24 resultados para Post processing


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The modern CFD process consists of mesh generation, flow solving and post-processing integrated into an automated workflow. During the last several years we have developed and published research aimed at producing a meshing and geometry editing system, implemented in an end-to-end parallel, scalable manner and capable of automatic handling of large scale, real world applications. The particular focus of this paper is the associated unstructured mesh RANS flow solver and the porting of it to GPU architectures. After briefly describing the solver itself, the special issues associated with porting codes using unstructured data structures are discussed - followed by some application examples. Copyright © 2011 by W.N. Dawes.

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The performance of a transonic fan operating within nonuniform inlet flow remains a key concern for the design and operability of a turbofan engine. This paper applies computational methods to improve the understanding of the interaction between a transonic fan and an inlet total pressure distortion. The test case studied is the NASA rotor 67 stage operating with a total pressure distortion covering a 120-deg sector of the inlet flow field. Full-annulus, unsteady, three-dimensional CFD has been used to simulate the test rig installation and the full fan assembly operating with inlet distortion. Novel post-processing methods have been applied to extract the fan performance and features of the interaction between the fan and the nonuniform inflow. The results of the unsteady computations agree well with the measurement data. The local operating condition of the fan at different positions around the annulus has been tracked and analyzed, and this is shown to be highly dependent on the swirl and mass flow redistribution that the rotor induces ahead of it due to the incoming distortion. The upstream flow effects lead to a variation in work input that determines the distortion pattern seen downstream of the fan stage. In addition, the unsteady computations also reveal more complex flow features downstream of the fan stage, which arise due to the three dimensionality of the flow and unsteadiness. © 2012 American Society of Mechanical Engineers.

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This work addresses the problem of deriving F0 from distanttalking speech signals acquired by a microphone network. The method here proposed exploits the redundancy across the channels by jointly processing the different signals. To this purpose, a multi-microphone periodicity function is derived from the magnitude spectrum of all the channels. This function allows to estimate F0 reliably, even under reverberant conditions, without the need of any post-processing or smoothing technique. Experiments, conducted on real data, showed that the proposed frequency-domain algorithm is more suitable than other time-domain based ones.

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The commercial far-range (>10 m) spatial data collection methods for acquiring infrastructure’s geometric data are not completely automated because of the necessary manual pre- and/or post-processing work. The required amount of human intervention and, in some cases, the high equipment costs associated with these methods impede their adoption by the majority of infrastructure mapping activities. This paper presents an automated stereo vision-based method, as an alternative and inexpensive solution, to producing a sparse Euclidean 3D point cloud of an infrastructure scene utilizing two video streams captured by a set of two calibrated cameras. In this process SURF features are automatically detected and matched between each pair of stereo video frames. 3D coordinates of the matched feature points are then calculated via triangulation. The detected SURF features in two successive video frames are automatically matched and the RANSAC algorithm is used to discard mismatches. The quaternion motion estimation method is then used along with bundle adjustment optimization to register successive point clouds. The method was tested on a database of infrastructure stereo video streams. The validity and statistical significance of the results were evaluated by comparing the spatial distance of randomly selected feature points with their corresponding tape measurements.

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The commercial far-range (>10m) infrastructure spatial data collection methods are not completely automated. They need significant amount of manual post-processing work and in some cases, the equipment costs are significant. This paper presents a method that is the first step of a stereo videogrammetric framework and holds the promise to address these issues. Under this method, video streams are initially collected from a calibrated set of two video cameras. For each pair of simultaneous video frames, visual feature points are detected and their spatial coordinates are then computed. The result, in the form of a sparse 3D point cloud, is the basis for the next steps in the framework (i.e., camera motion estimation and dense 3D reconstruction). A set of data, collected from an ongoing infrastructure project, is used to show the merits of the method. Comparison with existing tools is also shown, to indicate the performance differences of the proposed method in the level of automation and the accuracy of results.

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Understanding and controlling the hierarchical self-assembly of carbon nanotubes (CNTs) is vital for designing materials such as transparent conductors, chemical sensors, high-performance composites, and microelectronic interconnects. In particular, many applications require high-density CNT assemblies that cannot currently be made directly by low-density CNT growth, and therefore require post-processing by methods such as elastocapillary densification. We characterize the hierarchical structure of pristine and densified vertically aligned multi-wall CNT forests, by combining small-angle and ultra-small-angle x-ray scattering (USAXS) techniques. This enables the nondestructive measurement of both the individual CNT diameter and CNT bundle diameter within CNT forests, which are otherwise quantified only by delicate and often destructive microscopy techniques. Our measurements show that multi-wall CNT forests grown by chemical vapor deposition consist of isolated and bundled CNTs, with an average bundle diameter of 16 nm. After capillary densification of the CNT forest, USAXS reveals bundles with a diameter 4 m, in addition to the small bundles observed in the as-grown forests. Combining these characterization methods with new CNT processing methods could enable the engineering of macro-scale CNT assemblies that exhibit significantly improved bulk properties. © 2011 American Institute of Physics.

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Plants control their flowering time in order to ensure that they reproduce under favourable conditions. The components involved in this complex process have been identified using a molecular genetic approach in Arabidopsis and classified into genetically separable pathways. The autonomous pathway controls the level of mRNA encoding a floral repressor, FLC, and comprises three RNA-binding proteins, FCA, FPA and FLK. FCA interacts with the 3'-end RNA-processing factor FY to autoregulate its own expression post-transcriptionally and to control FLC. Other components of the autonomous pathway, FVE and FLD, regulate FLC epigenetically. This combination of epigenetic and post-transcriptional control gives precision to the control of FLC expression and flowering time.

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Small RNAs have several important biological functions. MicroRNAs (miRNAs) and trans-acting small interfering RNAs (tasiRNAs) regulate mRNA stability and translation, and siRNAs cause post-transcriptional gene silencing of transposons, viruses and transgenes and are important in both the establishment and maintenance of cytosine DNA methylation. Here, we study the role of the four Arabidopsis thaliana DICER-LIKE genes (DCL1-DCL4) in these processes. Sequencing of small RNAs from a dcl2 dcl3 dcl4 triple mutant showed markedly reduced tasiRNA and siRNA production and indicated that DCL1, in addition to its role as the major enzyme for processing miRNAs, has a previously unknown role in the production of small RNAs from endogenous inverted repeats. DCL2, DCL3 and DCL4 showed functional redundancy in siRNA and tasiRNA production and in the establishment and maintenance of DNA methylation. Our studies also suggest that asymmetric DNA methylation can be maintained by pathways that do not require siRNAs.

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The current procedures in post-earthquake safety and structural assessment are performed manually by a skilled triage team of structural engineers/certified inspectors. These procedures, and particularly the physical measurement of the damage properties, are time-consuming and qualitative in nature. This paper proposes a novel method that automatically detects spalled regions on the surface of reinforced concrete columns and measures their properties in image data. Spalling has been accepted as an important indicator of significant damage to structural elements during an earthquake. According to this method, the region of spalling is first isolated by way of a local entropy-based thresholding algorithm. Following this, the exposure of longitudinal reinforcement (depth of spalling into the column) and length of spalling along the column are measured using a novel global adaptive thresholding algorithm in conjunction with image processing methods in template matching and morphological operations. The method was tested on a database of damaged RC column images collected after the 2010 Haiti earthquake, and comparison of the results with manual measurements indicate the validity of the method.