The construction industry has embraced sensors that are embedded in concrete and measure its strength in real time. The technology, developed by civil engineers at Purdue University, allows project managers to save time and labor.
Just a few hours of delays per floor in the construction of a multistory building can cost more than a million dollars. General contractors can incur contractual penalties of up to $50,000 a day for not meeting a project’s deadline. This is in addition to the extra costs for equipment and labor when a project exceeds its projected timeline.
Similarly, public road construction projects that surpass projected timeframes add to traffic congestion, which costs drivers an estimated 21 gallons of fuel and 50 hours of time per year. This adds up annually to a loss of more than $1,080 per commuter and a nationwide cost of over $160 billion. Each United States household, on average, spends $3,400 per year coping with infrastructure repairs and deficiencies
Smart Concrete Sensors Offer Innovative Alternative
To address this deficiency, Professor Luna Lu’s team at the Lyles School of Civil Engineering at Purdue University is developing smart concrete sensors. These cost-effective and easy-to-use tools have the potential to address longstanding testing limitations by accurately determining proper curing time and other attributes of placed concrete.
Instead of concurrent samples that must be destructively tested in off-site facilities at a later time, the sensors are embedded in the placed concrete during construction and measure real-time concrete strength on an ongoing basis.The sensor technology takes advantage of the electromechanical effect to determine concrete strength and other attributes in just a few seconds at any post-placement time interval.
Mechanical vibrations of concrete reflect its strength and stiffness. Lu’s new piezoelectric sensors convert concrete’s vibrations into electrical signals, which are then read through sensor data loggers and processed using unique software and mathematical models developed by Lu’s team.
This technology works for any concrete mix design and does not require precalibration or preprocessing, which differentiates this technology from others like the maturity method. The strength information is more accurate compared with traditional off-site samples’ testing.