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At least 775 records · Page 43

Techniques for designing rotorcraft control systems

This report summarizes the work that was done on the project from 1 Apr. 1992 to 31 Mar. 1993. The main goal of this research is to develop a practical tool for rotorcraft control system design based on interactive optimization tools (CONSOL-OPTCAD) and classical rotorcraft design considerations (ADOCS). This approach enables the designer to combine engineering intuition and experience with parametric optimization. The combination should make it possible to produce a better design faster than would be possible using either pure optimization or pure intuition and experience. We emphasize that the goal of this project is not to develop an algorithm. It is to develop a tool. We want to keep the human designer in the design process to take advantage of his or her experience and creativity. The role of the computer is to perform the calculation necessary to improve and to display the performance of the nominal design. Briefly, during the first year we have connected CONSOL-OPTCAD, an existing software package for optimizing parameters with respect to multiple performance criteria, to a simplified nonlinear simulation of the UH-60 rotorcraft. We have also created mathematical approximations to the Mil-specs for rotorcraft handling qualities and input them into CONSOL-OPTCAD. Finally, we have developed the additional software necessary to use CONSOL-OPTCAD for the design of rotorcraft controllers.

Levine, William S.↗

The Effect of Approximating Some Molecular Integrals in Coupled-Cluster Calculations: Fundamental Frequencies and Rovibrational Spectroscopic Constants of Cyclopropenylidene

The singles and doubles coupled-cluster method that includes a perturbational estimate of connected triple excitations, denoted CCSD(T), has been used, in conjunction with approximate integral techniques, to compute highly accurate rovibrational spectroscopic constants of cyclopropenylidene, C3H2. The approximate integral technique was proposed in 1994 by Rendell and Lee in order to avoid disk storage and input/output bottlenecks, and today it will also significantly aid in the development of algorithms for distributed memory, massively parallel computer architectures. It is shown in this study that use of approximate integrals does not impact the accuracy of CCSD(T) calculations. In addition, the most accurate spectroscopic data yet for C3H2 is presented based on a CCSD(T)/cc-pVQZ quartic force field that is modified to include the effects of core-valence electron correlation. Cyclopropenylidene is of great astronomical and astrobiological interest because it is the smallest aromatic ringed compound to be positively identified in the interstellar medium, and is thus involved in the prebiotic processing of carbon and hydrogen. The singles and doubles coupled-cluster method that includes a perturbational estimate of

Lee, Timothy J.↗

Advanced Optical Diagnostics for Ice Crystal Cloud Measurements in the NASA Glenn Propulsion Systems Laboratory

A light extinction tomography technique has been developed to monitor ice water clouds upstream of a direct connected engine in the Propulsion Systems Laboratory (PSL) at NASA Glenn Research Center (GRC). The system consists of 60 laser diodes with sheet generating optics and 120 detectors mounted around a 36-inch diameter ring. The sources are pulsed sequentially while the detectors acquire line-of-sight extinction data for each laser pulse. Using computed tomography algorithms, the extinction data are analyzed to produce a plot of the relative water content in the measurement plane. To target the low-spatial-frequency nature of ice water clouds, unique tomography algorithms were developed using filtered back-projection methods and direct inversion methods that use Gaussian basis functions. With the availability of a priori knowledge of the mean droplet size and the total water content at some point in the measurement plane, the tomography system can provide near real-time in-situ quantitative full-field total water content data at a measurement plane approximately 5 feet upstream of the engine inlet. Results from ice crystal clouds in the PSL are presented. In addition to the optical tomography technique, laser sheet imaging has also been applied in the PSL to provide planar ice cloud uniformity and relative water content data during facility calibration before the tomography system was available and also as validation data for the tomography system. A comparison between the laser sheet system and light extinction tomography resulting data are also presented. Very good agreement of imaged intensity and water content is demonstrated for both techniques. Also, comparative studies between the two techniques show excellent agreement in calculation of bulk total water content averaged over the center of the pipe.

Bencic, Timothy J.↗

Highlights of Project Accomplishments (2000-2004): Redshift Dependence of the Interaction-Activity Connection

We completed this project by developing the new galaxy-galaxy collision simulation code that we originally proposed. We included star formation heuristically, along with gas recycling and energetic feedback into the interstellar medium of the galaxies. We ran several test simulations. And we finally validated the code by running models to emulate the double-ring galaxy AM 0644-741. Most of the exotic and unique features of this collisional ring galaxy were matched by our models, thereby validating our algorithm, which may now be used by us and by the community for additional dynamic studies of galaxies. A paper has been submitted to the Astrophysical Journal describing our algorithm and the results of the AM 0644-741 modeling.

