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At least 199 records · Page 11

Infrasound direction of arrival determination using a balloon-borne aeroseismometer

Free-floating balloons are an emerging platform for infrasound recording, but they cannot host arrays sufficiently wide for multi-sensor acoustic direction finding techniques. Because infrasound waves are longitudinal, the balloon motion in response to acoustic loading can be used to determine the signal azimuth. This technique, called “aeroseismometry,” permits sparse balloon-borne networks to geolocate acoustic sources. This is demonstrated by using an aeroseismometer on a stratospheric balloon to measure the direction of arrival of acoustic waves from successive ground chemical explosions. A geolocation algorithm adapted from hydroacoustics is then used to calculate the location of the explosions.

47 OTHER INSTRUMENTATION↗

Multiobjective Hyperparameter Optimization for Deep Learning Interatomic Potential Training Using NSGA-II

Deep neural network (DNN) potentials are an emerging tool for simulation of dynamical atomistic systems, with the promise of quantum mechanical accuracy at speedups of 10000$\times$. As with other DNN methods, hyperparameters used during training can make a substantial difference in model accuracy, and optimal settings vary with dataset. To enable rapid tuning of hyperparameters for DNN potential training, we developed a scalable multiobjective optimization evolutionary algorithm for supercomputers and tested it on the Summit system at the Oak Ridge Leadership Computing Facility (OLCF). The multiobjective approach is required due to the coupling of two learned values defining the potential: the energy and force. Using a large-scale implementation of the NSGA-II algorithm adapted for training DNN potentials, we discovered several optimal multiobjective combinations, including best choices of activation functions, learning rate scaling scheme, and pairing of the two radial cutoffs used in the three dimensional descriptor function.

Coletti, Mark↗

Efficient quadrature rules for finite element discretizations of nonlocal equations

In this paper we design efficient quadrature rules for finite element discretizations of nonlocal diffusion problems with compactly supported kernel functions. Two of the main challenges in nonlocal modeling and simulations are the prohibitive computational cost and the nontrivial implementation of discretization schemes, especially in three-dimensional settings. In this work we circumvent both challenges by introducing a parametrized mollifying function that improves the regularity of the integrand, utilizing an adaptive integration technique, and exploiting parallelization. We first showthat the “mollified” solution converges to the exact one as the mollifying parameter vanishes, then we illustrate the consistency and accuracy of the proposed method on several two- and three-dimensional test cases. Furthermore, we demonstrate the good scaling properties of the parallel implementation of the adaptive algorithm and we compare the proposed method with recently developed techniques for efficient finite element assembly.

97 MATHEMATICS AND COMPUTING↗

Contribution to methods for calculating the flow about thin lifting wings at transonic speeds: Analytic expressions for the far field

The problem of determining the small-disturbance flow about two-dimensional airfoils at transonic speeds has been successfully treated by the process of matching a numerical solution of the near field to analytic expressions for the far field. The three-dimensional problem, it would appear, can be treated in a similar way with the aid of algorithms adapted to high-speed and high-capacity computers. The far-field potential for both lifting and nonlifting three-dimensional wings at transonic speeds is developed herein for a subsonic free stream. This potential could be used for a three-dimensional-wing computation similar to the computation made for the two-dimensional wing.

Klunker, E. B.↗

A reduced adaptive observer for multivariable systems

An adaptive observer for multivariable systems is presented for which the dynamic order of the observer is reduced, subject to mild restrictions. The observer structure depends directly upon the multivariable structure of the system rather than a transformation to a single-output system. The number of adaptive gains is at most the sum of the order of the system and the number of input parameters being adapted. Moreover, for the relatively frequent specific cases for which the number of required adaptive gains is less than the sum of system order and input parameters, the number of these gains is easily determined by inspection of the system structure. This adaptive observer possesses all the properties ascribed to the single-input single-output adpative observer. Like the other adaptive observers some restriction is required of the allowable system command input to guarantee convergence of the adaptive algorithm, but the restriction is more lenient than that required by the full-order multivariable observer. This reduced observer is not restricted to cycle systems.

Carroll, R. L.↗

A reduced adaptive observer for multivariable systems

An adaptive observer for multivariable systems of order n having p output measurements is developed. The adaptive observer allows both the generation of the state of the system and - at least - the partial identification of the unknown parameters of the system. The order of this adaptive observer is n - p plus 1. The adaptive algorithm, based upon Liapunov synthesis, may be implemented in real time without the use of derivative operators. Eigenvalues of the observer may be arbitrarily or almost arbitrarily located. With some mild restriction upon the structure of the multivariable system, and upon the command system input, both generation of state and identification of parameters is guaranteed globally.

Carroll, R. L.↗

Digital adaptive controllers for VTOL vehicles. Volume 2: Software documentation

The VTOL approach and landing test (VALT) adaptive software is documented. Two self-adaptive algorithms, one based on an implicit model reference design and the other on an explicit parameter estimation technique were evaluated. The organization of the software, user options, and a nominal set of input data are presented along with a flow chart and program listing of each algorithm.

Hartmann, G. L.↗

On the solution of elastic-plastic static and dynamic postbuckling collapse of general structure

Many investigations have considered structural collapse from strictly the transient point of view. While such an approach is ideally correct, certain difficulties have to be overcome in its implementation. The present investigation is concerned with the development of self-adaptive algorithms which make it possible to conduct the analysis of both static elastic and elastic-plastic postbuckling, as well as static loading to the onset of buckling followed by subsequent dynamic postbuckling. The approach employed to solve the static portion of loading is to extend the constrained Incremental Newton-Raphson (INR) algorithm by incorporating elastic-plastic constitutive characterizations. Large deformation moderate strain theory is adopted to establish the overall strategy. Attention is given to governing field equations, aspects of algorithmic development, and numerical experiments conducted to illustrate the efficiency and stability of the developed schemes.

