scholarly journals Applying Artificial Intelligence to Improve On-Site Non-Destructive Concrete Compressive Strength Tests

Crystals ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1157
Author(s):  
Tu Quynh Loan Ngo ◽  
Yu-Ren Wang ◽  
Dai-Lun Chiang
Keyword(s):  
Artificial Intelligence ◽  
Compressive Strength ◽  
Prediction Models ◽  
Concrete Strength ◽  
Pulse Velocity ◽  
Statistical Regression ◽  
Concrete Compressive Strength ◽  
Major Drawback ◽  
Non Destructive

In the construction industry, non–destructive testing (NDT) methods are often used in the field to inspect the compressive strength of concrete. NDT methods do not cause damage to the existing structure and are relatively economical. Two popular NDT methods are the rebound hammer (RH) test and the ultrasonic pulse velocity (UPV) test. One major drawback of the RH test and UPV test is that the concrete compressive strength estimations are not very accurate when comparing them to the results obtained from the destructive tests. To improve concrete strength estimation, the researchers applied artificial intelligence prediction models to explore the relationships between the input values (results from the two NDT tests) and the output values (concrete strength). In-situ NDT data from a total of 98 samples were collected in collaboration with a material testing laboratory and the Professional Civil Engineer Association. In-situ NDT data were used to develop and validate the prediction models (both traditional statistical models and AI models). The analysis results showed that AI prediction models provide more accurate estimations when compared to statistical regression models. The research results show significant improvement when AI techniques (ANNs, SVM and ANFIS) are applied to estimate concrete compressive strength in RH and UPV tests.

scholarly journals Evaluation of Self-Compacting Concrete Strength with Non-Destructive Tests for Concrete Structures

2019 ◽  
Vol 9 (23) ◽  
pp. 5109 ◽  
Author(s):  
Miguel C. S. Nepomuceno ◽  
Luís F. A. Bernardo
Keyword(s):  
Compressive Strength ◽  
Concrete Strength ◽  
Surface Hardness ◽  
Pulse Velocity ◽  
Concrete Compressive Strength ◽  
Self Compacting Concrete ◽  
Coarse Aggregates ◽  
Pull Out ◽  
Concrete Maturity ◽  
Non Destructive

Self-compacting concrete (SCC) shows to have some specificities when compared to normal vibrated concrete (NVC), namely higher cement paste dosage and smaller volume of coarse aggregates. In addition, the maximum size of coarse aggregates is also reduced in SCC to prevent blocking effect. Such specificities are likely to affect the results of non-destructive tests when compared to those obtained in NVC with similar compressive strength and materials. This study evaluates the applicability of some non-destructive tests to estimate the compressive strength of SCC. Selected tests included the ultrasonic pulse velocity test (PUNDIT), the surface hardness test (Schmidt rebound hammer type N), the pull-out test (Lok-test), and the concrete maturity test (COMA-meter). Seven sets of SCC specimens were produced in the laboratory from a single mixture and subjected to standard curing. The tests were applied at different ages, namely: 1, 2, 3, 7, 14, 28, and 94 days. The concrete compressive strength ranged from 45 MPa (at 24 h) to 97 MPa (at 94 days). Correlations were established between the non-destructive test results and the concrete compressive strength. A test variability analysis was performed and the 95% confidence limits for the obtained correlations were computed. The obtained results for SCC showed good correlations between the concrete compressive strength and the non-destructive tests results, although some differences exist when compared to the correlations obtained for NVC.

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

2020 ◽  
Vol 7 ◽  
Author(s):  
Yu Ren Wang ◽  
Yen Ling Lu ◽  
Dai Lun Chiang
Keyword(s):  
Artificial Intelligence ◽  
Compressive Strength ◽  
Prediction Models ◽  
Concrete Compressive Strength ◽  
Concrete Material ◽  
Rebound Hammer ◽  
Existing Structures ◽  
Core Samples ◽  
Using Data

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.

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
Keyword(s):  
Compressive Strength ◽  
Linear Regression Analysis ◽  
Ultrasonic Pulse Velocity ◽  
Ultrasonic Pulse ◽  
Pulse Velocity ◽  
Test Results ◽  
Concrete Compressive Strength ◽  
The Third ◽  
Non Destructive

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.  

