function of time. Three different techniques for calculating sensitivities of the critical point constraints are presented. The first two are based on the straightforward application of the forward and central difference operators, respectively. The third is based on explicit differentiation of the equations of motion. Condition errors, finite difference truncation errors, and modal convergence errors for the three techniques are compared by applying them to a simple five-span-beam problem. Sensitivity results are presented for two different transient loading conditions and for both damped and undamped cases.

Greene, William H.↗

NASA NTRS1989

Computational aspects of sensitivity calculations in transient structural analysis

A key step in the application of formal automated design techniques to structures under transient loading is the calculation of sensitivities of response quantities to the design parameters. This paper considers response quantities to the design parameters. This paper considers structures with general forms of damping acted on by general transient loading and addresses issues of computational errors and computational efficiency. The equations of motion are reduced using the traditional basis of vibration modes and then integrated using a highly accurate, explicit integration technique. A critical point constraint formulation is used to place constraints on the magnitude of each response quantity as a function of time. Three different techniques for calculating sensitivities of the critical point constraints are presented. The first two are based on the straightforward application of the forward and central difference operators, respectively. The third is based on explicit differentiation of the equations of motion. Condition errors, finite difference truncation errors, and modal convergence errors for the three techniques are compared by applying them to a simple five-span-beam problem. Sensitivity results are presented for two different transient loading conditions and for both damped and undamped cases.

Greene, William H.↗

NASA NTRS1992

Progress in the determination of the gravitational coefficient of the earth

In most of the recent determinations of the geocentric gravitational coefficient (GM) of the earth, the laser ranging data to the Lageos satellite have had the greatest influence on the solution. These data, however, have generally been processed with a small but significant error in one of the range corrections. In a new determination of GM using the corrected center-of-mass offset, a value of 398600.4415 cu km/sq sec (including the mass of the atmosphere) has been obtained, with an estimated uncertainty (1 sigma of 0.0008 cu km/sq sec.

Ries, J. C.↗

NASA NTRS1992

Using neural networks and Dyna algorithm for integrated planning, reacting and learning in systems

The traditional AI answer to the decision making problem for a robot is planning. However, planning is usually CPU-time consuming, depending on the availability and accuracy of a world model. The Dyna system generally described in earlier work, uses trial and error to learn a world model which is simultaneously used to plan reactions resulting in optimal action sequences. It is an attempt to integrate planning, reactive, and learning systems. The architecture of Dyna is presented. The different blocks are described. There are three main components of the system. The first is the world model used by the robot for internal world representation. The input of the world model is the current state and the action taken in the current state. The output is the corresponding reward and resulting state. The second module in the system is the policy. The policy observes the current state and outputs the action to be executed by the robot. At the beginning of program execution, the policy is stochastic and through learning progressively becomes deterministic. The policy decides upon an action according to the output of an evaluation function, which is the third module of the system. The evaluation function takes the following as input: the current state of the system, the action taken in that state, the resulting state, and a reward generated by the world which is proportional to the current distance from the goal state. Originally, the work proposed was as follows: (1) to implement a simple 2-D world where a 'robot' is navigating around obstacles, to learn the path to a goal, by using lookup tables; (2) to substitute the world model and Q estimate function Q by neural networks; and (3) to apply the algorithm to a more complex world where the use of a neural network would be fully justified. In this paper, the system design and achieved results will be described. First we implement the world model with a neural network and leave Q implemented as a look up table. Next, we use a lookup table for the world model and implement the Q function with a neural net. Time limitations prevented the combination of these two approaches. The final section discusses the results and gives clues for future work.

Lima, Pedro↗

NASA NTRS1992

Integrating Test Results With Analysis to Improve Safe Separation Flight Tests

Although extensive ground testing, utilizing both the Captive Trajectory system (CTS) and grid method, generally precedes flight testing of new aircraft/weapon combinations, the flight test results often do not match the wind tunnel predictions. These discrepancies are generally attributed to model scale, wind tunnel test errors and Reynolds Number effects, and may have been the cause of several previous aircraft/weapon incidents. The paper describes the procedure used at the Naval Air Warfare Center, Aircraft Division, Warminster (NAWCADWAR) during the early phases of wind tunnel testing and analysis, as well as subsequent flight testing to validate the predicted trajectories. This approach is designed to improve the safety of the flight tests for the critical portions of the aircraft envelope.

Flight Testing↗

NASA NTRS1998

Standard Giant Branches in the Washington Photometric System

We have obtained CCD photometry in the Washington system C, T(sub 1) filters for some 850,000 objects associated with 10 Galactic globular clusters and 2 old open clusters. These clusters have well-known metal abundances, spanning a metallicity range of 2.5 dex from [Fe/H] approx -2.25 to +0.25 at a spacing of approx. 0.2 dex. Two independent observations were obtained for each cluster and internal checks, as well as external comparisons with existing photoelectric photometry, indicate that the final colors and magnitudes have overall uncertainties of 0.03 mag. Analogous to the method employed by Da Costa and Armandroff for V, I photometry , we then proceed to construct standard ((M(sub T),(C - T(sub 1))(sub 0)) giant branches for these clusters adopting the Lee et distance scale, using some 350 stars per globular cluster to define the giant branch. We then determine the metallicity sensitivity of the ((C - T(sub 1))(sub 0) color at a given M((sub T)(sub 1)) value. The Washington system technique is found to have three times the metallicity sensitivity of the V, I technique. At M((sub T)(sub 1)) = -2 (about a magnitude below the tip of the giant branch, roughly equivalent to M(sub I) = -3), the giant branches of 47 Tuc and M15 are separated by 1.16 magnitudes in (V - l)(sub 0) and only 0.38 magnitudes in (V - I)(sub 0). Thus, for a given photometric accuracy, metallicities can be determined three times more precisely with the Washington technique. We find a linear relationship between (C - T(sub l)(sub 0) (at M(sub T)(sub 1) = -2) and metallicity exists over the full metallicity range, with an rms of only 0.04 dex. We also derive metallicity calibrations for M(sub T)(sub 1) = -2.5 and -1.5, as well as for two other metallicity scales. The Washington technique retains almost the same metallicity sensitivity at faint magnitudes , and indeed the standard giant branches are still well separated even below the horizontal branch. The photometry is used to set upper limits in the range 0.03 - 0.09 dex for any intrinsic metallicity dispersion in the calibrating clusters. The calibrations are applicable to objects with ages approx. greater than 5 Gyr - any age effects are small or negligible for such objects. This new technique is found to have many advantages over the old two-color diagram technique for deriving metallicities from Washington photometry. In addition to only requiring 2 filters instead of 3 or 4, the new technique is generally much less sensitive to reddening and photometric errors, and the metallicity sensitivity is many times higher. The new technique is especially advantageous for metal-poor objects. The five metal-poor clusters determined by Geisler et al., using the old technique, to be much more metal-poor than previous indications, yield metallicities using the new technique which are in excellent agreement with the Zinn scale.

Geisler, Doug↗

NASA NTRS2003

Thermal Characterization of Functionally Graded Materials: Design of Optimum Experiments

This paper is a study of optimal experiment design applied to the measure of thermal properties in functionally graded materials. As a first step, a material with linearly-varying thermal properties is analyzed, and several different tran- sient experimental designs are discussed. An optimality criterion, based on sen- sitivity coefficients, is used to identify the best experimental design. Simulated experimental results are analyzed to verify that the identified best experiment design has the smallest errors in the estimated parameters. This procedure is general and can be applied to design of experiments for a variety of materials.

