Information technology in the modeling of fast nonlinear processes (on the example of interaction of submunitions with biological tissue)

2017 ◽  
Author(s):  
Андрей Гусев ◽  
Andrey Gusev ◽  
Геннадий Шабанов ◽  
Gennadiy Shabanov ◽  
Михаил Родионов ◽  
...  
Keyword(s):  
Neural Network ◽  
Mathematical Modeling ◽  
Finite Element Method ◽  
Information Technology ◽  
Finite Element ◽  
Pilot Study ◽  
Design Stage ◽  
Small Arms ◽  
Viscous State

The monograph is devoted to the problem of mathematical modeling of process of interaction of the bullet with the block simulator with a finite element method that enables the assessment of the damaging effect of bullets at the design stage, the development of neural network based on the evaluation of those factors on the parameters of the damaging effect of bullets provides a characterization of the striking element on the stages of the pilot study, conceptual design and technical design and development of methods for the assessment of the damaging effect of bullets of small arms ammunition, taking into account elastico viscous state of the target.

Finite Element Method-based geomechanical risk assessment of underground laboratory located in the deep copper mine

2021 ◽  
Author(s):  
Krzysztof Fulawka ◽  
Witold Pytel ◽  
Piotr Mertuszka ◽  
Marcin Szumny
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Numerical Analysis ◽  
New Technologies ◽  
Radiation Detection ◽  
Underground Laboratory ◽  
Design Stage ◽  
Copper Mine ◽  
Geophysical Surveys ◽  
Element Method

<p>Underground laboratories provide a unique environment for various industries and are a suitable place for developing new technologies for mining, geophysical surveys, radiation detection, as well as many other studies and measurements. Unfortunately, any operation in underground excavations is associated with exposure to many hazards not necessarily encountered in surface laboratories. One of the most dangerous events observed in underground conditions is the dynamic manifestation of rock mass pressure in form of rockburst, roof falls and mining tremors. Therefore, proper evaluation of geomechanical risk is a key element ensuring the safety of work in underground conditions. Finite Element Method-based numerical analysis is one of the tools which allow conducting a detailed geomechanical hazard assessment already at the object design stage. The results of such calculations may be the basis for the implementation of preventive measures before running up the underground facility.</p><p>Within this paper, the three-dimensional FEM-based numerical analysis of large-scale underground laboratory located in deep Polish copper mine was presented. The calculations were made with GTS NX software, which allowed determining the changes in the safety factor in surrounding of the analyzed area. Finally, the possibility of underground laboratory establishment, with respect to predicted stress and strain conditions, were determined.</p>

Acoustic Characterization of Inhomogenous Layers using Finite Element Method

2021 ◽  
Author(s):  
Per Kristian Bolstad ◽  
Tung Manh ◽  
Martijn Frijlink ◽  
Lars Hoff
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Acoustic Characterization ◽  
Element Method

scholarly journals Artificial Neural Network-Based Method for Seismic Analysis of Concrete-Filled Steel Tube Arch Bridges

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zhen Liu ◽  
Shibo Zhang
Keyword(s):  
Neural Network ◽  
Finite Element Method ◽  
Artificial Neural Network ◽  
Finite Element ◽  
Seismic Analysis ◽  
Steel Tube ◽  
Arch Bridge ◽  
Concrete Filled Steel Tube ◽  
Cfst Arch Bridge ◽  
Artificial Neural

Seismic analysis of concrete-filled steel tube (CFST) arch bridge based on finite element method is a time-consuming work. Especially when uncertainty of material and structural parameters are involved, the computational requirements may exceed the computational power of high performance computers. In this paper, a seismic analysis method of CFST arch bridge based on artificial neural network is presented. The ANN is trained by these seismic damage and corresponding sample parameters based on finite element analysis. In order to obtain more efficient training samples, a uniform design method is used to select sample parameters. By comparing the damage probabilities under different seismic intensities, it is found that the damage probabilities of the neural network method and the finite element method are basically the same. The method based on ANN can save a lot of computing time.

Comprehensive Mathematical Modeling and Dynamic Simulation of Fixed Bed Reactor with Finite Element Method

2011 ◽  
Author(s):  
Davood Dehestani ◽  
Hung Nguyen ◽  
Fahimeh Eftekhari ◽  
Jafar Madadnia ◽  
Steven Su ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Finite Element Method ◽  
Finite Element ◽  
Dynamic Simulation ◽  
Fixed Bed ◽  
Fixed Bed Reactor ◽  
Element Method
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