The Strain Sensitivity of Coal Reinforced Smart Concrete by Piezoresistive Effect

Abstract

The structures are challenged by earthquakes, material degradations and other environmental factors. In order to protect the lives, assets, and for maintenance planning, structural health monitoring (SHM) is important. In SHM applications, strain gages are widely used which have low durability, low sensitivity while they have high cost. To monitor a structure, large number of strain gages have to be used that increases the cost. In this study, seven coal reinforced concrete mixtures with 0, 0.35, 0.5, 0.8, 1, 1.5 and 2 volume % of coal were designed; three cubic samples for each mixture were fabricated. Simultaneous strain and electrical resistance measurements of the samples during the compression test were conducted. A strong linear relationship between strain and electrical resistance change with a correlation coefficient of 0.99 was determined. The concrete mixture having 0.8% coal volume had the highest strain sensitivity of K=44, which was 22 times the strain sensitivity of commercial metal strain gages while it had a linearity error of LE=6.9% that was low. This mixture with 0.8% coal volume is a candidate to be smart concrete which can sense its strain. As a contribution to the literature, a phenomenological model for the relationship between gage factor and coal volume percentage was explained in details. The multifunctional smart concrete will be used as a smart material, which can sense its strain in SHM applications while acting as a load bearing material.

Keywords

• smart concrete
• strain
• electrical resistance
• smart materials
• piezoresistivity

Project Number

213M452

The Strain Sensitivity of Coal Reinforced Smart Concrete by Piezoresistive Effect

Abstract

The structures are challenged by earthquakes, material degradations and other environmental factors. In order to protect the lives, assets, and for maintenance planning, structural health monitoring (SHM) is important. In SHM applications, strain gages are widely used which have low durability, low sensitivity while they have high cost. To monitor a structure, large number of strain gages have to be used that increases the cost. In this study, seven coal reinforced concrete mixtures with 0, 0.35, 0.5, 0.8, 1, 1.5 and 2 volume % of coal were designed; three cubic samples for each mixture were fabricated. Simultaneous strain and electrical resistance measurement of the samples during the compression test was conducted. A strong linear piezoresistive relationship between strain and electrical resistance change with a correlation coefficient of 0.99 was determined. The concrete mixture having 0.8 volume % coal had the highest strain sensitivity of K=44, which was 22 times the strain sensitivity of commercial metal strain gages while it had a linearity error of LE=6.9% that was low. This mixture with 0.8 volume % coal is a candidate to be smart concrete which can sense its strain. As a contribution to the literature, a phenomenological model for the relationship between gage factor and coal volume % was explained in details. The multifunctional smart concrete will be used as a smart material, which can sense its strain in SHM applications while acting as a load bearing material.

Keywords

• smart concrete
• strain
• electrical resistance
• smart materials
• piezoresistivity

Supporting Institution

TÜBİTAK

Project Number

213M452

Thanks

This work was supported by The Scientific and Technological Research Council of Turkey (TUBITAK) through project “Smart Concrete Production”, Grant no: 213M452. The authors would like to thank to Batıbeton Batıçim West Anatolia Cement Industry Inc. for supplying cement and aggregate; Sika Construction Chemicals Co. for supplying super plasticizer; BASF Chemical Co. for supplying silica fume, Turkish Coal Institution for supplying coal.

References

1. [1] Chung, D.D.L., Review functional properties of cement –matrix composites. Journal of Material Science, 36, 1315-1324, 2001.
2. [2] Chung, D.D.L., Piezoresistive cement-based materials for strain sensing. Journal of Intelligent Material Systems and Structures, 13(9), 599-609, 2002.
3. [3] Chung, D.D.L., Carbon materials for structural self-sensing, electromagnetic shielding and thermal interfacing. Carbon, 50(9), 3342-3353, 2012.
4. [4] Lu, S.N., Xie, N., Feng, L.C., Zhong, J., Applications of nanostructured carbon materials in constructions: the state of the art. Journal of Nanomaterials, ID: 807416, 2015.
5. [5] Han, B., Yu, X., Kwon, E., A self-sensing carbon nanotube/cement composite for traffic monitoring. Nanotechnology, 20(44), 1-5, 2009.
6. [6] Han, B., Zhang, K., Burnham, T., Kwon, E., Yu, X., Integration and road tests of a self-sensing CNT concrete pavement system for traffic detection. Smart Materials and Structures, 22(1), ID: 015020, 2013.
7. [7] Al-Dahawi, A., Sarwary, M. H., Öztürk, O., Yıldırım, G., Akın, A., Şahmaran, M., Lachemi, M., Electrical percolation threshold of cementitious composites possessing self-sensing functionality incorporating different carbon-based materials. Smart Materials and Structures, 25(10), ID: 105005, 2016.
8. [8] Jianlin, L., Kwok, L.C., Qiuyi, L., Shunjian, C., Lu, L., Dongshuai, H., Chunwei, Z., Piezoresistive properties of cement composites reinforced by functionalized carbon nanotubes using photo-assisted fenton. Smart Materials and Structures, 26(3), ID: 035025, 2017.

9. [9] Luo, J., Zhang, C., Duan, Z., Wang, B., Li, Q., Chung, K.L., Zhang, J., Chen, S., Influences of multi-walled carbon nanotube (MCNT) fraction, moisture, stress/strain level on the electrical properties of MCNT cement-based composites. Sensors and Actuators A: Physical, 280, 413–421, 2018.
10. [10] Meehan, D.G., Wang, S., Chung, D.D.L., Electrical-resistance-based sensing of impact damage in carbon fiber reinforced cement-based materials, Journal of Intelligent Material Systems and Structures, 21(1), 83-105, 2010.
11. [11] Han, B., Wang, Y., Dong, S., Zhang, L., Ding, S., Yu, X., Ou, J., Smart concretes and structures: A review. Journal of Intelligent Material Systems and Structures, 26(11), 1303-1345, 2015.
12. [12] Goldfeld, Y., Rabinovitch, O., Fishbain, B., Quadflieg, T., Gries, T., Sensory carbon fiber based textile-reinforced concrete for smart structures. Journal of Intelligent Material Systems and Structures, 27(4), 469-489, 2016.
13. [13] Han, B., Wang, Y., Ding, S., Yu, X., Zhang, L., Li, Z., Ou, J., Self-sensing cementitious composites incorporated with botryoid hybrid nano-carbon materials for smart infrastructures. Journal of Intelligent Material Systems and Structures. 28(6), 699-727, 2017.
14. [14] Wang, H., Gao, X., Liu, J., Coupling effect of salt freeze-thaw cycles and cyclic loading on performance degradation of carbon nanofiber mortar. Cold Regions Science and Technology, 154, 95–102, 2018.
15. [15] Wang, Y., Wang, Y., Wan, B., Han, B., Cai, G., Chang, R., Strain and damage self-sensing of basalt fiber reinforced polymer laminates fabricated with carbon nanofibers/epoxy composites under tension. Composites Part A, 113, 40–52, 2018b.
16. [16] Wang, Y., Wang, Y., Wan, B., Han, B., Cai, G., Li, Z., Properties and mechanisms of self-sensing carbon nanofibers/epoxy composites for structural health monitoring. Composite Structures, 200, 669–678, 2018.
17. [17] Li, H., Xiao, H., Ou, J., Effect of compressive strain on electrical resistivity of carbon black-filled cement –based composites. Cement and Concrete Composites, 28, 824-828, 2006.
18. [18] Li, H., Xiao, H., Ou, J., Electrical property of cement-based composites filled with carbon black under long-term wet and loading condition. Composites Science and Technology, 68, 2114-2119, 2008.
19. [19] Ozbulut, O. E., Jiang, Z., Harris, D. K., Exploring scalable fabrication of self-sensing cementitious composites with graphene nanoplatelets. Smart Materials and Structures, 27(11), ID: 115029, 2018.
20. [20] Rehman, S. K., Ibrahim, Z., Jameel, M., Memon, S. A., Javed, M. F., Aslam, M., Mehmood, K., Nazar, S., Assessment of rheological and piezoresistive properties of graphene based cement composites. International Journal of Concrete Structures and Materials, 12(1), UNSP 64, 2018.
21. [21] Teomete, E., Measurement of crack length sensitivity and strain gage factor of carbon fiber reinforced cement matrix composites. Measurement, 74, 21-30, 2015.
22. [22] Azhari, F., Banthia, N., Carbon fiber-reinforced cementitious composites for tensile strain sensing. ACI Materials Journal, 114(1), 129-136, 2017.
23. [23] Baeza, F. J., Galao, O., Zornoza, E., Garcés, P., Effect of aspect ratio on strain sensing capacity of carbon fiber reinforced cement composites. Materials & Design, 51, 1085-1094, 2013.
