Electrical Resistivity Of Concrete Research Articles

Influences of metakaolin and calcined clay blended cement on chloride resistance and electrical resistivity of concrete

There are many different grades of kaolinite clays around the world. Low-grade kaolinite clay is more abundant than high-grade kaolinite clay in various regions. To aim toward the utilization of low-grade kaolinite clay having an original kaolinite content of about 40% to produce calcined clay, this paper investigated the durability properties of concrete incorporating calcined clay produced from high-grade kaolinite clay or high kaolinite content (commercially available metakaolin or CC1) and calcined clay produced from a low-grade kaolinite clay (CC2). Concrete mixtures were designed to have a water-to-binder ratio of 0.60. A fly ash-to-binder ratio of 0.20 and calcined kaolinite clay-to-binder ratios of 0.10 and 0.20 were studied. The chloride penetration resistance and the electrical resistivity of concrete were assessed, while the mercury intrusion porosimetry (MIP) was utilized in evaluating the pore structure of concrete. The test results revealed that concrete with CC1 and CC2 exhibited superior chloride penetration resistance and chloride binding capacity than OPC and FA20 concretes. Moreover, using a higher calcined clay-to-binder ratio resulted in a more refined pore structure, which significantly enhanced the chloride resistance of concrete. Although CC2 revealed less performance in improving chloride resistance than CC1, it had superior performance compared to fly ash.

Application of electrical resistivity for estimating compressive strength of FRC at early-ages

ABSTRACT The addition of fibers improves the ductility and compressive strength of concrete. Utilizing fiber in concrete, on the other hand, alter the electrical conductivity of concrete and that is especially important when concrete is being used in applications that electrical resistivity of concrete has been taken into account in the design process. Electrical resistivity of concrete can be measured using nondestructive testing techniques. Electrical resistivity has been proven to be in relationship with compressive strength of cementitious materials. The link between surface electrical resistivity (ER) and compressive strength (CS) of FRC at early ages has been investigated in the current study. Twenty-one distinct FRC mixtures have been cast using various fiber types, w/c ratios and fiber volume fractions. Test results have shown a strong relationship between electrical resistivity and mechanical properties of fiber reinforced concrete. A novel empirical equation has been proposed to estimate the compressive strength of early-age fiber reinforced concrete. The adequacy of this equation was determined by comparing actual and projected compressive strength values for FRC using a coefficient of variation. The early-age compressive strength of FRC was found to be reliable when the proposed equations were utilized.

Non-destructive corrosion inspection of reinforced concrete structures using an autonomous flying robot

Autonomous non-destructive testing (NDT) on reinforced concrete structures has a large potential to overcome the limitations of current routine inspection techniques, often not capable of detecting corrosion at an early stage. Here, the development and validation of two probes, tailored to acquire contact-based NDT data with the help of a hexacopter, is presented. Each probe allows the combined measurement of two essential parameters in the condition assessment: half-cell potentials and concrete electrical resistivity. Strategies are presented to monitor probe functionality during operation and detect loss of contact between probe and structure, which is considered essential for autonomous NDT. The presented approach enables effective and reliable autonomous corrosion inspection, surpassing traditional visual inspections by localizing corrosion at an early stage, allowing engineers a better planning of maintenance. The successful application in a concrete bridge inspection sets the stage for future research in autonomous inspections with robots in various fields of applications.