Cole, Kevin D.↗

NASA NTRS1961

An Explicit Linear Filtering Solution for the Optimization of Guidance Systems with Statistical Inputs

The determination of optimum filtering characteristics for guidance system design is generally a tedious process which cannot usually be carried out in general terms. In this report a simple explicit solution is given which is applicable to many different types of problems. It is shown to be applicable to problems which involve optimization of constant-coefficient guidance systems and time-varying homing type systems for several stationary and nonstationary inputs. The solution is also applicable to off-design performance, that is, the evaluation of system performance for inputs for which the system was not specifically optimized. The solution is given in generalized form in terms of the minimum theoretical error, the optimum transfer functions, and the optimum transient response. The effects of input signal, contaminating noise, and limitations on the response are included. From the results given, it is possible in an interception problem, for example, to rapidly assess the effects on minimum theoretical error of such factors as target noise and missile acceleration. It is also possible to answer important questions regarding the effect of type of target maneuver on optimum performance.

Stewart, Elwood C.↗

NASA NTRS1999

The evolution of Crew Resource Management training in commercial aviation

In this study, we describe changes in the nature of Crew Resource Management (CRM) training in commercial aviation, including its shift from cockpit to crew resource management. Validation of the impact of CRM is discussed. Limitations of CRM, including lack of cross-cultural generality are considered. An overarching framework that stresses error management to increase acceptance of CRM concepts is presented. The error management approach defines behavioral strategies taught in CRM as error countermeasures that are employed to avoid error, to trap errors committed, and to mitigate the consequences of error.

Non-NASA Center↗

NASA NTRS2004

On Bayesian Inductive Inference & Predictive Estimation

We investigate Bayesian inference and the Principle of Maximum Entropy (PME) as methods for doing inference under uncertainty. This investigation is primarily through concrete examples that have been previously investigated in the literature. We find that it is possible to do Bayesian inference and PME inference using the same information, despite claims to the contrary, but that the results are not directly comparable. This is because Bayesian inference yields a probability density function (pdf) over the unknown model parameters, whereas PME yields point estimates. If mean estimates are extracted from the Bayesian pdfs, the resulting parameter estimates can differ radically from the PME values and also from the Maximum Likelihood values. We conclude that these differences are due to the Bayesian inference not assuming anything beyond the given prior probabilities and the data, whereas PME implicitly assumes that the given constraints are the only constraints that are operating. Since this assumption can be wrong, PME values may have to be revised when subsequent data shows evidence for more constraints. The entropy concentration previously "proved" by E. T. Jaynes is shown to be in error. Further, we show that PME is a generalized form of independence assumption, and so can be a very powerful method of inference when the variables being investigated are largely independent of each other.

Cheeseman, Peter↗

NASA NTRS2008

Towards Verification of Unstructured-Grid Solvers

New methodology for verification of computational methods using unstructured grids is presented. The discretization order properties are studied in computational windows, easily constructed within a collection of grids or a single grid. The windows can be adjusted to isolate the interior discretization, the boundary discretization, or singularities. A major component of the methodology is the downscaling test, introduced previously for studying the convergence rates of truncation and discretization errors of finite-volume discretization schemes on general unstructured grids. Demonstrations of the method are shown, including a comparative accuracy assessment of commonly-used schemes on general mixed grids and the identification of local accuracy deterioration at intersections of tangency and inflow/outflow boundaries. Recommendations for the use of the methodology in large-scale computational simulations are given.

Thomas, James L.↗

NASA NTRS2004

Software for Generating Strip Maps from SAR Data

Jurassicprok is a computer program that generates strip-map digital elevation models and other data products from raw data acquired by an airborne synthetic-aperture radar (SAR) system. This software can process data from a variety of airborne SAR systems but is designed especially for the GeoSAR system, which is a dual-frequency (P- and X-band), single-pass interferometric SAR system for measuring elevation both at the bare ground surface and top of the vegetation canopy. Jurassicprok is a modified version of software developed previously for airborne-interferometric- SAR applications. The modifications were made to accommodate P-band interferometric processing, remove approximations that are not generally valid, and reduce processor-induced mapping errors to the centimeter level. Major additions and other improvements over the prior software include the following: a) A new, highly efficient multi-stage-modified wave-domain processing algorithm for accurately motion compensating ultra-wideband data; b) Adaptive regridding algorithms based on estimated noise and actual measured topography to reduce noise while maintaining spatial resolution; c) Exact expressions for height determination from interferogram data; d) Fully calibrated volumetric correlation data based on rigorous removal of geometric and signal-to-noise decorrelation terms; e) Strip range-Doppler image output in user-specified Doppler coordinates; f) An improved phase-unwrapping and absolute-phase-determination algorithm; g) A more flexible user interface with many additional processing options; h) Increased interferogram filtering options; and i) Ability to use disk space instead of random- access memory for some processing steps.

