| Literature DB >> 35683133 |
Kousalya Ramachandran1, Ponmalar Vijayan1, Gunasekaran Murali2, Nikolai Ivanovich Vatin2.
Abstract
Self-sensing concrete is a smart material known for its cost-effectiveness in structural health-monitoring areas, which converts the external stimuli into a stress/strain sensing parameter. Self-sensing material has excellent mechanical and electrical properties that allow it to act as a multifunctional agent satisfying both the strength and structural health-monitoring parameters. The main objective of this review is to understand the theories and principles behind the self-sensing practices. Many review papers have focused on the different types of materials and practices that rely on self-sensing technology, and only a few articles have discussed the theories involved. Understanding the mechanism and the theories behind the conduction mechanism is necessary. This review paper provides an overview of self-sensing concrete, including the principles such as piezoresistivity and piezopermittivity; the tunnelling effect, percolation threshold, and electrical circuit theories; the materials used and methods adopted; and the sensing parameters. The paper concludes with an outline of the application of self-sensing concrete and future recommendations, thus providing a better understanding of implementing the self-sensing technique in construction.Entities:
Keywords: electrical resistance; gauge factor; percolation threshold; piezopermittive; piezoresistive; self-sensing; tunnelling effect
Year: 2022 PMID: 35683133 PMCID: PMC9181339 DOI: 10.3390/ma15113831
Source DB: PubMed Journal: Materials (Basel) ISSN: 1996-1944 Impact factor: 3.748
Conventional Sensors Used in Building Aspects.
| Sensor Type | Application | Limitations |
|---|---|---|
| Accelerometer [ | Measures the motion and vibration of a structure that is exposed to dynamic loads | Low durability and non-intrinsic |
| Extensometer [ | Measures the elongation of material subjected to stress | Vulnerable and less sensitivity |
| Strain gauge [ | Determines stresses in the structure by responding to the changes in dimensions due to creep, crack, temperature change, moisture change, etc. | Low sensing, worse durability and non-intrinsic |
| Piezoelectric sensors [ | Measure impedance-based damage detection, guided wave damage detection, and structural dynamics applications in a structure | More AUD is required and non-intrinsic |
| Optical fibre sensors [ | Measure the strain, temperature, and pressure in a structure | Vulnerable and non-intrinsic |
| Wireless smart sensors [ | Detect, locate, and assess structural damages in a structure | Complication in implementing |
| Vision-based displacement measurement system [ | Used for sensing the displacements in a structure | Not accurate and non-intrinsic |
| Shape Memory Alloy [ | Used in building materials to withstand varied thermal conditions by gaining its original properties | More AUD is required and non-intrinsic |
Figure 1Applications of self-sensing in building elements.
Figure 2Past literature works (Scopus Indexed) published on self-sensing.
Properties adopted for different methods of electromechanical principle.
| Condition | Piezoresistivity | Piezopermittivity | Piezoelectricity |
|---|---|---|---|
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| Change in electrical resistivity on the application of external stimuli | Change in capacitance on subjected to external stimuli | Change in Electric field, on subjected to external stimuli |
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| Conductive filler (steel fibre, nano nickel particles, carbon fibre, carbon nanotube, functionalized graphene groups) and non-conductive matrix (cement-based composites, alkali-based materials, etc.) | Composite (fibre reinforced polymer matrix, concrete), dielectric film and electrodes (copper, aluminium or steel) | Conductive filler (steel fibre, nano nickel particles, carbon fibre, carbon nanotube, functionalized graphene groups) and non-conductive matrix (cement-based composites, alkali-based materials, etc.) |
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| Current and Voltage | Frequency | Voltage |
Figure 3(a) Two-probe specimen setup. (b) Piezoresistive behaviour of the specimen under the loading condition.
Types of fillers used in self-sensing and their properties.
| Conductive Material | Geometric Shape | Tensile Strength (GPa) | Elastic Modulus (GPa) | Aspect Ratio | Density (kg/m3) |
|---|---|---|---|---|---|
| Steel fibres (straight) [ | Fibre (Micro filler) | 500 | 200 | 97.5 | 7850 |
| Steel fibres (twisted) [ | Fibre (Micro filler) | 2428 | 200 | 100 | 7900 |
| Carbon nano fibre [ | Particle (Micro filler) | 4900 | 230 | 100–500 | 1000 |
| CNT [ | Particle (Nano filler) | 11 | 300–1000 | ~1000 | 50–150 |
| Nano graphene platelets [ | Particle (Nano filler) | 5000 | 1000–2000 | 50–300 | 1800 |
| Carbon black [ | Particle (Nano filler) | 2000–2400 | - | 120 | 1800–2100 |
Figure 4Percolation graph.
Figure 5Thetunnelling effect.
Influencing parameters of the percolation threshold.
| Parameter | Formula | Description |
|---|---|---|
| Filler geometry |
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| Filler and matrix properties |
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| R1 = particle size of the major filler, R2 = particle size of the minor filler. | |
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| Ellipsoidal filler in an isotropic composite with random orientation [ | |
| Filler concentration |
| δ = electrical conductivity of the material, δf = conductivity of the filler material, φ = filler concentration, φc = percolation threshold, Insulation Zone Percolation Zone Conducting Zone |
Percolation thresholds for different filler materials with respect to their matrix.
| Filler | Matrix | % of Fibres | Percolation Threshold (%) | References |
|---|---|---|---|---|
| Carbon black | Cementitious material | 0.2–0.5 | 7.22–11.39 | [ |
| Expanded graphite | High Density Polyethylene | 0.1 | 4.46 | [ |
| Graphite | Epoxy | 0.5 | 1.13 | [ |
| Graphite | Poly(styrene-methyl methacrylate) | 0.5, 1 | 0.878 | [ |
| Expanded graphite | Polymethylmethacrylate | 1 | 0.529 | [ |
| Graphite nanoplatelets | Polypropylene | - | 0.67 | [ |
| Graphite nanoplatelets | Epoxy | 0.2, 0.4, 0.6 | 0.5 | [ |
| Graphite nanoplatelets | Polymer composite | 0.5 | 0.52 | [ |
| Carbon fibres | polymer matrix | 1, 1.5 | 0.9 | [ |
| MWCNT | Cementitious material | 0.5, 1.15 | 1.00 | [ |
| MWCNT | Cementitious material | 1 | 1.15 | [ |
| MWCNT | Cementitious material | 0.3–0.6 | 0.35–0.7 | [ |
Figure 6Four-probe and two-probe configurationsin concrete.
Resistivity of materials according to contact mode.
| Matrix | Fibre (%) | Method | Electrode Type | Current Type | Resistivity (Ω·cm) × 103 | References |
|---|---|---|---|---|---|---|
| Alkali activated blast furnace slag | Carbon fibre (0.58) | Four-probe method | Silver paint wrapped with copper wire | DC | 9.956 | [ |
| E.C.C. | Carbon fibre (1) | Surface electrodes | An electrode made up of copper plate | AC | 7.5 | [ |
| ECC | CNT (0.5) | Surface electrodes | An electrode made up of copper plate | AC | 84.5 | [ |
| E.C.C. | Carbon black (0.01) | Surface electrodes | An electrode made up of copper plate | AC | 97.34 | [ |
| UHPC | Steel fibre (2) | Two-probe method | - | AC | 420 | [ |
| Concrete | MWCNTs (0.05) | Four-probe method | An electrode made up of copper plate | DC | 181 | [ |
The resistances for the different types of circuit current.
| Circuit Type | Ohm’s Law | Description |
|---|---|---|
| Direct current circuit |
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| Alternating current circuit |
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The conditions adopted for determining sensitivity.
| Condition | F.C.R. | Gauge Factor | Sensitivity Criterion |
|---|---|---|---|
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| In case 1, the gauge factor is dictated by the change in resistivity ( |
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| In case 2, the maximum value of µ is 0.5, so the maximum value that the G.F. can obtain is 2, which is low. |
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| In case 3, the maximum G.F. that can be obtained is 3, which is low. |
Based on the above three conditions, case 2 and case 3 are limited due to low G.F. values; thus, case 1 is assumed to be suitable for obtaining high sensitivity.
