General Electric Company

Meng-Ling Hsiao

Weiping Wang

Michael Evans Graham

Michael Kent Cueman

Emily Yixie Shu

Charles Richard Evans

Thomas Huei Hwang

Richard Alan Ridilla

Kwok C Tam

Yves Lucien Trousset

Wayne J Eberhard

Edward A Hudacko

A method for detecting misalignment of initially-aligned fiber filaments in a composite. An optical fiber is placed among the fiber filaments in the composite, light is directed into the optical fiber, the intensity of the light in the optical fiber is measured during subsequent composite processing, and attenuation in such light intensity is ascertained which indicates such misalignment (e.g., wrinkling, bending, buckling, porosity, delamination and the like) is being detected during such processing. In another preferred method, before-processing and after-processing x-ray images are taken of an x-ray-attenuating fiber which has been placed among x-ray-transparent fiber filaments in a composite.

Method for detecting fiber misalignment in composite manufacturing

Detecting and minimizing fiber misalignment in a composite during

According to the present invention, a 3D connectivity-conserved grain-structured processing architecture uses connectable massively parallel processors. A 3D grain-structured processing architecture is provided. The 3D links of the grain-structured processing architecture provide direct local communication as well as global communication for voxel processing and analysis tasks. A novel transport naming scheme which is scalable in any three-dimension direction and the local/global communication protocol are disclosed. The 3D volumetric data set is first divided into a set of voxel sub-cubes. Each voxel subcube is processed by a processor element of the grain-structured processing architecture. Data discontinuity is produced after performing local operations in a massively parallel processors environment and requires replacing the resulted voxel data set in the overlap region for each voxel sub-cube. An inter-processor communication procedure for overcoming this problem in the 3D connected grain-structured processors architecture is also disclosed.

Grain structured processing architecture device and a method for

The present invention discloses a method and system for generating Radon derivative data in a cone beam computerized tomography implementation. Radon derivative data is computed by using a plurality of processors that partition the Radon space among the processors in a manner wherein the totality of the support of the Radon space handled by each processor is approximately equal. More specifically, each processor handles a number of vertical planes in the Radon space which are equally spaced within 180.degree. in the .phi..sub.k orientation. This procedure enables the plurality of processor to equalize the workload in computing the Radon derivative data and to perform the computations in a timely and efficient manner.

Method and system for efficiently generating radon derivative data in a

Cube-like processor array architecture

A parallel processing architecture and method, based on the 3D Algebra Reconstruction Technique (ART), for iteratively reconstructing from cone beam projection data a 3D voxel data set V representing an image of an object. The cone beam projection data is acquired by employing a cone beam x-ray source and a two-dimensional array detector to scan the object along a source scanning trajectory to obtain, at each of a plurality of discrete source positions .theta..sub.i on the source scanning trajectory, a 2D measured cone beam pixel data set P.sub.i. The 3D voxel data set V is subdivided into or organized as a plurality m of independent voxel subcubes V.sup.0 through V.sup.m-1 each containing a plurality of voxels. As a result of the subdivision of the 3D voxel data set V into voxel subcubes, the 2D measured cone beam pixel data set P.sub.i (measured projection data array) is correspondingly subdivided for each source position .theta..sub.i into projection data subsets, with overlapping regions between one or more adjacent projection data subsets corresponding to adjacent voxel subcubes. Each voxel subcube and its corresponding projection data strip or subset is processed in parallel with other pairs of voxel subcubes and corresponding projection data strips or subsets, without interference. A bi-level parallel-processor architecture is employed for iterative reproject and merge, and split and backproject operations.

Parallel processing method and apparatus based on the algebra

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Schenectady, NY, United States of America

Meng-Ling Hsiao