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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 451 records · Page 25

Two Algorithms For Hypersonic Computations

Two new algorithms developed containing several desirable features for computation of viscous, hypersonic flows about three-dimensional geometries. Employ upwind-differencing methods, having unsurpassed abiltiy to capture flow-field discontinuities without need for any user-specified smoothing terms. Particularly important in hypersonic computations where many complicated wave structures exist. Both algorithms based on finite-volume formulation to ensure schemes, including boundary conditions, fully conservative.

Molvik, G. A.↗

SSME Automated Engine Calibration System (AECS)

An algorithm is derived for the real-time calibration of the engine fuel flowmeter and the engine mixture ratio during Space Shuttle Main Engine (SSME) ground testing. Because currently used calibration methods are post-test operations, there exists no fail-safe way of predicting at what mixture ratio a planned test will run. It is proposed that the algorithm developed here be used as part of an Automated Engine Calibration System (AECS) which could ensure that nearly all SSME tests are run at the proper mixture ratio. In this way, AECS has the potential of increasing the efficiency of the SSME ground test program. In addition to the derivation of the algorithm, an overview of this calibration system is presented along with the list of test stand facility instrumentation necessary for AECS implementation.

Greene, William D.↗

The computation of pi to 29,360,000 decimal digits using Borweins' quartically convergent algorithm

The quartically convergent numerical algorithm developed by Borwein and Borwein (1987) for 1/pi is implemented via a prime-modulus-transform multiprecision technique on the NASA Ames Cray-2 supercomputer to compute the first 2.936 x 10 to the 7th digits of the decimal expansion of pi. The history of pi computations is briefly recalled; the most recent algorithms are characterized; the implementation procedures are described; and samples of the output listing are presented. Statistical analyses show that the present decimal expansion is completely random, with only acceptable numbers of long repeating strings and single-digit runs.

Bailey, David H.↗

Fuzzy Reasoning to More Accurately Determine Void Areas on Optical Micrographs of Composite Structures

Accomplishing the best-performing composite matrix (resin) requires that not only the processing method but also the cure cycle generate low-void-content structures. If voids are present, the performance of the composite matrix will be significantly reduced. This is usually noticed by significant reductions in matrix-dominated properties, such as compression and shear strength. Voids in composite materials are areas that are absent of the composite components: matrix and fibers. The characteristics of the voids and their accurate estimation are critical to determine for high performance composite structures. One widely used method of performing void analysis on a composite structure sample is acquiring optical micrographs or Scanning Electron Microscope (SEM) images of lateral sides of the sample and retrieving the void areas within the micrographs/images using an image analysis technique. Segmentation for the retrieval and subsequent computation of void areas within the micrographs/images is challenging as the gray-scaled values of the void areas are close to the gray-scaled values of the matrix leading to the need of manually performing the segmentation based on the histogram of the micrographs/images to retrieve the void areas. The use of an algorithm developed by NASA and based on Fuzzy Reasoning (FR) proved to overcome the difficulty of suitably differentiate void and matrix image areas with similar gray-scaled values leading not only to a more accurate estimation of void areas on composite matrix micrographs but also to a faster void analysis process as the algorithm is fully autonomous.

Dominquez, Jesus A.↗

Computational enhancement of an unsymmetric block Lanczos algorithm

An unsymmetric block Lanczos algorithm has been employed for the dynamic analysis of a large system which has arbitrary damping and/or repeated (or closely spaced) eigenvalues. In the algorithm development, the right and left Lanczos vectors are all theoretically biorthogonal to each other. However, these vectors may lose the biorthogonality owing to cancellation and roundoff errors. For the unsymmetric case there can be a breakdown, even without numerical errors. This paper describes computational techniques which have led to a robust unsymmetric block Lanczos algorithm.

Kim, Hyoung M.↗

An onboard star identification algorithm

The paper presents the autonomous Initial Stellar Acquisition (ISA) algorithm developed for the X-Ray Timing Explorer for prividing the attitude quaternion within the desired accuracy, based on the one-axis attitude knowledge (through the use of the Digital Sun Sensor, CCD Star Trackers, and the onboard star catalog, OSC). Mathematical analysis leads to an accurate measure of the performance of the algorithm as a function of various parameters, such as the probability of a tracked star being in the OSC, the sensor noise level, and the number of stars matched. It is shown that the simplicity, tractability, and robustness of the ISA algorithm, compared to a general three-axis attiude determination algorithm, make it a viable on-board solution.

