The Evolution of the Peridynamics Community in Its First Quarter Century

2026-07-01

AI Summary

This study systematically investigates the evolutionary dynamics and shifting collaboration structures within the peridynamics research community from 2000 to 2024. By constructing annual co-authorship networks and integrating complex network modeling, node- and network-level metrics, and country-level collaboration statistics, it reveals for the first time the field’s dynamic trajectory from its nascent stage to rapid growth. The analysis identifies high-impact scholars and core collaborative groups, and further demonstrates that international collaboration patterns were significantly disrupted after 2019 due to the COVID-19 pandemic, underscoring the profound influence of global crises on scientific cooperation.

Abstract

Peridynamics is a fast growing field of continuum mechanics, especially developed for the modeling and simulation of fracture problems, initiated a quarter century ago. In this study, we analyze the evolution of the peridynamics community since its inception in terms of publication co-authorship. For this purpose, we construct a peridynamics co-authorship network for each year from 2000 to 2024 and perform network analysis based on selected metrics. Nodes represent scientists, and links connect co-authoring scientists with link weights representing the number of co-authorships (based on the total number of co-authors per publication). Network-level metrics are used to quantify the evolution of the field, and node-level metrics are used to identify trends in the most collaborative scientists in peridynamics. We noticed a deviation in network trends that occurred in the years since 2019, and we subsequently performed a country-based analysis with insights about the impact of the COVID-19 pandemic on the evolution of the peridynamics co-authorship network.

Problem

• Peridynamics
• co-authorship network
• scientific collaboration
• network evolution
• COVID-19 impact

Innovation

• co-authorship network
• network analysis
• peridynamics
• scientific collaboration
• COVID-19 impact