A Weigh-in-Motion Characterization Algorithm for Smart Pavements Based on Conductive Cementitious Materials

by Hasan Borke Birgin ¹, Simon Laflamme ², Antonella D’Alessandro ¹, Enrique Garcia-Macias ¹ and Filippo Ubertini ^{1,* 1} Department of Civil and Environmental Engineering, University of Perugia, via Goffredo Duranti 93, 06125 Perugia, Italy ² Department of Civil, Construction and Environmental Engineering, Iowa State University, Ames, IA 50011, USA ^* Author to whom correspondence should be addressed.

Abstract

Smart materials are promising technologies for reducing the instrumentation cost required to continuously monitor road infrastructures, by transforming roadways into multifunctional elements capable of self-sensing. This study investigates a novel algorithm empowering smart pavements with weigh-in-motion (WIM) characterization capabilities. The application domain of interest is a cementitious-based smart pavement installed on a bridge over separate sections. Each section transduces axial strain provoked by the passage of a vehicle into a measurable change in electrical resistance arising from the piezoresistive effect of the smart material. The WIM characterization algorithm is as follows. First, basis signals from axles are generated from a finite element model of the structure equipped with the smart pavement and subjected to given vehicle loads. Second, the measured signal is matched by finding the number and weights of appropriate basis signals that would minimize the error between the numerical and measured signals, yielding information on the vehicle’s number of axles and weight per axle, therefore enabling vehicle classification capabilities. Third, the temporal correlation of the measured signals are compared across smart pavement sections to determine the vehicle weight. The proposed algorithm is validated numerically using three types of trucks defined by the Eurocodes. Results demonstrate the capability of the algorithm at conducting WIM characterization, even when two different trucks are driving in different directions across the same pavement sections. Then, a noise study is conducted, and the results conclude that a given smart pavement section operating with less than 5% noise on measurements could yield good WIM characterization results. View Full-Text Keywords: smart material; smart pavement; weigh-in-motion; piezoresistive; bridge; monitoring

Smart Graphite–Cement Composite for Roadway-Integrated Weigh-In-Motion Sensing

by Hasan Borke Birgin ¹, Antonella D’Alessandro ¹, Simon Laflamme ^2,* and Filippo Ubertini ^{1 1} Department of Civil and Environmental Engineering, University of Perugia, via Goffredo Duranti 93, 06125 Perugia, Italy ² Department of Civil, Iowa State University, Construction and Environmental Engineering, Ames, IA 50011, USA ^* Author to whom correspondence should be addressed.

Abstract

Smart multifunctional composites exhibit enhanced physical and mechanical properties and can provide structures with new capabilities. The authors have recently initiated a research program aimed at developing new strain-sensing pavement materials enabling roadway-integrated weigh-in motion (WIM) sensing. The goal is to achieve an accurate WIM for infrastructure monitoring at lower costs and with enhanced durability compared to off-the-shelf solutions. Previous work was devoted to formulating a signal processing algorithm for estimating the axle number and weights, along with the vehicle speed based on the outputs of a piezoresistive pavement material deployed within a bridge deck. This work proposes and characterizes a suitable low-cost and highly scalable cement-based composite with strain-sensing capabilities and sufficient sensitivity to meet WIM signal requirements. Graphite cement-based smart composites are presented, and their electromechanical properties are investigated in view of their application to WIM. These composites are engineered for scalability owing to the ease of dispersion of the graphite powder in the cement matrix, and can thus be used to build smart sections of road pavements. The research presented in this paper consists of electromechanical tests performed on samples of different amounts of graphite for the identification of the optimal mix in terms of signal sensitivity. An optimum inclusion level of 20% by weight of cement is obtained and selected for the fabrication of a plate of 30 × 15 × 5 cm³. Results from load identification tests conducted on the plate show that the proposed technology is capable of WIM. View Full-Text Keywords: smart materials; smart pavements; graphite; cement; weigh-in motion; strain