Borne, Kirk D.↗

Resilient Hierarchical Networked Control Systems: Secure Controls for Critical Locations and at Edge

Integration of information and communication technology (ICT) offers new opportunities in improving the management and operation of critical infrastructures such as power systems as it allows connection of different sensors and control components via a communication network, leading to the so-called networked control systems (NCS). However, the use of open and pervasive ICT such as the Internet or wireless communication technologies comes at a price of making NCS vulnerable to cyber intrusions/attacks which may cause physical damage. Here, this chapter presents control algorithms to ensure resilient and safe operation of NCS under unknown cyberattacks. Specifically, a variant of dynamic watermarking strategies is presented by embedding encoding/decoding components of chaotic signals into the NCS for secure control for critical locations where the measurement/control signals are transmitted to/from the control center via a communication network. In addition, resilient cooperative control algorithms are discussed to ensure safe operation at edge of the NCS which consists of a large number of distributed controllable devices. Several numerical examples are provided to illustrate the proposed control strategies.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Ground facility for large space structures dynamics and control verification

NASA Marshall Space Flight Center has developed a facility in which closed loop control of Large Space Structures (LSS) can be demonstrated and verified. The main objective of the facility is to verify LSS control system techniques so that on-orbit performance can be unsured. The facility consists of an LSS test article or payload which is connected to a 3-axis angular pointing mount assembly that provides control torque commands. The angular pointing mount assembly is attached to a base excitation system which will simulate disturbances most likely to occur for Orbiter and DOD payloads. The control computer contains the calibration software, the reference systems, the alignment procedures, the telemetry software, and the control algorithms. The total system is suspended in such a fashion that the LSS test article has the characteristics common to all LSS.

Waites, Henry↗

Large space structures ground experiment checkout

NASA Marshall Space Flight Center has developed a facility in which closed loop control of Large Space Structures (LSS) can be demonstrated and verified. The main objective of the facility is to verify LSS control system techniques so that on-orbit performance can be ensured. The facility consists of an LSS test article or payload which is connected to a 3-axis angular pointing mount assembly that provides control torque commands. The angular pointing mount assembly is attached to a base excitation system which will simulate disturbances most likely to occur for Orbiter and DOD payloads. The control computer contains the calibration software, the reference systems, the alignment procedures, the telemetry software, and the control algorithms. The total system is suspended in such a fashion that the LSS test article has the characteristics common to all LSS.

Waites, Henry B.↗

Ground facility for Large Space Structures dynamics and control verification

NASA Marshall Space Flight Center has developed a facility in which closed loop control of Large Space Structures (LSS) can be demonstrated and verified. The main objective of the facility is to verify LSS control system techniques so that on-orbit performance can be ensured. The facility consists of an LSS test article or payload which is connected to a 3-axis angular pointing mount assembly that provides control torque commands. The angular pointing mount assembly is attached to a base excitation system which will simulate disturbances most likely to occur for Orbiter and DOD payloads. The control computer contains the calibration software, the reference systems, the alignment procedures, the telemetry software, and the control algorithms. The total system is suspended in such a fashion that the LSS test article has the characteristics common to all LSS.

Waites, Henry↗

Contributions of Spherical Harmonics to Magnetic and Gravitational Fields

Gravitational forces are of cardinal importance in the dynamics of spacecraft; magnetic attractions sometime play a significant role also, as was the case with the Long Duration Exposure Facility, and as is now true for the first segment of Space Station Freedom. Both satellites depend on gravitational moment and a device known as a magnetic damper to stabilize their orientation. Magnetic fields are mathematically similar to gravitational fields in one important respect: each can be regarded as a gradient of a potential function that, in turn, can be described as an infinite series of spherical harmonics. Consequently, the two fields can be computed, in part, with quantities that need only be evaluated once, resulting in a savings of time when both fields are needed. The objective of this material is to present magnetic field and gravitational force expressions, and point out the terms that belong to both this is accomplished in Section 1 and 2. Section 3 contains the deductive reasoning with which one obtains the expressions of interest. Finally, examples in Section 4 show these equations can be used to reproduce others that arise in connection with special cases such as the magnetic field produced by a tilted dipole, and gravitational force exerted by an oblate spheroid. The mathematics are discussed in the context of terrestrial fields; however, by substituting appropriate constants, the results can be made applicable to fields belonging to other celestial bodies. The expressions presented here share the characteristics of algorithms set forth for computing gravitational force. In particular, computation is performed speedily by means of recursion formulae, and the expressions do not suffer from the shortcoming of a singularity when evaluated at points that lie on the polar axis.

