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At least 469 records · Page 26

Spatial compression of Seasat SAR imagery

The results of a study of techniques for spatial compression of synthetic-aperture-radar (SAR) imagery are summarized. Emphasis is on image-data volume reduction for archive and online storage applications while preserving the image resolution and radiometric fidelity. A quantitative analysis of various techniques, including vector quantization (VQ) and adaptive discrete cosine transform (ADCT), is presented. Various factors such as compression ratio, algorithm complexity, and image quality are considered in determining the optimal algorithm. The compression system requirements are established for electronic access of an online archive system based on the results of a survey of the science community. The various algorithms are presented and their results evaluated considering the effects of speckle noise and the wide dynamic range inherent in SAR imagery. The conclusion is that although the ADCT produces the best signal-to-distortion-noise ratio for a given compression ratio, the two-level tree-searched VQ technique is preferred due to its simplicity of decoding and near-optimal performance.

Chang, C. Y.↗

Real-time trajectory optimization on parallel processors

A parallel algorithm has been developed for rapidly solving trajectory optimization problems. The goal of the work has been to develop an algorithm that is suitable to do real-time, on-line optimal guidance through repeated solution of a trajectory optimization problem. The algorithm has been developed on an INTEL iPSC/860 message passing parallel processor. It uses a zero-order-hold discretization of a continuous-time problem and solves the resulting nonlinear programming problem using a custom-designed augmented Lagrangian nonlinear programming algorithm. The algorithm achieves parallelism of function, derivative, and search direction calculations through the principle of domain decomposition applied along the time axis. It has been encoded and tested on 3 example problems, the Goddard problem, the acceleration-limited, planar minimum-time to the origin problem, and a National Aerospace Plane minimum-fuel ascent guidance problem. Execution times as fast as 118 sec of wall clock time have been achieved for a 128-stage Goddard problem solved on 32 processors. A 32-stage minimum-time problem has been solved in 151 sec on 32 processors. A 32-stage National Aerospace Plane problem required 2 hours when solved on 32 processors. A speed-up factor of 7.2 has been achieved by using 32-nodes instead of 1-node to solve a 64-stage Goddard problem.

Psiaki, Mark L.↗

Low background IR detector and detector array evaluations

A technology program has been underway at Ames since 1978 to develop and evaluate detectors and integrated detector arrays for low-background astronomical applications. The approach is to evaluate existing (less than 24 micron) array technology under low-background conditions, with the aim of adapting and optimizing existing devices. For longer wavelengths, where the technology is much less mature, development is sponsored and devices are evaluated, in both discrete and array formats, for eventual applications. The status of this program has been reported previously. We rely on industrial and university sources for the detectors. Typically, after a brief functionality check in the supplier's laboratory, we work with the device at Ames to characterize its low-background performance. In the case of promising arrays or detectors, we conduct ground-based telescope testing to face the problems associated with real applications. A list of devices tested at Ames is given. In the array category, accumulation-mode charge-injection-devices (AMCIDs) appear repeatedly; this reflects our recent experience with the 2 x 64 and 16 x 16 arrays. Results from the 1 x 16 CID and InSb CCD have been reported. The status of our tests of the discrete Ge:x detectors from Lawrence Berkeley Laboratory are described below. Tests of a 1 x 2 switched sample photoconductor array are just beginning. A 32-channel CMOS multiplexer has been tested at 10 K. Low-temperature silicon MOSFETs and germanium JFETs have also been tested, primarily at Ball Aerospace. This paper describes results to date on three elements of this program: AMCID array, discrete Ge:Ga detectors, and Ge JFET preamplifiers.

Goebel, J. H.↗

Solving Upwind-Biased Discretizations: Multigrid Solver Using Semicoarsening - 2

This paper studies a novel multigrid approach to the solution for a second order upwind biased discretization of the convection equation in two dimensions. This approach is based on semi-coarsening and well balanced explicit correction terms added to coarse-grid operators to maintain on coarse-grid the same cross-characteristic interaction as on the target (fine) grid. Colored relaxation schemes are used on all the levels allowing a very efficient parallel implementation. The results of the numerical tests can be summarized as follows: 1) The residual asymptotic convergence rate of the proposed V(0, 2) multigrid cycle is about 3 per cycle. This convergence rate far surpasses the theoretical limit (4/3) predicted for standard multigrid algorithms using full coarsening. The reported efficiency does not deteriorate with increasing the cycle, depth (number of levels) and/or refining the target-grid mesh spacing. 2) The full multi-grid algorithm (FMG) with two V(0, 2) cycles on the target grid and just one V(0, 2) cycle on all the coarse grids always provides an approximate solution with the algebraic error less than the discretization error. Estimates of the total work in the FMG algorithm are ranged between 18 and 30 minimal work units (depending on the target (discretizatioin). Thus, the overall efficiency of the FMG solver closely approaches (if does not achieve) the goal of the textbook multigrid efficiency. 3) A novel approach to deriving a discrete solution approximating the true continuous solution with a relative accuracy given in advance is developed. An adaptive multigrid algorithm (AMA) using comparison of the solutions on two successive target grids to estimate the accuracy of the current target-grid solution is defined. A desired relative accuracy is accepted as an input parameter. The final target grid on which this accuracy can be achieved is chosen automatically in the solution process. the actual relative accuracy of the discrete solution approximation obtained by AMA is always better than the required accuracy; the computational complexity of the AMA algorithm is (nearly) optimal (comparable with the complexity of the FMG algorithm applied to solve the problem on the optimally spaced target grid).

