The Effect of Size on the Splitting Strength of Cubic Concrete Members

İnce, Ragıp; Gör, Mesut; Eren, Mehmet Esen; Alyamaç, Kürşat Esat

doi:10.1111/str.12127

Cited by 27 publications

(7 citation statements)

References 30 publications

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“…Diagonal tensile strength test called as also split tension strength of diagonal cubes is used to estimate fracture of concrete. However, assessment of fracture parameters of mortar is indispensable due to increasing lateral tensile stress under diagonal vertical loading condition [27]. For this purpose, diagonal tensile strength test was performed on the mortar specimen to measure tensile strength resistivity.…”

Section: Diagonal Tensile Strength Test Resultsmentioning

confidence: 99%

Properties of Self-Compacting Mortars with Different Contents of Synthetic Macro Fiber

Etli¹,

Cemalgil²,

Onat³

2018

acperpro

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This study is devoted to investigating engineering properties of Self-Compacting Mortar (SCMs) produced with synthetic macro fiber. For this purpose, five different mix designs were prepared with a constant w/c ratio of 0.55 to sustain self-compatibility. Fiber content in these mixtures were changed from 0% to 5%. Engineering properties were investigated in terms of workability, mechanical properties and abrasion resistance. Compressive strength and flexural strength tests were conducted on the specimens exposed to three different water curing age 7 days, 28 days and 56 days respectively. In this study, also optimum synthetic fiber amount was determined to sustain self-compatibility of mortar. It was revealed that 2 and 3 kg/m3 synthetic macro fiber ratio are the key proportions to improve workability and flexural strength properties of hardened mortar. Moreover, adding fiber to mortar decreased abrasion resistance at 28 days age. In reverse, fiber addition increased abrasion resistance at 56 days age.

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Section: Diagonal Tensile Strength Test Resultsmentioning

confidence: 99%

Properties of Self-Compacting Mortars with Different Contents of Synthetic Macro Fiber

Etli¹,

Cemalgil²,

Onat³

2018

acperpro

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“…Similar studies are performed in regard to hybrid metaheuristic optimization approaches [23][24][25][26][27][28][29]. Also, in the field of energy management, neural networks have emerged as one of the effective prediction tools [30][31][32][33].…”

Section: Introductionmentioning

confidence: 92%

Predicting Heating Load in Energy-Efficient Buildings Through Machine Learning Techniques

et al. 2019

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The heating load calculation is the first step of the iterative heating, ventilation, and air conditioning (HVAC) design procedure. In this study, we employed six machine learning techniques, namely multi-layer perceptron regressor (MLPr), lazy locally weighted learning (LLWL), alternating model tree (AMT), random forest (RF), ElasticNet (ENet), and radial basis function regression (RBFr) for the problem of designing energy-efficient buildings. After that, these approaches were used to specify a relationship among the parameters of input and output in terms of the energy performance of buildings. The calculated outcomes for datasets from each of the above-mentioned models were analyzed based on various known statistical indexes like root relative squared error (RRSE), root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (R2), and relative absolute error (RAE). It was found that between the discussed machine learning-based solutions of MLPr, LLWL, AMT, RF, ENet, and RBFr, the RF was nominated as the most appropriate predictive network. The RF network outcomes determined the R2, MAE, RMSE, RAE, and RRSE for the training dataset to be 0.9997, 0.19, 0.2399, 2.078, and 2.3795, respectively. The RF network outcomes determined the R2, MAE, RMSE, RAE, and RRSE for the testing dataset to be 0.9989, 0.3385, 0.4649, 3.6813, and 4.5995, respectively. These results show the superiority of the presented RF model in estimation of early heating load in energy-efficient buildings.

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“…To determine the split tensile strength of concrete, cylindrical specimens are proposed by [99] and were successfully applied to cubical specimens by Nilson., 1961 [100]. Various experiments on split tensile strength specimens have revealed that the nominal strength of specimen initially decreases with an increase in specimen size and subsequently approaches constant value [101]. Smaller size specimens show higher strain when compared to that of higher size specimens, resulting in higher strength for a smaller area of specimens.…”

Section: Impact Of Split Tensile Load Area On Strength Ratiomentioning

confidence: 99%

“…Most of the results from Figure 14 indicate that the higher split tensile strength area is notified for the lower grade of SCC predominantly. Analytical and numerical studies on split-tension specimens have revealed that nominal strength is highly affected by the width of the distributed load and the specimen size [101].…”

Section: Impact Of Split Tensile Load Area On Strength Ratiomentioning

confidence: 99%

“…A higher split tensile load area is observed for all the families from Figure 14, with a strength ratio from 0.05 to 0.15. The higher the split tensile load area and confinement area results in the higher the ratio is, due to the total length of cracks involved in the failure process of the specimen increasing with the increase in the size of the specimen [101].…”

Section: Impact Of Split Tensile Load Area On Strength Ratiomentioning

confidence: 99%

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Impact of Design Parameters on the Ratio of Compressive to Split Tensile Strength of Self-Compacting Concrete with Recycled Aggregate

Martínez‐García

Jagadesh²,

Búrdalo

et al. 2021

Materials

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Most concrete studies are concentrated on mechanical properties especially strength properties either directly or indirectly (fresh and durability properties). Hence, the ratio of split tensile strength to compressive strength plays a vital role in defining the concrete properties. In this review, the impact of design parameters on the strength ratio of various grades of Self-Compacting Concrete (SCC) with recycled aggregate is assessed. The design parameters considered for the study are Water to Cement (W/C) ratio, Water to Binder (W/B) ratio, Total Aggregates to Cement (TA/C) ratio, Fine Aggregate to Coarse Aggregate (FA/CA) ratio, Water to Solid (W/S) ratio in percentage, superplasticizer (SP) content (kg/cu.m), replacement percentage of recycled coarse aggregates (RCA), replacement percentage of recycled fine aggregates (RFA), fresh density and loading area of the specimen. It is observed that the strength ratio of SCC with recycled aggregates is affected by design parameters.

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The Effect of Size on the Splitting Strength of Cubic Concrete Members

Cited by 27 publications

References 30 publications

Properties of Self-Compacting Mortars with Different Contents of Synthetic Macro Fiber

Properties of Self-Compacting Mortars with Different Contents of Synthetic Macro Fiber

Predicting Heating Load in Energy-Efficient Buildings Through Machine Learning Techniques

Impact of Design Parameters on the Ratio of Compressive to Split Tensile Strength of Self-Compacting Concrete with Recycled Aggregate

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