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Results for “algorithmic structures”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

DeepSAT: A Deep Learning Approach to Tree-Cover Delineation in 1-m NAIP Imagery for the Continental United States

High resolution tree cover classification maps are needed to increase the accuracy of current land ecosystem and climate model outputs. Limited studies are in place that demonstrates the state-of-the-art in deriving very high resolution (VHR) tree cover products. In addition, most methods heavily rely on commercial softwares that are difficult to scale given the region of study (e.g. continents to globe). Complexities in present approaches relate to (a) scalability of the algorithm, (b) large image data processing (compute and memory intensive), (c) computational cost, (d) massively parallel architecture, and (e) machine learning automation. In addition, VHR satellite datasets are of the order of terabytes and features extracted from these datasets are of the order of petabytes. In our present study, we have acquired the National Agriculture Imagery Program (NAIP) dataset for the Continental United States at a spatial resolution of 1-m. This data comes as image tiles (a total of quarter million image scenes with ~60 million pixels) and has a total size of ~65 terabytes for a single acquisition. Features extracted from the entire dataset would amount to ~8-10 petabytes. In our proposed approach, we have implemented a novel semi-automated machine learning algorithm rooted on the principles of "deep learning" to delineate the percentage of tree cover. Using the NASA Earth Exchange (NEX) initiative, we have developed an end-to-end architecture by integrating a segmentation module based on Statistical Region Merging, a classification algorithm using Deep Belief Network and a structured prediction algorithm using Conditional Random Fields to integrate the results from the segmentation and classification modules to create per-pixel class labels. The training process is scaled up using the power of GPUs and the prediction is scaled to quarter million NAIP tiles spanning the whole of Continental United States using the NEX HPC supercomputing cluster. An initial pilot over the state of California spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles has produced true positive rates of around 88 percent for fragmented forests and 74 percent for urban tree cover areas, with false positive rates lower than 2 percent for both landscapes.

Imagery↗
NASA NTRS1985

A Taylor-Galerkin finite element algorithm for transient nonlinear thermal-structural analysis

A Taylor-Galerkin finite element solution algorithm for transient nonlinear thermal-structural analysis of large, complex structural problems subjected to rapidly applied thermal-structural loads is described. The two-step Taylor-Galerkin algorithm is an application of an algorithm recently developed for problems in compressible fluid dynamics. The element integrals that appear in the algorithm can be evaluated in closed form for two and three dimensional elements.

Thornton, Earl A.↗
NASA NTRS1986

A Taylor-Galerkin finite element algorithm for transient nonlinear thermal-structural analysis

A Taylor-Galerkin finite element method for solving large, nonlinear thermal-structural problems is presented. The algorithm is formulated for coupled transient and uncoupled quasistatic thermal-structural problems. Vectorizing strategies ensure computational efficiency. Two applications demonstrate the validity of the approach for analyzing transient and quasistatic thermal-structural problems.

Thornton, E. A.↗
NASA NTRS1986

A Taylor-Galerkin finite element algorithm for transient nonlinear thermal-structural analysis

A Taylor-Galerkin finite element method for solving large, nonlinear thermal-structural problems is presented. The algorithm is formulated for coupled transient and uncoupled quasistatic thermal-structural problems. Vectorizing strategies ensure computational efficiency. Two applications demonstrate the validity of the approach for analyzing transient and quasistatic thermal-structural problems.

Thornton, E. A.↗
NASA NTRS1983

Improvement of mixed time implicit-explicit algorithms for thermal analysis of structures

Computer implementation aspects and numerical evaluation of the recently introduced mixed time implicit-explicit algorithms in thermal analysis of structures are presented. A computationally useful method of estimating the critical time step for a linear quadrilateral element is given herein for the methods introduced by Liu and co-workers. Numerical tests confirm the stability criterion and accuracy characteristics of the methods. The superiority of these mixed time methods to the fully implicit method or the fully explicit method is also demonstrated.

Liu, W. K.↗
NASA NTRS1993

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.↗
NASA NTRS1979

An integrated computer procedure for sizing composite airframe structures

A computerized algorithm to generate cross-sectional dimensions and fiber orientations for composite airframe structures is described, and its application in a wing structural synthesis is established. The algorithm unifies computations of aeroelastic loads, stresses, and deflections, as well as optimal structural sizing and fiber orientations in an open-ended system of integrated computer programs. A finite-element analysis and a mathematical-optimization technique are discussed.

