• Computers and Concrete
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• 제15권3호
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• pp.473-484
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• 2015

In this study, the availability of Schmidt hammer has been investigated as a reliable method to determine the quality of concrete in irrigation networks. For this purpose, the 28-day compressive strength of concrete material used in the construction irrigation channel of Bafra lowland, which is one of the most fertile plains in Turkey was examined by means of concrete compression and as well as concrete Schmidt hammer in laboratory conditions. This study was carried out on cylindrical samples to represent the everyday concrete party ($150m^3$) produced by contractor firm as 3 replications. The statistical analysis of experimental data showed that the correlations between the values of 28-day compressive strength of Schmidt hammer and the rebound number was found to be 0.98. Differences of the compressive strength between compression testing and Schmidt hammer were statistically significant at P<0.01. In this context, it was found that the reliability of compressive strength of the concrete compression test are excellent, also the reliability of compressive strength of Schmidt hammer are fair in assessing the quality of concrete irrigation channels.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 춘계 학술발표회
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• pp.584-594
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• 2010

It is difficult to prepare a specimen for directly testing a tensile strength of soils. Therefore, a tensile strength of soils has been measured indirectly. In this study, a mold and sample preparation tool for directly testing a tensile strength of soils has been developed and a tensile strength of weakly cemented sand was measured by using such device. A compressive strength of the cemented sand was also measured and its value was 30 times greater than its tensile strength.

• Geomechanics and Engineering
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• 제23권1호
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• pp.61-69
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• 2020

The uniaxial compressive strength (UCS) of rock is a basic parameter in underground engineering design. The disadvantages of this commonly employed laboratory testing method are untimely testing, difficulty in performing core testing of broken rock mass and long and complicated onsite testing processes. Therefore, the development of a fast and simple in situ rock UCS testing method for field use is urgent. In this study, a multi-function digital rock drilling and testing system and a digital core bit dedicated to the system are independently developed and employed in digital drilling tests on rock specimens with different strengths. The energy analysis is performed during rock cutting to estimate the energy consumed by the drill bit to remove a unit volume of rock. Two quantitative relationship models of energy analysis-based core drilling parameters (ECD) and rock UCS (ECD-UCS models) are established in this manuscript by the methods of regression analysis and support vector machine (SVM). The predictive abilities of the two models are comparatively analysed. The results show that the mean value of relative difference between the predicted rock UCS values and the UCS values measured by the laboratory uniaxial compression test in the prediction set are 3.76 MPa and 4.30 MPa, respectively, and the standard deviations are 2.08 MPa and 4.14 MPa, respectively. The regression analysis-based ECD-UCS model has a more stable predictive ability. The energy analysis-based rock drilling method for the prediction of UCS is proposed. This method realized the quick and convenient in situ test of rock UCS.

• Computers and Concrete
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• 제7권3호
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• pp.271-283
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• 2010

Testing of ultrasonic pulse velocity (UPV) is one of the most popular and actual non-destructive techniques used in the estimation of the concrete properties in structures. In this paper, artificial neural network (ANN) approach has been proposed for the evaluation of relationship between concrete compressive strength, UPV, and density values by using the experimental data obtained from many cores taken from different reinforced concrete structures with different ages and unknown ratios of concrete mixtures. The presented approach enables to find practically concrete strengths in the reinforced concrete structures, whose records of concrete mixture ratios are not yet available. Thus, researchers can easily evaluate the compressive strength of concrete specimens by using UPV values. The method can be used in conditions including too many numbers of the structures and examinations to be done in restricted time duration. This method also contributes to a remarkable reduction of the computational time without any significant loss of accuracy. Statistic measures are used to evaluate the performance of the models. The comparison of the results clearly shows that the ANN approach can be used effectively to predict the compressive strength of concrete by using UPV and density data. In addition, the model architecture can be used as a non-destructive procedure for health monitoring of structural elements.

• Computers and Concrete
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• 제33권2호
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• pp.137-145
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• 2024

The technique of experimentally determining concrete's compressive strength for a given mix design is time-consuming and difficult. The goal of the current work is to propose a best working predictive model based on different machine learning algorithms such as Gradient Boosting Machine (GBM), Stacked Ensemble (SE), Distributed Random Forest (DRF), Extremely Randomized Trees (XRT), Generalized Linear Model (GLM), and Deep Learning (DL) that can forecast the compressive strength of ternary geopolymer concrete mix without carrying out any experimental procedure. A geopolymer mix uses supplementary cementitious materials obtained as industrial by-products instead of cement. The input variables used for assessing the best machine learning algorithm not only include individual ingredient quantities, but molarity of the alkali activator and age of testing as well. Myriad statistical parameters used to measure the effectiveness of the models in forecasting the compressive strength of ternary geopolymer concrete mix, it has been found that GBM performs better than all other algorithms. A sensitivity analysis carried out towards the end of the study suggests that GBM model predicts results close to the experimental conditions with an accuracy between 95.6 % to 98.2 % for testing and training datasets.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1999년도 학회창립 10주년 기념 1999년도 가을 학술발표회 논문집
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• pp.783-786
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• 1999

