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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Parallel Implicit Algorithms for CFD

The main goal of this project was efficient distributed parallel and workstation cluster implementations of Newton-Krylov-Schwarz (NKS) solvers for implicit Computational Fluid Dynamics (CFD.) "Newton" refers to a quadratically convergent nonlinear iteration using gradient information based on the true residual, "Krylov" to an inner linear iteration that accesses the Jacobian matrix only through highly parallelizable sparse matrix-vector products, and "Schwarz" to a domain decomposition form of preconditioning the inner Krylov iterations with primarily neighbor-only exchange of data between the processors. Prior experience has established that Newton-Krylov methods are competitive solvers in the CFD context and that Krylov-Schwarz methods port well to distributed memory computers. The combination of the techniques into Newton-Krylov-Schwarz was implemented on 2D and 3D unstructured Euler codes on the parallel testbeds that used to be at LaRC and on several other parallel computers operated by other agencies or made available by the vendors. Early implementations were made directly in Massively Parallel Integration (MPI) with parallel solvers we adapted from legacy NASA codes and enhanced for full NKS functionality. Later implementations were made in the framework of the PETSC library from Argonne National Laboratory, which now includes pseudo-transient continuation Newton-Krylov-Schwarz solver capability (as a result of demands we made upon PETSC during our early porting experiences). A secondary project pursued with funding from this contract was parallel implicit solvers in acoustics, specifically in the Helmholtz formulation. A 2D acoustic inverse problem has been solved in parallel within the PETSC framework.

Keyes, David E.↗
NASA NTRS2018

An Active Subspace Method for Accelerating Convergence in Delaunay-Based Optimization via Dimension Reduction

Delaunay-based derivative-free optimization, ∆DOGS, is an efficient and provably-convergent global optimization method for the problems which has computationally expensive objection function and the analytical expression for the objective function is not available. ∆-DOGS is a novel optimization scheme in the family of response surface methods (RSMs); however, it suffers from the curse of dimensionality since the computational cost increases dramatically as the number of design parameters increases. As a result, the number of design parameters in ∆-DOGS algorithm is relatively low (n.10). To avoid such problems, this paper proposes a combination of derivative-free optimization, seeking the global minimizer of an expensive and nonconvex objective function f(x) and active subspace method, detecting the directions of the most variability using evaluations of the gradient. The contribution of other directions to the objective function is bounded by a sufficiently small constant. This new algorithm iteratively applied Delaunay-based derivative-free optimization to seek the minimizer on the d-dimensional active subspace that has most function variation. Inverse mapping is needed to project data from active subspace to full-model for evaluating function values. This task is overcome by solving an inequality constrained problem that curves the response surface of the objective function. The test results show that this strategy is effective on a handful of optimization problems.

Bewley, Thomas R.↗
NASA NTRS2011

Ensuring Success of Adaptive Control Research Through Project Lifecycle Risk Mitigation

Lessons Learne: 1. Design-out unnecessary risk to prevent excessive mitigation management during flight. 2. Consider iterative checkouts to confirm or improve human factor characteristics. 3. Consider the total flight test profile to uncover unanticipated human-algorithm interactions. 4. Consider test card cadence as a metric to assess test readiness. 5. Full-scale flight test is critical to development, maturation, and acceptance of adaptive control laws for operational use.

Pavlock, Kate M.↗
NASA NTRS2012

NASA Tech Briefs, August 2012

Topics covered include: Mars Science Laboratory Drill; Ultra-Compact Motor Controller; A Reversible Thermally Driven Pump for Use in a Sub-Kelvin Magnetic Refrigerator; Shape Memory Composite Hybrid Hinge; Binding Causes of Printed Wiring Assemblies with Card-Loks; Coring Sample Acquisition Tool; Joining and Assembly of Bulk Metallic Glass Composites Through Capacitive Discharge; 670-GHz Schottky Diode-Based Subharmonic Mixer with CPW Circuits and 70-GHz IF; Self-Nulling Lock-in Detection Electronics for Capacitance Probe Electrometer; Discontinuous Mode Power Supply; Optimal Dynamic Sub-Threshold Technique for Extreme Low Power Consumption for VLSI; Hardware for Accelerating N-Modular Redundant Systems for High-Reliability Computing; Blocking Filters with Enhanced Throughput for X-Ray Microcalorimetry; High-Thermal-Conductivity Fabrics; Imidazolium-Based Polymeric Materials as Alkaline Anion-Exchange Fuel Cell Membranes; Electrospun Nanofiber Coating of Fiber Materials: A Composite Toughening Approach; Experimental Modeling of Sterilization Effects for Atmospheric Entry Heating on Microorganisms; Saliva Preservative for Diagnostic Purposes; Hands-Free Transcranial Color Doppler Probe; Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer LogScope; TraceContract; AIRS Maps from Space Processing Software; POSTMAN: Point of Sail Tacking for Maritime Autonomous Navigation; Space Operations Learning Center; OVERSMART Reporting Tool for Flow Computations Over Large Grid Systems; Large Eddy Simulation (LES) of Particle-Laden Temporal Mixing Layers; Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing; Iterative Transform Phase Diversity: An Image-Based Object and Wavefront Recovery; 3D Drop Size Distribution Extrapolation Algorithm Using a Single Disdrometer; Social Networking Adapted for Distributed Scientific Collaboration; General Methodology for Designing Spacecraft Trajectories; Hemispherical Field-of-View Above-Water Surface Imager for Submarines; and Quantum-Well Infrared Photodetector (QWIP) Focal Plane Assembly.

