scholarly journals Statistical Equations to Estimate the In-situ Concrete Compressive Strength from Non-destructive Tests

2018 ◽  
Vol 24 (11) ◽  
pp. 53
Author(s):  
Ahmed Faleh Al-Bayati

The aim of this study is to propose reliable equations to estimate the in-situ concrete compressive strength from the non-destructive test. Three equations were proposed: the first equation considers the number of rebound hummer only, the second equation consider the ultrasonic pulse velocity only, and the third equation combines the number of rebound hummer and the ultrasonic pulse velocity. The proposed equations were derived from non-linear regression analysis and they were calibrated with the test results of 372 concrete specimens compiled from the literature. The performance of the proposed equations was tested by comparing their strength estimations with those of related existing equations from literature. Comparisons revealed that the proposed ultrasonic pulse velocity and combined equations achieved better agreements with the test results than the related existing equations, whereas the proposed and the existing rebound hummer equations were inconsistent.  

2013 ◽  
Vol 12 (3) ◽  
Author(s):  
Sudarmadi Sudarmadi

In this paper a case study about concrete strength assessment of bridge structure experiencing fire is discussed. Assessment methods include activities of visual inspection, concrete testing by Hammer Test, Ultrasonic Pulse Velocity Test, and Core Test. Then, test results are compared with the requirement of RSNI T-12-2004. Test results show that surface concrete at the location of fire deteriorates so that its quality is decreased into the category of Very Poor with ultrasonic pulse velocity ranges between 1,14 – 1,74 km/s. From test results also it can be known that concrete compressive strength of inner part of bridge pier ranges about 267 – 274 kg/cm2 and concrete compressive strength of beam and plate experiencing fire directly is about 173 kg/cm2 and 159 kg/cm2. It can be concluded that surface concrete strength at the location of fire does not meet the requirement of RSNI T-12-2004. So, repair on surface concrete of pier, beam, and plate at the location of fire is required.


2021 ◽  
Vol 318 ◽  
pp. 03004
Author(s):  
AbdulMuttalib I. Said ◽  
Baqer Abdul Hussein Ali

This paper has carried out an experimental program to establish a relatively accurate relation between the ultrasonic pulse velocity (UPV) and the concrete compressive strength. The program involved testing concrete cubes of (100) mm and prisms of (100×100×300) cast with specified test variables. The samples are tested by using ultrasonic test equipment with two methods, direct ultrasonic pulse (DUPV) and surface (indirect) ultrasonic pulse (SUPV) for each sample. The obtained results were used as input data in the statistical program (SPSS) to predict the best equation representing the relation between the compressive strength and the ultrasonic pulse velocity. In this research 383 specimens were tested, and an exponential equation is proposed for this purpose. The statistical program has been used to prove which type of UPV is more suitable, the (SUPV) test or the (DUPV) test, to represent the relation between the ultrasonic pulse velocity and the concrete compressive strength. In this paper, the effect of salt content on the connection between the ultrasonic pulse velocity and the concrete compressive strength has also been studied.


2021 ◽  
Vol 1164 ◽  
pp. 77-86
Author(s):  
Bogdan Bolborea ◽  
Sorin Dan ◽  
Claudiu Matei ◽  
Aurelian Gruin ◽  
Cornelia Baeră ◽  
...  

Developing a non-destructive method which delivers fast, accurate and non-invasive results regarding the concrete compressive strength, is an important issue, currently investigated by many researchers all over the world. Different methodologies, like using the simple non-destructive testing (NDT) or the fusion of different techniques approach, were taken into consideration in order to find the optimal, most suitable method. The purpose of this paper is to present a new approach in this direction. The methodology consists in predicting the concrete compressive strength through ultrasonic testing, for non-destructive determination of the dynamic and static moduli of elasticity. One important, basic assumption of the proposed methodology considers values provided by technical literature for concrete dynamic Poisson’s coefficient. The air-dry density was experimentally determined on concrete cores. The dynamic modulus of elasticity was also experimentally determined by using the ultrasonic pulse velocity (UPV) method on concrete cores. Further on, the static modulus of elasticity and the concrete compressive strength can be mathematically calculated, by using the previously mentioned parameters. The experimental procedures were performed on concrete specimens, namely concrete cores extracted from the raft foundation of a multistorey building; initially they were subjected to the specific NDT, namely ultrasonic testing, and the validation of the results and the proposed methodology derives from the destructive testing of the specimens. The destructive testing is generally recognized as the most trustable method. The precision of the proposed method, established with respect to the destructive testing, revealed a high level of confidence, exceeding 90% (as mean value). It was noticed that even the cores with compressive strength outside of mean range interval (minimum and maximum values) presented high rate of precision, not influencing the overall result. The high rate of accuracy makes this method a suitable research background for further investigations, in order to establish a reliable NDT methodology which could substitute the very invasive and less convenient, destructive method.


