Integrating Nondestructive Evaluation/Visual Inspection Data for Enhanced Concrete Bridge Assessment

Integrating Nondestructive Evaluation and Visual Inspection Data for Enhanced Concrete Bridge Condition Assessment
Presented By: Ibukunoluwa Olowe, University of Texas Arlington
Deterioration of concrete bridge decks is a significant issue affecting the service life of bridges. This is due to factors such as heavy traffic loads, fatigue, temperature fluctuations, and environmental conditions. However, traditional methods of evaluating bridge conditions, such as visual inspection, are subjective and often fail to identify subsurface defects. This research aims to develop a novel concrete bridge deck condition rating system by integrating Nondestructive Evaluation (NDE) and visual inspection to overcome the uncertainties of traditional methods. The study includes extensive data collection using Ground Penetrating Radar (GPR) and Impact Echo (IE) on seven full-scale concrete bridges in Texas, USA, analyzing the data to identify patterns and anomalies and using Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to integrate NDE and visual inspection results. The objective is to create a robust condition rating system that enhances concrete bridge infrastructure assessment, promoting safer and more efficient bridge management practices.