Source record↗
NASA NTRS2021

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↗
NASA NTRS1994

Multigrid techniques for nonlinear eigenvalue probems: Solutions of a nonlinear Schroedinger eigenvalue problem in 2D and 3D

This paper presents multigrid (MG) techniques for nonlinear eigenvalue problems (EP) and emphasizes an MG algorithm for a nonlinear Schrodinger EP. The algorithm overcomes the mentioned difficulties combining the following techniques: an MG projection coupled with backrotations for separation of solutions and treatment of difficulties related to clusters of close and equal eigenvalues; MG subspace continuation techniques for treatment of the nonlinearity; an MG simultaneous treatment of the eigenvectors at the same time with the nonlinearity and with the global constraints. The simultaneous MG techniques reduce the large number of self consistent iterations to only a few or one MG simultaneous iteration and keep the solutions in a right neighborhood where the algorithm converges fast.

Costiner, Sorin↗
NASA NTRS2010

A General Algorithm for Reusing Krylov Subspace Information. I. Unsteady Navier-Stokes

A general algorithm is developed that reuses available information to accelerate the iterative convergence of linear systems with multiple right-hand sides A x = b (sup i), which are commonly encountered in steady or unsteady simulations of nonlinear equations. The algorithm is based on the classical GMRES algorithm with eigenvector enrichment but also includes a Galerkin projection preprocessing step and several novel Krylov subspace reuse strategies. The new approach is applied to a set of test problems, including an unsteady turbulent airfoil, and is shown in some cases to provide significant improvement in computational efficiency relative to baseline approaches.

Carpenter, Mark H.↗
NASA NTRS2010

Implementation of an Autonomous Multi-Maneuver Targeting Sequence for Lunar Trans-Earth Injection

Using a fully analytic initial guess estimate as a first iterate, a targeting procedure that constructs a flyable burn maneuver sequence to transfer a spacecraft from any closed Moon orbit to a desired Earth entry state is developed and implemented. The algorithm is built to support the need for an anytime abort capability for Orion. Based on project requirements, the Orion spacecraft must be able to autonomously calculate the translational maneuver targets for an entire Lunar mission. Translational maneuver target sequences for the Orion spacecraft include Lunar Orbit Insertion (LOI), Trans-Earth Injection (TEI), and Trajectory Correction Maneuvers (TCMs). This onboard capability is generally assumed to be supplemental to redundant ground computation in nominal mission operations and considered as a viable alternative primarily in loss of communications contingencies. Of these maneuvers, the ability to accurately and consistently establish a flyable 3-burn TEI target sequence is especially critical. The TEI is the sole means by which the crew can successfully return from the Moon to a narrowly banded Earth Entry Interface (EI) state. This is made even more critical by the desire for global access on the lunar surface. Currently, the designed propellant load is based on fully optimized TEI solutions for the worst case geometries associated with the accepted range of epochs and landing sites. This presents two challenges for an autonomous algorithm: in addition to being feasible, the targets must include burn sequences that do not exceed the anticipated propellant load.

Whitley, Ryan J.↗
NASA NTRS1993

Development of iterative techniques for the solution of unsteady compressible viscous flows

The work done under this project was documented in detail as the Ph. D. dissertation of Dr. Duane Hixon. The objectives of the research project were evaluation of the generalized minimum residual method (GMRES) as a tool for accelerating 2-D and 3-D unsteady flows and evaluation of the suitability of the GMRES algorithm for unsteady flows, computed on parallel computer architectures.