Roithmayr, Carlos M.↗

Image Segmentation Analysis for NASA Earth Science Applications

NASA collects large volumes of imagery data from satellite-based Earth remote sensing sensors. Nearly all of the computerized image analysis of this data is performed pixel-by-pixel, in which an algorithm is applied directly to individual image pixels. While this analysis approach is satisfactory in many cases, it is usually not fully effective in extracting the full information content from the high spatial resolution image data that s now becoming increasingly available from these sensors. The field of object-based image analysis (OBIA) has arisen in recent years to address the need to move beyond pixel-based analysis. The Recursive Hierarchical Segmentation (RHSEG) software developed by the author is being used to facilitate moving from pixel-based image analysis to OBIA. The key unique aspect of RHSEG is that it tightly intertwines region growing segmentation, which produces spatially connected region objects, with region object classification, which groups sets of region objects together into region classes. No other practical, operational image segmentation approach has this tight integration of region growing object finding with region classification This integration is made possible by the recursive, divide-and-conquer implementation utilized by RHSEG, in which the input image data is recursively subdivided until the image data sections are small enough to successfully mitigat the combinatorial explosion caused by the need to compute the dissimilarity between each pair of image pixels. RHSEG's tight integration of region growing object finding and region classification is what enables the high spatial fidelity of the image segmentations produced by RHSEG. This presentation will provide an overview of the RHSEG algorithm and describe how it is currently being used to support OBIA or Earth Science applications such as snow/ice mapping and finding archaeological sites from remotely sensed data.

Tilton, James C.↗

Automated algorithms to build active galactic nucleus classifiers

ABSTRACT We present a machine learning model to classify active galactic nuclei (AGNs) and galaxies (AGN-galaxy classifier) and a model to identify type 1 (optically unabsorbed) and type 2 (optically absorbed) AGN (type 1/2 classifier). We test tree-based algorithms, using training samples built from the X-ray Multi-Mirror Mission–Newton (XMM–Newton) catalogue and the Sloan Digital Sky Survey (SDSS), with labels derived from the SDSS survey. The performance was tested making use of simulations and of cross-validation techniques. With a set of features including spectroscopic redshifts and X-ray parameters connected to source properties (e.g. fluxes and extension), as well as features related to X-ray instrumental conditions, the precision and recall for AGN identification are 94 and 93 per cent, while the type 1/2 classifier has a precision of 74 per cent and a recall of 80 per cent for type 2 AGNs. The performance obtained with photometric redshifts is very similar to that achieved with spectroscopic redshifts in both test cases, while there is a decrease in performance when excluding redshifts. Our machine learning model trained on X-ray features can accurately identify AGN in extragalactic surveys. The type 1/2 classifier has a valuable performance for type 2 AGNs, but its ability to generalize without redshifts is hampered by the limited census of absorbed AGN at high redshift.

Falocco, S. (ORCID:0000000299841103)↗

Machine learning study of magnetism in uranium-based compounds

Actinide and lanthanide-based materials display exotic properties that originate from the presence of itinerant or localized f electrons and include unconventional superconductivity and magnetism, hidden order, and heavy-fermion behavior. Due to the strongly correlated nature of the 5f electrons, magnetic properties of these compounds depend sensitively on applied magnetic field and pressure, as well as on chemical doping. However, precise connection between the structure and magnetism in actinide-based materials is currently unclear. In this investigation, we established such structure-property links by assembling and mining two datasets that aggregate, respectively, the results of high-throughput density functional theory simulations and experimental measurements for the families of uranium- and neptunium-based binary compounds. Various regression algorithms were utilized to identify correlations among accessible attributes (features or descriptors) of the material systems and predict their cation magnetic moments and general forms of magnetic ordering. Descriptors representing compound structural parameters and cation f-subshell occupation numbers were identified as most important for accurate predictions. The best machine learning model developed employs the random forest regression algorithm. It can predict both spin and orbit moment size with root-mean-square error of 0.17 μ B and 0.19 μ B , respectively. Lastly, the random forest classification algorithm is used to predict the ordering (paramagnetic, ferromagnetic, and antiferromagnetic) of such systems with 76% accuracy.