24. [24] Gao, D., Sturm, M., Mo, Y. L., Electrical resistance of carbon-nanofiber concrete, Smart Materials and Structures, 18(9), ID:095039, 2009.
25. [25] Wang, W., Wu, S., Dai, H., Fatigue behavior and life prediction of carbon fiber reinforced concrete under cyclic flexural loading. Materials Science and Engineering, 434(1-2), 347-351, 2006.
26. [26] Chu, H. Y., Chen, J. K., The experimental study on the correlation of resistivity and damage for conductive concrete. Cement and Concrete Composites, 67, 12-19, 2016.
27. [27] Wen, S., Chung, D. D. L., A comparative study of steel- and carbon–fibre cement as piezoresistive strain sensors. Advances in Cement Research, 15(3), 119–128, 2003.
28. [28] Teomete, E., Kocyigit, O. I., Tensile strain sensitivity of steel fiber reinforced cement matrix composites tested by split tensile test. Construction and Building Materials, 47, 962-968, 2013.
29. [29] Dong, S., Han, B., Ou, J., Li, Z., Han, L., Yu, X., Electrically conductive behaviors and mechanisms of short-cut super-fine stainless wire reinforced reactive powder concrete. Cement & Concrete Composites, 72, 48-65, 2016.
30. [30] Lee, S. H., Kim, S., Yoo, D. Y., Hybrid effects of steel fiber and carbon nanotube on self-sensing capability of ultra-high-performance concrete. Construction and Building Materials. 185, 530 -544, 2018.
31. [31] Yoo, D. Y., Kim, S., Lee, S. H., Self-sensing capability of ultra-high-performance concrete containing steel fibers and carbon nanotubes under tension. Sensors and Actuators A-Physical, 276, 125-136, 2018.
32. [32] D'Alessandro, A., Meoni, A., Ubertini, F., Stainless steel microfibers for strain-sensing smart clay bricks. Journal of Sensors, ID:7431823, 2018.
33. [33] Karimaei, M., Dabbaghi, F., Sadeghi-Nik, A., Dehestani, M., Mechanical performance of green concrete produced with untreated coal waste aggregates. Construction and Building Materials, 233, Article Number: UNSP 117264, 2020.
34. [34] Wang, Y., Tan, Y., Wang, Y., Liu, C., Mechanical properties and chloride permeability of green concrete mixed with fly ash and coal gangue. Construction and Building Materials, 233, Article Number: 117166, 2020.
35. [35] Khataei, B., Nasrollahi, M., Optimizing the tensile strength of concrete containing coal waste considering the cost. Sn Applied Sciences, 2 (1) Article Number: 103, 2020.
36. [36] Shamsaei, M., Khafajeh, R., Aghayan, I., Laboratory evaluation of the mechanical properties of roller compacted concrete pavement containing ceramic and coal waste powders. Clean Technologies and Environmental Policy, 21(3), 707-716, 2019.
37. [37] Modarresa, A., Hesamia, S., Soltaninejada, M., Madanib, H., Application of coal waste in sustainable roller compacted concrete pavement-environmental and technical assessment. International Journal of Pavement Engineering, 19(8), 748-761, 2018.
38. [38] Chiarello, M., Zinno, R., Electrical conductivity of self-monitoring CFRC. Cement and Concrete Composites, 27, 463-469, 2005.
39. [39] Han, B., Guan, X., Ou, J., Electrode design, measuring method and data acquisition system of carbon fiber cement paste piezoresistive sensors. Sensors and Actuators A, 135, 360-369, 2007.
40. [40] Chen, B., Liu, J., Damage in carbon fiber –reinforced concrete, monitored by both electrical resistance measurement and acoustic emission analysis. Construction and Building Materials, 22, 2196-2201, 2008.