2018 ◽  
Vol 792 ◽  
pp. 166-169
Author(s):  
Yu Ren Wang ◽  
Loan T.Q. Ngo ◽  
Yi Fan Shih ◽  
Yen Ling Lu ◽  
Yi Ming Chen

SONREB method is a non-destructive testing (NDT) method for estimating the concrete compressive strength. It is conducted by combining two popular NDT methods: ultrasonic pulse velocity (UPV) test and rebound hammer (RH) test. Several researches have been attempted to find the correlation of the different testing method data with actual compressive strength. This research proposes a new Artificial Intelligence based approach, Artificial Neural Networks (ANNs), to estimate the concrete compressive strength using the UPV and RH test data. Data from a total of 315 cylinder concrete samples are collected to develop and validate the ANFIS prediction model. The model prediction results are compared with actual compressive strength using mean absolute percentage error (MAPE). With the adaption of ANFIS, the estimation error of SONREB test can be reduced to 5.98% (measured by MAPE).


2016 ◽  
Vol 64 (4) ◽  
pp. 687-695 ◽  
Author(s):  
L. Brunarski ◽  
M. Dohojda

Abstract The paper presents the problem of estimating in-situ compressive strength of concrete in a comprehensive way, taking into account the possibility of direct tests of cored specimens and indirect methods of non-destructive tests: rebound hammer tests and ultrasonic pulse velocity measurements. The paper approaches the discussed problem in an original, scientifically documented and exhaustive way, in particular in terms of application.


Author(s):  
Saïdou Bamogo ◽  
David Y. K. Toguyeni ◽  
Fati Zoma ◽  
Mohamed Yerbanga

The method used to evaluate the quality of concrete in structures includes, among other things, compressive strength testing of specimens cast on site. This method has shortcomings due to the non-uniformity in their formulation processes of the concrete studied in laboratories and that of the structure on site and the tardiness in obtaining test results. This is why the development of reliable methods of non-destructive assessment of the compressive strength of concrete in situ is essential for a better performance assessment of structures.There are a multitude of non-destructive methods, but in this article, the ultrasonic pulse velocity (UPV) and the rebound hammer (RH) are the methods used as they are easy to get manipulate, accessible and permit fast access to results. Analyses using single and multiple linear regression methods have been carried out with the results from compression tests and measurements of pulse velocity and rebound indices carried out between February and April 2018 on over 90 specimen samples in total. This resulted in correlation equations for the in-situ estimation of the compressive strength of the concrete studied.


2011 ◽  
Vol 243-249 ◽  
pp. 165-169 ◽  
Author(s):  
Iqbal Khan Mohammad

Nondestructive testing (NDT) is a technique to determine the integrity of a material, component or structure. The commonly NDT methods used for the concrete are dynamic modulus of elasticity and ultrasonic pulse velocity. The dynamic modulus of elasticity of concrete is related to the structural stiffness and deformation process of concrete structures, and is highly sensitive to the cracking. The velocity of ultrasonic pulses travelling in a solid material depends on the density and elastic properties of that material. Non-destructive testing namely, dynamic modulus of elasticity and ultrasonic pulse velocity was measured for high strength concrete incorporating cementitious composites. Results of dynamic modulus of elasticity and ultrasonic pulse velocity are reported and their relationships with compressive strength are presented. It has been found that NDT is reasonably good and reliable tool to measure the property of concrete which also gives the fair indication of the compressive strength development.


2018 ◽  
Vol 207 ◽  
pp. 01001
Author(s):  
Tu Quynh Loan Ngo ◽  
Yu-Ren Wang

In the construction industry, to evaluate the compressive strength of concrete, destructive and non-destructive testing methods are used. Non-destructive testing methods are preferable due to the fact that those methods do not destroy concrete samples. However, they usually give larger percentage of error than using destructive tests. Among the non-destructive testing methods, the ultrasonic pulse velocity test is the popular one because it is economic and very simple in operation. Using the ultrasonic pulse velocity test gives 20% MAPE more than using destructive tests. This paper aims to improve the ultrasonic pulse velocity test results in estimating the compressive strength of concrete using the help of artificial intelligent. To establish a better prediction model for the ultrasonic pulse velocity test, data collected from 312 cylinder of concrete samples are used to develop and validate the model. The research results provide valuable information when using the ultrasonic pulse velocity tests to the inputs data in addition with support vector machine by learning algorithms, and the actual compressive strengths are set as the target output data to train the model. The results show that both MAPEs for the linear and nonlinear regression models are 11.17% and 17.66% respectively. The MAPE for the support vector machine models is 11.02%. These research results can provide valuable information when using the ultrasonic pulse velocity test to estimate the compressive strength of concrete.


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