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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Simulations of the Modular Axisymmetric Scramjet Test Rig Under Reacting Flow Conditions

Simulations of the Air Force Research Laboratory (AFRL) Modular Axisymmetric Scramjet Test Rig (MASTeR) are presented. MASTeR is a parametric test article capable of investigating various scramjet cavity flameholder designs and fueling strategies with the goal to characterize and optimize flameholding capability. In the current work, three cavity aspect ratios, three depths, and two fueling strategies (upstream and in-cavity) with ethylene at a nominal facility pressure and temperature conditions are evaluated. The simulations are performed for mixing-only and reacting flows, and the resulting flow characteristics are compared. For each configuration and fueling strategy, cavity residence time, entrainment rate, and fuel-air equivalence ratio are computed. The MASTeR geometry is defined in the Engineering Sketch Pad (ESP) and the simulations use a sketch-to-solution (S2S) automated unstructured grid adaptation tool in VULCAN-CFD. This tool automatically generates a simulation grid from the ESP geometry and systematically adapts it to the numerical solution based on the Hessian error estimate of a specified flow field parameter. Reynolds averaged simulations (RAS) are used with typical two-equation linear eddy viscosity and diffusivity model. The resulting database can be compared with the experimental data as those becomes available and explored to develop models for cavity performance for scramjet propulsion design applications.

hypersonics↗
NASA NTRSDate not supplied

GT2024-128885: Flow Reconstruction in a Transonic Turbine Cascade using Physics-Informed Neural Networks (PINNs)

This presentation investigates the application of Physics-Informed Neural Networks (PINNs) for the analysis of turbine blades in a transonic cascade. PINNs are a machine learning method trained on losses calculated from reconstructed governing equations, assigned boundary/initial conditions, and measured data. We reconstruct the 2-D flow field in a transonic turbine cascade in two ways: the traditional forward approach (without training/experimental data) and by training the PINN using experimental data. We then compare the PINN solutions to measured data. This is repeated for three different turbine blades with distinct loading characteristics. The experimental data used for training is the static pressure measurements along the suction and pressure sides of each blade. The PINN is trained utilizing all available data, half the available data, data from only the leading edge region, and data from only the trailing edge region. It's shown that the PINN can reconstruct the flow field in all cases with acceptable errors. Cases where the PINN is trained on all the data, and even half the data, resulted in the lowest errors. The exit Mach number is inferred for each case and compared to the experimentally calculated value.

Machine Learning↗
NASA NTRS1986

Accuracy of wind measurements using an airborne Doppler lidar

Simulated wind fields and lidar data are used to evaluate two sources of airborne wind measurement error. The system is sensitive to ground speed and track angle errors, with accuracy required of the angle to within 0.2 degrees and of the speed to within 1 knot, if the recovered wind field is to be within five percent of the correct direction and 10 percent of the correct speed. It is found that errors in recovered wind speed and direction are dependent on wind direction relative to the flight path. Recovery of accurate wind fields from nonsimultaneous sampling errors requires that the lidar data be displaced to account for advection so that the intersections are defined by air parcels rather than fixed points in space.

Carroll, J. J.↗
NASA NTRS1993

Unstructured adaptive mesh computations of rotorcraft high-speed impulsive noise

A new method is developed for modeling helicopter high-speed impulsive (HSI) noise. The aerodynamics and acoustics near the rotor blade tip are computed by solving the Euler equations on an unstructured grid. A stationary Kirchhoff surface integral is then used to propagate these acoustic signals to the far field. The near-field Euler solver uses a solution-adaptive grid scheme to improve the resolution of the acoustic signal. Grid points are locally added and/or deleted from the mesh at each adaptive step. An important part of this procedure is the choice of an appropriate error indicator. The error indicator is computed from the flow field solution and determines the regions for mesh coarsening and refinement. Computed results for HSI noise compare favorably with experimental data for three different hovering rotor cases.

