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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Approximate scaling properties of RNA free energy landscapes

RNA free energy landscapes are analysed by means of "time-series" that are obtained from random walks restricted to excursion sets. The power spectra, the scaling of the jump size distribution, and the scaling of the curve length measured with different yard stick lengths are used to describe the structure of these "time series". Although they are stationary by construction, we find that their local behavior is consistent with both AR(1) and self-affine processes. Random walks confined to excursion sets (i.e., with the restriction that the fitness value exceeds a certain threshold at each step) exhibit essentially the same statistics as free random walks. We find that an AR(1) time series is in general approximately self-affine on timescales up to approximately the correlation length. We present an empirical relation between the correlation parameter rho of the AR(1) model and the exponents characterizing self-affinity.

Signal Processing, Computer-Assisted↗
NASA NTRS1999

Neural Network and Regression Approximations Used in Aircraft Design

NASA Lewis Research Center's CometBoards Test Bed was used to create regression and neural network models for a High-Speed Civil Transport (HSCT) aircraft. Both approximation models that replaced the actual analysis tool predicted the aircraft response in a trivial computational effort. The models allow engineers to quickly study the effects of design variables on constraint and objective values for a given aircraft configuration. For example, an engineer can change the engine size by 1000 pounds of thrust and quickly see how this change affects all the output values without rerunning the entire simulation. In addition, an engineer can change a constraint and use the approximation models to quickly reoptimize the configuration. Generating the neural network and the regression models is a time-consuming process, but this exercise has to be carried out only once. Furthermore, an automated process can reduce calculations substantially.

Patnaik, Surya N.↗
NASA NTRS2000

Cascade Optimization Strategy with Neural Network and Regression Approximations Demonstrated on a Preliminary Aircraft Engine Design

A preliminary aircraft engine design methodology is being developed that utilizes a cascade optimization strategy together with neural network and regression approximation methods. The cascade strategy employs different optimization algorithms in a specified sequence. The neural network and regression methods are used to approximate solutions obtained from the NASA Engine Performance Program (NEPP), which implements engine thermodynamic cycle and performance analysis models. The new methodology is proving to be more robust and computationally efficient than the conventional optimization approach of using a single optimization algorithm with direct reanalysis. The methodology has been demonstrated on a preliminary design problem for a novel subsonic turbofan engine concept that incorporates a wave rotor as a cycle-topping device. Computations of maximum thrust were obtained for a specific design point in the engine mission profile. The results (depicted in the figure) show a significant improvement in the maximum thrust obtained using the new methodology in comparison to benchmark solutions obtained using NEPP in a manual design mode.

Hopkins, Dale A.↗
NASA NTRS2007

Can the Equivalent Sphere Model Approximate Organ Doses in Space Radiation Environments?

In space radiation calculations it is often useful to calculate the dose or dose equivalent in blood-forming organs (BFO). the skin or the eye. It has been customary to use a 5cm equivalent sphere to approximate the BFO dose. However previous studies have shown that a 5cm sphere gives conservative dose values for BFO. In this study we use a deterministic radiation transport with the Computerized Anatomical Man model to investigate whether the equivalent sphere model can approximate organ doses in space radiation environments. We find that for galactic cosmic rays environments the equivalent sphere model with an organ-specific constant radius parameter works well for the BFO dose equivalent and marginally well for the BFO dose and the dose equivalent of the eye or the skin. For solar particle events the radius parameters for the organ dose equivalent increase with the shielding thickness, and the model works marginally for BFO but is unacceptable for the eye or the skin The ranges of the radius parameters are also shown and the BFO radius parameters are found to be significantly larger than 5 cm in all eases.

Zi-Wei, Lin↗
NASA NTRS2008

Approximation of Failure Probability Using Conditional Sampling

In analyzing systems which depend on uncertain parameters, one technique is to partition the uncertain parameter domain into a failure set and its complement, and judge the quality of the system by estimating the probability of failure. If this is done by a sampling technique such as Monte Carlo and the probability of failure is small, accurate approximation can require so many sample points that the computational expense is prohibitive. Previous work of the authors has shown how to bound the failure event by sets of such simple geometry that their probabilities can be calculated analytically. In this paper, it is shown how to make use of these failure bounding sets and conditional sampling within them to substantially reduce the computational burden of approximating failure probability. It is also shown how the use of these sampling techniques improves the confidence intervals for the failure probability estimate for a given number of sample points and how they reduce the number of sample point analyses needed to achieve a given level of confidence.

Giesy. Daniel P.↗
NASA NTRS2004

Spitzer 24micron Observations of Optical/Near-IR Selected Extremely Red Galaxies: Evidence for Assembly of Massive Galaxies at z approximately 1 - 2?

