Abstract
Rural footbridges have proved to be an impetus for growth in vulnerable areas of the developing world, increasingly being built in many isolated communities around continents. Yet, little prior assessment of their dynamic characteristics had been made due to the non-traditional constraints that arise from instrumenting footbridges in rural, off-grid settings across multiple continents. Their characteristics remain largely unknown even if the low mass and flexible nature of rural footbridges make them vulnerable to wind-induced motions. To this end, this study proposes a data-enabled prediction framework based on a novel citizen sensing protocol, which aims at predicting the dynamic properties of rural footbridges during the conceptual design phase to enhance their safety under winds. The protocol is established which enables non-experts including local citizens in isolated communities to collect vibration data of rural footbridges by way of rapidly deployable and low-cost sensing systems in a novel application to full-scale monitoring with the concept of the community engagement. This citizen sensing data helps not only establish database with dynamic properties, but also develop empirical models to predict their dynamic properties of a footbridge in the conceptual design phase without detailed and bridge-specific dynamic modeling. In addition. a simple yet effective batch processing procedure to be done by non-experts is also devised to readily process upcoming citizen sensing data from new footbridges in the future, which offers instant and continuous updates of existing database with minimal efforts for enhancing the knowledge and the prediction of dynamic characteristics of rural footbridges.
Highlights
Rural infrastructure plays an important role in poverty alleviation, giving isolated communities access to essential healthcare, education, and economic opportunities
The data-enabled prediction framework involving novel citizen sensing protocol, database framework, empirical models, and batch processing procedure introduced in this study allow for the establishment of baseline dynamic properties for a rural footbridge design
Trends from the current set of sixteen footbridges that have been monitored to date provide a starting point for establishing trends in the relationship between key input design variables and natural frequencies and damping ratios of footbridges
Summary
Rural infrastructure plays an important role in poverty alleviation, giving isolated communities access to essential healthcare, education, and economic opportunities. Note that data obtained through the citizen sensing protocol are utilized to estimate the fundamental frequencies and damping values of the vertical and torsional modes of rural footbridges. The databasing procedure considers the following constraints to accommodate: (a) Data from multiple footbridges; (b) Data inputs of variable quality; (c) Variable time synchronization between sensors; (d) Variable fidelity of output dynamic properties These constraints are overcome through the following Framework Controls procedure (Figure 6): (a) Automatic dominant mode identification; (b) “Goodness of fit” threshold; (c) Automatic time shifting; (d) Spatial Repeatability Measure. It is the only one in the database which was not built by the B2P; it was constructed through a TABLE 4 | Design parameters of B2P footbridges
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