Strawn, Roger↗
NASA NTRS1980

An error analysis of basic kinematic quantities

A description is presented of the computational procedures used to obtain spatial fields of relative vorticity, advection of vorticity, horizontal divergence, and vertical motion. An investigation is conducted of the effectiveness of these procedures to reduce the effects of deliberately introduced random errors, giving attention to the confidence which can be placed on values of the derived parameters. It is concluded that fields of 500 mb vorticity and 700 mb vertical velocity, which are frequently used in synoptic scale forecasting schemes, show minimal effects of the deliberately introduced errors. Vorticity advection is found to be the most sensitive term to input data errors. Large fluctuations in fields of this parameter are evident both statistically and qualitatively.

Berecek, E. M.↗
NASA NTRS1973

Mixed finite-difference scheme for analysis of simply supported thick plates.

A mixed finite-difference scheme is presented for the stress and free vibration analysis of simply supported nonhomogeneous and layered orthotropic thick plates. The analytical formulation is based on the linear, three-dimensional theory of orthotropic elasticity and a Fourier approach is used to reduce the governing equations to six first-order ordinary differential equations in the thickness coordinate. The governing equations possess a symmetric coefficient matrix and are free of derivatives of the elastic characteristics of the plate. In the finite difference discretization two interlacing grids are used for the different fundamental unknowns in such a way as to reduce both the local discretization error and the bandwidth of the resulting finite-difference field equations. Numerical studies are presented for the effects of reducing the interior and boundary discretization errors and of mesh refinement on the accuracy and convergence of solutions. It is shown that the proposed scheme, in addition to a number of other advantages, leads to highly accurate results, even when a small number of finite difference intervals is used.

Noor, A. K.↗
NASA NTRS1987

An algorithm to design finite field multipliers using a self-dual normal basis

Finite field multiplication is central in the implementation of some error-correcting coders. Massey and Omura have presented a revolutionary design for multiplication in a finite field. In their design, a normal base is utilized to represent the elements of the field. The concept of using a self-dual normal basis to design the Massey-Omura finite field multiplier is presented. Presented first is an algorithm to locate a self-dual normal basis for GF(2 sup m) for odd m. Then a method to construct the product function for designing the Massey-Omura multiplier is developed. It is shown that the construction of the product function base on a self-dual basis is simpler than that based on an arbitrary normal base.

Wang, C. C.↗
NASA NTRS2002

Sensitivity of Lower Stratospheric Assimilated Ozone on Error Covariance Modeling and Data Selection

Assimilated ozone is produced at the NASA/Goddard Data Assimilation Office by blending ozone retrieved from the Solar Backscatter UltraViolet/2 (SBUV/2) instrument and the Earth Probe Total Ozone Mapping Spectrometer (EP TOMS) measurements into an off-line transport model. The current system tends to overestimate the amount of lower stratospheric ozone. This is a region where ozone plays a key role in the forcing of climate. A biased ozone field in this region will adversely impact calculations of the stratosphere-troposphere exchange and, when used as a first guess in retrievals, the values determined from satellite observations. Since these are all important applications of assimilated ozone products, effort is being directed towards reducing this bias. The SBUV ozone data have a coarse vertical resolution with increased uncertainty below the ozone maximum, and TOMS provides only total ozone columns. Thus, the assimilated ozone in the lower stratosphere, and its vertical distribution in particular, are only weakly constrained by the incoming SBUV and TOMS data. Consequently, the assimilated ozone distribution should be sensitive to changes in inputs to the statistical analysis scheme. Accordingly, the sensitivity of the assimilated lower stratospheric ozone fields to changes in the TOMS error-covariance modeling and the SBUV data selection has been investigated. The use of a spatially correlated TOMS error covariance model led to improvements in the product. However, withholding the SBUV/2 data for the layer between 63 and 126 hPa typically degraded the product, a result which vindicates the use of this layer ozone product, despite its known errors. These efforts to improve the lower stratospheric distribution will be extended to include a more advanced forecast error covariance model, and by assimilating ozone products from new instruments on Envisat and EOS Aura.

