The main goal of this paper is to provide a Reduced Order Model (ROM) able to predict the liquid induced dissipation of the violent and vertical sloshing problem for a wide range of liquid viscosities, surface tensions and tank filling levels. For that purpose, the Delta Smoothed Particle Hydrodynamics (δ-SPH) formulation is used to build a database of simulation cases where the physical parameters of the liquid are varied. For each simulation case, a bouncing ball-based equivalent mechanical model is identified to emulate sloshing dynamics. Then, an interpolating hypersurface-based ROM is defined to establish a mapping between the considered physical parameters of the liquid and the identified ball models. The resulting hypersurface effect...
This paper proposes Reduced-Order Models (ROMs) based on data provided by CFD codes, for the study o...
Smoothed particle hydrodynamics (SPH) is a popular meshfree, Lagrangian particle method with attract...
In this paper, a nonlinear reduced order model based on neural networks is introduced in order to mo...
The main goal of this paper is to provide a Reduced Order Model (ROM) able to predict the liquid ind...
The main aims of this work are to identify, verify, and validate a smoothed particle hydrodynamics ...
This paper proposes Reduced-Order Models (ROMs) based on data provided by Computational Fluid Dynami...
In this paper, a nonlinear reduced order model based on neural networks is introduced in order to mo...
Smoothed particle hydrodynamics (SPH), a true mesh less method has been used to simulated the sloshi...
Prediction of energy dissipation in violent sloshing flows simulated by Smoothed Particle Hydrodynam...
A 3D model of liquid slosh inside a partially filled tank is done by using Smoothed Particle Hydrody...
Sloshing phenomena regard the dynamic excitation of a partially filled tank which leads to the motio...
Copyright © Abdelraheem M. Aly et al.This is an open access article distributed under the Creative C...
As part of the Sloshing Wing Dynamics H2020 EU project, an experimental campaign was conducted to st...
A stabilized incompressible smoothed particle hydrodynamics (ISPH) method with the addition of a den...
The aim of this work is to provide a reduced-order model to describe the dissipative behavior of non...
This paper proposes Reduced-Order Models (ROMs) based on data provided by CFD codes, for the study o...
Smoothed particle hydrodynamics (SPH) is a popular meshfree, Lagrangian particle method with attract...
In this paper, a nonlinear reduced order model based on neural networks is introduced in order to mo...
The main goal of this paper is to provide a Reduced Order Model (ROM) able to predict the liquid ind...
The main aims of this work are to identify, verify, and validate a smoothed particle hydrodynamics ...
This paper proposes Reduced-Order Models (ROMs) based on data provided by Computational Fluid Dynami...
In this paper, a nonlinear reduced order model based on neural networks is introduced in order to mo...
Smoothed particle hydrodynamics (SPH), a true mesh less method has been used to simulated the sloshi...
Prediction of energy dissipation in violent sloshing flows simulated by Smoothed Particle Hydrodynam...
A 3D model of liquid slosh inside a partially filled tank is done by using Smoothed Particle Hydrody...
Sloshing phenomena regard the dynamic excitation of a partially filled tank which leads to the motio...
Copyright © Abdelraheem M. Aly et al.This is an open access article distributed under the Creative C...
As part of the Sloshing Wing Dynamics H2020 EU project, an experimental campaign was conducted to st...
A stabilized incompressible smoothed particle hydrodynamics (ISPH) method with the addition of a den...
The aim of this work is to provide a reduced-order model to describe the dissipative behavior of non...
This paper proposes Reduced-Order Models (ROMs) based on data provided by CFD codes, for the study o...
Smoothed particle hydrodynamics (SPH) is a popular meshfree, Lagrangian particle method with attract...
In this paper, a nonlinear reduced order model based on neural networks is introduced in order to mo...