Sobieszczanski-Sobieski, J.↗
NASA NTRS1993

The use of linked lists in the simulation of controller-structure interaction

An algorithm for the computer simulation of large space structures under active control is considered. Linked lists are used in a matrix data structure to implement the trapezoidal rule on system differential equations. The use of the trapezoidal rule ensures that the numerical stability is equivalent to the system stability, which is essential for this type of simulation. The sparsity of the system matrices is exploited by the linked lists, and the algorithm efficiently steps through the lists in an orderly fashion. Results of simulations on a NASA large space structure experiment are reported.

Quan, R.↗
NASA NTRS1993

The use of linked lists in the simulation of controller-structure interaction

An algorithm for the computer simulation of large space structures under active control is considered. Linked lists are used in a matrix data structure to implement the trapezoidal rule on the system differential equations. The use of the trapezoidal rule ensures that the numerical stability is equivalent to the system stability, which is essential for this type of simulation. The sparsity of the system matrices is exploited by the linked lists, and the algorithm efficiently steps through the lists in an orderly fashion. Results of simulations on a NASA large space structure experiment are reported.

Quan, Ralph↗
NASA NTRS1993

Structured adaptive grid generation using algebraic methods

The accuracy of the numerical algorithm depends not only on the formal order of approximation but also on the distribution of grid points in the computational domain. Grid adaptation is a procedure which allows optimal grid redistribution as the solution progresses. It offers the prospect of accurate flow field simulations without the use of an excessively timely, computationally expensive, grid. Grid adaptive schemes are divided into two basic categories: differential and algebraic. The differential method is based on a variational approach where a function which contains a measure of grid smoothness, orthogonality and volume variation is minimized by using a variational principle. This approach provided a solid mathematical basis for the adaptive method, but the Euler-Lagrange equations must be solved in addition to the original governing equations. On the other hand, the algebraic method requires much less computational effort, but the grid may not be smooth. The algebraic techniques are based on devising an algorithm where the grid movement is governed by estimates of the local error in the numerical solution. This is achieved by requiring the points in the large error regions to attract other points and points in the low error region to repel other points. The development of a fast, efficient, and robust algebraic adaptive algorithm for structured flow simulation applications is presented. This development is accomplished in a three step process. The first step is to define an adaptive weighting mesh (distribution mesh) on the basis of the equidistribution law applied to the flow field solution. The second, and probably the most crucial step, is to redistribute grid points in the computational domain according to the aforementioned weighting mesh. The third and the last step is to reevaluate the flow property by an appropriate search/interpolate scheme at the new grid locations. The adaptive weighting mesh provides the information on the desired concentration of points to the grid redistribution scheme. The evaluation of the weighting mesh is accomplished by utilizing the weight function representing the solution variation and the equidistribution law. The selection of the weight function plays a key role in grid adaptation. A new weight function utilizing a properly weighted boolean sum of various flowfield characteristics is defined. The redistribution scheme is developed utilizing Non-Uniform Rational B-Splines (NURBS) representation. The application of NURBS representation results in a well distributed smooth grid by maintaining the fidelity of the geometry associated with boundary curves. Several algebraic methods are applied to smooth and/or nearly orthogonalize the grid lines. An elliptic solver is utilized to smooth the grid lines if there are grid crossings. Various computational examples of practical interest are presented to demonstrate the success of these methods.

Yang, Jiann-Cherng↗
NASA NTRS1989

A new unified architecture of thermal/structural dynamic algorithms - Applications to coupled thermoelasticity

A new unified architecture of robust thermal-structural dynamic algorithms is presented with emphasis on applications to coupled thermoelasticity. The proposed formulations are based on Lax-Wendroff/Taylor-Galerkin explicit time integration methodology. The applicability of the proposed unified architecture to interdisciplinary problems relevant to coupled dynamic thermoelasticity is demonstrated. The basic concepts and characteristic features of the unified formulations are discussed.

Tamma, Kumar K.↗
NASA NTRS1985

Experimental Verification of Identification Algorithms for Control of Flexible Structures

An on going simple laboratory experiment, referred to as the Beam Control Experiment (BCE) is described which has the essential features of a large flexible structure. The experiment is used to develop and evaluate identification and control algorithms which lock promising in the active control of high performance large space structures. Some results on the maximum likelihood identification of the parameters of the beam actuator sensor assembly from experimental data is presented.

