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1.
A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.  相似文献   
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ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.  相似文献   
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1 INTRODUCTION Blazars, including BL Lac objects, highly polarized and optically violently variable quasars,and flat-spectrum radio quasars (FSRQs), are characterized by highly variable non-thermalemission which dominates their characteristics from radio to y-ray bands. The mechanismbelieved to be responsible for their broadband emission is synchrotron radiation followed by in-verse Compton (IC) scattering at higher energies (e.g. Blandford & Konigl 1979). Relativisticbeaming of a jet…  相似文献   
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In a previous paper, it was suggested that contamination of the nuclear luminosity by the host galaxy plays an important role in determining the parameters of the standard a disk of AGNs. Using the nuclear absolute B band magnitude instead of the total absolute B band magnitude, we have recalculated the central black hole masses, accretion rates and disk inclinations for 20 Seyfert 1 galaxies and 17 Palomar-Green (PG) quasars. It is found that a small value of a is needed for the Seyfert 1 galaxies than for the PG quasars. This difference in a possibly leads to the different properties of Seyfert 1 galaxies and quasars. Furthermore, we find most of the objects in this sample are not accreting at super-Eddington rates if we adopt the nuclear optical luminosity in our calculation.  相似文献   
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Cygnus A     
Cygnus A was the first hyper-active galaxy discovered, and it remains by far the closest of the ultra-luminous radio galaxies. As such, Cygnus A has played a fundamental role in the study of virtually all aspects of extreme activity in galaxies. We present a review of jet theory for powering the double-lobed radio emitting structures in powerful radio galaxies, followed by a review of observations of Cygnus A in the radio, optical, and X-ray relevant to testing various aspects of jet theory. Issues addressed include: jet structure from pc- to kpc-scales, jet stability, confinement, composition, and velocity, the double shock structure for the jet terminus and the origin of multiple radio hotspots, the nature of the filamentary structure in the radio lobes, and the hydrodynamic evolution of the radio lobes within a dense cluster atmosphere, including an analysis of pressure balance between the various gaseous components. Also discussed are relativistic particle acceleration and loss mechanisms in Cygnus A, as well as magnetic field strengths and geometries both within the radio source, and in the intracluster medium. We subsequently review the classification, cluster membership, and the emission components of the Cygnus A galaxy. The origin of the activity is discussed. Concentrating on the nuclear regions of the galaxy, we review the evidence for an obscured QSO, also given the constraints on the orientation of the radio source axis with respect to the sky plane. We present an overview of models of central engines in AGN and observations of Cygnus A which may be relevant to testing such models. We conclude with a brief section concerning the question of whether Cygnus A is representative of powerful high redshift radio galaxies. Received October 10, 1995  相似文献   
9.
We present subarcsec angular resolution observations of the neutral gas in the nearby starburst galaxy NGC 520. The central kpc region of NGC 520 contains an area of significantly enhanced star formation. The radio continuum structure of this region resolves into ∼10 continuum components. By comparing the flux densities of the brightest of these components at 1.4 GHz with published 15-GHz data we infer that these components detected at 1.4 and 1.6 GHz are related to the starburst and are most likely to be collections of several supernova remnants within the beam. None of these components is consistent with emission from an active galactic nuclei. Both neutral hydrogen (H  i ) and hydroxyl (OH) absorption lines are observed against the continuum emission, along with a weak OH maser feature probably related to the star formation activity in this galaxy. Strong H  i absorption  ( N H∼ 1022 atoms cm−2)  traces a velocity gradient of 0.5 km s−1 pc−1 across the central kpc of NGC 520. The H  i absorption velocity structure is consistent with the velocity gradients observed in both the OH absorption and in CO emission observations. The neutral gas velocity structure observed within the central kpc of NGC 520 is attributed to a kpc-scale ring or disc. It is also noted that the velocity gradients observed for these neutral gas components appear to differ with the velocity gradients observed from optical ionized emission lines. This apparent disagreement is discussed and attributed to the extinction of the optical emission from the actual centre of this source hence implying that optical ionized emission lines are only detected from regions with significantly different radii to those sampled by the observations presented here.  相似文献   
10.
We use the observed polarization properties of a sample of 26 powerful radio galaxies and radio-loud quasars to constrain the conditions in the Faraday screens local to the sources. We adopt the cosmological redshift, low-frequency radio luminosity and physical size of the large-scale radio structures as our 'fundamental' parameters. We find no correlation of the radio spectral index with any of the fundamental parameters. The observed rotation measure is also independent of these parameters, suggesting that most of the Faraday rotation occurs in the Galactic foreground. The difference between the rotation measures of the two lobes of an individual source, as well as the dispersion of the rotation measure, shows significant correlations with the source redshift, but not with the radio luminosity or source size. This is evidence that the small-scale structure observed in the rotation measure is caused by a Faraday screen local to the sources. The observed asymmetries between the lobes of our sources show no significant trends with each other or other source properties. Finally, we show that the commonly used model for the depolarization of synchrotron radio emission by foreground Faraday screens is inconsistent with our observations. We apply alternative models to our data and show that they require a strong increase of the dispersion of the rotation measure inside the Faraday screens with cosmological redshift. Correcting our observations with these models for redshift effects, we find a strong correlation of the depolarization measure with redshift and a significantly weaker correlation with radio luminosity. We do not find any (anti-)correlation of depolarization measure with source size. All our results are consistent with a decrease in the order of the magnetic field structure of the Faraday screen local to the sources for increasing cosmological redshift.  相似文献   
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