1,046 research outputs found

    A fourier pseudospectral method for some computational aeroacoustics problems

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    A Fourier pseudospectral time-domain method is applied to wave propagation problems pertinent to computational aeroacoustics. The original algorithm of the Fourier pseudospectral time-domain method works for periodical problems without the interaction with physical boundaries. In this paper we develop a slip wall boundary condition, combined with buffer zone technique to solve some non-periodical problems. For a linear sound propagation problem whose governing equations could be transferred to ordinary differential equations in pseudospectral space, a new algorithm only requiring time stepping is developed and tested. For other wave propagation problems, the original algorithm has to be employed, and the developed slip wall boundary condition still works. The accuracy of the presented numerical algorithm is validated by benchmark problems, and the efficiency is assessed by comparing with high-order finite difference methods. It is indicated that the Fourier pseudospectral time-domain method, time stepping method, slip wall and absorbing boundary conditions combine together to form a fully-fledged computational algorithm

    Adaptive mesh refinement computation of acoustic radiation from an engine intake

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    A block-structured adaptive mesh refinement (AMR) method was applied to the computational problem of acoustic radiation from an aeroengine intake. The aim is to improve the computational and storage efficiency in aeroengine noise prediction through reduction of computational cells. A parallel implementation of the adaptive mesh refinement algorithm was achieved using message passing interface. It combined a range of 2nd- and 4th-order spatial stencils, a 4th-order low-dissipation and low-dispersion Rungeā€“Kutta scheme for time integration and several different interpolation methods. Both the parallel AMR algorithms and numerical issues were introduced briefly in this work. To solve the problem of acoustic radiation from an aeroengine intake, the code was extended to support body-fitted grid structures. The problem of acoustic radiation was solved with linearised Euler equations. The AMR results were compared with the previous results computed on a uniformly fine mesh to demonstrate the accuracy and the efficiency of the current AMR strategy. As the computational load of the whole adaptively refined mesh has to be balanced between nodes on-line, the parallel performance of the existing code deteriorates along with the increase of processors due to the expensive inter-nodes memory communication costs. The potential solution was suggested in the end

    A Novel High-Fidelity Simulation for Finishing Operations: Hybrid Image Mosaic and Wavelet Decomposition.

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    In finishing simulations, achieving accurate results can be challenging due to the minimal amount of material removal and the limited measurement range of surface micro-topography instruments. To overcome these limitations, a novel high-fidelity modeling method combining image mosaic and wavelet decomposition technologies is proposed in this paper. We achieve the stitching of narrow field and high pixel micro morphology images through four steps: image feature extraction, overlapped feature matching, feature fusion, and stitching effect evaluation. On this basis, the wavelet decomposition method is employed to separate detection signals based on their respective frequencies, allowing the establishment of a datum plane and a roughness surface. The point cloud model undergoes a transformation into a continuous geometric model via the Poisson reconstruction algorithm. In the case study, four sample images of an aluminum alloy sheet after barrel finishing were collected using the ZeGage Plus optical profiler. Each image has an actual size of 834.37 Ī¼m Ɨ 834.37 Ī¼m. Subsequently, a comparison was carried out between the physical and simulation experiments. The results clearly indicate that the proposed method has the potential to enhance the accuracy of the finishing simulation by over 30%. The error between the resulting model and the actual surface of the part can be controlled within 1 Ī¼m

    Effect of recombinant human bone morphogenetic protein 2/poly-lactide-co-glycolic acid (rhBMP-2/PLGA) with core decompression on repair of rabbit femoral head necrosis

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    ABSTRACTObjectiveTo observe the effect of recombinant human bone morphogenetic protein 2/poly-lactide-co-glycolic acid (rhBMP-2/PLGA) with core decompression on repair of rabbit femoral head necrosis.MethodBilateral femoral head necrosis models of rabbit were established by steroid injection. A total of 48 rabbits (96 femoral head necrosis) were randomly divided into 4 groups: Group A, control group with12 rabbits, 24 femoral head necrosis; Group B, treated with rhBMP-2/PLGA implantation after core depression, with 12 rabbits, 24 femoral head necrosis; Group C, treated with rhBMP-2 implantation after core depression, with 12 rabbits, 24 femoral head necrosis; Group D treated with core depression group without implantation, with 12 rabbits, 24 femoral head necrosis. All animals were sacrificed after 12 weeks. The ability of repairing bone defect was evaluated by X-ray radiograph. Bone mineral density analysis of the defect regions were used to evaluate the level of ossification. The morphologic change and bone formation was assessed by HE staining. The angiogenesis was evaluated by VEGF immunohistochemistry.ResultsThe osteogenetic ability and quality of femoral head necrosis in group B were better than those of other groups after 12 weeks by X-ray radiograph and morphologic investigation. And the angiogenesis in group B was better than other groups. Group C had similar osteogenetic quality of femoral head necrosis and angiogenesis with group D.ConclusionThe treatment of rhBMP-2/PLGA implantation after core depression can promote the repair of rabbit femoral head necrosis. It is a promising and efficient synthetic bone material to treat the femoral head necrosis

    Regional disparities and dynamic evolution of competitiveness of marine fish aquaculture industry āˆ’ A study of China

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    China has emerged as a major player in marine fish aquaculture, contributing significantly to economic, social, and environmental development. Analyzing the competitive evolution pattern of regional marine aquaculture is critical to promote the synergistic development of this industry. The ā€œvertical and horizontalā€ scatter degree method was employed to examine the dynamic evolution trend and spatial non-equilibrium of the competitiveness level of marine fish aquaculture in nine Chinese provinces and cities. Using the Ļƒ-convergence model and absolute Ī²-convergence model, the evolution of absolute differences was characterized. The study reveals the existence of stage and regional characteristics of marine fish aquaculture in the nine provinces and cities, with an observable gradient effect. The overall difference is observed to decrease, indicating a trend towards regional synergistic development in the marine fish aquaculture industry. This finding holds practical significance and theoretical value in promoting the growth of the industry

    Overhead Line Defect Recognition Based on Unsupervised Semantic Segmentation

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    Overhead line inspection greatly benefits from defect recognition using visible light imagery. Addressing the limitations of existing feature extraction techniques and the heavy data dependency of deep learning approaches, this paper introduces a novel defect recognition framework. This is built on the Faster RCNN network and complemented by unsupervised semantic segmentation. The approach involves identifying the type and location of the target equipment, utilizing semantic segmentation to differentiate between the device and its backdrop, and finally employing similarity measures and logical rules to categorize the type of defect. Experimental results indicate that this methodology focuses more on the equipment rather than the defects when identifying issues in overhead lines. This leads to a notable enhancement in accuracy and exhibits impressive adaptability. Thus, offering a fresh perspective for automating the inspection of distribution network equipment
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