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Huang Y.-M.,Luoyang Opt EleCenter ofvelopment Center | Ge S.,Luoyang Opt EleCenter ofvelopment Center | Wu W.,Luoyang Opt EleCenter ofvelopment Center | Yu K.-H.,Luoyang Opt EleCenter ofvelopment Center | And 2 more authors.
Zhendong yu Chongji/Journal of Vibration and Shock | Year: 2013

The supporting of a pipeline conveying fluid is one of influence factors on its dynamic characteristics. The supporting position and rigidity changes may cause the dynamic characteristics changes of the pipeline conveying fluid. Based on the fluid-structure interaction, and simplifying the supporting as an equivalent mass and a spring with rigidity coefficients in six directions, the natural frequencies and relative amplitude values of the pipeline conveying fluid were analyzed under different supporting rigidities. And then the effect of different supporting rigidities on the dynamic characteristics integrity of the pipeline conveying fluid was studied and evaluated. The results showed that choosing an appropriate supporting rigidity can play an important role in perfecting the dynamic characteristics integrity of a pipeline conveying fluid. Source


Yu K.,Henan University of Science and Technology | Yu K.,Luoyang Opt EleCenter ofvelopment Center | Yang X.,Henan University of Science and Technology | Mo Z.,Luoyang Opt EleCenter ofvelopment Center
Journal of Fluids Engineering, Transactions of the ASME | Year: 2014

This paper presents a new profile modeling method and multifidelity optimization procedure for the solid rocket motor contoured nozzle design. Two quartic splines are proposed to construct the nozzle divergent section profile, and the coefficients of the splines' functions are calculated by a fortran program. Two-dimensional axisymmetric and three-dimensional compressible Navier-Stokes equations with Re-Normalisation Group (RNG) k-ε turbulent models solve the flow field as low-and high-fidelity models, respectively. An optimal Latin hypercube sampling method produces the sampling points, and Kriging functions establish the surrogate model combining with the low-and high-fidelity models. Finally, the adaptive simulated annealing algorithm is selected to complete the profile optimization, with the objectives of maximizing the thrust and the total pressure recovery coefficient. The optimization improves the thrust by 4.27%, and enhances the recovery coefficient by 4.63%. The result shows the proposed profile modeling method is feasible and effective to enhance the nozzle performance. The multifidelity optimization strategy is valid for improving the computational efficiency. Copyright © 2014 by ASME. Source


Hui W.,Luoyang Opt EleCenter ofvelopment Center | DongJie T.,Luoyang Opt EleCenter ofvelopment Center | FangFang Z.,Luoyang Opt EleCenter ofvelopment Center | ShiWei G.,Luoyang Opt EleCenter ofvelopment Center | XiTao Z.,Luoyang Opt EleCenter ofvelopment Center
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

A blind pixel compensation algorithm based on Kalman Prediction is proposed, and a mathematical model is established. Kalman prediction is used to detect blind pixels in a row data in an image. The blind pixel is displaced by the middle pixel in the neighbor data set. The algorithm is optimized for the real time application. The virtue of the proposed approach is illustrated with a comparison with median filter and mean filter on computation complexity and time consuming. Theory and experiments demonstrate the applicability in real time systems. © 2012 Springer-Verlag. Source


Yu K.,Luoyang Opt EleCenter ofvelopment Center | Yu K.,Henan University of Science and Technology | Duan S.,Luoyang Opt EleCenter ofvelopment Center | Li C.,Luoyang Opt EleCenter ofvelopment Center | Zhou S.,Luoyang Opt EleCenter ofvelopment Center
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | Year: 2012

Multi-fidelity design optimization methodology for a phased array radar antenna was studied. Based on agent model, a multi-level multi-fidelity optimization methodology, including antenna unite optimization, array optimization and approximate model was proposed to improve the computational efficiency. KS (kreisselmeier-steinhauser) envelop function method was exploited to transform the multi-objective into a single function. A phased array radar antenna design optimization procedure was established by employing the commercial software Insight, geometry model parameters of radar antenna as design variables, electromagnetic properties as objectives, and temperature, stress, and deformation as constraints. Multidisciplinary design optimization of the radar antenna array was completed, and electromagnetic properties of the radar antenna were improved. Source

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