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+ | ==Abstract== | ||
+ | Particle methods such as the SPH and MPS methods have problems because | ||
+ | it is difficult to treat curved bottom surfaces such as seabed surfaces accurately. In | ||
+ | this study, regarding this problem, the curved bottom surfaces’ treatments have been | ||
+ | improved using a coordinate transformation using the high-order second derivative model | ||
+ | called SPH(2). Although the theory for the coordinate transformation was established in | ||
+ | the MPS method, its accuracy did not give the desired accuracy because of the numerical | ||
+ | errors of the second derivative models. Therefore, the numerical errors in these coordinate | ||
+ | transformations were overcome by applying the second derivative model of SPH(2) to | ||
+ | the coordinate transformation formulas. The superiority and validity of the proposed | ||
+ | coordinate transformation using SPH(2) are demonstrated through validation examples | ||
+ | such as the hydrostatic pressure and dam-break problems. | ||
+ | |||
+ | == Full Paper == | ||
+ | <pdf>Media:Draft_Sanchez Pinedo_144844635pap_139.pdf</pdf> |
Particle methods such as the SPH and MPS methods have problems because it is difficult to treat curved bottom surfaces such as seabed surfaces accurately. In this study, regarding this problem, the curved bottom surfaces’ treatments have been improved using a coordinate transformation using the high-order second derivative model called SPH(2). Although the theory for the coordinate transformation was established in the MPS method, its accuracy did not give the desired accuracy because of the numerical errors of the second derivative models. Therefore, the numerical errors in these coordinate transformations were overcome by applying the second derivative model of SPH(2) to the coordinate transformation formulas. The superiority and validity of the proposed coordinate transformation using SPH(2) are demonstrated through validation examples such as the hydrostatic pressure and dam-break problems.
Published on 23/11/23
Submitted on 23/11/23
Volume Particle-Based Methods for Natural Hazards Simulation, 2023
DOI: 10.23967/c.particles.2023.025
Licence: CC BY-NC-SA license
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