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At least 757 records · Page 42

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NASA NTRS1986

On some equivalent configurations of systolic arrays

A systematic approach is presented for designing systolic arrays and their equivalent configurations for certain general classes of recursively formulated algorithms. A new method is also introduced to reduce the input bandwidth and storage requirements of the systolic arrays through the study of dependence among the input data. Many well known systolic arrays can be rederived and also many new systolic arrays can be discovered by this approach.

Chang, C. Y.↗

NASA NTRS1987

Optimal placement of excitations and sensors for verification of large dynamical systems

The computationally difficult problem of the optimal placement of excitations and sensors to maximize the observed measurements is studied within the framework of combinatorial optimization, and is solved numerically using a variation of the simulated annealing heuristic algorithm. Results of numerical experiments including a square plate and a 960 degrees-of-freedom Control of Flexible Structure (COFS) truss structure, are presented. Though the algorithm produces suboptimal solutions, its generality and simplicity allow the treatment of complex dynamical systems which would otherwise be difficult to handle.

Salama, M.↗

NASA NTRS1987

State-space formulation of multi-shaker modal analysis

As modal testing techniques have improved in recent years, the demands placed on the accuracy of modal test results have increased. This paper describes a new multi-input, multi-output modal parameter estimation algorithm suitable for the identification of reduced-order models of structures. The method described is a frequency-domain method based on excitation and response spectra. The principal features of the algorithm are: (1) applicability to general linear, time-invariant systems, (2) direct use of multiple input and multiple response data, (3) identification of reduced-order models with minimum user interaction through the use of two automatic model-reduction techniques, (4) identification of a consistent set of modal parameters through the use of numerically stable least-squares techniques, and (5) complete user documentation.

Craig, Roy R., Jr.↗

NASA NTRS1989

Analysis of whisker-toughened ceramic components: A design engineer's viewpoint

The use of ceramics components in gas turbines, cutting tools, and heat exchangers has been limited by the relatively low flaw tolerance of monolithic ceramics. The development of whisker toughened ceramic composites offers the potential for considerable improvement in fracture toughness as well as strength. However, the variability of strength is still too high for the application of deterministic design approaches. Several phenomenological reliability theories proposed for this material system are reviewed and the development is reported of a public domain computer algorithm. This algorithm, when coupled with a general purpose finite element program, predicts the fast fracture reliability of a structural component under multiaxial loading conditions.

Duffy, Stephen F.↗

NASA NTRS1991

Consistent detection of global predicates

A fundamental problem in debugging and monitoring is detecting whether the state of a system satisfies some predicate. If the system is distributed, then the resulting uncertainty in the state of the system makes such detection, in general, ill-defined. Three algorithms are presented for detecting global predicates in a well-defined way. These algorithms do so by interpreting predicates with respect to the communication that has occurred in the system.

Cooper, Robert↗

NASA NTRS1991

Evaluation of a transfinite element numerical solution method for nonlinear heat transfer problems

Laplace transform techniques have been widely used to solve linear, transient field problems. A transform-based algorithm enables calculation of the response at selected times of interest without the need for stepping in time as required by conventional time integration schemes. The elimination of time stepping can substantially reduce computer time when transform techniques are implemented in a numerical finite element program. The coupling of transform techniques with spatial discretization techniques such as the finite element method has resulted in what are known as transfinite element methods. Recently attempts have been made to extend the transfinite element method to solve nonlinear, transient field problems. This paper examines the theoretical basis and numerical implementation of one such algorithm, applied to nonlinear heat transfer problems. The problem is linearized and solved by requiring a numerical iteration at selected times of interest. While shown to be acceptable for weakly nonlinear problems, this algorithm is ineffective as a general nonlinear solution method.

Cerro, J. A.↗

NASA NTRS1995

Femtolensing: Beyond the semiclassical approximation

Femtolensoing is a gravitational lensing effect in which the magnification is a function not only of the position and sizes of the source and lens, but also of the wavelength of light. Femtolensing is the only known effect of 10(exp -13) - 10(exp -16) solar mass) dark-matter objects and may possibly be detectable in cosmological gamma-ray burst spectra. We present a new and efficient algorithm for femtolensing calculation in general potentials. The physical optics results presented here differ at low frequencies from the semiclassical approximation, in which the flux is attributed to a finite number of mutually coherent images. At higher frequencies, our results agree well with the semicalssical predictions. Applying our method to a point-mass lens with external shear, we find complex events that have structure at both large and small spectral resolution. In this way, we show that femtolensing may be observable for lenses up to 10(exp -11) solar mass, much larger than previously believed. Additionally, we discuss the possibility of a search femtolensing of white dwarfs in the Large Magellanic Cloud at optical wavelengths.