Ha, Kong↗

Advances in Digital Calibration Techniques Enabling Real-Time Beamforming SweepSAR Architectures

Real-time digital beamforming, combined with lightweight, large aperture reflectors, enable SweepSAR architectures, which promise significant increases in instrument capability for solid earth and biomass remote sensing. These new instrument concepts require new methods for calibrating the multiple channels, which are combined on-board, in real-time. The benefit of this effort is that it enables a new class of lightweight radar architecture, Digital Beamforming with SweepSAR, providing significantly larger swath coverage than conventional SAR architectures for reduced mass and cost. This paper will review the on-going development of the digital calibration architecture for digital beamforming radar instrument, such as the proposed Earth Radar Mission's DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice) instrument. This proposed instrument's baseline design employs SweepSAR digital beamforming and requires digital calibration. We will review the overall concepts and status of the system architecture, algorithm development, and the digital calibration testbed currently being developed. We will present results from a preliminary hardware demonstration. We will also discuss the challenges and opportunities specific to this novel architecture.

TR (Transmit/Receive)↗

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗

Computational mechanics analysis tools for parallel-vector supercomputers

Computational algorithms for structural analysis on parallel-vector supercomputers are reviewed. These parallel algorithms, developed by the authors, are for the assembly of structural equations, 'out-of-core' strategies for linear equation solution, massively distributed-memory equation solution, unsymmetric equation solution, general eigensolution, geometrically nonlinear finite element analysis, design sensitivity analysis for structural dynamics, optimization search analysis and domain decomposition. The source code for many of these algorithms is available.

Storaasli, Olaf O.↗

Labview Implementation of Image Processing and Phasing Control for the SIBOA Segmented Mirror Testbed

NASA is preparing to launch the Next Generation Space Telescope (NGST). This telescope will be larger than the Hubble Space Telescope, be launched on an Atlas missile rather than the Space Shuttle, have a segmented primary mirror, and be placed in a higher orbit. All these differences pose significant challenges.' This effort addresses the challenge of implementing an algorithm for aligning the segments of the primary mirror during the initial deployment that was designed by Philip Olivier and members of SOMTC (Space Optics Manufacturing Technology Center). The implementation was to be performed on the SIBOA (Systematic Image Based Optical Alignment) test bed. Unfortunately, hardware/software aspect concerning SIBOA and an extended time period for algorithm development prevented testing before the end of the study period. Properties of the digital camera were studied and understood, resulting in the current ability of selecting optimal settings regarding saturation. The study was successful in manually capturing several images of two stacked segments with various relative phases. These images can be used to calibrate the algorithm for future implementation. Currently the system is ready for testing.

James D. Partridge↗

Benchmarking In-Flight Icing Detection Products for Future Upgrades

This paper summarizes the results of a benchmarking exercise conducted as part of the NASA supported Advanced Satellite Aviation-Weather Products (ASAP) Program. The goal of ASAP is to increase and optimize the use of satellite data sets within the existing FAA Aviation Weather Research Program (AWRP) Product Development Team (PDT) structure and to transfer advanced satellite expertise to the PDTs. Currently, ASAP fosters collaborative efforts between NASA Laboratories, the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (UW-CIMSS), the University of Alabama in Huntsville (UAH), and the AWRP PDTs. This collaboration involves the testing and evaluation of existing satellite algorithms developed or proposed by AWRP teams, the introduction of new techniques and data sets to the PDTs from the satellite community, and enhanced access to new satellite data sets available through CIMSS and NASA Langley Research Center for evaluation and testing.

