Big data-enabled multiscale serviceability analysis for aging bridges

This work is dedicated to constructing a multi-scale structural health monitoring system to monitor and evaluate the serviceability of bridges based on the Hadoop Ecosystem （MS-SHM-Hadoop）. By taking the advantages of the fault-tolerant distributed file system called the Hadoop Distributed File System （HDFS） and high-performance parallel data processing engine called MapReduce programming paradigm, MS- SHM-Hadoop features include high scalability and robustness in data ingestion, fusion, processing, retrieval, and analytics. MS-SHM-Hadoop is a multi-scale reliability analysis framework, which ranges from nationwide bridge-surveys, global structural integrity analysis, and structural component reliability analysis. This Nationwide bridge survey uses deep-learning techniques to evaluate the bridge service- ability according to real-time sensory data or archived bridge-related data such as traffic status, weather conditions and bridge structural configuration. The global structural integrity analysis of a targeted bridge is made by processing and analyzing the measured vibration signals incurred by external loads such as wind and traffic flow. Component-wise reliability analysis is also enabled by the deep learning technique, where the input data is derived from the measured structural load effects, hyper-spectral images, and moisture measurement of the structural components. As one of its major contributions, this work employs a Bayesian network to formulate the integral serviceability of a bridge according to its components serviceability and inter-component correlations. Here the inter-component correlations are jointly specified using a statistics-oriented machine learning method （e.g., association rule learning） or structural mechanics modeling and simulation.

Simplified full-depth precast concrete deck panel systems for accelerated bridge construction

A simplified full-depth precast concrete deck panel system for accelerating bridge construction （ABC） is introduced and a finite dement analysis （FEA） is con- ducted to investigate the static and dynamic responses of this conceptual deck system. The FEA results are compared to those of the traditional full-depth precast concrete deck panel system. The comparison results show that the mechanical behavior of the new deck system is different from that of the traditional deck system. The concrete decks in the new system act as two-way slabs, instead of the one-way slab in the traditional system. Meanwhile, the connections in both the longitudinal and transverse direc- tions may need to accommodate the negative moments. Compared to those in the traditional system, the longitu- dinal nominal stress at middle span increases a lot in the new deck system and the effective flange width varies significantly. In addition, the dynamic results show that the impact factor is influenced by the spacing of connections. Finally, some design concerns of the new deck system are proposed.