Stajner, Ivanka↗
DOE OSTI2024

A Study on Particle Trajectory Error in Finite-Element Particle-in-Cell Algorithms

Particle-in-cell (PIC) algorithms are widely used for the simulation of kinetic plasmas. PIC algorithms account for the interaction between charged particles in a plasma and the electromagnetic field in ambient space, including self-field interactions. The objective of this article is to study the error in charged particle trajectories present in finite-element (FE)-based PIC algorithms on unstructured meshes. We study how the trajectory error behaves according to the FE mesh resolution and the matrix solver employed in the FE algorithm. The study is performed by considering a trajectory established by a parabolic electric potential and an axial magnetic force acting on the charged particle. Under a proper choice combination of electric and magnetic field parameters, the 2-D particle trajectories comprise closed orbits. Numerical errors cause small perturbations on the trajectories, with cumulative effects. As a result, the resulting orbital trajectories exhibit distortions including spurious apsidal precession. These distortions provide a clear imprint of the numerical error. Here, we also study the numerical error in a quantitative fashion by computing the distance norm between the trajectories obtained by the exact fields and numerical fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2001

The Computational Complexity, Parallel Scalability, and Performance of Atmospheric Data Assimilation Algorithms

The computational complexity of algorithms for Four Dimensional Data Assimilation (4DDA) at NASA's Data Assimilation Office (DAO) is discussed. In 4DDA, observations are assimilated with the output of a dynamical model to generate best-estimates of the states of the system. It is thus a mapping problem, whereby scattered observations are converted into regular accurate maps of wind, temperature, moisture and other variables. The DAO is developing and using 4DDA algorithms that provide these datasets, or analyses, in support of Earth System Science research. Two large-scale algorithms are discussed. The first approach, the Goddard Earth Observing System Data Assimilation System (GEOS DAS), uses an atmospheric general circulation model (GCM) and an observation-space based analysis system, the Physical-space Statistical Analysis System (PSAS). GEOS DAS is very similar to global meteorological weather forecasting data assimilation systems, but is used at NASA for climate research. Systems of this size typically run at between 1 and 20 gigaflop/s. The second approach, the Kalman filter, uses a more consistent algorithm to determine the forecast error covariance matrix than does GEOS DAS. For atmospheric assimilation, the gridded dynamical fields typically have More than 10(exp 6) variables, therefore the full error covariance matrix may be in excess of a teraword. For the Kalman filter this problem can easily scale to petaflop/s proportions. We discuss the computational complexity of GEOS DAS and our implementation of the Kalman filter. We also discuss and quantify some of the technical issues and limitations in developing efficient, in terms of wall clock time, and scalable parallel implementations of the algorithms.

Lyster, Peter M.↗
NASA NTRS2013

The Role of Model and Initial Condition Error in Numerical Weather Forecasting Investigated with an Observing System Simulation Experiment

A series of experiments that explore the roles of model and initial condition error in numerical weather prediction are performed using an observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO). The use of an OSSE allows the analysis and forecast errors to be explicitly calculated, and different hypothetical observing networks can be tested with ease. In these experiments, both a full global OSSE framework and an 'identical twin' OSSE setup are utilized to compare the behavior of the data assimilation system and evolution of forecast skill with and without model error. The initial condition error is manipulated by varying the distribution and quality of the observing network and the magnitude of observation errors. The results show that model error has a strong impact on both the quality of the analysis field and the evolution of forecast skill, including both systematic and unsystematic model error components. With a realistic observing network, the analysis state retains a significant quantity of error due to systematic model error. If errors of the analysis state are minimized, model error acts to rapidly degrade forecast skill during the first 24-48 hours of forward integration. In the presence of model error, the impact of observation errors on forecast skill is small, but in the absence of model error, observation errors cause a substantial degradation of the skill of medium range forecasts.

Model Error↗
NASA NTRS2020

ANC of Radiated Sound from a Small UAS Rotor using Virtual Error Sensors

Small unmanned aerial systems (UAS) are becoming increasingly common for private, military, and commercial use, increasing community noise exposure. Reducing the noise produced by UAS could help improve community acceptance. Active noise control (ANC) might be used to attenuate noise produced by UAS, however, traditional ANC systems require a physical sensor in the far-field, which is not feasible. This paper assesses a virtual error sensing (VES) method that eliminates the need for a far-field sensor. This paper describes the proposed VES strategy, and presents numerical simulations and experimental results that highlight the benefits and limitations of the approach. Results for the VES system alone and with an ANC approach are presented and discussed. Experimental testing focused on attenuating the tonal noise produced by one 2-bladed rotor with a tip radius of 11.9 cm. Pressure variations caused by blade rotation were measured in the near and far-field using electret microphones and externally polarized condenser microphones, respectively. The filtered-x least mean squares algorithm was used in conjunction with the VES system to attenuate the far-field response. Experimental results show reductions between 6-13 dB at varying far-field locations and rotation rates.