We carried out the direct measurement of the fraction of dusty sources in a sample of extremely red galaxies with (R-K(sub s)) greater than or equal to 5.3 mag and K(sub s) less than 20.2 mag, using from the Spitzer Space Telescope. Combining deep 24 micrometers, K(sub s)- and R-band data over an area of approximately 64 sq.arcmin in the ELAIS N1 field of the Spitzer First Look Survey (FLS), we find that 50 +/- 60% of our ERO sample have measurable 24 micrometer flux above the 3(sigma) flux limit of 40 microns Jy. This flux limit corresponds to a SFR of 12 solar mass/yr at z approximately 1, much mo previous long wavelength measurement. The 24fJ,m-detected EROs have 24-to2.2 and 24-to-0.7micrometr flux ratios consistent with infrared luminous, dusty sources at z approx. 1, and an order of magnitude too red to be explained by an infrared quiescent spiral or a pure old stellar population at any redshift. Some of these 24 micrometer-detected EROs could be AGN, however, the fraction among the whole ERO sample is probably small, 10-20%, as suggested by deep X-ray observations as well as optical spectroscopy. Keck optical spectroscopy of a sample of similarly selected EROs in the FLS field suggests that most of the EROs in ELAIS Nl are probably at z approx. 1.

galaxy evolution↗
NASA NTRS2011

The Atmospheric Mutual Coherence Function From the First and Second Rytov Approximations and Its Comparison to That of Strong Fluctuation Theory

An expression for the mutual coherence function (MCF) of an electromagnetic beam wave propagating through atmospheric turbulence is derived within the confines of the Rytov approximation. It is shown that both the first and second Rytov approximations are required. The Rytov MCF is then compared to that which issues from the parabolic equation method of strong fluctuation theory. The agreement is found to be quite good in the weak fluctuation case. However, an instability is observed for the special case of beam wave intensities. The source of the instabilities is identified to be the characteristic way beam wave amplitudes are treated within the Rytov method.

Manning, Robert M.↗
NASA NTRS2011

Investigating Material Approximations in Spacecraft Radiation Analysis

During the design process, the configuration of space vehicles and habitats changes frequently and the merits of design changes must be evaluated. Methods for rapidly assessing astronaut exposure are therefore required. Typically, approximations are made to simplify the geometry and speed up the evaluation of each design. In this work, the error associated with two common approximations used to simplify space radiation vehicle analyses, scaling into equivalent materials and material reordering, are investigated. Over thirty materials commonly found in spacesuits, vehicles, and human bodies are considered. Each material is placed in a material group (aluminum, polyethylene, or tissue), and the error associated with scaling and reordering was quantified for each material. Of the scaling methods investigated, range scaling is shown to be the superior method, especially for shields less than 30 g/cm2 exposed to a solar particle event. More complicated, realistic slabs are examined to quantify the separate and combined effects of using equivalent materials and reordering. The error associated with material reordering is shown to be at least comparable to, if not greater than, the error associated with range scaling. In general, scaling and reordering errors were found to grow with the difference between the average nuclear charge of the actual material and average nuclear charge of the equivalent material. Based on this result, a different set of equivalent materials (titanium, aluminum, and tissue) are substituted for the commonly used aluminum, polyethylene, and tissue. The realistic cases are scaled and reordered using the new equivalent materials, and the reduced error is shown.

Walker, Steven A.↗
NASA NTRS2010

Assessment of Biases in MODIS Surface Reflectance Due to Lambertian Approximation

Using MODIS data and the AERONET-based Surface Reflectance Validation Network (ASRVN), this work studies errors of MODIS atmospheric correction caused by the Lambertian approximation. On one hand, this approximation greatly simplifies the radiative transfer model, reduces the size of the look-up tables, and makes operational algorithm faster. On the other hand, uncompensated atmospheric scattering caused by Lambertian model systematically biases the results. For example, for a typical bowl-shaped bidirectional reflectance distribution function (BRDF), the derived reflectance is underestimated at high solar or view zenith angles, where BRDF is high, and is overestimated at low zenith angles where BRDF is low. The magnitude of biases grows with the amount of scattering in the atmosphere, i.e., at shorter wavelengths and at higher aerosol concentration. The slope of regression of Lambertian surface reflectance vs. ASRVN bidirectional reflectance factor (BRF) is about 0.85 in the red and 0.6 in the green bands. This error propagates into the MODIS BRDF/albedo algorithm, slightly reducing the magnitude of overall reflectance and anisotropy of BRDF. This results in a small negative bias of spectral surface albedo. An assessment for the GSFC (Greenbelt, USA) validation site shows the albedo reduction by 0.004 in the near infrared, 0.005 in the red, and 0.008 in the green MODIS bands.