Study on the effect of dynamic flexural load on the electrical resistivity of concrete

Study on the effect of dynamic flexural load on the electrical resistivity of concrete

Influence of various parameters on the current distribution and protection degree of impressed current cathodic protection for reinforced concrete with TiMMO mesh anodes

Impressed current cathodic protection (ICCP) is an effective technique to control reinforcement corrosion in concrete structures. The efficiency and design of an ICCP system with titanium mixed metal oxide (TiMMO) anodes in a mortar overlay is strongly influenced by the current distribution to the different reinforcement layers of a reinforced concrete element. An in-depth experimental study is performed to investigate the effect of various parameters on the current distribution and degree of corrosion protection: (i) chloride content, (ii) cement type, and (iii) reinforcement configuration. 24-hour depolarization measurements (EN ISO 12696:2022) indicate that an increase in chloride concentration in the concrete, related to an increase in the rate of reinforcement corrosion, leads to a general decrease in the degree of protection. The use of a CEM III/A cement leads to a large increase in concrete electrical resistivity compared to concrete with an ordinary Portland cement (CEM I). This causes a lower total current output to the reinforcement and a less uniform distribution of current. Finally, a lower steel reinforcement density resulted in a larger current density, as the total current is distributed over a smaller steel surface area, causing higher depolarization values.

The impact of GGBS and ferrous on the flow of electrical current and compressive strength of concrete

• The impact of mix proportions on the electrical resistivity and compressive strength of normal strength concrete incorporated GGBS and waste steel slag. • Multi-scale models were developed to predict the electrical resistivity and compressive strength of normal strength concrete. • A difference-based method for constructing target electrical resistivity and compressive strength is proposed. • Models of use to improve the prediction accuracy of normal strength concrete modified with GGBS and SSA learning are proposed. Steel slag (SS) and Ground-granulated blast-furnace slag (GGBS) were widely utilized in concrete as a portion replacement for normal and crushed stone aggregate to improve mechanical qualities, namely compressive strength (CS), and electrical resistivity (ER). Mechanical attributes obtained early in construction are now crucial in construction design. Electrical resistivity (ER) is a frequently used non-destructive approach for evaluating the microstructure and quality of concrete. Moreover, (ER) is a key concrete feature since it allows engineers to monitor the concrete easily. The effect of steel slag as a partial substitute on concrete electrical resistivity and compressive strength requires a mathematical model. In this way, 134 literature data were gathered and examined. During the modeling process, the most significant elements that impact the CS and ER of concrete with steel slag substitute were examined, including curing time (1–90 days), cement content (92–469) kg/m 3 , water to cement ratio (0.3–0.75), fine aggregate (620–773.3 kg/m 3 ), and steel slag content (0–365 kg/m 3 ). The effect of steel slag as a partial substitute on concrete electrical resistivity and compressive strength requires a computational formula. Designers and concrete producers may use mathematical models to combine concrete with steel slag to obtain specified compressive strength without any experiments. In this study, the Multi Logistic Regression (MLR), an Artificial Neural Network (ANN), and a Full Quadratic (FQ) model were employed to predict the CS and ER of concrete with steel slag aggregate substitution. According to statistical analysis, the artificial neural network model predicted the CS and ER of concrete, including steel slag replacement, better than the other models (MLR, PQ). It has a higher coefficient of determination of 0.992 for ER and 0.993 for compressive strength (CS). It has a small root mean square error (RMSE) of 1.39 MPa and resistance of 28.82 Ω.m for CS and ER of concrete.

A Hybrid Particle Swarm Optimization with Dragonfly for Adaptive ANFIS to Model the Corrosion Rate in Concrete Structures

The use of reinforced concrete is common in marine structures. Failure of reinforcement due to corrosion has detrimental impacts on nearly all of these structures. Hence, proposing an accurate and reliable model was imperative. The goal of this paper is to develop a new hybrid model by combining Particle Swarm Optimization (PSO) with Dragonfly Algorithm (DA) for Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict the corrosion current density (C11) of marine reinforced concrete. The neuro-fuzzy-based methods have emerged as suitable techniques for encountering uncertainties associated with the corrosion phenomenon in marine structures. To the best of our knowledge, this is the first research that predicts the C11 through a model integrating fuzzy learning, neural learning rules, and meta-heuristics. 2460 data are collected from 37 regions in Persian Gulf. The input parameters are age, concrete repairing history, height above the sea level, distance from sea, concrete compressive strength, rebar diameter, concrete cover depth, concrete electrical resistivity, chloride ion concentration and pH. The proposed rules for the estimation of C11 based on collected dataset are assessed based on the several metrics such as R2, efficiency, mean absolute percentage error (MAPE), and median of absolute error (MEDAE). According to the results, ANFIS-PSO–DA enables to predict C11 by R2 (0.92), MAPE (1.67), MEDAE (0.14), and EF (0.97). The results of sensitivity analysis revealed that concrete compressive strength and pH are the most effective parameters on the corrosion current density of reinforced concrete.

Effects of Cement Type, Water-Cement Ratio, Specimen Size, and Curing Time on Concrete Electrical Resistivity

Effects of Cement Type, Water-Cement Ratio, Specimen Size, and Curing Time on Concrete Electrical Resistivity

Equivalent method for obtaining concrete age on the basis of electrical resistivity

Concrete age is the time since the moment water is added to the cement, and the age of concrete comprehensively reflects the physical properties of the concrete when curing under standard conditions. For concrete under nonstandard conditions, its physical properties are directly related to both its age and temperature history. The equivalent age of concrete is the time at which concrete under nonstandard conditions reaches the same state as concrete under standard conditions. Most equivalent methods, such as the Nurse-Saul function and the Arrhenius function, are based on a maturity index. However, the accuracy of these methods breaks down when the curing temperature range is wide. In this paper, the electrical resistivity of concrete is used as the index to determine the equivalent age of concrete. This method is based on the assumption that concrete with the same mixture proportions has the same electrical resistivity when the maturity of the concrete is the same, regardless of the curing history. The proposed method is advantageous because it can be performed in real time and is nondestructive. To constantly measure the electrical resistivity of concrete, an automatic data acquisition system is developed to monitor the electrical resistivity of concrete and reduce the error caused by polarization as much as possible. Then, a model for predicting the electrical resistivity of concrete under different curing temperatures is proposed to conveniently calculate the equivalent coefficient. Finally, the results calculated by the proposed equivalent method are compared with those of the standard method (Nurse-Saul equation), and the results of the proposed model are found to be more reasonable.

Using electrical resistivity to determine the efficiency of supplementary cementitious materials to prevent alkali-silica reaction in concrete

In this study, the miniature concrete prism test (MCPT) was used to evaluate expansion due to alkali-silica reaction (ASR) in concrete mixtures with very highly reactive fine aggregates and supplementary cementitious materials (SCMs). The concrete pore solution alkalinity and transport properties of concrete measured through bulk electrical resistivity were determined to investigate their correlation to the MCPT expansions. The findings showed that the concrete mixtures with SCM combinations that resulted in higher bulk electrical resistivity and lower pore solution alkalinity had less ASR expansion in the MCPT conditions. A potential new approach to determine the efficiency of SCM combinations to prevent ASR was proposed by combining the hydroxide concentration of pore solution and electrical resistivity of concrete.

Spatial variability of concrete electrical resistivity and corrosion rate in laboratory conditions

Spatial variability of reinforced concrete structures is responsible for part of the uncertainties that are associated with most parameters in structural durability and reliability models. Consequently, its effects should not be overlooked on structural reliability analysis for deteriorating structures. The present study characterized the spatial variability of concrete electrical resistivity and corrosion rate by means of descriptive statistics, estimations of probability density functions and correlation matrices. Data for these two corrosion parameters was obtained by monitoring two 50cm×40cm×10cm reinforced concrete slabs on a laboratory environment. Chloride was added to the mix of one of these specimens in order to promote corrosion. The main objective of the test set was to contribute in quantifying and characterizing the spatial variability of these two corrosion parameters in order to improve inspection planning of concrete structures and also probabilistic models that employ these parameters as variables. The variation obtained for corrosion rate and resistivity was considerable taking into account the small size of specimens tested. When compared with concrete resistivity, corrosion rates presented a larger spatial variability, especially when there is active corrosion. Data distribution for resistivity was found to be positively skewed. Correlation between resistivity values obtained in different locations of the slabs was strong, decreasing with distance as expected. As such, the spatial autocorrelation was determined for the concrete resistivity. On the contrary, adjacent measurements of corrosion rate showed no correlation between themselves. A better knowledge of the variables behaviour is fundamental for the quality of any probability based model.

Effect of the Geometrical Constraints to the Wenner Four-Point Electrical Resistivity Test of Reinforced Concrete Slabs.

The main objectives of this study are to evaluate the effect of geometrical constraints of plain concrete and reinforced concrete slabs on the Wenner four-point concrete electrical resistivity (ER) test through numerical and experimental investigation and to propose measurement recommendations for laboratory and field specimens. First, a series of numerical simulations was performed using a 3D finite element model to investigate the effects of geometrical constraints (the dimension of concrete slabs, the electrode spacing and configuration, and the distance of the electrode to the edges of concrete slabs) on ER measurements of concrete. Next, a reinforced concrete slab specimen (1500 mm (width) by 1500 mm (length) by 300 mm (thickness)) was used for experimental investigation and validation of the numerical simulation results. Based on the analytical and experimental results, it is concluded that measured ER values of regularly shaped concrete elements are strongly dependent on the distance-to-spacing ratio of ER probes (i.e., distance of the electrode in ER probes to the edges and/or the bottom of the concrete slabs normalized by the electrode spacing). For the plain concrete, it is inferred that the thickness of the concrete member should be at least three times the electrode spacing. In addition, the distance should be more than twice the electrode spacing to make the edge effect almost negligible. It is observed that the findings from the plain concrete are also valid for the reinforced concrete. However, for the reinforced concrete, the ER values are also affected by the presence of reinforcing steel and saturation of concrete, which could cause disruptions in ER measurements.

RETRACTED: Influence of magnetized water and water/cement ratio on the properties of untreated coal fine aggregates concrete

This study intends to find solutions to increase the untreated coal fine aggregate (UCFA) content as a replacement of natural fine aggregates (NFA) using magnetized water (MW). 112 concrete mixes are produced and tested. Seven UCFA incorporation ratios are used: 0%, 5%, 10%, 15%, 20%, 25% and 30% in term of weight. Using MW in concrete has a significant effect on both the fresh- and hardened-state properties of concrete. Hence, four water magnetization intensities are used (0, 0.6, 1.2 and 1.8 T). Moreover, four base concrete mixes with water-to-cement ratios (W/C) of 0.35, 0.4, 0.45, and 0.5 are produced, and the slump, compressive, tensile and flexural strengths, modulus of elasticity and electrical resistivity of concrete are evaluated. One sample is selected as a control specimen with no UCFA and with tap water. The results are compared with those from previous models to predict the mechanical properties of concrete, and new models are developed to anticipate the hardened-state performance of concrete when both UCFA and MW are used. The results show that 15% NFA can be replaced with UCFA when 1.2 T MW is used with no reduction in compressive and tensile strengths. Moreover, the proposed models can be employed with high accuracy to estimate the modulus of elasticity, splitting tensile and flexural strengths of UCFA concrete based on the compressive strength when MW at different intensities is used. • Effect of water magnetization intensity and W/C ratio on the properties of UCFA concrete. • Effect of UCFA on the fresh and hardened properties of concrete. • 112 mixes with various UCFA contents and water magnetization intensities are produced. • New models predict the hardened-state properties of UCFA concrete with magnetized water.

