Evaluating the Possibility of Replacing Natural Fine Aggregates in Concrete with Recycled Aggregates

This paper presents an investigation on the possibility of replacing natural fine aggregates with recycled aggregates in concrete. The studied recycled aggregates were acquired from crushed waste concrete from demolishing works. The rate of replacement of natural fine aggregates was 10%, 20%, and 30% by weight. Compressive and flexural tensile strength of concrete incorporating recycled aggregates was investigated at 28 days of curing. The results show that the compressive and flexural strength of concrete is strongly affected by the percentage of recycled aggregates. It has been found that the strength decreases linearly with increasing recycled aggregate content. So, in order to apply recycled waste to concrete as fine aggregates, it is necessary to perform supplement research with appropriate additives to compensate for the loss of compressive and flexural strength.

Investigation of ANN architecture for predicting the compressive strength of concrete containing GGBFS

An extensive simulation program is used in this study to discover the best ANN model for predicting the compressive strength of concrete containing Ground Granulated Blast Furnace Slag (GGBFS). To accomplish this purpose, an experimental database of 595 samples is compiled from the literature and utilized to find the best ANN architecture. The cement content, water content, coarse aggregate content, fine aggregate content, GGBFS content, carboxylic type hyper plasticizing content, superplasticizer content, and testing age are the eight inputs in this database. As a result, the optimal selection of the ANN design is carried out and evaluated using conventional statistical metrics. The results demonstrate that utilizing the best architecture [8–14–4–1] among the 240 investigated architectures, and the best ANN model, is a very efficient predictor of the compressive strength of concrete using GGBFS, with a maximum R2 value of 0.968 on the training part and 0.965 on the testing part. Furthermore, a sensitivity analysis is performed over 500 Monte Carlo simulations using the best ANN model to determine the reliability of ANN model in predicting the compressive strength of concrete. The findings of this research may make it easier and more efficient to apply the ANN model to many civil engineering challenges.

Characteristics of Soil Aggregates and Its Organic Carbon in Daxing'anling Forest Region

The distribution and spatial variability of soil aggregates and their organic carbon and their responses to environmental factors in Daxing'anling forest region were studied by field investigation and laboratory analysis. In Daxing'anling forest region, 75 sampling points were set up based on kilometer grid, and the sample circle with radius of 17.85m was set at each sampling point. In each circle, three samples of 0-20 cm topsoil were taken to determine soil chemical indexes, soil aggregates and their organic carbon content. The results showed that: (1) the soil aggregate content followed the order as (0.25~2 mm aggregate) > (<0.053 mm aggregate) > (0.053~0.25 mm aggregate). The spatial autocorrelation of each fraction of aggregate were moderate, and they were affected by the structural factors such as climate, vegetation, soil and random factors such as human activities. The content of 0.25~2 mm and <0.053 mm aggregates decreased gradually from north to south, while the content of 0.053~0.25 mm aggregates was opposite to them. (2) The organic carbon content of soil aggregates was mainly concentrated in the 0.25~2 mm large aggregates (19.84 g/kg) with the contribution rate 50.39%; the organic carbon contents of each fraction of aggregate showed high spatial autocorrelation which was mainly affected by structural factors; the spatial difference of soil aggregate content in each particle size was not significant, and the distribution was patchy. There was no significant spatial difference in the organic carbon contents of soil aggregate in different fractions with patch distribution characteristics. (3) Temperature had no significant effect on the formation and stability of soil aggregates, and precipitation is beneficial to the formation of micro-aggregates <0.053 mm; soil organic carbon was conducive to the cementation of small-sized aggregates into large aggregates, which had a positive effect on the stability of soil aggregates. There was a significant positive correlation between SOC and organic carbon of soil aggregates in different fractions, and the correlation degree was gradually weakened with the decrease of particle size; the contents of soil nitrogen, phosphorus, potassium and other nutrients could promote the organic carbon accumulation in soil aggregates. The results can provide the basis for the soil rational use and the carbon fixation capacity improvement of forest in Daxing'anling forest region.

Lightweight Concretes with Improved Water and Water Vapor Transport for Remediation of Damp Induced Buildings

Most of the historical and old building stock in Europe are constructed from masonry, when brick, stones, or their combination are bound with traditional mortars. Rising damp, due to accompanying effects, is the main factor influencing the quality of indoor climate as well as having an important impact on the durability of masonry structures. In this study, new types of lightweight concrete with waste aggregate content as a suitable material for remediation of damp damaged masonries were designed and tested. Alternative aggregate served as silica sand substitution in the range of 0–100 vol.%. Basic structural properties, mechanical resistance, water, and water vapor transport properties were measured after 28 days of water curing and were compared with dense reference concrete and with traditional masonry materials as well. Moreover, the porous structure of produced concretes and changes caused by usage of alternative aggregate usage were evaluated with the mercury intrusion porosimetry (MIP) technique. Obtained experimental data showed the suitability of modified concretes with 25–50 vol.% of waste aggregate content to ensure acceptable strength and hydric properties, and these properties were found to be comparable with masonry structures and materials used in the past.