Diskin, Boris↗

Digital controllers for VTOL aircraft

Using linear-optimal estimation and control techniques, digital-adaptive control laws have been designed for a tandem-rotor helicopter which is equipped for fully automatic flight in terminal area operations. Two distinct discrete-time control laws are designed to interface with velocity-command and attitude-command guidance logic, and each incorporates proportional-integral compensation for non-zero-set-point regulation, as well as reduced-order Kalman filters for sensor blending and noise rejection. Adaptation to flight condition is achieved with a novel gain-scheduling method based on correlation and regression analysis. The linear-optimal design approach is found to be a valuable tool in the development of practical multivariable control laws for vehicles which evidence significant coupling and insufficient natural stability.

Stengel, R. F.↗

Packing and flow particle simulations

Granular material is present across natural and industrial processes on Earth and other planets. Granular particles show up in space exploration (lunar regolith), avalanches (boulders), food (coffee), construction (concrete powder) and manufacturing (additive manufacturing powder, battery slurries). Important phenomena emerge from large collections of granular particles. The size scales of the particles in granular material, 10 μm diameter or larger, makes particle-based simulations a tractable computational method. This seminar will present the packing and flow of granular matter using particle-based discrete element modeling simulations. Particles modeled with rotational friction only require as few as 2.6 contacts for mechanical stability, as opposed to 6 contacts for frictionless particles. Optimal parameters for in-space manufacturing particulate material are identified. Specifically, the maximum density and contacts occurs for a large-to-small particle volume ratio of 0.265. Stress and contact fabric fluctuations of flowing dry granular matter have power-law scaling with strain rate, and a kink. The pressure-dependent slope change kink could identify the transition between slower, quasistatic and faster, inertial flows.

granular↗

Packing and flow particle simulations

Granular material is present across natural and industrial processes on Earth and other planets. Granular particles show up in space exploration (lunar regolith), avalanches (boulders), food (coffee), construction (concrete powder) and manufacturing (additive manufacturing powder, battery slurries). Important phenomena emerge from large collections of granular particles. The size scales of the particles in granular material, 10 μm diameter or larger, makes particle-based simulations a tractable computational method. This seminar will present the packing and flow of granular matter using particle-based discrete element modeling simulations. Particles modeled with rotational friction only require as few as 2.6 contacts for mechanical stability, as opposed to 6 contacts for frictionless particles. Optimal parameters for in-space manufacturing particulate material are identified. Specifically, the maximum density and contacts occurs for a large-to-small particle volume ratio of 0.265. Stress and contact fabric fluctuations of flowing dry granular matter have power-law scaling with strain rate, and a kink. The pressure-dependent slope change kink could identify the transition between slower, quasistatic and faster, inertial flows.

granular↗

Optimal maintenance center inventories for fault-tolerant repairable systems

A probabilistic approach is taken to determine the optimal repairable parts inventory for a maintenance center, servicing machines which contain several m-out-of-n systems of different parts, with a constraint on the total inventory investment. A model, based on the discrete Markov process, accounts for a typical ultrareliable avionics system, such as one presently being developed by NASA. The dynamic programming algorithm for minimizing the stockout and holding costs is applied to an exemplary maintenance center, and solutions for single-item and multi-item cases are given. The computational burden is noted to be reasonable and a computer program is used to generate optimal solutions.

Lawrence, S. H.↗

Human controller modeling in environments that include non-control tasks

In complex environments where the human operator is a supervisor, he must allocate his attention between different kinds of tasks for optimum overall performance. When a portion of the future reference trajectory for the control task is available for preview, scheduling various activities is possible. A model has been developed for this situation using dynamic programming to solve an optimal control problem. An experiment was conducted where subjects controlled an airplane symbol over a map, shown a fixed distance into the future. Discrete, non-control tasks were introduced as number entry tasks. Results from the model are compared with experimental results.

Govindaraj, T.↗

Galerkin/Runge-Kutta discretizations for semilinear parabolic equations

A new class of fully discrete Galerkin/Runge-Kutta methods is constructed and analyzed for semilinear parabolic initial boundary value problems. Unlike any classical counterpart, this class offers arbitrarily high, optimal order convergence. In support of this claim, error estimates are proved, and computational results are presented. Furthermore, it is noted that special Runge-Kutta methods allow computations to be performed in parallel so that the final execution time can be reduced to that of a low order method.

