EFFECTS OF VARYING WATER-CEMENT RATIOS ON DIFFERENT GRADES OF CONCRETE USING LOCALLY MATERIALS

This research focused on laboratory tests that was conducted using locally available 10mm washed all-in gravel, quarry dust with varying water cement ratio. The research was carried-out using 108 (150 x 150 x 150) mm standard cubes that were all tested from three designed concrete mixes. In the present study, the role of water-cement ratio in compressive strength of concrete was investigated. The mixed concrete samples with water-cement ratios of 0.3, 0.35 and 0.40 were experimented for 3, 7, 21 and 28 days of curing. The results of compressive strength experiment showed that due to increase in water-cement ratio from 0.3 to 0.40, the compressive strength improved from 22 N/mm2 to 24.33 N/mm2 for 1:1.5:3 design mix, the compressive strength improved from 22.88 N/mm2 to 24 N/mm2 for 1:2:1 design mix, while compressive strength improved from 24 N/mm2 to 25.3 N/mm2 for 1:1:2 design mix respectively. The results for compressive strength experiments showed that the 0.4 water-cement ratio resulted in the optimum compressive strength for all three design mixes.

Computation of Compressive Strength of GGBS Mixed Concrete using Machine Learning

Concrete is a composite material formed by cement, water, and aggregate. Concrete is an important material for any Civil Engineering project. Several concretes are produced as per the functional requirements using waste materials or by-products. Many researchers reported that these waste materials or by-products enhance the concrete properties, but the laboratory procedures for determining the concrete properties are time-consuming. Therefore, numerous researchers used statistical and artificial intelligence methods for predicting concrete properties. In the present research work, the compressive strength of GGBS mixed concrete is computed using AI technologies, namely Regression Analysis (RA), Support Vector Machine (SVM), Decision Tree (DT), and Artificial Neural Networks (ANNs). The cement content (CC), C/F ratio, w/c ratio, GGBS (in Kg & %), admixture, and age (days) are selected as input parameters to construct the RA, SVM, DT, ANNs models for computing the compressive strength of GGBS mixed concrete. The CS_MLR, Link_CS_SVM, 20LF_CS_DT, and GDM_CS_ANN models are identified as the best architectural AI models based on the performance of AI models. The performance of the best architectural AI models is compared to determine the optimum performance model. The correlation coefficient is computed for input and output variables. The compressive strength of GGBS mixed concrete is highly influenced by age (curing days). Comparing the performance of optimum performance AI models and models available in the literature study shows that the optimum performance AI model outperformed the published models.

Study on the Mechanical Properties and Frost Resistance of Multiple Modified Concrete

To study the effects of graphene oxide (GO), fly ash, and steel fiber on the mechanical properties and durability of concrete, the mechanical properties, frost resistance, and internal pore structure of modified concrete are investigated by compression tests, freeze–thaw cycle tests, and industrial computed tomography (CT) tests. The test results show that the compressive strength of concrete with GO is better than that of mixed concrete, concrete mixed with only steel fiber, and ordinary concrete. Further, it is strongest at all ages when the GO content is 0.03%; the compressive strength of mixed concrete with 30% of fly ash is generally better than that with 15% and 45% of fly ash. In general, the frost resistance of concrete with only GO is better than that of ordinary concrete. With the increase in fly ash content, the internal porosity of concrete decreases, and its compressive strength increases accordingly; as GO increases, the porosity decreases and then increases, with the lowest porosity and the highest compressive strength of concrete at 0.03% of GO. With an increase in porosity, the mass loss and relative dynamic elastic modulus of concrete increase after 100 freeze–thaw cycles, which indicates that porosity directly affects the frost resistance of concrete.

Materials for 3D Concrete Printing: Approach to Standardization in Russia

3D Concrete Printing (3DCP) technology, compared to traditional monolithic construction, gives a possibility to increase the workspeed and reduce the manual laborproportion, reduce material consumption and also improve the architectural appearance of buildings being erected. At the same time, more stringent requirements are imposed on the material for 3D printing in terms of rheological characteristicscontrol, strength developmentkinetics, interplay adhesion and some other parameters than for conventional ready-mixed concrete. Therefore, to ensure the mass application of technologies for additive construction production using concrete as printing ink, it is necessary to develop a regulatory and technical base, including the development of standard test methods to determine the operational properties of this typeofmaterials. The article examines the main trends in the management of the materials’properties for construction 3D printing based on cement binders and describes the principles of building a system for standardizing materials for 3D printing construction in Russia, which was developed with the participation of the authors of this article.

Interlaboratory Comparative Tests in Ready-Mixed Concrete Quality Assessment

Proper quality assessment of ready-mixed concrete, which is currently the principal material for construction, land engineering and architecture, has an impact on the optimisation and verification of correct functioning of individual stages of the production process. According to the European Standard EN 206 “Concrete–Specification, performance, production and conformity”, obligatory conformity control of concrete is carried out by the producer during its production. In order to verify the quality of concrete, investors generally commission independent laboratory units to perform quality assessment of both concrete mix and hardened concrete, which guarantees a high quality of construction works. One of the essential tools for ensuring the quality of test results is the participation of laboratories in the so-called proficiency testing (PT) or inter-laboratory comparisons (ILC). Participation in PT/ILC programmes is, on the one hand, a tool for demonstrating the laboratory’s performance, on the other hand an aid for maintaining the quality of available concrete tests and validating test methods. Positive evaluation is a confirmation of the laboratory’s capability for performing the tests. The paper presents the results of laboratory proficiency tests carried out by means of inter-laboratory comparisons, as shown in the example of quality assessment of ready-mixed concrete for nine participating laboratories. The tests were performed for concrete of the following parameters: strength class C30/37, consistency S3, frost resistance degree F150, and water resistance degree W8. This involved determining consistencies, air content and density of the concrete mix, and compressive strength of hardened concrete. For the evaluation of laboratory performance results, z-score, ζ-score and En-score were applied. The innovation of the proposed study lies in employing both classical and iterative robust statistical methods. In comparison with classical statistical methods, robust methods ensure a smaller impact of outliers and other anomalies on the measurement results. Following the analyses, clear differences were found between the types of detected discrepancy of test results, which occurred due to the nature of individual parameters. For two laboratories, two scores revealed unsatisfactory results for concrete mix consistency. The main reasons can be pouring into the cone-shaped form a concrete mixture that is too dry, or incorrect use of a measuring tool also creating a possibility that the obtained value can be wrongly recorded. Other possible reasons are discussed in the paper. Participation in inter-laboratory comparison programmes is undoubtedly a way to verify and raise the quality of tests performed for concrete mix and hardened concrete, whereas individual analysis of the results allows the laboratory quality system to be improved.