Hensley, Scott↗

NASA NTRS2019

Lidar-Polarimeter Retrieval OSSEs in Support of NASA's Aerosols and Clouds-Convection-Precipitation (ACCP) Study

The 2017 Decadal Survey (DS) highlighted Earth System Science themes, science and application questions, and several high priority objectives that have led to the inclusion of Aerosols (A) and Clouds-Convection-Precipitation (CCP) as Designated Observables (DOs). On June 1, 2018, several NASA centers (GSFC, LaRC, JPL, MSFC, GRC and ARC) submitted a joint Study Plan to the NASA Earth Science Division for the Aerosol (A) and Cloud, Convection, and Precipitation (CCP) Pre-formulation Study (A-CCP). The DS and the A-CCP team recognized the science merit in combining the A and CCP DOs for both enhancing the ability to address a number of science objectives and also to provide an expanded capability to address additional objectives beyond those addressed by individual DOs.A critical element of the A-CCP observing strategy is to make extensive use of new passive and active sensors as well as of the so-called Program-of-Record (PoR), complemented by a fully integrated sub-orbital component. Central to this observing system design is the adoption of a Value Framework in which quantitative assessment of the science benefits of space-and air-borne assets is a key element. Given pre-defined A-CCP science objectives and geophysical variables with desired accuracies, A-CCP relies on a spectrum of Observing System Simulation Experiments (OSSEs) aimed at addressing pixel level retrieval uncertainties and sampling trade-offs. In this talk we will discuss a subset of Retrieval OSSEs being considered for A-CCP, namely, synergistic lidar-polarimeter retrievals of particular relevance for the A-CCP aerosol science objectives. Starting with aerosol states from the GEOS-5 Nature Run (G5NR) sampled along specific satellite orbits, we simulate polarized radiances at the desired polarimeter wavelengths with the Vector Linearized Direct Ordinate Radiative Transfer (VLIDORT) model, alongside the lidar signal for the relevant lidars with realistic error characterization. Next, inversions are performed with the Generalized Retrieval of Aerosol and Surface Properties (GRASP) system and the accuracy of the retrieved geophysical variables are assessed. In this presentation we will highlight results for key architectures being considered for A-CCP.

da Silva, Arlindo↗

NASA NTRSDate not supplied

Lidar-Polarimeter Retrieval OSSEs using a Nature Run in Support of NASA's Aerosols, Clouds, Convection and Precipitation (ACCP) Study

