scholarly journals 2D FLOOD INUNDATION SIMULATION BASED ON A LARGE SCALE PHYSICAL MODEL USING COURSE NUMERICAL GRID METHOD

2019 ◽  
Vol 17 (59) ◽  
Author(s):  
Muhammad Azraie Abdul Kadir
Author(s):  
Jun-hui Wang ◽  
Jing-ming Hou ◽  
Jia-hui Gong ◽  
Bing-yao Li ◽  
Bao-shan Shi ◽  
...  

2018 ◽  
Vol 2018.31 (0) ◽  
pp. 293
Author(s):  
Naoki NAKAYA ◽  
Mitsuteru ASAI ◽  
Keita OGASAWARA ◽  
Mikito FURUICHI ◽  
Daisuke NISHIURA

2020 ◽  
Vol 584 ◽  
pp. 124308 ◽  
Author(s):  
Youtong Rong ◽  
Ting Zhang ◽  
Yanchen Zheng ◽  
Chunqi Hu ◽  
Ling Peng ◽  
...  

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Mohammadreza Yaghoobi ◽  
Krzysztof S. Stopka ◽  
Aaditya Lakshmanan ◽  
Veera Sundararaghavan ◽  
John E. Allison ◽  
...  

AbstractThe PRISMS-Fatigue open-source framework for simulation-based analysis of microstructural influences on fatigue resistance for polycrystalline metals and alloys is presented here. The framework uses the crystal plasticity finite element method as its microstructure analysis tool and provides a highly efficient, scalable, flexible, and easy-to-use ICME community platform. The PRISMS-Fatigue framework is linked to different open-source software to instantiate microstructures, compute the material response, and assess fatigue indicator parameters. The performance of PRISMS-Fatigue is benchmarked against a similar framework implemented using ABAQUS. Results indicate that the multilevel parallelism scheme of PRISMS-Fatigue is more efficient and scalable than ABAQUS for large-scale fatigue simulations. The performance and flexibility of this framework is demonstrated with various examples that assess the driving force for fatigue crack formation of microstructures with different crystallographic textures, grain morphologies, and grain numbers, and under different multiaxial strain states, strain magnitudes, and boundary conditions.


2013 ◽  
Vol 462-463 ◽  
pp. 462-465 ◽  
Author(s):  
Yi Du ◽  
Ting Zhang

It is difficult to reconstruct the unknown information only by some sparse known data in the reconstruction of porous media. Multiple-point geostatistics (MPS) has been proved to be a powerful tool to capture curvilinear structures or complex features in training images. One solution to capture large-scale structures while considering a data template with a reasonably small number of grid nodes is provided by the multiple-grid method. This method consists in scanning a training image using increasingly finer multiple-grid data templates instead of a big and dense data template. The experimental results demonstrate that multiple-grid data templates and MPS are practical in porous media reconstruction.


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