Abstract
With the help of community participants, smartphones can become useful wireless sensor network (WSN) components, form a self-governing structural health monitoring (SHM) system, and merge structural mechanics with participatory sensing and server computing. This paper presents a methodology and framework of such a cyber-physical system (CPS) that generates a bridge finite element model (FEM) integrated with vibration measurements from smartphone WSNs and centralized/distributed computational facilities, then assesses structural reliability based on updated FEMs. Structural vibration data obtained from smartphones are processed on a server to identify modal frequencies of an existing bridge. Without design drawings and supportive documentation but field measurements and observations, FEM of the bridge is drafted with uncertainties in the structural mass, stiffness, and boundary conditions (BCs). Then, 2700 FEMs are autonomously generated, and the baseline FEM is updated by minimizing the error between the crowdsourcing-based modal identification results and the FEM analysis. Furthermore, using 151 strong ground motion records from databases, the bridge response time history simulations are conducted to obtain displacement demand distribution. Finally, based on reference performance criteria, structural reliability of the bridge is estimated. Integrating the cyber (FEM analysis) and the physical (the bridge structure and measured vibration characteristics) worlds, this crowdsourcing-based CPS can provide a powerful tool for supporting rapid, remote, autonomous, and objective infrastructure-related decision-making. This study presents a new example of the emerging fourth industrial revolution from structural engineering and SHM perspective.
Highlights
Deriving economical, sustainable, and practical solutions without a compromise in infrastructure safety and integrity is a broad challenge in civil and structural engineering disciplines
At the end of the loop analyses, the optimal model which minimizes the error between the. In the former studies, the authors adopted Least Square Method (LSM) to formulate the objective function [46,47] whereas different approaches are present in the literature [55,56], in this study, the mode=1 where boundary conditions (BCs), K, M represent changing finite element model (FEM) parameters such as boundary condition (BC), member stiffness, and mass values, respectively
Following the outline presented in the methodology, the testbed bridge data is used for modal identification, FEM updating, and reliability estimation with the updated model
Summary
Sustainable, and practical solutions without a compromise in infrastructure safety and integrity is a broad challenge in civil and structural engineering disciplines. Collecting the distributed crowd sensed information through a central server and conducting modal identification autonomously, civil infrastructures as physical objects are connected with server-side computing in a massive scale forming a CPS [37,38,39,40,41], or in some cases, an Internet of Things system [42,43,44,45]. This highlights a significant potential to evolve from pure theoretical structural response simulation (FEM) to experiment-aided and calibrated models (model updating) in massive scales.
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