In this study, a novel discrete Peridynamics framework called the “State-Based Peridynamic Particle Model (SPPM)” is introduced. In this approach, a solid body is simulated by neither solving differential equations nor integral equations; instead, the simulation is accomplished by directly solving discrete systems of equations using finite summations. SPPM is formulated for a random distribution of particles, hence, it can be considered as a meshfree method. The assumptions of continuity and homogeneity are not necessary for this approach. The SPPM is a generalization of the “State-Based Peridynamic Lattice Model (SPLM)”. In the SPLM formulation, for sake of simplicity and computational efficiency, a lattice of particles is employed and the horizon size is fixed. The proposed SPLM approach differs from the previous versions in that the procedures for calculating the bond forces, damage and plasticity are improved. A novel and robust damage approach called the “Two Spring Damage Model”, with the capability of modeling partial damage, is also proposed and developed for the SPPM and the SPLM.
The re-formulated SPLM method is then calibrated and employed to simulate concrete structures. The obtained results are compared with the previous SPLM versions, experimental tests, and the commercial finite element software, Abaqus. The advantages and difficulties of each modeling approach are described. The re-formulated SPLM demonstrates significant improvements over the previous versions. The obtained simulation results indicate that the SPLM approach produces similar, and in some ways, more realistic results than the well-developed Abaqus methods, but is much simpler to understand and use. The obtained results also reasonably replicate the available laboratory data.
simulation, peridynamics, Meshless, lattice, concrete, fracture, damage
Level of Degree
First Committee Member (Chair)
Dr. Walter Gerstle
Second Committee Member
Dr. Yu-Lin Shen
Third Committee Member
Dr. Fernando Moreu
Nikravesh Kazeroni, Siavash. "State-based Peridynamic Particle Method." (2017). https://digitalrepository.unm.edu/ce_etds/189