Effect of Ether-Typed Polycarboxylate Superplasticizer on the Adsorption, Rheology and Concrete Properties

This article disclosed the influence of acid-ether ratio, n(SH)/n(IPEG), and n(APS)/n(IPEG) on adsorption and fluidity performance. The optimum synthetic parameters of acid-ether ratio, n(SH)/n(IPEG) and n(APS)/n(IPEG) were 0.5, 0.35 and 0.05, respectively. The rheology fitting equation was τ= 719.55γ+ 1834.54. And the correlation coefficient was 0.9843. The cement paste conformed to the law of pseudoplastic fluid. The preferred PCE-11 had excellent performance in freshly mixed and hardened concrete.

A Users Guide to Performance Engineered Mixtures

Performance Engineered Mixtures is an initiative, spearheaded by the Federal Highway Administration and the National Concrete Pavement Technology Center, in cooperation with state Departments of Transportation and the concrete paving industry, to develop a comprehensive approach to modernizing the way concrete is specified, tested, and accepted. It focusses on three components: testing of six critical concrete properties, a robust approach to quality control, and the replacement of prescriptive specifications. Many new tests have been recently developed that provide the ability to test concrete properties more easily and quicker than in the past. This paper provides background of how this initiative began. It elaborates on each of the six properties of concrete that are the focus of PEM. The new tests that are integral to the PEM process are described. The effects PEM will have on the acceptance process and the quality control responsibilities are outlined. Finally, tables are included which list the properties and the tests that are associated with each property, as well as how each is applied to each step of the paving process.

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.

Concrete Properties using Treated Recycled EPS

The study explores the mechanical properties of treated recycled extended polystyrene (TEPS) concrete, treated by two methods, one by heating, and the other by immersed recycled EPS in cement neat. By substituting 0 %, 15 %, 25 %, and 35 % of the coarse aggregate volume with treated recycled EPS, (for both method). Treated recycled TEPS concrete ratios are experimentally prepared, while the cement is substituted thru 10 % silica fume (SF). Tests were carried out, like compressive strength, splitting tensile strength, modulus of rupture, and density. The outcomes display the decreasing of the compressive strength, tensile strength and modulus of rupture of TEPS concretes with rise TEPS percentage around 26 %, 17 % and 32 %, respectively (35% TEPS) related to standard concrete. They also show that TEPS concrete density decrease about 30 % of normal concrete. The TEPS is suitable in concrete and meets provisions.