virtual error sensor↗
NASA NTRS1990

Orbit determination and gravitational field accuracy for a Mercury transponder satellite

Covariance studies were performed to investigate the orbit determination problem for a small transponder satellite in a nearly circular polar orbit with 4-hour period around Mercury. With X band and Ka band Doppler and range measurements, the analysis indicates that the gravitational field through degree and order 10 can be solved for from as few as 40 separate 8-hour arcs of tracking data. In addition, the earth-Mercury distance can be determined during each ranging period with about 6-cm accuracy. The expected geoid accuracy is 10 cm up through degree 5, and 1 m through degree 8. The main error sources were the geocentric range measurement error, the uncertainties in higher degree gravity field terms, which were not solved for, and the solar radiation pressure uncertainty.

Vincent, Mark A.↗
NASA NTRS1981

Influence of gravity field uncertainties on the results from POGO and Magsat geomagnetic surveys

Errors in the gravity models used in satellite position calculations are examined as a possible source of the 0 to 100% variance found between POGO and Magsat magnetic data and the extrapolations of aerial magnetic survey data to satellite heights. For POGO data obtained over the New York Bight region using a relatively poor gravity field (a hybrid spherical harmonic model of degree 7 and order 6 with three higher order resonance terms), the magnitude of the error in the satellite height component is found to be sufficient to account for the amplitude of the discrepancy, however the frequency of the quasi-periodic orbital error is too large to explain the localized nature of the differences. For the case of the Magsat satellite, in which a more accurate gravity model was used, it is found that a 30 mgal gravitational anomaly distributed over a 5 x 5 deg area will produce insufficiently large position errors to account for the variations. The agreement between the two sets of satellite data in the New York Bight region suggests either a consistent error in satellite measurements, or problems with the reduction and processing of the aeromagnetic data.

Taylor, P. T.↗
NASA NTRS2011

Modeling the Height of Young Forests Regenerating from Recent Disturbances in Mississippi using Landsat and ICESat data

Many forestry and earth science applications require spatially detailed forest height data sets. Among the various remote sensing technologies, lidar offers the most potential for obtaining reliable height measurement. However, existing and planned spaceborne lidar systems do not have the capability to produce spatially contiguous, fine resolution forest height maps over large areas. This paper describes a Landsat-lidar fusion approach for modeling the height of young forests by integrating historical Landsat observations with lidar data acquired by the Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud, and land Elevation (ICESat) satellite. In this approach, "young" forests refer to forests reestablished following recent disturbances mapped using Landsat time-series stacks (LTSS) and a vegetation change tracker (VCT) algorithm. The GLAS lidar data is used to retrieve forest height at sample locations represented by the footprints of the lidar data. These samples are used to establish relationships between lidar-based forest height measurements and LTSS-VCT disturbance products. The height of "young" forest is then mapped based on the derived relationships and the LTSS-VCT disturbance products. This approach was developed and tested over the state of Mississippi. Of the various models evaluated, a regression tree model predicting forest height from age since disturbance and three cumulative indices produced by the LTSS-VCT method yielded the lowest cross validation error. The R(exp 2) and root mean square difference (RMSD) between predicted and GLAS-based height measurements were 0.91 and 1.97 m, respectively. Predictions of this model had much higher errors than indicated by cross validation analysis when evaluated using field plot data collected through the Forest Inventory and Analysis Program of USDA Forest Service. Much of these errors were due to a lack of separation between stand clearing and non-stand clearing disturbances in current LTSS-VCT products and difficulty in deriving reliable forest height measurements using GLAS samples when terrain relief was present within their footprints. In addition, a systematic underestimation of about 5 m by the developed model was also observed, half of which could be explained by forest growth that occurred between field measurement year and model target year. The remaining difference suggests that tree height measurements derived using waveform lidar data could be significantly underestimated, especially for young pine forests. Options for improving the height modeling approach developed in this study were discussed.