36 MATERIALS SCIENCE↗

Two Methods for Efficient Solution of the Hitting-Set Problem

A paper addresses much of the same subject matter as that of Fast Algorithms for Model-Based Diagnosis (NPO-30582), which appears elsewhere in this issue of NASA Tech Briefs. However, in the paper, the emphasis is more on the hitting-set problem (also known as the transversal problem), which is well known among experts in combinatorics. The authors primary interest in the hitting-set problem lies in its connection to the diagnosis problem: it is a theorem of model-based diagnosis that in the set-theory representation of the components of a system, the minimal diagnoses of a system are the minimal hitting sets of the system. In the paper, the hitting-set problem (and, hence, the diagnosis problem) is translated from a combinatorial to a computational problem by mapping it onto the Boolean satisfiability and integer- programming problems. The paper goes on to describe developments nearly identical to those summarized in the cited companion NASA Tech Briefs article, including the utilization of Boolean-satisfiability and integer- programming techniques to reduce the computation time and/or memory needed to solve the hitting-set problem.

Vatan, Farrokh↗

Multi-Area Distribution System State Estimation Using Decentralized Physics-Aware Neural Networks

The development of active distribution grids requires more accurate and lower computational cost state estimation. In this paper, the authors investigate a decentralized learning-based distribution system state estimation (DSSE) approach for large distribution grids. The proposed approach decomposes the feeder-level DSSE into subarea-level estimation problems that can be solved independently. The proposed method is decentralized pruned physics-aware neural network (D-P2N2). The physical grid topology is used to parsimoniously design the connections between different hidden layers of the D-P2N2. Monte Carlo simulations based on one-year of load consumption data collected from smart meters for a three-phase distribution system power flow are developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares and state-of-the-art learning-based DSSE approaches. Numerical results show that the D-P2N2 outperforms the state-of-the-art methods in terms of estimation accuracy and computational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Empirical modeling for intelligent, real-time manufacture control

Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper.

Xu, Xiaoshu↗

The Latitudinal Excursion of Coronal Magnetic Field Lines in Response to Differential Rotation: MHD Simulations

Solar energetic particles, which are believed to originate from corotating interacting regions (CIRS) at low heliographic latitude, were observed by the Ulysses spacecraft even as it passed over the Sun's poles. One interpretation of this result is that high-latitude field lines intercepted by Ulysses connect to low-latitude CIRs at much larger heliocentric distances. The Fisk model explains the latitudinal excursion of magnetic field lines in the solar corona and heliosphere as the inevitable consequence of the interaction of a tilted dipole in a differentially rotating photosphere with rigidly rotating coronal holes. We use a time-dependent three-dimensional magnetohydrodynamic (MHD) algorithm to follow the evolution of a simple model of the solar corona in response to the differential rotation of the photospheric magnetic flux. We examine the changes of the coronal-hole boundaries, the redistribution of the line-of-sight magnetic field, and the precession of field lines in the corona. Our results confirm the basic idea of the Fisk model, that differential rotation leads to changes in the heliographic latitude of magnetic field lines. However, the latitudinal excursion of magnetic field lines in this simple "tilted dipole" model is too small to explain the Ulysses observations. Although coronal holes in our model rotate more rigidly than do photospheric features (in general agreement with observations), they do not rotate strictly rigidly as assumed by Fisk. This basic difference between our model and Fisk's will be explored in the future by considering more realistic magnetic flux distributions, as observed during Ulysses polar excursions.

Lionello, Roberto↗

Universal image representation based on a multimodal graph

A system for classifying a target image with segments having attributes is provided. The system generates a graph for the target image that includes vertices representing segments of the image and edges representing relationships between the connected vertices. For each vertex, the system generates a subgraph that includes the vertex as a home vertex and neighboring vertices representing segments of the target image within a neighborhood of the segment represented by the home vertex. The system applies an autoencoder to each subgraph to generate latent variables to represent the subgraph. The system applies a machine learning algorithm to a feature vector comprising a universal image representation of the target image that is derived from the generated latent variables of the subgraphs to generate a classification for the target image.

Bremer, Peer-Timo↗

Universal image representation based on a multimodal graph

A system for classifying a target image with segments having attributes is provided. The system generates a graph for the target image that includes vertices representing segments of the image and edges representing relationships between the connected vertices. For each vertex, the system generates a subgraph that includes the vertex as a home vertex and neighboring vertices representing segments of the target image within a neighborhood of the segment represented by the home vertex. The system applies an autoencoder to each subgraph to generate latent variables to represent the subgraph. The system applies a machine learning algorithm to a feature vector comprising a universal image representation of the target image that is derived from the generated latent variables of the subgraphs to generate a classification for the target image.

Bremer, Peer-Timo↗