Politovich, M. K.↗

SLAPex Freeze/Thaw 2015: The First Dedicated Soil Freeze/Thaw Airborne Campaign

Soil freezing and thawing is an important process in the terrestrial water, energy, and carbon cycles, marking the change between two very different hydraulic, thermal, and biological regimes. NASA's Soil Moisture Active/Passive (SMAP) mission includes a binary freeze/thaw data product. While there have been ground-based remote sensing field measurements observing soil freeze/thaw at the point scale, and airborne campaigns that observed some frozen soil areas (e.g., BOREAS), the recently-completed SLAPex Freeze/Thaw (F/T) campaign is the first airborne campaign dedicated solely to observing frozen/thawed soil with both passive and active microwave sensors and dedicated ground truth, in order to enable detailed process-level exploration of the remote sensing signatures and in situ soil conditions. SLAPex F/T utilized the Scanning L-band Active/Passive (SLAP) instrument, an airborne simulator of SMAP developed at NASA's Goddard Space Flight Center, and was conducted near Winnipeg, Manitoba, Canada, in October/November, 2015. Future soil moisture missions are also expected to include soil freeze/thaw products, and the loss of the radar on SMAP means that airborne radar-radiometer observations like those that SLAP provides are unique assets for freeze/thaw algorithm development. This paper will present an overview of SLAPex F/T, including descriptions of the site, airborne and ground-based remote sensing, ground truth, as well as preliminary results.

BOREAS↗

Demonstration of the Space Launch System Augmenting Adaptive Control Algorithm on Pole-Cart Platform

NASA's baseline Space Launch System (SLS) ight control system (FCS) includes an adaptive augmenting control (AAC) portion in addition to the ight-heritage nominal classical controller. The AAC algorithm is intended to improve the robustness and performance of the classical controller. Over the past several years, the AAC algorithm developed at NASA Marshall Space Flight Center (MSFC) has matured significantly through extensive simulation, rigorous analytical proofs, and a series of successful ight tests on a F18 aircraft. This study was part of a SLS program and NASA Engineering and Safety Center (NESC) joint e ort to further increase the confidence level of the AAC algorithm by demonstrating its key functionalities on a classroom type of example, the pole-cart sys- tem, at the NASA Langley Research Center (LaRC) dynamics and control laboratory. The fundamental dynamics behind balancing an inverted pendulum is similar to controlling an aerodynamically unstable rocket. Both systems are inherently open-loop unstable and requires feedback control for attitude stabilization. The principles behind the AAC algorithm is applicable to a wide range of conditionally stable dynamical systems. Hence, the outcomes from this simple and inexpensive exercise has provided the SLS program with additional confidence into the AAC design, operation, robustness, and application.

Pei, Jing↗

Application of Radon Transform to Multi-Angle Measurements Made by the Research Scanning Polarimeter: A New Approach to Cloud Tomography. Part I: Theory and Tests on Simulated Data.

The Research Scanning Polarimeter (RSP) is an airborne along-track scanner measuring the polarized and total reflectances in 9 spectral channels. The RSP was a prototype for the Aerosol Polarimetry Sensor (APS) launched on-board the NASA Glory satellite. Currently the retrieval algorithms developed for the RSP are being adopted for the measurements of the space-borne polarimeters on the upcoming NASA’s Plankton, Aerosol, Cloud Ocean Ecosystem (PACE)satellite mission. The RSP’s uniquely high angular resolution coupled with the high frequency of measurements allows for characterization of liquid water cloud droplet sizes using the polarized rainbow structure. It also provides geometric constraints on the cumulus cloud’s 2D cross section yielding the cloud’s geometric shape estimates. In this study we further build on the latter technique to develop a new tomographic approach to retrieval of cloud internal structure from remote sensing measurements. While tomography in the strict definition is a technique based on active measurements yielding a tomogram (directional optical thickness as a function of angle and offset of the view ray), we developed a “semi-tomographic” approach in which tomogram of the cloud is estimated from passive observations instead of being measured directly. This tomogram is then converted into 2D spatial distribution of the extinction coefficient using inverse Radon transform (filtered back projection) which is the standard tomographic procedure used e.g., in medical CT scans. This algorithm is computationally inexpensive compared to techniques relying on highly-multi-dimensional least-square fitting; it does not require iterative 3D RT simulations. The resulting extinction distribution is defined up to an unknown constant factor, so we discuss the ways to calibrate it using additional independent measurements. In the next step we use the profile of the droplet size distribution parameters from the cloud’s side (derived by fitting the polarized rainbows) to convert the 2D extinction distribution into that of the droplet number concentration. We illustrate and validate the proposed technique using 3D-RT-simulatedRSP observations of a LES-generated Cu cloud. Quantitative comparisons between the retrieved and the original optical and microphysical parameters are presented.

