scholarly journals Optimal transportation meshfree method in geotechnical engineering problems under large deformation regime

2018 ◽  
Vol 115 (10) ◽  
pp. 1217-1240 ◽  
Author(s):  
Pedro Navas ◽  
Susana López-Querol ◽  
Rena C. Yu ◽  
Manuel Pastor
Keyword(s):  
Large Deformation ◽  
Geotechnical Engineering ◽  
Meshfree Method ◽  
Optimal Transportation ◽  
Deformation Regime ◽  
Engineering Problems

Finite Element Analysis about the Properties of CFG-Pile Composite Foundation Based on Parametric Language PYTHON

2011 ◽  
Vol 320 ◽  
pp. 20-25
Author(s):  
Wei Dong Pan ◽  
Ren Guo Gu ◽  
Ke Zhu ◽  
Yong Gang Lv
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Geotechnical Engineering ◽  
Composite Foundation ◽  
Engineering Structures ◽  
Element Analysis ◽  
Model Code ◽  
Engineering Problems ◽  
Cfg Pile Composite Foundation ◽  
Cfg Pile

As an international general finite element analysis software, ABAQUS has super nonlinear analysis function and is playing an increasingly important role in the numerical calculation analysis of geotechnical engineering structures. CAE module of its own provides a certain amount of convenience for the beginners, but it is inadequate in the face of more complex geotechnical engineering problems. Based on parametric language PYTHON, using its modular model code, bypassing the CAE module, the ABAQUS finite element analysis calculated and analyzed the influence of ER on the CFG pile composite foundation settlement and pile side friction. Finite element analysis and the results show that: the process of ABAQUS finite element analysis, which is based on the parameter language PYTHON, is simple and has very high computational efficiency and accuracy in the analysis complex geotechnical engineering problems.

scholarly journals Recent Advances and Future Challenges for Artificial Neural Systems in Geotechnical Engineering Applications

2009 ◽  
Vol 2009 ◽  
pp. 1-9 ◽  
Author(s):  
Mohamed A. Shahin ◽  
Mark B. Jaksa ◽  
Holger R. Maier
Keyword(s):  
Geotechnical Engineering ◽  
Neural Systems ◽  
Ann Modeling ◽  
Computational Capability ◽  
Engineering Problems ◽  
Future Challenges ◽  
Classical Mathematics ◽  
Artificial Neural ◽  
High Level ◽  
Almost All

Artificial neural networks (ANNs) are a form of artificial intelligence that has proved to provide a high level of competency in solving many complex engineering problems that are beyond the computational capability of classical mathematics and traditional procedures. In particular, ANNs have been applied successfully to almost all aspects of geotechnical engineering problems. Despite the increasing number and diversity of ANN applications in geotechnical engineering, the contents of reported applications indicate that the progress in ANN development and procedures is marginal and not moving forward since the mid-1990s. This paper presents a brief overview of ANN applications in geotechnical engineering, briefly provides an overview of the operation of ANN modeling, investigates the current research directions of ANNs in geotechnical engineering, and discusses some ANN modeling issues that need further attention in the future, including model robustness; transparency and knowledge extraction; extrapolation; uncertainty.

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