Keeling, Stephen L.↗

Technology development program for the Space Infrared Telescope Facility (SIRTF) science instruments

A coordinated technology program for the Space Infrared Telescope Facility (SIRTF) is described. The program encompasses detector technology, cryogenic mechanisms technology, and an adiabatic demagnetization refrigerator. Discrete detectors, detector arrays, detector readouts, and testing of engineering models under simulated flight environment conditions are considered. Several focal planes will be optimized at a particular wavelength range to make up over 247,000 detector pixels from about 1.8 to 1000 microns.

Ramos, Ruben↗

Joint Chance-Constrained Dynamic Programming

This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.

Ono, Masahiro↗

Discrete observability and numerical quadrature

The authors consider the problem of approximate observability of a one-dimensional diffusion equation on a finite spatial domain with spatial point measurements. The problem of the optimal selection of the measurement points is considered under three conditions: (1) no preassigned measurement nodes; (2) one preassigned node and; (3) two preassigned nodes. The main observation is that the optimal choice is related to three classical procedures in numerical analysis: (1) Gaussian quadrature; (2) Radau quadrature and; (3) Lobatto quadrature. It is shown that the existence of the Radau and Lobatto quadrature is closely related to classical root locus theory.

Martin, Clyde F.↗

Shape design sensitivities using fully automatic 3-D mesh generation

Previous work in three dimensional shape optimization involved specifying design variables by associating parameters directly with mesh points. More recent work has shown the use of fully-automatic mesh generation based upon a parameterized geometric representation. Design variables have been associated with a mathematical model of the part rather than the discretized representation. The mesh generation procedure uses a nonuniform grid intersection technique to place nodal points directly on the surface geometry. Although there exists an associativity between the mesh and the geometrical/topological entities, there is no mathematical functional relationship. This poses a problem during certain steps in the optimization process in which geometry modification is required. For the large geometrical changes which occur at the beginning of each optimization step, a completely new mesh is created. However, for gradient calculations many small changes must be made and it would be too costly to regenerate the mesh for each design variable perturbation. For that reason, a local remeshing procedure has been implemented which operates only on the specific edges and faces associated with the design variable being perturbed. Two realistic design problems are presented which show the efficiency of this process and test the accuracy of the gradient computations.

Botkin, M. E.↗

Investigation, development, and application of optimal output feedback theory. Volume 3: The relationship between dynamic compensators and observers and Kalman filters

Relationships between observers, Kalman Filters and dynamic compensators using feedforward control theory are investigated. In particular, the relationship, if any, between the dynamic compensator state and linear functions of a discrete plane state are investigated. It is shown that, in steady state, a dynamic compensator driven by the plant output can be expressed as the sum of two terms. The first term is a linear combination of the plant state. The second term depends on plant and measurement noise, and the plant control. Thus, the state of the dynamic compensator can be expressed as an estimator of the first term with additive error given by the second term. Conditions under which a dynamic compensator is a Kalman filter are presented, and reduced-order optimal estimaters are investigated.

Broussard, John R.↗

A comparison of two closely-related approaches to aerodynamic design optimization

Two related methods for aerodynamic design optimization are compared. The methods, called the implicit gradient approach and the variational (or optimal control) approach, both attempt to obtain gradients necessary for numerical optimization at a cost significantly less than that of the usual black-box approach that employs finite difference gradients. While the two methods are seemingly quite different, they are shown to differ (essentially) in that the order of discretizing the continuous problem, and of applying calculus, is interchanged. Under certain circumstances, the two methods turn out to be identical. We explore the relationship between these methods by applying them to a model problem for duct flow that has many features in common with transonic flow over an airfoil. We find that the gradients computed by the variational method can sometimes be sufficiently inaccurate to cause the optimization to fail.

Shubin, G. R.↗

An Optimized Multicolor Point-Implicit Solver for Unstructured Grid Applications on Graphics Processing Units

In the field of computational fluid dynamics, the Navier-Stokes equations are often solved using an unstructuredgrid approach to accommodate geometric complexity. Implicit solution methodologies for such spatial discretizations generally require frequent solution of large tightly-coupled systems of block-sparse linear equations. The multicolor point-implicit solver used in the current work typically requires a significant fraction of the overall application run time. In this work, an efficient implementation of the solver for graphics processing units is proposed. Several factors present unique challenges to achieving an efficient implementation in this environment. These include the variable amount of parallelism available in different kernel calls, indirect memory access patterns, low arithmetic intensity, and the requirement to support variable block sizes. In this work, the solver is reformulated to use standard sparse and dense Basic Linear Algebra Subprograms (BLAS) functions. However, numerical experiments show that the performance of the BLAS functions available in existing CUDA libraries is suboptimal for matrices representative of those encountered in actual simulations. Instead, optimized versions of these functions are developed. Depending on block size, the new implementations show performance gains of up to 7x over the existing CUDA library functions.

Zubair, Mohammad↗