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Aims and scope

The aim is to serve as the focal journal to disseminate original research and review articles addressing theoretical development of peridynamics and its modeling and simulation applications.

Peridynamics, a nonlocal theory, removes the computational challenges inherent in the classical continuum mechanics, and enables the solution of complex governing field equations in the presence of jump discontinuities or singularities while providing a bridge between different length scales. It presents the capability to address challenging problems across different disciplines such as failure of materials, multi-scale and multi-physics modeling, computational material design and its micro structural evolution, additive manufacturing, soft tissue modeling, reliability and optimal design, optimization, signal and image processing, digital image correlation, structural health monitoring, mathematical biology, geophysics and rock mechanics, by using high performance computing.

A list of topics included in the scope of the journal.
(1) Fundamental and theoretical aspects of peridynamics

(2) Computational aspects of peridynamics
Utilization of GPU computer architecture
High performance computing
Numerical discretization schemes
Numerical integration schemes
Coupling with other existing methods such as FEM and SPH

(3) Fracture and failure of materials with peridynamics
Brittle and ductile fracture metallic materials
Progressive failure of composite structures
Impact and penetration mechanics

(4) Peridynamic applications in geomechanics

(5) Multi-physics modeling with peridynamics

(6) Multi-scale modeling with peridynamics
Computational design of materials
Micro structural evolution
Crystal plasticity

(7) Peridynamics for image analysis
Signal and image processing and medical imaging
Digital image correlation

(8) Peridynamics for discrete data analysis

(9) Inverse problems with peridynamics
Structural health monitoring

(10) Optimization with peridynamics

(11) Other applications of peridynamics
Soft tissue modeling
Mathematical biology

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