A multi-scale multi-frequency deconvolution algorithm for synthesis imaging in radio interferometry

Aims : We describe MS-MFS, a multi-scale multi-frequency deconvolution algorithm for wide-band synthesis-imaging, and present imaging results that illustrate the capabilities of the algorithm and the conditions under which it is feasible and gives accurate results. Methods : The MS-MFS algorithm models the wide-band sky-brightness distribution as a linear combination of spatial and spectral basis functions, and performs image-reconstruction by combining a linear-least-squares approach with iterative $\chi^2$ minimization. This method extends and combines the ideas used in the MS-CLEAN and MF-CLEAN algorithms for multi-scale and multi-frequency deconvolution respectively, and can be used in conjunction with existing wide-field imaging algorithms. We also discuss a simpler hybrid of spectral-line and continuum imaging methods and point out situations where it may suffice. Results : We show via simulations and application to multi-frequency VLA data and wideband EVLA data, that it is possible to reconstruct both spatial and spectral structure of compact and extended emission at the continuum sensitivity level and at the angular resolution allowed by the highest sampled frequency.Comment: 17 pages, 11 figure

The application of ANFIS prediction models for thermal error compensation on CNC machine tools

Thermal errors can have significant effects on CNC machine tool accuracy. The errors come from thermal deformations of the machine elements caused by heat sources within the machine structure or from ambient temperature change. The effect of temperature can be reduced by error avoidance or numerical compensation. The performance of a thermal error compensation system essentially depends upon the accuracy and robustness of the thermal error model and its input measurements. This paper first reviews different methods of designing thermal error models, before concentrating on employing an adaptive neuro fuzzy inference system (ANFIS) to design two thermal prediction models: ANFIS by dividing the data space into rectangular sub-spaces (ANFIS-Grid model) and ANFIS by using the fuzzy c-means clustering method (ANFIS-FCM model). Grey system theory is used to obtain the influence ranking of all possible temperature sensors on the thermal response of the machine structure. All the influence weightings of the thermal sensors are clustered into groups using the fuzzy c-means (FCM) clustering method, the groups then being further reduced by correlation analysis. A study of a small CNC milling machine is used to provide training data for the proposed models and then to provide independent testing data sets. The results of the study show that the ANFIS-FCM model is superior in terms of the accuracy of its predictive ability with the benefit of fewer rules. The residual value of the proposed model is smaller than ±4 μm. This combined methodology can provide improved accuracy and robustness of a thermal error compensation system

Astrometric Microlensing with the GAIA satellite

GAIA is the ``super-Hipparcos'' survey satellite selected as a Cornerstone 6 mission by the European Space Agency. GAIA can measure microlensing by the small excursions of the light centroid that occur during events. The all-sky source-averaged astrometric microlensing optical depth is about 10^{-5}. Some 25000 sources will have a significant variation of the centroid shift, together with a closest approach, during the lifetime of the mission. A covariance analysis is used to study the propagation of errors and the estimation of parameters from realistic sampling of the GAIA datastream of transits in the along-scan direction during microlensing events. Monte Carlo simulations are used to study the 2500 events for which the mass can be recovered with an error of less than 50 per cent. These high quality events are dominated by disk lenses within a few tens of parsecs and source stars within a few hundred parsecs. We show that the local mass function can be recovered from the high quality sample to good accuracy. GAIA is the first instrument with the capabilities of measuring the mass locally in very faint objects like black holes and very cool white and brown dwarfs. For only 5 per cent of all astrometric events will GAIA record even one photometric datapoint. There is a need for a dedicated telescope that densely samples the Galactic Centre and spiral arms, as this can improve the accuracy of parameter estimation by a factor of about 10.Comment: 18 pages, 18 figures, MNRAS, in pres

Radiation sensitive area detection device and method

A radiation sensitive area detection device for use in conjunction with an X ray, ultraviolet or other radiation source is provided which comprises a phosphor containing film which releases a stored diffraction pattern image in response to incoming light or other electromagnetic wave. A light source such as a helium-neon laser, an optical fiber capable of directing light from the laser source onto the phosphor film and also capable of channelling the fluoresced light from the phosphor film to an integrating sphere which directs the light to a signal processing means including a light receiving means such as a photomultiplier tube. The signal processing means allows translation of the fluoresced light in order to detect the original pattern caused by the diffraction of the radiation by the original sample. The optical fiber is retained directly in front of the phosphor screen by a thin metal holder which moves up and down across the phosphor screen and which features a replaceable pinhole which allows easy adjustment of the resolution of the light projected onto the phosphor film. The device produces near real time images with high spatial resolution and without the distortion that accompanies prior art devices employing photomultiplier tubes. A method is also provided for carrying out radiation area detection using the device of the invention

Combined numerical-experimental framework for strain based design and flaw assessment of girth welds

An increasing number of transmission pipelines have to be installed and operated in harsh conditions, due to the diminishing reserves of exploited fossil fuel sources. Under certain environment related circumstances, longitudinal plastic strains are imposed. When tensile, these may induce failure in girth welds in conjunction with the inevitable presence of weld defects. A large number of factors related to environment, material, geometry and operating conditions influence the tensile strain capacity and, hence, the acceptability of girth weld flaws. Therefore, a project specific development of guidelines in this strain based context is recommended. This paper provides systematic frameworks on (a) how to design pipelines under strain based conditions, and (b) how to assess girth weld flaws that were detected using non destructive testing. Attention is given to several technical and economical aspects related to the selection and qualification of pipe and weld metals, and to the evaluation of flaw acceptability. Both frameworks comprise a combined experimental-numerical approach, collecting project development reports from literature with research carried out at Soete Laboratory. Concretely, four in-house realizations are adopted: the UGent equation for strain capacity, the curved wide plate tension test, the UGent stress-strain equation and a finite element model of full scale pressurized pipe tension testing. The proposed frameworks aim to facilitate in performing thorough and economically justifiable strain based design and assessment processes

Detection of holes in an elastic body based on eigenvalues and traces of eigenmodes

We consider the numerical solution of an inverse problem of finding the shape and location of holes in an elastic body. The problem is solved by minimizing a functional depending on the eigenvalues and traces of corresponding eigenmodes. We use the adjoint method to calculate the shape derivative of this functional. The optimization is performed by BFGS, using a genetic algorithm as a preprocessor and the Method of Fundamental Solutions as a solver for the direct problem. We address several numerical simulations that illustrate the good performance of the method.info:eu-repo/semantics/publishedVersio