PENGKAJIAN KEKUATAN BETON STRUKTUR JEMBATAN PASCA KEBAKARAN

2013 ◽  
Vol 12 (3) ◽  
Author(s):  
Sudarmadi Sudarmadi
Keyword(s):  
Compressive Strength ◽  
Concrete Strength ◽  
Ultrasonic Pulse Velocity ◽  
Ultrasonic Pulse ◽  
Pulse Velocity ◽  
Test Results ◽  
Concrete Compressive Strength ◽  
Strength Assessment ◽  
Concrete Testing

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.

scholarly journals Assessment of Concrete Compressive Strength by Ultrasonic Non-Destructive Test

2021 ◽  
Vol 318 ◽  
pp. 03004
Author(s):  
AbdulMuttalib I. Said ◽  
Baqer Abdul Hussein Ali
Keyword(s):  
Compressive Strength ◽  
Salt Content ◽  
Ultrasonic Pulse Velocity ◽  
Ultrasonic Pulse ◽  
Pulse Velocity ◽  
Experimental Program ◽  
Concrete Compressive Strength ◽  
Statistical Program ◽  
Non Destructive ◽  
Accurate Relation

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.

scholarly journals PENGARUH GENANGAN AIR TERHADAP PENGECORAN BETON IN-SITU

2018 ◽  
Vol 14 (2) ◽  
pp. 158-168
Author(s):  
Aminullah Aminullah
Keyword(s):  
Compressive Strength ◽  
Pulse Velocity ◽  
Test Machine ◽  
Concrete Compressive Strength ◽  
Normal Concrete ◽  
Waterlogged Condition ◽  
Frame Work ◽  
Building Project ◽  
Mixed Concrete

ABSTRACTHigh rainfall intensity maybe occur during the dry season. This can certainly disturb the erection of a building project, especially in a case of construction works requiring dry condition, such in concrete item. Various attempts have been made to reduce the height of the puddle, when mixing the fresh concrete in a frame work of sub-structure elements, e.g. the foot-plate foundation. The puddles in the foundry area potentially affect the composition of the mortar especially in water-cement ratio (wcr). This caused a decrease of compressive strength (f’c) of the concrete then causing the quality decreaseof the concrete. This research used two types of mixed concreteconditions: dry and waterlogged condition. The water cement ratioshould be changed when mixing concrete had been performed in waterlogged condition. One determinedcontrol sample was based on a normal concrete mixture with characteristic strength (f'c) = 25 MPa. The standard of concrete mixing used is SNI-2834-2000 on the mixingprocedure of a normal concrete mixed design. The concrete sampleswere tested using a concrete compressor universal test machine (UTM) than comparedto hammer and Ultra Pulse Velocity (UPV) test.Based on the results of the study, the quality of mixed concrete in waterlogged conditions was much lower than the compressive strength design. The percentage reduction in compressed strength of mixed concrete under water submerged conditions ranged from 30.82% to 32.63% to normal concrete compressive strength. The higher level of puddlecaused the lower compressive strength of the concrete.There was a match between the measurements of concrete compressive strength using UTM comparedto hammer and UPV tests.The percentage differences in measurement of hammer test to UTM test results were 10.73% and 9.26% to 21.79% by the UPV test. Keywords: concrete, foot plate, mix design, puddle, wcr Intesitas hujan yang cukup tinggi juga dapat terjadi pada musim kemarau. Hal ini tentu dapat mengganggu pelaksanaan suatu pekerjaan bangunan, khususnya pekerjaan konstruksi yang telah disyaratkan untuk dikerjakan dalam kondisi kering.  Berbagai macam upaya telah dilakukan untuk mengurangi tinggi genangan air pada saat pengecoran elemen sub-structure, seperti halnya pondasi telapak (foot-plate). Genangan air yang terdapat pada daerah pengecoran berpotensi mempengaruhi komposisi adukan khususnya pada faktor air semen (fas). Hal tersebut dapat mengakibatkan kuat tekan beton (f’c) berkurang sehingga mengakibatkan mutu beton menjadi berkurang. Kajian ini menggunakan dua jenis kondisi pengecoran, yaitu: kondisi kering dan kondisi pada genangan air. Faktor air semen berubah seiring dengan kegiatan pengecoran beton dalam kondisi basah (tergenang air).  Satu buah sampel kontrol telah ditentukan berdasarkan adukan beton normal dengan kekuatan karakteristik (f’c) = 25 MPa. Standar pencampuran beton yang digunakan adalah SNI-2834-2000 tentang tata cara pembuatan rencana campuran beton normal. Sampel beton akan diuji dengan alat kuat tekan beton yang dilengkapi dengan dial ekstensometer sehingga dapat diperoleh kurva tegangan-regangan beton berdasarkan variasi fas yang diberikan. Berdasarkan hasil penelitianmaka kualitas beton yang dicor dalam kondisi tergenang air jauh lebih rendah dari nilai kuat tekan beton desain,  Persentase penurunan kuat tekan beton yang dicor dalam kondisi terendam air berkisar antara 30,82% sampai dengan 32,63% terhadap kuat tekan beton normal,  Semakin tinggi genangan air maka semakin rendah kuat tekan beton, Terdapat kesesuaian antara pengukuran kuat tekan beton menggunakan UTM  dengan uji hammer dan UPV, Persentase perbedaan pengukuran uji hammer terhadap hasil uji UTM adalah 10,73% dan 9,26% sampai dengan Kualitas beton yang dicor dalam kondisi tergenang air jauh lebih rendah dari nilai kuat tekan beton desain,  Persentase penurunan kuat tekan beton yang dicor dalam kondisi terendam air berkisar antara 30,82% sampai dengan 32,63% terhadap kuat tekan beton normal,  Semakin tinggi genangan air maka semakin rendah kuat tekan beton, Terdapat kesesuaian antara pengukuran kuat tekan beton menggunakan UTM  dengan uji hammer dan UPV, Persentase perbedaan pengukuran uji hammer terhadap hasil uji UTM adalah 10,73% dan 9,26% sampai dengan21,79% untuk uji UPV.Kata kunci: beton, foot plate, genangan, campuran

