Automated generation of FE model for digital twin of concrete structures from segmented 3D point cloud
Paper in proceeding, 2019

To achieve real-time structural health monitoring (SHM), a concept of digital twin - a digital copy of a structure has been brought up and investigated. It provides an up-to-date virtual model of structures, with the integration of physical as well as data information. The goal of this research is to provide faster and more accurate procedures to capture the spatial information required by a digital twin of a concrete structure using 3D point cloud data. Given that the method is intended for real-scale structures, such as bridges, the work can be divided to 3 steps: (1) to segment and extract geometric information for structural components; (2) to convert the geometry information to FE mesh with consideration of element types; (3) to assign material property as well as boundary conditions based on extracted components type. Linear FE analyses have been carried out to evaluate the structural performance based on the FE model created from the point cloud. The automation of such a process is an essential part of the creation of a digital twin of infrastructures.


Jiangpeng Shu

Zhejiang University

Kamyab Zandi

Chalmers, Architecture and Civil Engineering, Structural Engineering

Tanay Topac

Stanford University

Ruiqi Chen

Stanford University

Chun Fan

Nordic Semiconductor ASA

Structural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring

Vol. 1 428-434

12th International Workshop on Structural Health Monitoring
Stanford, USA,

Subject Categories

Applied Mechanics

Civil Engineering

Computer Vision and Robotics (Autonomous Systems)



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