A Weigh-in-Motion Characterization Algorithm for Smart Pavements Based on Conductive Cementitious Materials
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The Department of Civil, Construction, and Environmental Engineering seeks to apply knowledge of the laws, forces, and materials of nature to the construction, planning, design, and maintenance of public and private facilities. The Civil Engineering option focuses on transportation systems, bridges, roads, water systems and dams, pollution control, etc. The Construction Engineering option focuses on construction project engineering, design, management, etc.
History
The Department of Civil Engineering was founded in 1889. In 1987 it changed its name to the Department of Civil and Construction Engineering. In 2003 it changed its name to the Department of Civil, Construction and Environmental Engineering.
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1889-present
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- Department of Civil Engineering (1889-1987)
- Department of Civil and Construction Engineering (1987-2003)
- Department of Civil, Construction and Environmental Engineering (2003–present)
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- College of Engineering (parent college)
The Department of Electrical and Computer Engineering (ECpE) contains two focuses. The focus on Electrical Engineering teaches students in the fields of control systems, electromagnetics and non-destructive evaluation, microelectronics, electric power & energy systems, and the like. The Computer Engineering focus teaches in the fields of software systems, embedded systems, networking, information security, computer architecture, etc.
History
The Department of Electrical Engineering was formed in 1909 from the division of the Department of Physics and Electrical Engineering. In 1985 its name changed to Department of Electrical Engineering and Computer Engineering. In 1995 it became the Department of Electrical and Computer Engineering.
Dates of Existence
1909-present
Historical Names
- Department of Electrical Engineering (1909-1985)
- Department of Electrical Engineering and Computer Engineering (1985-1995)
Related Units
- College of Engineering (parent college)
- Department of Physics and Electrical Engineering (predecessor)
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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.
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This article is published as Birgin, Hasan Borke, Simon Laflamme, Antonella D’Alessandro, Enrique Garcia-Macias, and Filippo Ubertini. "A Weigh-in-Motion Characterization Algorithm for Smart Pavements Based on Conductive Cementitious Materials." Sensors 20, no. 3 (2020): 659. DOI: 10.3390/s20030659. Posted with permission.