Ulmer, Andrew↗

NASA NTRS1996

Artificial Boundary Conditions for Computation of Oscillating External Flows

In this paper, we propose a new technique for the numerical treatment of external flow problems with oscillatory behavior of the solution in time. Specifically, we consider the case of unbounded compressible viscous plane flow past a finite body (airfoil). Oscillations of the flow in time may be caused by the time-periodic injection of fluid into the boundary layer, which in accordance with experimental data, may essentially increase the performance of the airfoil. To conduct the actual computations, we have to somehow restrict the original unbounded domain, that is, to introduce an artificial (external) boundary and to further consider only a finite computational domain. Consequently, we will need to formulate some artificial boundary conditions (ABC's) at the introduced external boundary. The ABC's we are aiming to obtain must meet a fundamental requirement. One should be able to uniquely complement the solution calculated inside the finite computational domain to its infinite exterior so that the original problem is solved within the desired accuracy. Our construction of such ABC's for oscillating flows is based on an essential assumption: the Navier-Stokes equations can be linearized in the far field against the free-stream back- ground. To actually compute the ABC's, we represent the far-field solution as a Fourier series in time and then apply the Difference Potentials Method (DPM) of V. S. Ryaben'kii. This paper contains a general theoretical description of the algorithm for setting the DPM-based ABC's for time-periodic external flows. Based on our experience in implementing analogous ABC's for steady-state problems (a simpler case), we expect that these boundary conditions will become an effective tool for constructing robust numerical methods to calculate oscillatory flows.

Tsynkov, S. V.↗

NASA NTRS1997

Absorption of Sunlight by Water Vapor in Cloudy Conditions: A Partial Explanation for the Cloud Absorption Anomaly

The atmospheric radiative transfer algorithms used in most global general circulation models underestimate the globally-averaged solar energy absorbed by cloudy atmospheres by up to 25 W/sq m. The origin of this anomalous absorption is not yet known, but it has been attributed to a variety of sources including oversimplified or missing physical processes in these models, uncertainties in the input data, and even measurement errors. Here, a sophisticated atmospheric radiative transfer model was used to provide a more comprehensive description of the physical processes that contribute to the absorption of solar radiation by the Earth's atmosphere. We found that the amount of sunlight absorbed by a cloudy atmosphere is inversely proportional to the solar zenith angle and the cloud top height, and directly proportional to the cloud optical depth and the water vapor concentration within the clouds. Atmospheres with saturated, optically-thick, low clouds absorbed about 12 W/sq m more than clear atmospheres. This accounts for about 1/2 to 1/3 of the anomalous ab- sorption. Atmospheres with optically thick middle and high clouds usually absorb less than clear atmospheres. Because water vapor is concentrated within and below the cloud tops, this absorber is most effective at small solar zenith angles. An additional absorber that is distributed at or above the cloud tops is needed to produce the amplitude and zenith angle dependence of the observed anomalous absorption.

Crisp, D.↗

NASA NTRS1999

Implementation of Multispectral Image Classification on a Remote Adaptive Computer

As the demand for higher performance computers for the processing of remote sensing science algorithms increases, the need to investigate new computing paradigms its justified. Field Programmable Gate Arrays enable the implementation of algorithms at the hardware gate level, leading to orders of m a,gnitude performance increase over microprocessor based systems. The automatic classification of spaceborne multispectral images is an example of a computation intensive application, that, can benefit from implementation on an FPGA - based custom computing machine (adaptive or reconfigurable computer). A probabilistic neural network is used here to classify pixels of of a multispectral LANDSAT-2 image. The implementation described utilizes Java client/server application programs to access the adaptive computer from a remote site. Results verify that a remote hardware version of the algorithm (implemented on an adaptive computer) is significantly faster than a local software version of the same algorithm implemented on a typical general - purpose computer).

Figueiredo, Marco A.↗

NASA NTRS2005

Fault protection techniques in JPL Spacecraft

While every JPL spacecraft requires some unique mission specific fault protection, there are many requirements which are common to all spacecraft configurations. These consist of protecting command and data processing & attitude control computers, protection against communication loss with the spacecraft, ensuring that safe external and internal temperature levels are maintained, and recovery from power overloads. Additionally, most JPL spacecraft are equipped with a general-purpose 'Safe Mode' response algorithm which configures the spacecraft to a lower power state which is safe and predictable so that diagnosis of more complex faults can be addressed by the Operations Team. This paper details the generic application of fault protection techniques which are implemented into most JPL spacecraft designs.

fault protection↗

NASA NTRS2007

Protecting Against Faults in JPL Spacecraft

A paper discusses techniques for protecting against faults in spacecraft designed and operated by NASA s Jet Propulsion Laboratory (JPL). The paper addresses, more specifically, fault-protection requirements and techniques common to most JPL spacecraft (in contradistinction to unique, mission specific techniques), standard practices in the implementation of these techniques, and fault-protection software architectures. Common requirements include those to protect onboard command, data-processing, and control computers; protect against loss of Earth/spacecraft radio communication; maintain safe temperatures; and recover from power overloads. The paper describes fault-protection techniques as part of a fault-management strategy that also includes functional redundancy, redundant hardware, and autonomous monitoring of (1) the operational and health statuses of spacecraft components, (2) temperatures inside and outside the spacecraft, and (3) allocation of power. The strategy also provides for preprogrammed automated responses to anomalous conditions. In addition, the software running in almost every JPL spacecraft incorporates a general-purpose "Safe Mode" response algorithm that configures the spacecraft in a lower-power state that is safe and predictable, thereby facilitating diagnosis of more complex faults by a team of human experts on Earth.