Effect of Capillary Water Absorption on Electrical Resistivity of Concrete with Coal Gangue Ceramsite as Coarse Aggregates

This study intends to access the influence of the capillary action on electrical property of the concrete containing the coal gangue ceramsite. For this purpose, four kinds of concrete samples were prepared; the coal gangue ceramsite was adopted at four volume ratios of 0%, 30%, 60%, and 100%, respectively. The resistivity of the samples was explored using the two-electrode method during the capillary action. The effects of the coal gangue ceramsite contents on capillary water absorption capacity and resistivity of the matrix were verified. The variation of the resistivity of the matrix under the influence of capillary water transmission was analyzed. The results demonstrated that, for the unsaturated concrete, the resistivity of the matrix increased with the increment of the coal gangue ceramsite dosage. The electrical properties of the concrete were affected noticeably by the capillary water absorption of the matrix; the resistivity of the matrix dropped significantly under the capillary suction, which may be attributed to the formation of the new conductive channels caused by the absorbed water. The variation of the resistivity of the concrete under the capillary suction sustained the two-stage reduction curve. The ability of the capillary water absorption of concrete was enhanced with the addition of coal gangue ceramsite, compared to the traditional aggregates concrete, the initial sorptivity, and secondary sorptivity of the matrix increased by 47% and 16% with the 100% content of coal gangue ceramsite. However, during the process of the capillary suction, the resistivity of the coal gangue ceramic concrete was always greater than that of the concrete with traditional crushed aggregates.

The influence of the binder type & aggregate nature on the electrical resistivity of conventional concrete

Concrete has been largely used in civil engineering due to its interesting fresh and hardened state properties. The 28-day compressive strength is the most important concrete property, being frequently used as an indicator of the material's quality. In this context, early-age mechanical properties (e.g., compressive strength) are becoming more critical nowadays to optimize construction scheduling. Several advanced techniques have been proposed in this regard and among those, electrical resistivity (ER) has been showing promising results. Yet, recent literature data have evidenced that ER might be significantly influenced by a variety of parameters such as the supplementary cementing materials (SCM) type/amount and aggregates nature used in the mix. These factors can hinder the practical benchmark of concrete mixtures proportioned with distinct raw materials. This work aims to appraise the influence of the coarse aggregate nature and binder replacement/amount on concrete ER and compressive strength prediction models through ER measurements using 24 mixtures manufactured with two different coarse aggregates natures (i.e., granite and limestone), two water-to-binder ratios (i.e., 0.6 and 0.4), and incorporating two different SCMs (i.e., slag, and fly-ash class F) with different replacement levels. Three distinct ER techniques (e.g., bulk, surface, and internal) and compressive strength tests were performed at different concrete ages (i.e., 3, 7, 14, and 28 days). Results indicated that the binder type and replacement amount significantly affect ER and compressive strength. The coarse aggregate nature presented minor influence for “ordinary” quality mixtures, while showing important impact on refined microstructure mixes. Finally, ER techniques, especially internal ER, were found to be quite reliable to predict the compressive strength of conventional concrete made of single, binary, and ternary binder blends. • The electrical resistivity (ER) setup highly influences the test outcomes. • The SCMs type and replacement amount significantly impacts on ER results. • The coarse aggregate nature does influence on the ER of low-quality mixtures. • The coarse aggregate nature affects ER of mixtures with refined microstructure.

An Embedded-Sensor Approach for Concrete Resistivity Measurement in On-Site Corrosion Monitoring: Cell Constants Determination.

The concrete electrical resistivity is a prominent parameter in structural health monitoring, since, along with corrosion potential, it provides relevant qualitative diagnosis of the reinforcement corrosion. This study proposes a simple expression to reliable determine resistivity from the concrete electrical resistance (RE) provided by the corrosion sensor of the Integrated Network of Sensors for Smart Corrosion Monitoring (INESSCOM) we have developed. The novelty here is that distinct from common resistivity sensors, the cell constants obtained by the proposed expression are intended to be valid for any sensor implementation scenario. This was ensured by studying most significant geometrical features of the sensor in a wide set of calibration solutions. This embedded-sensor approach is intended to be applicable for RE measurements obtained both using potential step voltammetry (PSV, used in the INESSCOM sensor for corrosion rate measurement) and alternating current methods. In this regard, we present a simple protocol to reliably determine RE, and therefore resistivity, from PSV measurements. It consists in adding a very short potentiostatic pulse to the original technique. In this way, we are able to easy monitor resistivity along with corrosion rate through a single sensor, an advantage which is not usual in structural health monitoring.