The compressive strength of concrete is one of the most important properties in concrete structures. There are, two methods for the testing of concrete compressive strength in structure ; coring and nondestructive testing. The latter is more often used than the former in a view of time and expenses. The Nondestructive test methods used nowadays include Rebound Hammer test and Ultrasonic Pulse Velocity test. Carbonation through aging makes changes of the interior structure and the properties of concrete. It is well-known fact that the surface hardness of concrete is increased by its carbonation. This fact makes it difficult in estimating the compressive strength of concrete using Rebound Hammer test. This study aimed to quantitatively analyzed the effects of carbonation on results of the Rebound Hammer test.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2018년도 추계 학술논문 발표대회
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• pp.65-66
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• 2018

As a result of this study, it was possible to derive the compressive strength curves of ordinary to ultra high strength concrete using the hammer type non - destructive testing equipment. In order to obtain reliable results, it is necessary to construct additional data. In addition, if reliability is ensured through construction site evaluation, it is considered that the application is possible on construction site.

• 한국분말재료학회지
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• 제27권6호
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• pp.503-508
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• 2020

The mechanical properties and microstructures of hexagonal boron nitride (h-BN)-reinforced cement composites are experimentally studied for three and seven curing days. Various sizes (5, 10, and 18 ㎛) and concentrations (0.1%, 0.25%, 0.5%, and 1.0%) of h-BN are dispersed by the tip ultrasonication method in water and incorporated into the cement composite. The compressive strength of the h-BN reinforced cements increases by 40.9%, when 0.5 wt% of 18 ㎛-sized h-BN is added. However, the compressive strength decreases when the 1.0 wt% cement composite is added, owing to the aggregation of the h-BNs in the cement composite. The microstructural characterization of the h-BN-reinforced cement composite indicates that the h-BNs act as bridges connecting the cracks, resulting in improved mechanical properties for the reinforced cement composite.

• Geomechanics and Engineering
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• 제37권5호
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• pp.499-510
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• 2024

In northern China, abundant summer rainfall and a higher water table can weaken the soil due to salt heave, collapsibility, and increased moisture absorption, thus the chlorine saline soil (silty clay) needs to be stabilized prior to use in road embankments. To optimize chlorine saline soil stabilizing programs, unconfined compressive strength tests were conducted on soil treated with five different stabilizers before and after soaking, followed by field compaction test and unconfined compressive strength test on a trial road embankment. In situ testing were performed with the stabilized soils in an expressway embankment, and the results demonstrated that the stabilized soil with lime and SH agent (an organic stabilizer composed of modified polyvinyl alcohol and water) is suitable for road embankments. The appropriate addition ratio of stabilized soil is 10% lime and 0.9% SH agent. SH agent wrapped soil particles, filled soil pores, and generated a silk-like web to improve the moisture stability, strength, and stress-strain performance of stabilized soil.

• Computers and Concrete
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• 제19권6호
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• pp.717-724
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• 2017

In this paper, four formulas are proposed via gene expression programming (GEP)-based models and regression analysis (RA) to predict the flexural strength ($f_s$) values of mortars containing different mineral admixtures that are ground granulated blast-furnace slag (GGBFS), silica fume (SF) and fly ash (FA) at different ages. Three formulas obtained from the GEP-I, GEP-II and GEP-III models are constituted to predict the $f_s$ values from the age of specimen, water-binder ratio and compressive strength. Besides, one formula obtained from the RA is constituted to predict the $f_s$ values from the compressive strength. To achieve these formulas in the GEP and RA models, 972 data of the experimental studies presented with mortar mixtures were gathered from the literatures. 734 data of the experimental studies are divided without pre-planned for these formulas achieved from the training and testing sets of GEP and RA models. Beside, these formulas are validated with 238 data of experimental studies un-employed in training and testing sets. The $f_s$ results obtained from the training, testing and validation sets of these formulas are compared with the results obtained from the experimental studies and the formulas given in the literature for concrete. These comparisons show that the results of the formulas obtained from the GEP and RA models appear to well compatible with the experimental results and find to be very credible according to the results of other formulas.