scholarly journals Assessment of core strength of concrete by artificial neural networks

2021 ◽  
Vol 73 (10) ◽  
pp. 1007-1016

The proposed work deals with the use of Ultrasonic pulse velocity technique as an alternative method to identify compressive strength of the core concrete. The use of non-destructive technique without causing damages to the structure is tedious with interpretation of results influenced by various factors. Hence, an empirical relationship is developed using artificial neural network model for creating a regression between pulse velocity and compressive strength of concrete core specimens. Tests were conducted on reinforced concrete cylinders at various orientation angles (0°, 45°, 90°). The tests were conducted based on the design of experiment using the Box-Behnken model. These results were trained using the Levenberg-Marquardt back propagation model with hidden layers. Results indicate that the prediction of core compressive strength for the grade mixes is nearer for the two-level factorial design with R2 = 0.897, and the sum of squared error is found to be 0.9968.

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.


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.


This study focuses on assessing the durability property of engineered cementitious composites using Ultrasonic pulse velocity method (direct and semi direct) to compute the compressive strength. Even the effect of mineral admixture on the mortar properties for different curing regimes shall be determined using this method. Mortar specimens containing microsilica in different percentages ranging from 5% to 25%, replacing portland cement by weight and adding polypropylene fibres ranging from 0.5% to 2% are chosen for evaluation. 20% of microsilica and 2% of polypropylene fibres induced to increase the range of UPV from 3463 m/s to 3505 m/s for 7 and 28 day curing regimes and also the compressive strength significantly improved for the above constituent. However there was a marginal decrease in the compressive strength and UPV outcomes when cement is replaced by microsilica greater than 20%. A relationship had been framed between ultrasound pulse velocity and compressive strength.


Materials ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 389 ◽  
Author(s):  
Radosław Jasiński ◽  
Łukasz Drobiec ◽  
Wojciech Mazur

Minor-destructive (MDT) and non-destructive (NDT) techniques are not commonly used for masonry as they are complex and difficult to perform. This paper describes validation of the following methods: semi-non-destructive, non-destructive, and ultrasonic technique for autoclaved aerated concrete (AAC). The subject of this study covers the compressive strength of AAC test elements with declared various density classes of: 400, 500, 600, and 700 (kg/m3), at various moisture levels. Empirical data including the shape and size of specimens, were established from tests on 494 cylindrical and cuboid specimens, and standard cube specimens 100 mm × 100 mm × 100 mm using the general relationship for ordinary concrete (Neville’s curve). The effect of moisture on AAC was taken into account while determining the strength fBw for 127 standard specimens tested at different levels of water content (w = 100%, 67%, 33%, 23%, and 10%). Defined empirical relations were suitable to correct the compressive strength of dry specimens. For 91 specimens 100 mm × 100 mm × 100 mm, the P-wave velocity cp was tested with the transmission method using the ultrasonic pulse velocity method with exponential transducers. The curve (fBw–cp) for determining the compressive strength of AAC elements with any moisture level (fBw) was established. The developed methods turned out to be statistically significant and can be successfully applied during in-situ tests. Semi-non-destructive testing can be used independently, whereas the non-destructive technique can be only applied when the developed curve fbw–cp is scaled.


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.


2021 ◽  
Vol 1021 ◽  
pp. 45-54
Author(s):  
Mohammed Al-Helfi ◽  
Ali Allami

Non-Destructive methods have greater advantage in assessing the homogeneity, compressive strength, corrosion of rebars in concrete etc. of damaged structures. The aim of the present study is to assess the existing building, which is 41 year old, in the Technical Institute of Amara affiliated with the Southern Technical University, Maysan, Iraq. The research focus on the assessment of the concrete strength and the inspection of the damages in the building. Besides the visual inspection, the ultrasonic pulse velocity and schmidt hammer were used as a non-destructive test method for testing of 30 columns and 15 beams for a building consisting of three floors. The concrete compressive strength was estimated by using SonReb method. The equations proposed by Gasparik, 1984, Di Leo & Pascale, 1994, Arioglu et al., 1996, Cristofaro et al. (EXP), 2020 and Cristofaro et al (PW), 2020 were used for assessment the compressive strength of oncrete. The non-destructive test results indicated that the average strength of the structural elements greater than the design compressive strength of the tested elements. Therefore, the building can be considered structurally is safe.


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).


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