Effect of sawdust ash and laterite on the electrical resistivity of concrete

Effect of sawdust ash and laterite on the electrical resistivity of concrete

Electrical properties of fibrous self-compacting concrete reinforced with different types of fibers

Abstract Concrete is a heterogeneous multiple-phased material, and its microstructure contains many flaws. These flaws are microcracks, cavities, interconnected micropores. External current if applied on concrete which can be transferred through the migrating ions. Hence, the electrical resistivity measurement is a reliable facility for exploring the microstructure of concrete. The electrical resistivity of concrete is an essential factor describing the ability of a material to conduct current. The addition of discreet Fibers to reinforcing concrete is broadly used due to its advantageous mechanical properties. The rapid spread of concrete microcracks can be reduced or avoided due to the fibres' prepotent tensile strength. This paper investigates the effects of three types of steel fibres; these fibres are straight, hooked end, and micro steel fibres. Also, three types of carbon fibres were added to the SSC mixes, these fibres are; whiskers, multi-walled carbon nanotubes, and single-walled carbon nanotubes fibre predetermine percentages. Electrical resistivity calculations were done at 200 V, 220 V, and 240 V. The mechanical properties include compressive strength, flexural strength, and static modulus of elasticity. The results show that the carbon nanotubes fibres improve the electrical resistivity by 400% and 423% for SWCNTs and MWCNTS. Moreover, the strengths and ultrasonic pulse velocity of self-compacted concrete (SCC) are increased compared to plain concrete (control mix).

Strength and durability characteristics of binary blended recycled coarse aggregate concrete containing microsilica and metakaolin

Concrete is an important construction material. However, the consumption of natural aggregates in concrete production is responsible for depleting natural resources. Utilization of construction waste as recycled aggregate to replace natural aggregate in concrete construction is a great way to save the natural aggregate and manage the construction waste in an efficient manner. In the current study, compressive strength, water absorption and electrical resistance of concrete were investigated by replacing the natural coarse aggregate (NCA) with recycled coarse aggregate (RCA) in the ratio of 50% and 100%. In addition, 10% cement was replaced with microsilica (MS) and metakaolin (MK) in RCA concrete mixes. Results show that RCA concrete had lower strength than NCA concrete; however, the strength of RCA concrete was improved by using binary blends of supplementary cementitious materials (SCMs). The SCM’s effect was found to be positive on water absorption and electrical resistivity of RCA concrete, water absorption was reduced, and electrical resistivity was increased. Further, the electrical resistivity results show that inclusion of SCMs reduces the chance of having corrosion in RCA concrete particularly using MK. Moreover, the microstructure investigations revealed that the incorporation of binary blends of SCMs reduces the voids in the RCA concrete and the microstructure of the concrete appears to be dense. Eventually, 100% RCA with binary blends of MS or MK can be used for the production of up to M35 grade concrete for practical concrete construction applications.

Prediction of the Tensile Strength and Electrical Resistivity of Concrete with Organic Polymer and their Influence on Carbonation Using Data Science and a Machine Learning Technique

The inclusion of additions to concrete blends helps to improve performance in certain conditions. The analysis of two concrete blends was performed, a blend with the addition of a natural organic polymer and a control blend to make predictive models and find a correlation. Tree tests were performed: Electrical resistivity (Er) test, Tensile strength (Ft) and Carbonation resistance. One of the most popular non-destructive tests on concrete is , due to the simplicity of measuring readings on concrete elements. It is a non-destructive test that determines the interconnectivity that exists in the concrete cementitious matrix by determining the quality of the concrete. The blend with the addition showed improved performance in all the tests. Data science techniques were used to generate artificial data, the Machine Learning technique (ML) is based on Tree regression (Tr) with satisfactory accuracy to assess the reliability.