Padovan, J.↗

Remote sensing /Nimbus-7 CZCS/ analysis of phytoplankton distribution in coastal waters of the Gulf of Lions /northwestern Mediterranean/

The distribution of phytoplankton in the northwestern Mediterranean was studied using the experimental satellite Nimbus 7, which is equipped with a coastal zone color scanner (CZCS). The most characteristic boundaries of this biomass and its variations throughout the year of 1979 were also investigated by treating the CZCS data, collected through different channels with defined wavelengths, with a computer. Using specially adapted algorithms, characteristic features such as mesoscale cyclonic eddy, out-flow of freshwater from the Rhone river, and coastal upwelling were revealed. It is confirmed that the biomass of phytoplankton is a good indicator for the mesoscale distribution of water masses, and that the remote sensing in the visible spectrum can permit the study of frontal boundaries in the sea.

Caraux, D.↗

Adaptive control: Myths and realities

It was found that all currently existing globally stable adaptive algorithms have three basic properties in common: positive realness of the error equation, square-integrability of the parameter adjustment law and, need for sufficient excitation for asymptotic parameter convergence. Of the three, the first property is of primary importance since it satisfies a sufficient condition for stabillity of the overall system, which is a baseline design objective. The second property has been instrumental in the proof of asymptotic error convergence to zero, while the third addresses the issue of parameter convergence. Positive-real error dynamics can be generated only if the relative degree (excess of poles over zeroes) of the process to be controlled is known exactly; this, in turn, implies perfect modeling. This and other assumptions, such as absence of nonminimum phase plant zeros on which the mathematical arguments are based, do not necessarily reflect properties of real systems. As a result, it is natural to inquire what happens to the designs under less than ideal assumptions. The issues arising from violation of the exact modeling assumption which is extremely restrictive in practice and impacts the most important system property, stability, are discussed.

Athans, M.↗

Radar data smoothing filter study

The accuracy of the current Wallops Flight Facility (WFF) data smoothing techniques for a variety of radars and payloads is examined. Alternative data reduction techniques are given and recommendations are made for improving radar data processing at WFF. A data adaptive algorithm, based on Kalman filtering and smoothing techniques, is also developed for estimating payload trajectories above the atmosphere from noisy time varying radar data. This algorithm is tested and verified using radar tracking data from WFF.

White, J. V.↗

NTSC composite video at 1.6 bits/pel

An adaptive algorithm for intraframe compression of NTSC composite color video signal is described. With an average of 80 percent compression (1.6 bits/pixel) and a bit error rate of 0.0001, excellent broadcast quality pictures were obtained. This is confirmed by a subjective evaluation of processed pictures by five viewers. The algorithm and the results of the subjective evaluation are given in this paper.

Kwatra, S. C.↗

Space station dynamic modeling, disturbance accommodation, and adaptive control

Dynamic models for two space station configurations were derived. Space shuttle docking disturbances and their effects on the station and solar panels are quantified. It is shown that hard shuttle docking can cause solar panel buckling. Soft docking and berthing can substantially reduce structural loads at the expense of large shuttle and station attitude excursions. It is found predocking shuttle momentum reduction is necessary to achieve safe and routine operations. A direct model reference adaptive control is synthesized and evaluated for the station model parameter errors and plant dynamics truncations. The rigid body and the flexible modes are treated. It is shown that convergence of the adaptive algorithm can be achieved in 100 seconds with reasonable performance even during shuttle hard docking operations in which station mass and inertia are instantaneously changed by more than 100%.

Wang, S. J.↗

Parallel multilevel adaptive methods

The progress of a project for the design and analysis of a multilevel adaptive algorithm (AFAC/HM/) targeted for the Navier Stokes Computer is discussed. The results of initial timing tests of AFAC, coupled with multigrid and an efficient load balancer, on a 16-node Intel iPSC/2 hypercube are included. The results of timing tests are presented.

Dowell, B.↗

Experiments on structural control of sound transmitted through an elastic plate

Active control of sound transmission through an elastic plate has been experimentally studied. The control was applied directly to the plate by point force vibration inputs, and the error information and performance was measured in the radiated acoustic field by discrete microphones. Test cases were studied in which the error sensors were accelerometers mounted on the plate. A time-domain least-mean-squares adaptive algorithm was used as the basis of the control system design. The results showed an impressive increase in plate transmission loss over a wide range of frequencies with a maximum of two control shakers. The advantages of using error information derived from the radiated acoustic field rather than structural response is demonstrated. The mechanisms behind the efficiency of this control approach are discussed.

Fuller, C. R.↗

Intensity dependent spread processor and workstation

The Intensity Dependent Spread (IDS) is an adaptive algorithm which is modified according to the local intensity in the scene. (This results in a nonlinear process which cannot take advantage of rather nice linear transform methods.) The computation is similar to a neural net whereby intensity information is moving from each input pixel to a set of surrounding output pixels in a manner described by Cornsweet and Yellott. A prototype of a very large scale integration IDS processor is being developed and implemented in a workstation environment. The workstation consists of a SUN 3/260 and a DATACUBE pipeline processor. The IDS prototype is a board set which operates in the DATA CUBE processor. The SUN 3/260 performs control, background processing, IDS simulation and image display functions.

Westrom, George↗

Discrete-time adaptive control of robot manipulators

A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that asymptotic trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation.

Tarokh, M.↗

A discrete-time adaptive control scheme for robot manipulators

A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.

Tarokh, M.↗