Accurate strength prediction models of ordinary concrete using early-age complex permittivity

Early determination of correct cement dosage for concrete mixes and prediction of their compressive strengths are very valuable in construction industry. This article presents a few compressive-strength prediction models for ordinary concrete using early-age measurements of relative complex permittivity. Both the dielectric constant and loss factor of the first-seven-day concrete with four types of mix proportions were measured for building the mathematical models composed of exponential functions at 6 GHz, whereas the measured dielectric data at 28 d were used for model validations. The proposed models not only have high regression accuracy with R2-values of greater than 0.97 but also the low prediction errors of within 10%, which significantly outperform the existing models of the same kind. Through Cole–Cole plot analysis, this article reveals an interesting finding that a minimum loss factor was located at 3 GHz regardless of the age of concrete, which would be useful for wireless network design and planning inside a building. The average loss tangents of various concrete mixes have also been verified to have the same value (~ 0.33) regardless of concrete age, which explains the confidence in use of early-age dielectric properties. Moreover, this article also initiates a precise prediction method of using loss factor and dielectric constant simultaneously in a 3-dimensional plot, wherein no explicit mathematical model is required.

[1]  Hadi Alidoustaghdam,et al.  Non-Destructive Testing of Concrete Tunnels With Qualitative Microwave Imaging , 2020, 2020 German Microwave Conference (GeMiC).

[2]  Kwok L. Chung,et al.  Dielectric Characterization of Chinese Standard Concrete for Compressive Strength Evaluation , 2017 .

[3]  M. A. Aziz,et al.  Application of microwave waveguide techniques for investigating the effect of concrete dielectric and reflection properties during curing , 2021 .

[4]  Reza Zoughi,et al.  Feasibility of using near-field microwave reflectometry for monitoring autogenous crack healing in cementitious materials , 2018 .

[5]  H. Leuenberger,et al.  Cole–Cole plot analysis of dielectric behavior of monoalkyl ethers of polyethylene glycol (CnEm) , 2008 .

[6]  Fazhou Wang,et al.  Hydration monitoring and strength prediction of cement-based materials based on the dielectric properties , 2016 .

[7]  O. Uyanik,et al.  Determination of the reinforced concrete strength by apparent resistivity depending on the curing conditions , 2018, Journal of Applied Geophysics.

[8]  H. Al-Mattarneh Determination of chloride content in concrete using near- and far-field microwave non-destructive methods , 2016 .

[9]  L. Jofre,et al.  Debye Frequency-Extended Waveguide Permittivity Extraction for High Complex Permittivity Materials: Concrete Setting Process Characterization , 2020, IEEE Transactions on Instrumentation and Measurement.

[10]  Zhe Li,et al.  Influence of Moisture Content on Electromagnetic Response of Concrete Studied Using a Homemade Apparatus , 2019, Sensors.

[12]  Li Sun,et al.  Microwave Non-Destructive Inspection and Prediction of Modulus of Rupture and Modulus of Elasticity of Engineered Cementitious Composites (ECCs) Using Dual-Frequency Correlation , 2017, Sensors.

[13]  Kok Yeow You,et al.  Review on microwave nondestructive testing techniques and its applications in concrete technology , 2019, Construction and Building Materials.

[15]  Hongyan Ma,et al.  Reactive Molecular Simulation on Water Confined in the Nanopores of the Calcium Silicate Hydrate Gel: Structure, Reactivity, and Mechanical Properties , 2015 .

[16]  José Luís Duarte Granja,et al.  Testing Concrete E‐modulus at Very Early Ages Through Several Techniques: An Inter‐laboratory Comparison , 2016 .

[17]  B. Bhattacharjee,et al.  Electrical response-based technique for estimation of degree of moisture saturation in cement concrete and mortar in drying and wetting cycle , 2020 .

[18]  Sergey Kharkovsky,et al.  Monitoring of Microwave Properties of Early-Age Concrete and Mortar Specimens , 2015, IEEE Transactions on Instrumentation and Measurement.

[19]  K. Chung,et al.  Prediction of concrete compressive strength based on early-age effective conductivity measurement , 2020 .

[20]  Ravindra K. Dhir,et al.  Establishing a relationship between modulus of elasticity and compressive strength of recycled aggregate concrete , 2016 .

[21]  R. Lovell Application of Kramers-Kronig relations to the interpretation of dielectric data , 1974 .

[22]  Niwat Angkawisittpan,et al.  Determination of Relationship between Dielectric Properties, Compressive Strength, and Age of Concrete with Rice Husk Ash Using Planar Coaxial Probe , 2016 .

[23]  Reza Zoughi,et al.  Comparison of Alkali–Silica Reaction Gel Behavior in Mortar at Microwave Frequencies , 2015, IEEE Transactions on Instrumentation and Measurement.

[24]  M. Jamil,et al.  Concrete dielectric properties investigation using microwave nondestructive techniques , 2013 .

[25]  G. Song,et al.  Monitoring early-age hydration and setting of portland cement paste by piezoelectric transducers via electromechanical impedance method , 2020 .

[26]  Zhitian Liu,et al.  Study on the hydration of young concrete based on dielectric property measurement , 2019, Construction and Building Materials.

[27]  Dan G Zollinger,et al.  Concrete pavements curing evaluation with non-destructive tests , 2017 .

[28]  Francesco Fabbrocino,et al.  An Embedded Wireless Sensor Network with Wireless Power Transmission Capability for the Structural Health Monitoring of Reinforced Concrete Structures , 2017, Sensors.

[29]  Na Lu,et al.  Embeddable Piezoelectric Sensors for Strength Gain Monitoring of Cementitious Materials: The Influence of Coating Materials , 2020 .

[30]  Li Lu,et al.  Piezoresistive properties of cement composites reinforced by functionalized carbon nanotubes using photo-assisted Fenton , 2017 .

[31]  H. Pan,et al.  Piezoelectric cement sensor-based electromechanical impedance technique for the strength monitoring of cement mortar , 2020 .

[32]  David J. Edwards,et al.  Real-time structural health monitoring for concrete beams: a cost-effective ‘Industry 4.0’ solution using piezo sensors , 2020 .

[33]  Anna De Falco,et al.  Dynamic structural health monitoring for concrete gravity dams based on the Bayesian inference , 2020 .

[34]  Maria A. Stuchly,et al.  ANA Calibration Method for Measurements of Dielectric Properties , 1983, IEEE Transactions on Instrumentation and Measurement.

[35]  P. Rattanadecho,et al.  Microwave-assisted heating of cementitious materials: Relative dielectric properties, mechanical property, and experimental and numerical heat transfer characteristics☆ , 2010 .

[36]  F. Boone,et al.  Design and Calibration of a Large Open-Ended Coaxial Probe for the Measurement of the Dielectric Properties of Concrete , 2008, IEEE Transactions on Microwave Theory and Techniques.

[37]  Said Jalali,et al.  NDT measurements for the prediction of 28-day compressive strength , 2010 .

[38]  Nicholas J. Carino,et al.  The Maturity Method: Theory and Application , 1984 .

[39]  Ming Wang,et al.  Calibration of Elasto-Magnetic Sensors on In-Service Cable-Stayed Bridges for Stress Monitoring , 2018, Sensors.