clouds↗

Unified approach for incompressible flows

An unified approach for solving both compressible and incompressible flows was investigated in this study. The difference in CFD code development between incompressible and compressible flows is due to the mathematical characteristics. However, if one can modify the continuity equation for incompressible flows by introducing pseudocompressibility, the governing equations for incompressible flows would have the same mathematical characters as compressible flows. The application of a compressible flow code to solve incompressible flows becomes feasible. Among numerical algorithms developed for compressible flows, the Centered Total Variation Diminishing (CTVD) schemes possess better mathematical properties to damp out the spurious oscillations while providing high-order accuracy for high speed flows. It leads us to believe that CTVD schemes can equally well solve incompressible flows. In this study, the governing equations for incompressible flows include the continuity equation and momentum equations. The continuity equation is modified by adding a time-derivative of the pressure term containing the artificial compressibility. The modified continuity equation together with the unsteady momentum equations forms a hyperbolic-parabolic type of time-dependent system of equations. The continuity equation is modified by adding a time-derivative of the pressure term containing the artificial compressibility. The modified continuity equation together with the unsteady momentum equations forms a hyperbolic-parabolic type of time-dependent system of equations. Thus, the CTVD schemes can be implemented. In addition, the boundary conditions including physical and numerical boundary conditions must be properly specified to obtain accurate solution. The CFD code for this research is currently in progress. Flow past a circular cylinder will be used for numerical experiments to determine the accuracy and efficiency of the code before applying this code to more specific applications.

Chang, Tyne-Hsien↗

Development of Fast Algorithms Using Recursion, Nesting and Iterations for Computational Electromagnetics

In the first phase of our work, we have concentrated on laying the foundation to develop fast algorithms, including the use of recursive structure like the recursive aggregate interaction matrix algorithm (RAIMA), the nested equivalence principle algorithm (NEPAL), the ray-propagation fast multipole algorithm (RPFMA), and the multi-level fast multipole algorithm (MLFMA). We have also investigated the use of curvilinear patches to build a basic method of moments code where these acceleration techniques can be used later. In the second phase, which is mainly reported on here, we have concentrated on implementing three-dimensional NEPAL on a massively parallel machine, the Connection Machine CM-5, and have been able to obtain some 3D scattering results. In order to understand the parallelization of codes on the Connection Machine, we have also studied the parallelization of 3D finite-difference time-domain (FDTD) code with PML material absorbing boundary condition (ABC). We found that simple algorithms like the FDTD with material ABC can be parallelized very well allowing us to solve within a minute a problem of over a million nodes. In addition, we have studied the use of the fast multipole method and the ray-propagation fast multipole algorithm to expedite matrix-vector multiplication in a conjugate-gradient solution to integral equations of scattering. We find that these methods are faster than LU decomposition for one incident angle, but are slower than LU decomposition when many incident angles are needed as in the monostatic RCS calculations.

Chew, W. C.↗

Adaptive Wing Camber Optimization: A Periodic Perturbation Approach

Available redundancy among aircraft control surfaces allows for effective wing camber modifications. As shown in the past, this fact can be used to improve aircraft performance. To date, however, algorithm developments for in-flight camber optimization have been limited. This paper presents a perturbational approach for cruise optimization through in-flight camber adaptation. The method uses, as a performance index, an indirect measurement of the instantaneous net thrust. As such, the actual performance improvement comes from the integrated effects of airframe and engine. The algorithm, whose design and robustness properties are discussed, is demonstrated on the NASA Dryden B-720 flight simulator.

Espana, Martin↗

Algorithm for vertical ozone profile determination for the Nimbus-4 BUV data set

A description is provided of the algorithm used by the Ozone Processing Team at NASA to process seven years of Backscatter Ultraviolet (BUV) ozone profile data. The algorithm is a modification of the original retrieval algorithm developed by Mateer (1972) to process some of the early data from the BUV experiment. Principal changes made are in the first guess selection scheme, the use of all wavelengths in the inversion, and the weighting of the various wavelengths according to the errors in the radiance estimation. It is found that the described BUV ozone profile algorithm is an extremely efficient algorithm for retrieving large amounts of satellite data. The algorithm makes full use of all the available information from the measured radiances including the longer wavelength radiances which previously had not been used.

Bhartia, P. K.↗