Sankar, Lakshmi↗
NASA NTRSDate not supplied

NOR Flash Memory Scrubbing Application for Boot File Preservation of NASA’s Descent and Landing Computer (DLC)

Progress on NASA’s Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project continues, specifically with this development of the Descent and Landing Computer (DLC). One of the DLC’s primary contributions as a SPLICE technology is its implementation of algorithms and operation of sensors to autonomously guide a spacecraft in performing more precise and safer landings on celestial bodies such as the Moon and Mars [1]. The second iteration of the DLC is known as the Engineering Test Unit (ETU) and one of its desired functionalities is the ability to preserve the fidelity of the system’s boot file through the use of memory scrubbing [2]. The ETU has two primary boards, one for housing a Multi-Processor System on a Chip (MPSoC) and the other for housing a Xilinx Kintex Ultrascale FPGA*. To emulate a memory scrubbing function implemented on the ETU’s FPGA board, the design and testing of a software application was performed on a Xilinx KCU105 FPGA evaluation board. The memory scrubbing application had to meet certain key criteria such as (1) properly utilize with the flash memory’s Serial Peripheral Interface (SPI) to read, write, and erase flash memory properly, (2) be able to detect arbitrarily large or small amounts of bit-errors, (3) be able to correct all detected errors, and (4) perform memory scrubbing indefinitely and autonomously. A prototype implementation was constructed and tested, demonstrating successful detection and correction of bit errors in multiple configurations. In the form of burst errors or singular bit flips, and in amounts of errors ranging from one to fifteen (per 256 Bytes), the application was successful in preserving memory fidelity.

Flash memory↗
NASA NTRS1999

Low Density Parity Check Codes Based on Finite Geometries: A Rediscovery and More

Low density parity check (LDPC) codes with iterative decoding based on belief propagation achieve astonishing error performance close to Shannon limit. No algebraic or geometric method for constructing these codes has been reported and they are largely generated by computer search. As a result, encoding of long LDPC codes is in general very complex. This paper presents two classes of high rate LDPC codes whose constructions are based on finite Euclidean and projective geometries, respectively. These classes of codes a.re cyclic and have good constraint parameters and minimum distances. Cyclic structure adows the use of linear feedback shift registers for encoding. These finite geometry LDPC codes achieve very good error performance with either soft-decision iterative decoding based on belief propagation or Gallager's hard-decision bit flipping algorithm. These codes can be punctured or extended to obtain other good LDPC codes. A generalization of these codes is also presented.

Kou, Yu↗
NASA NTRSDate not supplied

Biomass Harmonization and SAR Analysis with the Multi-mission Algorithm and Analysis Platform (MAAP)

The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.

cloud computing↗
NASA NTRS2010

Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction

An algorithm was developed to generate crop yield predictions from orbital remote sensing observations, by analyzing thousands of pixels per county and the associated historical crop yield data for those counties. The algorithm determines which pixels contain which crop. Since each known yield value is associated with thousands of individual pixels, this is a multiple instance learning problem. Because individual crop growth is related to the resulting yield, this relationship has been leveraged to identify pixels that are individually related to corn, wheat, cotton, and soybean yield. Those that have the strongest relationship to a given crop s yield values are most likely to contain fields with that crop. Remote sensing time series data (a new observation every 8 days) was examined for each pixel, which contains information for that pixel s growth curve, peak greenness, and other relevant features. An alternating-projection (AP) technique was used to first estimate the "salience" of each pixel, with respect to the given target (crop yield), and then those estimates were used to build a regression model that relates input data (remote sensing observations) to the target. This is achieved by constructing an exemplar for each crop in each county that is a weighted average of all the pixels within the county; the pixels are weighted according to the salience values. The new regression model estimate then informs the next estimate of the salience values. By iterating between these two steps, the algorithm converges to a stable estimate of both the salience of each pixel and the regression model. The salience values indicate which pixels are most relevant to each crop under consideration.

Wagstaff, Kiri L.↗
NASA NTRS1981

An evaluation of ISOCLS and CLASSY clustering algorithms for forest classification in northern Idaho

Both the iterative self-organizing clustering system (ISOCLS) and the CLASSY algorithms were applied to forest and nonforest classes for one 1:24,000 quadrangle map of northern Idaho and the classification and mapping accuracies were evaluated with 1:30,000 color infrared aerial photography. Confusion matrices for the two clustering algorithms were generated and studied to determine which is most applicable to forest and rangeland inventories in future projects. In an unsupervised mode, ISOCLS requires many trial-and-error runs to find the proper parameters to separate desired information classes. CLASSY tells more in a single run concerning the classes that can be separated, shows more promise for forest stratification than ISOCLS, and shows more promise for consistency. One major drawback to CLASSY is that important forest and range classes that are smaller than a minimum cluster size will be combined with other classes. The algorithm requires so much computer storage that only data sets as small as a quadrangle can be used at one time.