The 2017 Decadal Survey (DS) highlighted Earth System Science themes, science and application questions, and several high priority objectives that have led to the inclusion of Aerosols (A) and Clouds-Convection-Precipitation (CCP) as Designated Observables (DOs). On June 1, 2018, several NASA centers (GSFC, LaRC, JPL, MSFC, GRC and ARC) submitted a joint Study Plan to the NASA Earth Science Division for the Aerosol (A) and Cloud, Convection, and Precipitation (CCP) Pre-formulation Study (ACCP). The DS and the ACCP team recognized the science merit in combining the A and CCP DOs for both enhancing the ability to address a number of science objectives and also to provide an expanded capability to address additional objectives beyond those addressed by individual DOs. A critical element of the ACCP observing strategy is to make extensive use of new passive and active sensors as well as of the so-called Program-of-Record (PoR), complemented by a fully integrated sub-orbital component. Central to this observing system design is the adoption of a Value Framework in which quantitative assessment of the science benefits of space- and air-borne assets is a key element. Given pre-defined ACCP science objectives and geophysical variables with desired accuracies, ACCP relies on a spectrum of Observing System Simulation Experiments (OSSEs) aimed at addressing pixel level retrieval uncertainties and sampling trade-offs. In this talk we will discuss a subset of Retrieval OSSEs being considered for ACCP, namely, synergistic lidar-polarimeter retrievals based on observation simulations from the GEOS-5 Nature Run (G5NR). Starting with aerosol states from the GEOS-5 Nature Run (G5NR) sampled along specific satellite orbits, we simulate polarized radiances at the desired polarimeter wavelengths with the Vector Linearized Direct Ordinate Radiative Transfer (VLIDORT) model, alongside the lidar signal for the relevant lidars with realistic error characterization. Next, inversions are performed with the Generalized Retrieval of Aerosol and Surface Properties (GRASP) system and the accuracy of the retrieved geophysical variables are assessed. In this presentation we will highlight results for key architectures being considered for ACCP with emphasis on geophysical variables of particular relevance to ACCP’s aerosol science objectives.

A Da Silva↗

NASA NTRSDate not supplied

Going beyond reliability to achieve robustness

Reliability is the ability to perform well and consistently. More formally, reliability is defined as the mathematical probability that a system does not fail during a specified time period under its specified operating conditions. The specified operating conditions often go beyond the nominal environment to include variations and challenges encountered in operational use. The difficulty is that systems are often operated outside of their specified operating conditions and, if they fail, the designers are in theory blameless. Unanticipated damaging events include internal failures, external disruptions in supporting systems, accidents, and repurposing. The most common explanation of a system failure is human error, which is usually the first assumption of the system designers. Robustness is the capability to perform without failure under a wide range of conditions that go beyond the specified operating conditions. The first step towards improving robustness would be to expand the system’s specified operating conditions to include a wider range of anticipated challenges, especially human error. Beyond this, there is a need for general approach to reduce the impact of unanticipated future events, the unknown unknowns, by improving the system’s general ability to cope. Robustness can be improved by providing additional processing capacity, larger flow control buffers, increased backup storage, more online redundancy, and more capable supervisory monitoring and control.

Harry W Jones↗

NASA NTRS2023

Uncertainty Analysis of Slug Calorimeters in the HyMETS Arc-Jet Facility

The objective of this work is to perform an uncertainty analysis of the deduced stagnation heat flux environment on a slug calorimeter for conditions that span the performance envelope of the Hypersonic Materials Environmental Test System arc-jet facility located at NASA Langley Research Center. Analytical solutions are developed for boundary-value problems on the slug element accounting for non-ideal effects, including spatial variation in the slug heat flux, multi-dimensional thermal conduction, and back-face losses, which departs from the state-of-the-art method derived from the American Society of Testing and Materials. Boundary-value problem definitions are informed by preliminary finite element thermal analysis of the slug calorimeter assembly (including both slug and housing) and just the slug element. The analytical solutions are presented in a general sense and in a truncated form from error analysis. Results are shown in optimizing and validating the analytical models against available slug back-face thermal data. The optimization results indicate that the appropriate epistemic uncertainty of the deduced stagnation heat flux on the slug calorimeter is at most±2.5% for both a high-and low-enthalpy test condition. In addition, a numerical approach is used to determine the aleatory (probabilistic) uncertainty component in the slug stagnation heat flux by applying a marching least-squares slope routine through the steady-state portion of the slug back-face thermal response. Results indicate a compromise between the number of samples and the filter frequency of slug back-face thermal data points when evaluating the standard deviation of the deduced stagnation heat flux statistics. When combining the mixed uncertainty, both aleatory and epistemic, the interval of uncertainty in the deduced stagnation heat flux is determined to be up to ±4%, which is at least a 60% reduction from the standard uncertainty used in the state-of-the-art method.

uncertainty↗