Wang, Yujie↗
NASA NTRS2012

The Epoch of Disk Formation: z is Approximately l to Today

We present data on galaxy kinematics, morphologies, and star-formation rates over 0.1 less than z less than 1.2 for approximately 500 blue galaxies. These data show how systems like our own Milky-Way have come into being. At redshifts around 1, about half the age of the Universe ago, Milky-Way mass galaxies were different beasts than today. They had a significant amount of disturbed motions, disturbed morphologies, shallower potential wells, higher specific star-formation rates, and likely higher gas fractions. Since redshift approximately 1, galaxies have decreased in disturbed motions, increased in rotation velocity and potential well depth, become more well-ordered morphologically, and decreased in specific star-formation rate. We find interrelationships between these measurements. Galaxy kinematics are correlated with morphology and specific star-formation rate such that galaxies with the fastest rotation velocities and the least amounts of disturbed motions have the most well-ordered morphologies and the lowest specific star-formation rates. The converse is true. Moreover, we find that the rate at which galaxies become more well-ordered kinematically (i.e., increased rotation velocity, decreased disturbed motions) and morphologically is directly proportional to their stellar mass.

Kassin, Susan↗
NASA NTRS2012

Spectral Invariant Approximation within Atmospheric Radiative Transfer; Applications to EarthCare

Certain algebraic combinations of single-scattering albedo and solar radiation reflected from, or transmitted through, vegetation canopies do not vary with wavelength. These "spectrally-invariant relationships" are the consequence of wavelength independence of the extinction coefficient and scattering phase function in vegetation. In general, this wavelength-independence does not hold in the atmosphere, but in cloud-dominated atmospheres the total extinction and total scattering phase function vary only weakly with wavelength. We identify the conditions under which the spectrally-invariant approximation can accurately describe the extinction and scattering properties of cloudy atmospheres. Validity of the assumptions and accuracy of the approximation is tested with radiative transfer calculations. We discuss the physics behind this phenomenon and possible applications to remote sensing, climate, and the EarthCare, mission in particular.

Marshak, Alexander↗
NASA NTRS2011

Spectrally-Invariant Approximation Within Atmospheric Radiative Transfer

Certain algebraic combinations of single scattering albedo and solar radiation reflected from, or transmitted through, vegetation canopies do not vary with wavelength. These "spectrally invariant relationships" are the consequence of wavelength independence of the extinction coefficient and scattering phase function in vegetation. In general, this wavelength independence does not hold in the atmosphere, but in cloud~dominated atmospheres the total extinction and total scattering phase function vary only weakly with wavelength. This paper identifies the atmospheric conditions under which the spectrally invariant approximation can accurately describe the extinction. and scattering properties of cloudy atmospheres. The validity of the assumptions and the accuracy of the approximation are tested with ID radiative transfer calculations using publicly available radiative transfer models: Discrete Ordinate Radiative Transfer (DISORT) and Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART). It is shown for cloudy atmospheres with cloud optical depth above 3, and for spectral intervals that exclude strong water vapor absorption, that the spectrally invariant relationships found in vegetation canopy radiative transfer are valid to better than 5%. The physics behind this phenomenon, its mathematical basis, and possible applications to remote sensing and climate are discussed.

Marshak, A.↗
NASA NTRS2011

Spectrally Invariant Approximation within Atmospheric Radiative Transfer

Certain algebraic combinations of single scattering albedo and solar radiation reflected from, or transmitted through, vegetation canopies do not vary with wavelength. These spectrally invariant relationships are the consequence of wavelength independence of the extinction coefficient and scattering phase function in vegetation. In general, this wavelength independence does not hold in the atmosphere, but in cloud-dominated atmospheres the total extinction and total scattering phase function vary only weakly with wavelength. This paper identifies the atmospheric conditions under which the spectrally invariant approximation can accurately describe the extinction and scattering properties of cloudy atmospheres. The validity of the assumptions and the accuracy of the approximation are tested with 1D radiative transfer calculations using publicly available radiative transfer models: Discrete Ordinate Radiative Transfer (DISORT) and Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART). It is shown for cloudy atmospheres with cloud optical depth above 3, and for spectral intervals that exclude strong water vapor absorption, that the spectrally invariant relationships found in vegetation canopy radiative transfer are valid to better than 5%. The physics behind this phenomenon, its mathematical basis, and possible applications to remote sensing and climate are discussed.