Chloride Ion Diffusion and Durability Characteristics of Rural-Road Concrete Pavement of South Korea Using Air-Cooled Slag Aggregates

In the construction industry, the lack of supply and demand for high-quality natural aggregates is a problem. In the case of South Korea, according to data from the Ministry of Environment, it is predicted that the depletion of aggregate resources will occur in 20 years, considering the amount of aggregate used in construction every year and the amount of natural aggregate. Therefore, it is necessary to develop recycled aggregates that can replace natural aggregates for construction. The purpose of this study is to evaluate the applicability of recyclable air-cooled slag (ACS) aggregates as a substitute material for natural aggregates applied to rural-road pavement concrete. That is, the applicability of rural-road pavement concrete is evaluated by evaluating the strength and durability of rural-road pavement concrete to which an ACS aggregate is applied. Durability was assessed in terms of the chloride ion diffusion, repeated wetting-drying, abrasion resistance, impact resistance, and repeated freezing-thawing tests. The test result showed that the diffusion coefficient of the mixture to which the ACS aggregate was applied was slightly larger. In addition, the diffusion coefficient was slightly larger in the case of applying the air-cooled slag coarse aggregate (GG) than in the case of applying the air-cooled slag fine aggregate (GS). The results of abrasion and impact resistance tests of ACS-aggregate-incorporated rural-road concrete indicated that abrasion and impact resistance decreased as the aggregate content increased. The ACS retained some of the properties of the blast furnace slag. Thus, in repetitive wetting-drying tests, which can cause changes in chemical properties, the ACS aggregate increased the concrete’s long-term residual strength. In addition, the results showed that the relative dynamic elastic modulus targeting repeated freezing-thawing resistance satisfied the 80% target. The freeze-thaw resistance improved as the ACS aggregate content increased. In conclusion, the results of this study showed that the durability of rural-road pavement concrete can be improved experimentally by applying both GG and GS at the same time. Therefore, it is shown that ACS aggregates can be applied to rural-road pavement concrete as a substitute for natural aggregates.

Prediction of the Compressive Strength of Recycled Aggregate Concrete Based on Artificial Neural Network

Recycled aggregate concrete (RAC), due to its high porosity and the residual cement and mortar on its surface, exhibits weaker strength than common concrete. To guarantee the safe use of RAC, a compressive strength prediction model based on artificial neural network (ANN) was built in this paper, which can be applied to predict the RAC compressive strength for 28 days. A data set containing 88 data points was obtained by relative tests with different mix proportion designs. The data set was used to develop an ANN, whose optimal structure was determined using the trial-and-error method by taking cement content (C), sand content (S), natural coarse aggregate content (NCA), recycled coarse aggregate content (RCA), water content (W), water–colloid ratio (WCR), sand content rate (SR), and replacement rate of recycled aggregate (RRCA) as input parameters. On the basis of different numbers of hidden layers, numbers of hidden layer neurons, and transfer functions, a total of 840 different back propagation neural network (BPNN) models were developed using MATLAB software, which were then sorted according to the correlation coefficient R2. In addition, the optimal BPNN structure was finally determined to be 8–12–8–1. For the training set, the correlation coefficient R2 = 0.97233 and RMSE = 2.01, and for the testing set, the correlation coefficient R2 = 0.96650 and RMSE = 2.42. The model prediction deviations of the two were both less than 15%, and the results show that the ANN achieved pretty accurate prediction on the compressive strength of RAC. Finally, a sensitivity analysis was carried out, through which the impact of the input parameters on the predicted compressive strength of the RAC was obtained.

Bond and flexural performance of basalt fiber–reinforced polymer bar–reinforced seawater sea sand glass aggregate concrete beams

This article proposes a new type of basalt fiber–reinforced polymer (BFRP) bar–reinforced seawater sea sand glass aggregate concrete (SSGC) beam with broad application prospects in ocean engineering. Crushed tempered glasses were utilized as coarse aggregates in the concrete mixture to realize the efficient and harmless recycling of waste glass. First, the bond behaviors between the BFRP bars and SSGC with different glass aggregate replacement ratios were investigated. Then, four-point bending tests were conducted to investigate the flexural performance of the SSGC beams completely reinforced with BFRP bars. Based on this, the tested flexural strengths were compared with the calculated strengths to evaluate whether the existing specifications were still applicable to the design of the BFRP bar–reinforced SSGC beams. Test results showed that although the compressive strength of the SSGC gradually decreased with increased glass aggregate content, the bond performance between BFRP bars and SSGC did not follow the same degradation pattern. There were no obvious differences in the form of the bond–slip curves between BFRP bars and different types of SSGC. With increasing glass aggregate content, the ultimate bearing capacity and energy consumption of BFRP bar–reinforced SSGC beams decreased. All calculated ultimate flexural capacities were higher than the experimental values, which shows that the application of existing specifications to BFRP bar–reinforced SSGC beams needs to be studied further.