Compressive strength evaluation by non-destructive techniques: An automated approach in construction industry

Rashid, Khuram; Waqas, Rumman

doi:10.1016/j.jobe.2017.05.010

Cited by 41 publications

(17 citation statements)

References 12 publications

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“…This proves that the dual linear regression expression used in this study can give a good prediction for the strength evaluation of HSC by combining two significant influencing factors: measured UPV and RH. [10] f c = 3.34exp 0.0598R0 36.4 Exponential Kim [35] f c = 1.267R 0 + 9.7868 60 1st polynomial Kwon [36] f c = 2.59R 0 − 51.5 65 1st polynomial Mohammed [37] f c = 9.5879exp 0.0384R0 40 Exponential Qasrawi [13] f c = 1.353R 0 − 17.393 42 1st polynomial Rashid [38] f c = −0.08R 2 0 + 8.37R 0 − 157.54 52 2nd polynomial Willetts [39] f c = 0.00935R 2 0 + 0.8R 0 − 12.06 -2nd polynomial Table 5. Previous equations for the ultrasonic pulse velocity method.…”

Section: Comparison With Previous Equationsmentioning

confidence: 99%

“…f c = 21.5V p − 62 45 1st polynomial Ali-benyahia [34] f c = 0.6401V 2.5654 p 21.9 Power Atici [10] f c = 0.0316exp 1.3Vp 36.4 Exponential Del Rio [40] f c = e [(−5.4±0.8)+(0.00185±0.00018)Vp] 34.0 Exponential Khan [17] f c = 0.5208V 5 p 100 Power Kim [10] f c = 50.163V p − 178.2 60 1st polynomial Najim [11] f c = 0.0136V p − 21.34 50 1st polynomial Qasrawi [13] f c = 32.72V p − 129.077 42 1st polynomial Rashid [38] f c = 38.05V 2 p − 316.76V p + 681.62 52 2nd polynomial Trtnik et al [16] f c = 0.854exp 1.2882Vp 50 Power * calculated by using the results in Table 3. * calculated by using the results in Table 3.…”

Section: Aij [4]mentioning

confidence: 99%

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Estimation of Compressive Strength of High Strength Concrete Using Non-Destructive Technique and Concrete Core Strength

Park

2017

Applied Sciences

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Abstract:Estimating the compressive strength of high strength concrete (HSC) is an essential investigation for the maintenance of nuclear power plant (NPP) structures. This study intends to evaluate the compressive strength of HSC using two approaches: non-destructive tests and concrete core strength. For non-destructive tests, samples of HSC were mixed to a specified design strength of 40, 60 and 100 MPa. Based on a dual regression relation between ultrasonic pulse velocity (UPV) and rebound hammer (RH) measurements, an estimation expression is developed. In comparison to previously published estimation equations, the equation proposed in this study shows the highest accuracy and the lowest root mean square error (RMSE). For the estimation of compressive strength using concrete core specimens, three different concrete core diameters were examined: 30, 50, and 100 mm. Based on 61 measured compressive strengths of core specimens, a simple strength correction factor is investigated. The compressive strength of a concrete core specimen decreases as the core diameter reduces. Such a relation is associated with the internal damage of concrete cores and the degree of coarse aggregate within the core diameter from the extracting process of the cores. The strength estimation expressions was formulated using the non-destructive technique and the core strength estimation can be updated with further test results and utilized for the maintenance of NPP.

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Section: Comparison With Previous Equationsmentioning

confidence: 99%

Section: Aij [4]mentioning

confidence: 99%

Estimation of Compressive Strength of High Strength Concrete Using Non-Destructive Technique and Concrete Core Strength

Park

2017

Applied Sciences

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“…Therefore, it is recommended that the RH tests can be combined with other nondestructive test methods (such as UPV tests) to improve concrete compressive strength estimations. Research results have shown that the SonReb (UPV + RH test) method (Rilem Report TC43-CND, 1993) might improve concrete strength estimations in NDT tests (Nobile, 2015;Rashid and Waqas, 2017;Pereira and Romão, 2018). For this research, the results are obtained from the 100-sample data collected.…”

Section: Conclusion and Recommendationsmentioning

confidence: 99%

Adapting Artificial Intelligence to Improve In Situ Concrete Compressive Strength Estimations in Rebound Hammer Tests

Wang

Chiang

2020

Front. Mater.

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Compressive strength is probably one the most crucial properties of concrete material. For existing structures, core samples are drilled and tested to obtain the concrete compressive strength. Many times, taking core samples is not feasible, and as a result, nondestructive methods to examine the concrete are required. The rebound hammer test is one of the most popular methods to estimate concrete compressive strength without causing damage to the existing structure. The test is inexpensive and can be easily conducted compared to other nondestructive testing methods. Also, concrete compressive strength estimations can be obtained almost instantly. However, previous results have shown that concrete compressive strength estimations obtained from rebound hammer tests are not very accurate. As a result, this research attempts to apply artificial intelligence prediction models to estimate concrete compressive strength using data from in situ rebound hammer tests. The results show that artificial intelligence methods can effectively improve in situ concrete compressive strength estimations in rebound hammer tests.

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“…There is also a growing demand for educated personnel with a high level of knowledge, and therefore education in this field is becoming very important. Currently, non-destructive testing techniques are the subject of many scientific and technical conferences, and are used to diagnose civil engineering structures [ 1 , 2 , 3 , 4 ]. Among them you can find both traditional methods, e.g., ultrasonic, penetration, or sclerometric methods, as well as laser, radar, or optical techniques allowing for determination of the deformation of an element [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

The Assessment of Strength of Cementitious Materials Impregnated Using Hydrophobic Agents Based on Near-Surface Hardness Measurements

Nieświec

Sadowski

2021

Materials

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Recently, the surfaces of concrete structures are impregnated to protect them against the environment in order to increase their durability. It is still not known how the use of these agents affects the near-surface hardness of concrete. This is especially important for experts who use the near-surface hardness of concrete for estimating its compressive strength. The impregnation agents are colorless and, thus, without knowledge of their use, mistakes can be made when testing the surface hardness of concrete. This paper presents the results of investigations concerning the impact of impregnation on the subsurface hardness concrete measured using a Schmidt hammer. For this research, samples of cement paste with a water–cement ratio of 0.4 and 0.5 were used. The samples were impregnated with one, two, and three layers of two different agents. The first agent has been made based on silanes and siloxanes and the second agent has been made based on based on polymers. The obtained research results allow for the conclusion that impregnation affects the near-surface hardness of concrete. This research highlights the fact that a lack of knowledge about the applied impregnation of concrete when testing its near-surface hardness, which is then translated into its compressive strength, can lead to serious mistakes.

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Compressive strength evaluation by non-destructive techniques: An automated approach in construction industry

Cited by 41 publications

References 12 publications

Estimation of Compressive Strength of High Strength Concrete Using Non-Destructive Technique and Concrete Core Strength

Estimation of Compressive Strength of High Strength Concrete Using Non-Destructive Technique and Concrete Core Strength

Adapting Artificial Intelligence to Improve In Situ Concrete Compressive Strength Estimations in Rebound Hammer Tests

The Assessment of Strength of Cementitious Materials Impregnated Using Hydrophobic Agents Based on Near-Surface Hardness Measurements

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