Marshak, A.↗
NASA NTRS2010

Faster Antenna Noise Temperature Calculations Using a Novel Approximation Technique

In order to properly tradeoff the various antenna and feed configurations for the Square Kilometre Array (SKA) optical design it is necessary to evaluate the gain and noise temperature of each configuration over a wide range of frequencies. German Cortes describes the standard technique for computing antenna noise temperature. However, since the total antenna pattern needs to be calculated over the entire 4 pi steradians at a fine enough resolution to accurately include the main beam, the computer time required is enormous. Even at modest frequencies and reflector sizes (approximately 5 to 10 GHz for a 12 meter main reflector) the technique can take days on a single node of a supercomputer. Utilizing the standard technique to compute the noise temperature for all the cases required to properly characterize the SKA design is clearly not feasible. At least a 100 to 1000 speedup in the computation time is required. This paper describes an approximation technique that can accomplish this improvement with extremely small errors in noise temperature calculation of a few tenths of Kelvin.

Reflector Antennas↗
NASA NTRS1973

An Approximate Equation For The Multiply Scattered Contribution to A Lidar Return

An approximate equation is developed which describes the contribution of Nth order scattering to a lidar return. This development assumes a homogeneous scattering medium characterized by a scattering function sharply peaked in the forward direction and relatively insensitive to angle near the backscatter direction. The derivation includes the effects of finite divergence of the transmitted laser beam, finite receiver field of view, finite separation between the laser and the receiver and nonparallel system alignment. The derivation presented uses small angle approximations to reduce the time dependent multiple scattering problem to a time independent form which is then solved with techniques previously developed for multiple small angle nuclear scattering.

Eloranta, Edwin W.↗
NASA NTRS2017

The Quantum Approximation Optimization Algorithm for MaxCut: A Fermionic View

Farhi et al. recently proposed a class of quantum algorithms, the Quantum Approximate Optimization Algorithm (QAOA), for approximately solving combinatorial optimization problems. A level-p QAOA circuit consists of steps in which a classical Hamiltonian, derived from the cost function, is applied followed by a mixing Hamiltonian. The 2p times for which these two Hamiltonians are applied are the parameters of the algorithm. As p increases, however, the parameter search space grows quickly. The success of the QAOA approach will depend, in part, on finding effective parameter-setting strategies. Here, we analytically and numerically study parameter setting for QAOA applied to MAXCUT. For level-1 QAOA, we derive an analytical expression for a general graph. In principle, expressions for higher p could be derived, but the number of terms quickly becomes prohibitive. For a special case of MAXCUT, the Ring of Disagrees, or the 1D antiferromagnetic ring, we provide an analysis for arbitrarily high level. Using a Fermionic representation, the evolution of the system under QAOA translates into quantum optimal control of an ensemble of independent spins. This treatment enables us to obtain analytical expressions for the performance of QAOA for any p. It also greatly simplifies numerical search for the optimal values of the parameters. By exploring symmetries, we identify a lower-dimensional sub-manifold of interest; the search effort can be accordingly reduced. This analysis also explains an observed symmetry in the optimal parameter values. Further, we numerically investigate the parameter landscape and show that it is a simple one in the sense of having no local optima.

quantum algorithm↗
NASA NTRS2019

A Neural Network Correction to the Scalar Approximation in Radiative Transfer

The next generation of advanced high-resolution sensors in geostationary orbit will gather detailed information for studying the Earth system. There is an increasing desire to perform observing system simulation experiments (OSSEs) for new sensors during the development phase of the mission in order to better leverage information content from the new and existing sensors. Forward radiative transfer calculations that simulate the observing characteristics of a new instrument are the first step to an OSSE, and they are computationally intensive. The scalar approximation to the radiative transfer equation, a simplification of the vector representation, can save considerable computational cost, but produces errors in top of the atmosphere (TOA) radiance as large as 10% due to neglecting polarization effects. This article presents an artificial neural network technique to correct scalar TOA radiance over both land and ocean surfaces to within 1% of vector-calculated radiance. A neural network was trained on a database of scalar-vector TOA radiance differences at a large range of solar and viewing angles for several thousand realistic atmospheric vertical profiles that were sampled from a high resolution (7 km) global atmospheric transport model. The profiles include Rayleigh scattering and aerosol scattering and absorption. Training and validation of the neural network was demonstrated for two wavelengths in the ultraviolet-visible (US-Vis) spectral range (354 nm and 670 nm). The significant computational savings accrued from using a scalar approximation plus neural network correction approach to simulating TOA radiance will make feasible hyperspectral forward simulations of high-resolution sensors on geostationary satellites, such as TEMPO, GOES-R, GEMS, and SENTINEL-4.

TOA↗