Morgan, Paula↗

NASA NTRSDate not supplied

Path Planning: Differential Dynamic Programming and Model Predictive Path Integral Control on VTOL Aircraft

This paper explores two optimal control approaches, widely used in robotics, to establish their viability as real-time trajectory planners for vehicle configurations envisioned for the emerging aviation sector of Urban Air Mobility (UAM). Differential Dynamic Programming (DDP) enables planning over highly nonlinear dynamics using second-order approximations along a nominal trajectory, and displays quadratic convergence to a local solution. Model Predictive Path Integral (MPPI) is a stochastic sampling-based algorithm that can optimize for general cost criteria, including potentially highly nonlinear formulations, and supports parallel computation through the use of modern GPU hardware. In this work, DDP and MPPI were implemented using model predictive control (MPC), and the results indicate they are able to successfully transition the aircraft over different flight envelopes and generate trajectories unique to UAM vehicles.

Differential Dynamic Programming↗

NASA NTRSDate not supplied

Bayesian Model Selection for Reducing Bloat and Overfitting in Genetic Programming for Symbolic Regression

When performing symbolic regression using genetic programming, overfitting and bloat can negatively impact generalizability and interpretability of the resulting equations as well as increase computation times. A Bayesian fitness metric is introduced and its impact on bloat and overfitting during population evolution is studied and compared to common alternatives in the literature. The proposed approach was found to be more robust to noise and data sparsity in numerical experiments, guiding evolution to a level of complexity appropriate to the dataset. Further evolution of the population resulted not in overfitting or bloat, but rather in slight simplifications in model form. The ability to identify an equation of complexity appropriate to the scale of noise in the training data was also demonstrated. In general, the Bayesian model selection algorithm was shown to be an effective means of regularization which resulted in less bloat and overfitting when any amount of noise was present in the training data.

G F Bomarito↗

NASA NTRSDate not supplied

Bayesian Model Selection for Reducing Bloat and Overfitting in Genetic Programming for Symbolic Regression

Uncertainty quantification↗

DOE OSTI2023

On the Approximability of Random-Hypergraph MAX-3-XORSAT Problems with Quantum Algorithms

Constraint satisfaction problems are an important area of computer science. Many of these problems are in the complexity class NP which is exponentially hard for all known methods, both for worst cases and often typical. Fundamentally, the lack of any guided local minimum escape method ensures the hardness of both exact and approximate optimization classically, but the intuitive mechanism for approximation hardness in quantum algorithms based on Hamiltonian time evolution is poorly understood. We explore this question using the prototypically hard MAX-3-XORSAT problem class. We conclude that the mechanisms for quantum exact and approximation hardness are fundamentally distinct. We qualitatively identify why traditional methods such as quantum adiabatic optimization are not good approximation algorithms. We propose a new spectral folding optimization method that does not suffer from these issues and study it analytically and numerically. We consider random rank-3 hypergraphs including extremal planted solution instances, where the ground state satisfies an anomalously high fraction of constraints compared to truly random problems. We show that, if we define the energy to be $E = N_{unsat}-N_{sat}$, then spectrally folded quantum optimization will return states with energy $E \leq A E_{GS}$ (where $E_{GS}$ is the ground state energy) in polynomial time, where conservatively, $A \simeq 0.6$. We thoroughly benchmark variations of spectrally folded quantum optimization for random classically approximation-hard (planted solution) instances in simulation, and find performance consistent with this prediction. We do not claim that this approximation guarantee holds for all possible hypergraphs, though our algorithm's mechanism can likely generalize widely. These results suggest that quantum computers are more powerful for approximate optimization than had been previously assumed.

Kapit, Eliot↗

DOE OSTI2022

GSAS Tools

SAND2023-06684O GSAS Tools is a web application that manages user access to modeling and simulation tools and promotional material. This software, which is a spiking neural network (SNN) simulator, represents an SNN as a graph of stochastic differential equations and simulates the time-evolution of these equations. It has the capability of reading inputs from file and writing outputs to file, and generally supports experimentation, analysis, and algorithm development using SNNs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Noel, Todd↗

NASA NTRS1977

Integration-free interval doubling for Riccati equation solutions

Starting with certain identities obtained by Reid (1972) and Redheffer (1962) for general matrix Riccati equations (RE's), we give various algorithms for the case of constant coefficients. The algorithms are based on two ideas - first, relate the RE solution with general initial conditions to anchored RE solutions; and second, when the coefficients are constant, the anchored solutions have a basic shift-invariance property. These ideas are used to construct an integration-free, superlinearly convergent iterative solution to the algebraic RE. Preliminary numerical experiments show that our algorithms, arranged in square-root form, provide a method that is numerically stable and appears to be competitive with other methods of solving the algebraic RE.

Sidhu, G. S.↗