Numerical implementation of the Neumann-Michell theory incorporating with the analytical panel integral for ship waves

2021 ◽  
Vol 236 ◽  
pp. 109566
Author(s):  
Le Zha ◽  
Renchuan Zhu ◽  
Hui Wang ◽  
Shan Huang
1999 ◽  
Author(s):  
Chi Yang ◽  
Rainald Lohner ◽  
Francis Noblesse
Keyword(s):  

2020 ◽  
Vol 1596 ◽  
pp. 012062
Author(s):  
Davide Terzani ◽  
Pasquale Londrillo ◽  
Paolo Tomassini ◽  
Leonida A Gizzi

2021 ◽  
Vol 11 (12) ◽  
pp. 5368
Author(s):  
Guoqing Cai ◽  
Bowen Han ◽  
Mengzi Li ◽  
Kenan Di ◽  
Yi Liu ◽  
...  

An unsaturated soil constitutive model considering the influence of microscopic pore structure can more accurately describe the hydraulic–mechanical behavior of unsaturated soil, but its numerical implementation is more complicated. Based on the fully implicit Euler backward integration algorithm, the ABAQUS software is used to develop the established hydro-mechanical coupling constitutive model for unsaturated soil, considering the influence of micro-pore structure, and a new User-defined Material Mechanical Behavior (UMAT) subroutine is established to realize the numerical application of the proposed model. The developed numerical program is used to simulate the drying/wetting cycle process of the standard triaxial specimen. The simulation results are basically consistent with those calculated by the Fortran program, which verifies the rationality of the developed numerical program.


2020 ◽  
Vol 10 (1) ◽  
pp. 65-70
Author(s):  
Andrei Gorchakov ◽  
Vyacheslav Mozolenko

AbstractAny real continuous bounded function of many variables is representable as a superposition of functions of one variable and addition. Depending on the type of superposition, the requirements for the functions of one variable differ. The article investigated one of the options for the numerical implementation of such a superposition proposed by Sprecher. The superposition was presented as a three-layer Feedforward neural network, while the functions of the first’s layer were considered as a generator of space-filling curves (Peano curves). The resulting neural network was applied to the problems of direct kinematics of parallel manipulators.


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