Werth, L. F.↗
NASA NTRS1989

Globally convergent techniques in nonlinear Newton-Krylov

Some convergence theory is presented for nonlinear Krylov subspace methods. The basic idea of these methods is to use variants of Newton's iteration in conjunction with a Krylov subspace method for solving the Jacobian linear systems. These methods are variants of inexact Newton methods where the approximate Newton direction is taken from a subspace of small dimensions. The main focus is to analyze these methods when they are combined with global strategies such as linesearch techniques and model trust region algorithms. Most of the convergence results are formulated for projection onto general subspaces rather than just Krylov subspaces.

Brown, Peter N.↗
NASA NTRS2019

Implementation and Testing of Inverse Kinematics on Robotic Arm

COSIE (Coronal Spectrographic Imager in the Extreme Ultraviolet) is a proposed solar tracking ISS imaging payload that will help bridge the theoretical gap between the physics of the low corona and the heliosphere. This scientific instrument requires high pointing accuracy, on the order of arc seconds. The instrument is mounted on to a three revolute joint robotic arm in order to track the roll, pitch and yaw motion of the Sun. The goal of this project is to construct a prototype model of the robotic arm and implement the proposed analytical inverse kinematics algorithm. In robotics, the inverse kinematics problem is solving for the set of joint angles that achieve the desired end effect or location and/or orientation. In this case, orientation is the focus. Depending on the configuration, multiple sets of joint angle solutions may exist. Due to the complexity of robotics, typically iterative methods are used to solve for the joint angle solution sets. However, in this case, an analytical solution exists. A small robotic arm representative of the full size hardware was constructed. The inverse kinematics algorithm, originally in MATLAB/Simulink, was converted into C in order to interface with the motors. This C software was implemented on a Windows PC and micro-controller, and serial communication between the two was established, allowing the motors to be directly controlled by the inverse kinematics algorithm. Testing the inverse kinematics on a physical system will allow the validity and accuracy of the analytic solution to be verified.

Franz, Carter↗
NASA NTRS1993

Implementing abstract multigrid or multilevel methods

Multigrid methods can be formulated as an algorithm for an abstract problem that is independent of the partial differential equation, domain, and discretization method. In such an abstract setting, problems not arising from partial differential equations can be treated. A general theory exists for linear problems. The general theory was motivated by a series of abstract solvers (Madpack). The latest version was motivated by the theory. Madpack now allows for a wide variety of iterative and direct solvers, preconditioners, and interpolation and projection schemes, including user callback ones. It allows for sparse, dense, and stencil matrices. Mildly nonlinear problems can be handled. Also, there is a fast, multigrid Poisson solver (two and three dimensions). The type of solvers and design decisions (including language, data structures, external library support, and callbacks) are discussed. Based on the author's experiences with two versions of Madpack, a better approach is proposed. This is based on a mixed language formulation (C and FORTRAN + preprocessor). Reasons for not using FORTRAN, C, or C++ (individually) are given. Implementing the proposed strategy is not difficult.

Douglas, Craig C.↗
NASA NTRS2006

Morphing: A Novel Approach to Astronaut Suit Sizing

The fitting of a spacesuit to an astronaut is an iterative process consisting of two parts. The first uses anthropometric data to provide an approximation of the suit components that will fit the astronaut. The second part is the subjective fitting, where small adjustments are made based on the astronaut s preference. By providing a better approximation of the correct suit components, the entire fit process time can be reduced significantly. The goals of this project are twofold: (1) To evaluate the effectiveness of the existing sizing algorithm for the Mark III Hybrid suit and (2) to determine what additional components are needed in order to provide adequate sizing for the existing astronaut population. A single subject was scanned using a 3D whole-body scanner (VITUS 3D) in the Mark III suit in eight different poses and four subjects in minimal clothing were also scanned in similar poses. The 3D external body scans of the suit and the subject are overlaid and visually aligned in a customized MATLAB program. The suit components were contracted or expanded linearly along the subjects limbs to match the subjects segmental lengths. Two independent measures were obtained from the morphing program on four subjects and compared with the existing sizing information. Two of the four subjects were in correspondence with the sizing algorithm and morphing results. The morphing outcome for a third subject, incompatible with the suit, suggested that an additional arm element at least 6 inches smaller than the existing smallest suit component would need to be acquired. The morphing result of the fourth subject, deemed incompatible with the suit using the sizing algorithm, indicated a different suit configuration which would be compatible. This configuration matched with the existing suit fit check data.

Margerum, Sarah↗