Estimating the Concrete Compressive Strength by Using the Concrete Ultrasonic Pulse Velocity and Moduli of Elasticity

2021 ◽  
Vol 1164 ◽  
pp. 77-86
Author(s):  
Bogdan Bolborea ◽  
Sorin Dan ◽  
Claudiu Matei ◽  
Aurelian Gruin ◽  
Cornelia Baeră ◽  
...  
Keyword(s):  
Compressive Strength ◽  
Ultrasonic Testing ◽  
Ultrasonic Pulse Velocity ◽  
Ultrasonic Pulse ◽  
Pulse Velocity ◽  
High Rate ◽  
Concrete Compressive Strength ◽  
Destructive Testing ◽  
Non Destructive ◽  
Moduli Of Elasticity

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.

Assessment of Compressive Strength for RC Building Using the Non-Destructive Test and the SonReb Method: A Case Study

2021 ◽  
Vol 1021 ◽  
pp. 45-54
Author(s):  
Mohammed Al-Helfi ◽  
Ali Allami
Keyword(s):  
Compressive Strength ◽  
Concrete Strength ◽  
Ultrasonic Pulse Velocity ◽  
Ultrasonic Pulse ◽  
Pulse Velocity ◽  
Test Method ◽  
Technical Institute ◽  
Existing Building ◽  
Destructive Test ◽  
Non Destructive

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.

Adapting ANNs in SONREB Test to Estimate Concrete Compressive Strength

2018 ◽  
Vol 792 ◽  
pp. 166-169
Author(s):  
Yu Ren Wang ◽  
Loan T.Q. Ngo ◽  
Yi Fan Shih ◽  
Yen Ling Lu ◽  
Yi Ming Chen
Keyword(s):  
Compressive Strength ◽  
Estimation Error ◽  
Ultrasonic Pulse Velocity ◽  
Ultrasonic Pulse ◽  
Pulse Velocity ◽  
Percentage Error ◽  
Non Destructive Testing ◽  
Concrete Compressive Strength ◽  
Destructive Testing ◽  
Non Destructive

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).

scholarly journals Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Palika Chopra ◽  
Rajendra Kumar Sharma ◽  
Maneek Kumar
Keyword(s):  
Compressive Strength ◽  
Genetic Programming ◽  
Prediction Models ◽  
Model Development ◽  
Strength Prediction ◽  
Ann Model ◽  
Concrete Compressive Strength ◽  
Compressive Strength Of Concrete ◽  
Artificial Neural

An effort has been made to develop concrete compressive strength prediction models with the help of two emerging data mining techniques, namely, Artificial Neural Networks (ANNs) and Genetic Programming (GP). The data for analysis and model development was collected at 28-, 56-, and 91-day curing periods through experiments conducted in the laboratory under standard controlled conditions. The developed models have also been tested on in situ concrete data taken from literature. A comparison of the prediction results obtained using both the models is presented and it can be inferred that the ANN model with the training function Levenberg-Marquardt (LM) for the prediction of concrete compressive strength is the best prediction tool.

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