Crack control optimization of basement concrete structures using the Mask-RCNN and temperature effect analysis.

ABSTRACT: In order to enhance the mitigation of crack occurrence and propagation within basement concrete structures, this research endeavors to propose an optimization methodology grounded in the Mask Region-based Convolutional Neural Network (Mask-RCNN) and an analysis of temperature effects. Initially, the Mask-RCNN algorithm is employed to perform image segmentation of the basement concrete structure, facilitating the precise identification of crack locations and shapes within the structure. Subsequently, the finite element analysis method is harnessed to simulate the structural stress and deformation in response to temperature variations. An optimization algorithm is introduced to adjust geometric parameters and material properties using insights from the temperature effect analysis. This algor

SUBMITTER: Wu S 

PROVIDER: S-EPMC10553232 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature