scholarly journals Analyzing earthquake clustering features by using stochastic reconstruction

2004 ◽  
Vol 109 (B5) ◽  
Author(s):  
Jiancang Zhuang ◽  
Yosihiko Ogata ◽  
David Vere-Jones
Keyword(s):  
Stochastic Reconstruction ◽  
Earthquake Clustering

A hybrid process-based and stochastic reconstruction method of porous media

2008 ◽  
Vol 110 (1) ◽  
pp. 92-99 ◽  
Author(s):  
M.G. Politis ◽  
E.S. Kikkinides ◽  
M.E. Kainourgiakis ◽  
A.K. Stubos
Keyword(s):  
Porous Media ◽  
Hybrid Process ◽  
Reconstruction Method ◽  
Stochastic Reconstruction

Stochastic Reconstruction of Complex Heavy Oil Molecules Using an Artificial Neural Network

2017 ◽  
Vol 31 (11) ◽  
pp. 11932-11938 ◽  
Author(s):  
Celal Utku Deniz ◽  
Muzaffer Yasar ◽  
Michael T. Klein
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Heavy Oil ◽  
Stochastic Reconstruction ◽  
Artificial Neural

scholarly journals Stochastic Reconstruction and Interpolation of Precipitation Fields Using Combined Information of Commercial Microwave Links and Rain Gauges

2017 ◽  
Vol 53 (12) ◽  
pp. 10740-10756 ◽  
Author(s):  
B. Haese ◽  
S. Hörning ◽  
C. Chwala ◽  
A. Bárdossy ◽  
B. Schalge ◽  
...  
Keyword(s):  
Rain Gauges ◽  
Stochastic Reconstruction ◽  
Commercial Microwave Links

scholarly journals Uplift rate transients at subduction margins due to earthquake clustering

Tectonics ◽  
2016 ◽  
Vol 35 (10) ◽  
pp. 2370-2384 ◽  
Author(s):  
Vasiliki Mouslopoulou ◽  
Onno Oncken ◽  
Sebastian Hainzl ◽  
Andrew Nicol
Keyword(s):  
Uplift Rate ◽  
Earthquake Clustering

scholarly journals Stochastic 3D Carbon Cloth GDL Reconstruction and Transport Prediction

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 572
Author(s):  
Yuan Gao ◽  
Teng Jin ◽  
Xiaoyan Wu
Keyword(s):  
Reconstruction Algorithm ◽  
Gas Diffusion ◽  
Reconstruction Method ◽  
Carbon Cloth ◽  
Statistical Characterization ◽  
Stochastic Reconstruction ◽  
Classical Simulation ◽  
The Many ◽  
Transport Prediction ◽  
Structure Properties

This paper presents the 3D carbon cloth gas diffusion layer (GDL) to predict transport behaviors of anisotropic structure properties. A statistical characterization and stochastic reconstruction method is established to construct the 3D micro-structure using the data from the true materials. Statistics of the many microstructure characteristics, such as porosity, pore size distribution, and shape of the void, are all quantified by image-based characterization. Furthermore, the stochastic reconstruction algorithm is proposed to generate random and anisotropic 3D microstructure models. The proposed method is demonstrated by some classical simulation prediction and to give the evaluation of the transport properties. Various reconstructed GDLs are also generated to demonstrate the capability of the proposed method. In the end, the adapted structure properties are offered to optimize the carbon cloth GDLs.

Stochastic reconstruction of 3D porous media from 2D images using generative adversarial networks

2020 ◽  
Vol 399 ◽  
pp. 227-236
Author(s):  
Andrea Valsecchi ◽  
Sergio Damas ◽  
Cristina Tubilleja ◽  
Javier Arechalde
Keyword(s):  
Porous Media ◽  
Generative Adversarial Networks ◽  
Stochastic Reconstruction ◽  
Adversarial Networks ◽  
2D Images
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