Sridher, B.↗
NASA NTRS1992

Parallel solver for trajectory optimization search directions

A key algorithmic element of a real-time trajectory optimization hardware/software implementation is presented, the search step solver. This is one piece of an algorithm whose overall goal is to make nonlinear trajectory optimization fast enough to provide real-time commands during guidance of a vehicle such as an aeromaneuvering orbiter or the National Aerospace Plane. Many methods of nonlinear programming require the solution of a quadratic program (QP) at each iteration to determine the search step. In the trajectory optimization case, the QP has a special dynamic programming structure. The algorithm exploits this special structure with a divide- and conquer type of parallel implementation. The algorithm solves a (p.N)-stage problem on N processors in O(p + log2 N) operations. The algorithm yields a factor of 8 speed-up over the fastest known serial algorithm when solving a 1024-stage test problem on 32 processors.

Psiaki, M. L.↗
NASA NTRSDate not supplied

Validation of the Hypersolve CFD Solver for Entry Descent and Landing Applications

The functional equivalence of the HyperSolve unstructured edge-based, finite-volume computational fluid dynamics code to the Langley Aerothermodynamic Upwind Relaxation Algorithm multiblock structured grid code is documented for applications of interest to the Entry, Descent, and Landing community. A suite of cases using a range of thermochemical gas models on relevant vehicle configurations were analyzed with both codes and the results compared. A tolerance of ±4% difference in surface pressure and surface heat flux from a benchmark LAURA solution was used as the criterion for functional equivalence, and comparisons of flowfield quantities are also included to verify that the thermochemical nonequilibrium capabilities in HyperSolve match those of the LAURA code. The functional equivalence of the HyperSolve unstructured edge-based finite-volume computational fluid dynamics (CFD) code to the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) multiblock structured grid code is documented for applications of interest to the Entry, Descent, and Landing (EDL) community. A suite of cases using a range of thermochemical gas models on EDL-relevant vehicle configurations were analyzed with both codes and the results compared. A tolerance of ±4% difference in surface pressure and surface heat flux from a benchmark LAURA solution was used as the criterion for functional equivalence, and comparisons of flow field quantities are also included to verify that the thermochemical nonequilibrium capabilities in HyperSolve match those of the LAURA code. In general, HyperSolve predictions for surface pressure and surface heat flux are in close agreement with those predicted by LAURA.

hypersolve↗
NASA NTRSDate not supplied

Validation of the HyperSolve CFD Solver for Entry Descent and Landing Applications

The functional equivalence of the HyperSolve unstructured edge-based, finite-volume computational fluid dynamics code to the Langley Aerothermodynamic Upwind Relaxation Algorithm multiblock structured grid code is documented for applications of interest to the Entry, Descent, and Landing community. A suite of cases using a range of thermochemical gas models on relevant vehicle configurations were analyzed with both codes and the results compared. A tolerance of ±4% difference in surface pressure and surface heat flux from a benchmark LAURA solution was used as the criterion for functional equivalence, and comparisons of flowfield quantities are also included to verify that the thermochemical nonequilibrium capabilities in HyperSolve match those of the LAURA code. The functional equivalence of the HyperSolve unstructured edge-based finite-volume computational fluid dynamics (CFD) code to the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) multiblock structured grid code is documented for applications of interest to the Entry, Descent, and Landing (EDL) community. A suite of cases using a range of thermochemical gas models on EDL-relevant vehicle configurations were analyzed with both codes and the results compared. A tolerance of ±4% difference in surface pressure and surface heat flux from a benchmark LAURA solution was used as the criterion for functional equivalence, and comparisons of flow field quantities are also included to verify that the thermochemical nonequilibrium capabilities in HyperSolve match those of the LAURA code. In general, HyperSolve predictions for surface pressure and surface heat flux are in close agreement with those predicted by LAURA.

hypersolve↗
NASA NTRS1986

Experimental Parallel-Processing Computer

Master processor supervises slave processors, each with its own memory. Computer with parallel processing serves as inexpensive tool for experimentation with parallel mathematical algorithms. Speed enhancement obtained depends on both nature of problem and structure of algorithm used. In parallel-processing architecture, "bank select" and control signals determine which one, if any, of N slave processor memories accessible to master processor at any given moment. When so selected, slave memory operates as part of master computer memory. When not selected, slave memory operates independently of main memory. Slave processors communicate with each other via input/output bus.

Mcgregor, J. W.↗