Sensing parameters for different fibre proportions.
| Type of Filler | Type of Matrix | Percentage of Filler Material (%) | Sensitivity Properties | References | ||
|---|---|---|---|---|---|---|
| F.C.R. | Gauge Factor | Resistivity (Ohms·cm) | ||||
| Steel Fiber | Cementitious matrix | 0.5 | - | 87.26 | 102.86 | [ |
| 1 | - | 155.99 | 21.43 | |||
| 1.5 | - | 164.24 | 17.13 | |||
| 2 | - | 156.45 | 11.39 | |||
| Concrete | 20 | 0.194 | 1.78 | - | ||
| 40 | 0.13 | 4.68 | - | |||
| 60 | 0.122 | 0.77 | - | |||
| Cement | Lengthy twisted (1.5) | 138.09 | 55.54 | |||
| Lengthy smooth (1.5) | - | 99.85 | 109.06 | |||
| Lengthy hooked (1.5) | - | 88.5 | 175.03 | |||
| Medium twisted (1.5) | - | 139.68 | 113.58 | |||
| Medium smooth (1.5) | - | 99.7 | 352.11 | |||
| Short smooth (1.5) | - | 52.9 | 628.97 | |||
| Carbon Nanotube | Cement paste | 0.2 | 0.02 | - | - | [ |
| 0.3 | 0.03 | - | - | |||
| Cement paste | 0.6 | - | 1 | 1 | ||
| 0.7 | - | 50 | 50 | |||
| 1.2 | - | 2 | 2 | |||
| Concrete | 0.25 | 20 | - | - | ||
| 0.5 | 25 | - | - | |||
| Carbon Fiber | Concrete | 0.5 | 12.5 | - | - | [ |
| 1 | 11 | - | ||||
| Cement paste | 0.5 | 405.3 | ||||
| Cement paste | 0.1 | 13 | ||||
| 0.5 | 3 | |||||
| 1 | 2 | |||||
| Concrete | 0.5 | 0.37 | ||||
| 2 | 1.01 | |||||
| 3 | 1.32 | |||||
| C.F., C.N.T. | Cement paste | 0.1, 0.5 | 160.3 | 25 | [ | |
| S.F., C.N.T | Concrete | 2, 0.5 | 0.236 | 67.8 | [ | |
| S.F, CB | Concrete | 20, 1 (kg/m3) | 0.323 | 1.08 | - | [ |
| S.F, CB, CF | concrete | 60, 1, 2 (kg/m3) | 0.169 | 1.55 | [ | |
Permittivity and resistivity values for different materials.
| Conducting Type | Material | Permittivity |
|---|---|---|
| Conducting | CFRP | 1.6 × 103 |
| Conducting | Copper | 2.4 × 103 |
| Conducting | Carbon fibre | 4.0 × 103 |
| Non-Conducting | Cement paste | 28 |
| Non-Conducting | Mortar | 13.2 |
| Non-Conducting | Concrete | 11.9 |
Figure 7The specimen setup for capacitance measurement.
Figure 8Graphical representation for determining (.
Conditions adopted for determining sensitivity nature.
| Condition | Sensing Effectiveness |
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Figure 9Graphical representation of fractional changes in resistivity for different loading conditions.
Figure 10Curing effects for different fibres at different curing ages.
Figure 11Nyquist curve.
Figure 12The specimen setup for AC impedance analysis.
Figure 13The circuit model for microstructural analysis.
Figure 14The circuit model for the hydration study.
Figure 15The circuit model for the analysis of the effect of the conductive medium in the composite.
Figure 16The circuit model for the analysis of chloride migration.