Li, Ainong↗
NASA NTRS1995

Error in predicting hydrosol backscattering from remotely sensed reflectance

Monte Carlo simulations are carried out to determine the error in the inversion of backscattering from remotely sensed reflectance when geometrical shape factors of the light field are assumed to be unity. The results show that error in backscattering inversion can vary from a 40% overestimation to a 20% underestimation and is dependent on the solar angle and the hydrosol consituents contributing to backscattering. The simulations also demostrate that for chlorophyll concentrations ranging from 0.05 to 20 mg/cu m the most dramatic change in the geometrical shape factors occurs near 1.0 to 1.5 mg/cu m chlorophyll. The potential importance of bacteria in influencing the shape factor and the subsequent effect of bacteria on the retrieval of the backscattering from remote sensing reflectance are shown. Quartzlike material's strong impact on geometrical shape factors and errors of retrieval of backscattering at low chlorophyll concentrations are also demonstrated. Remote sensing reflectance inversion schemes must include information about the backscattering function to be successful.

Weidemann, A. D.↗
NASA NTRS2008

Coaxial Electric Heaters

Coaxial electric heaters have been conceived for use in highly sensitive instruments in which there are requirements for compact heaters but stray magnetic fields associated with heater electric currents would adversely affect operation. Such instruments include atomic clocks and magnetometers that utilize heated atomic-sample cells, wherein stray magnetic fields at picotesla levels could introduce systematic errors into instrument readings. A coaxial electric heater is essentially an axisymmetric coaxial cable, the outer conductor of which is deliberately made highly electrically resistive so that it can serve as a heating element. As in the cases of other axisymmetric coaxial cables, the equal magnitude electric currents flowing in opposite directions along the inner and outer conductors give rise to zero net magnetic field outside the outer conductor. Hence, a coaxial electric heater can be placed near an atomic-sample cell or other sensitive device. A coaxial electric heater can be fabricated from an insulated copper wire, the copper core of which serves as the inner conductor. For example, in one approach, the insulated wire is dipped in a colloidal graphite emulsion, then the emulsion-coated wire is dried to form a thin, uniform, highly electrically resistive film that serves as the outer conductor. Then the film is coated with a protective layer of high-temperature epoxy except at the end to be electrically connected to the power supply. Next, the insulation is stripped from the wire at that end. Finally, electrical leads from the heater power supply are attached to the exposed portions of the wire and the resistive film. The resistance of the graphite film can be tailored via its thickness. Alternatively, the film can be made from an electrically conductive paint, other than a colloidal graphite emulsion, chosen to impart the desired resistance. Yet another alternative is to tailor the resistance of a graphite film by exploiting the fact that its resistance can be changed permanently within about 10 percent by heating it to a temperature above 300 C. A coaxial heater, with electrical leads attached, that has been bent into an almost full circle for edge heating of a circular window is shown. (In the specific application, there is a requirement for a heated cell window, through which an optical beam enters the cell.)

Strekalov, Dmitry↗
NASA NTRS1995

Clouds and the Earth's Radiant Energy System (CERES) algorithm theoretical basis document: Overviews (subsystem 0) - Volume 1

The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and the Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 1 provides both summarized and detailed overviews of the CERES Release 1 data analysis system. CERES will produce global top-of-the-atmosphere shortwave and longwave radiative fluxes at the top of the atmosphere, at the surface, and within the atmosphere by using the combination of a large variety of measurements and models. The CERES processing system includes radiance observations from CERES scanning radiometers, cloud properties derived from coincident satellite imaging radiometers, temperature and humidity fields from meteorological analysis models, and high-temporal-resolution geostationary satellite radiances to account for unobserved times. CERES will provide a continuation of the ERBE record and the lowest error climatology of consistent cloud properties and radiation fields. CERES will also substantially improve our knowledge of the Earth's surface radiation budget.

Wielicki, Bruce A.↗