Artificial Intelligence Based Structural Assessment for Regional Short- and Medium-Span Concrete Beam Bridges with Inspection Information

Abstract

The functional and structural characteristics of civil engineering works, in particular bridges, influence the performance of transport infrastructure. Remote sensing technology and other advanced technologies could help bridge managers review structural conditions and deteriorations through bridge inspection. This paper proposes an artificial intelligence-based methodology to solve the condition assessment of regional bridges and optimize their maintenance schemes. It includes data integration, condition assessment, and maintenance optimization. Data from bridge inspection reports is the main source of this data-driven approach, which could provide a substantial amount og condition-related information to reveal the time-variant bridge condition deterioration and effect of maintenance behaviors. The regional bridge condition deterioration model is established by neural networks, and the impact of the maintenance scheme on the future condition of bridges is quantified. Given the need to manage limited resources and ensure safety and functionality, adequate maintenance schemes for regional bridges are optimized with genetic algorithms. The proposed data-driven methodology is applied to real regional highway bridges. The regional inspection information is obtained with the help of emerging technologies. The established structural deterioration models achieve up to 85% prediction accuracy. The obtained optimal maintenance schemes could be chosen according to actual structural conditions, maintenance requirements, and total budget. Data-driven decision support can substantially aid in smart and efficient maintenance planning of road bridges.

Numerical Modeling of Ice Accumulation on Three-Dimensional Bridge Cables under Freezing Rain and Natural Wind Conditions

“…The associated aerodynam acteristics were also investigated in this paper. Several conclusions can be drawn (1) To accurately predict the final iced shape, a three-dimensional ice accum model based on Messinger theory was proposed, which was programmed a bedded into computational fluid software. The proposed model can conside such as wind speed, temperature, air moisture content, and raindrop falling By controlling these factors, the possible iced shapes of bridge cables under d weather conditions can be obtained.…”

“…Bridges are critical for connecting people and goods in the transportation system [1,2]. Freezing rain has a serious impact on daily human life, such as the destruction of infrastructure facilities, the reduction of agriculture outputs, and even the malfunction of aircraft [3,4].…”

Application of Soft Computing Techniques in Bridge Health Assessment: A Review

“…The classification algorithm and clustering algorithm both were applied for solving the categorization and uncertainty problem. Xia et al proposed an artificial intelligence-based approach for condition assessment of regional bridges and optimizing their maintenance schemes [13]. The approach aggregated data, condition assessment and maintenance optimization.…”

Prediction of the severity of exceeding design traffic loads on highway bridges

“…Focusing on bridge engineering, MLMs have achieved encouraging levels of performance for several purposes. For example, they can: (a) establish data-driven bridge condition deterioration models at a regional level by relying on inspection reports; (b) develop fragility functions for bridges subjected to pier scour under vehicular loads; (c) quantify bridge damage by processing accelerometric signals ([ 34 , 35 ], and [ 36 ]).…”