Literatura académica sobre el tema "Gridless numerical method"
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Artículos de revistas sobre el tema "Gridless numerical method"
Zhang, Zhao. "Numerical Analysis and Comparison of Gridless Partial Differential Equations". International Journal of Circuits, Systems and Signal Processing 15 (31 de agosto de 2021): 1223–31. http://dx.doi.org/10.46300/9106.2021.15.133.
Texto completoLong, Haining, Ting Su, Xianpeng Wang y Mengxing Huang. "Gridless Multiple Measurements Method for One-Bit DOA Estimation with a Nested Cross-Dipole Array". Wireless Communications and Mobile Computing 2021 (31 de agosto de 2021): 1–10. http://dx.doi.org/10.1155/2021/6635220.
Texto completoPu, Sai Hu. "Gridless Adaptive Method for Simulating Unsteady Flows with Moving Shocks". Applied Mechanics and Materials 271-272 (diciembre de 2012): 948–52. http://dx.doi.org/10.4028/www.scientific.net/amm.271-272.948.
Texto completoChhatkuli, Subas, Seiichi Koshizuka y Mitsuru Uesaka. "Dynamic Tracking of Lung Deformation during Breathing by Using Particle Method". Modelling and Simulation in Engineering 2009 (2009): 1–7. http://dx.doi.org/10.1155/2009/190307.
Texto completoLANDRINI, M., A. COLAGROSSI, M. GRECO y M. P. TULIN. "Gridless simulations of splashing processes and near-shore bore propagation". Journal of Fluid Mechanics 591 (30 de octubre de 2007): 183–213. http://dx.doi.org/10.1017/s0022112007008142.
Texto completoSANJOU, Michio y Iehisa NEZU. "NUMERICAL SIMULATION OF OPEN-CHANNEL FLOWS INCLUDING BUBBLE PLUMES BY USING A GRIDLESS DISCRETE VORTEX METHOD". PROCEEDINGS OF HYDRAULIC ENGINEERING 49 (2005): 703–8. http://dx.doi.org/10.2208/prohe.49.703.
Texto completoLu, Aihong, Yan Guo y Sixing Yang. "Gridless Super-Resolution Direction-of-Arrival Estimation with Arbitrary Planar Sparse Array". Frequenz 74, n.º 3-4 (26 de marzo de 2020): 103–10. http://dx.doi.org/10.1515/freq-2019-0131.
Texto completoAlabideen, Lama Zien, Oumayma Al-Dakkak y Khaldoun Khorzom. "Hybrid Reweighted Optimization Method for Gridless Direction of Arrival Estimation in Heteroscedastic Noise Environment". Mathematical Modelling of Engineering Problems 8, n.º 1 (28 de febrero de 2021): 125–33. http://dx.doi.org/10.18280/mmep.080116.
Texto completoAlabideen, Lama Zien, Oumayma Al-Dakkak y Khaldoun Khorzom. "Reweighted Covariance Fitting Based on Nonconvex Schatten-p Minimization for Gridless Direction of Arrival Estimation". Mathematical Problems in Engineering 2020 (27 de abril de 2020): 1–11. http://dx.doi.org/10.1155/2020/3012952.
Texto completoTan, Weijie y Xi’an Feng. "Covariance Matrix Reconstruction for Direction Finding with Nested Arrays Using Iterative Reweighted Nuclear Norm Minimization". International Journal of Antennas and Propagation 2019 (18 de marzo de 2019): 1–13. http://dx.doi.org/10.1155/2019/7657898.
Texto completoTesis sobre el tema "Gridless numerical method"
Tsukamoto, Marcio Michiharu. "Desenvolvimento do método de partículas na representação de corpos flutuantes em ondas altamente não-lineares". Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/3/3135/tde-19092006-111325/.
Texto completoA numerical method called Moving Particle Semi-implicit (MPS) method was developed in this study to analyze incompressible fluids. It is a particle method using a lagrangean representation without any grid. The governing equations are the Navier-Stokes equation and continuity equation for incompressible and non-viscous flow. Most of the computational fluid dynamics (CFD) methods are based on eulerian representation and use grids to describe the geometry of the simulated domain. These differences make the MPS method easier to analyze highly nonlinear phenomena as free surface with wave breaking, sloshing, slamming, etc. In previously published articles, results of physical experiments had shown good agreement with the numerical results obtained with MPS method. In the present work, results of exciting forces were compared with the results obtained with a validated program called Wave Analysis MIT (WAMIT). It had a good agreement of results between these two programs. The optimization of the neighborhood calculation function got a good economy of computational time. The greatest contribution of this study was the optimization of the linear system solver. It was made implementing in the developed code a parallelized public code called Portable, Extensible Toolkit for Scientific Computation (PETSc) that provided a good performance profit.
Actas de conferencias sobre el tema "Gridless numerical method"
Yang, Ruiyue, Wei Liu, Xiaozhou Qin, Zhongwei Huang, Yu Shi, Zhaoyu Pang, Yiqun Zhang, Jingbin Li y Tianyu Wang. "A Physics-Constrained Data-Driven Workflow for Predicting Coalbed Methane Well Production Using A Combined Gated Recurrent Unit and Multi-Layer Perception Neural Network Model". En SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205903-ms.
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