This study used two types of Recycled Concrete Aggregates (RCAs) with the same original virgin aggregate, but with different amounts of residual mortars. To verify that the mechanical properties of the concrete were affected by changing the unit volume of residual mortar, fresh mortar, and total mortar of the concrete, a series of paving concrete mixes were made using a modified equivalent mortar volume (EMV) mix design, along with a conventional American Concrete Institute (ACI) mix design. The test results showed that the RCA concrete with the conventional mix design, which led to a prominent decrease in compressive strength and elastic modulus at each age, had 10% greater total mortar volume than that with the modified EMV mix design. As for the conventional ACI mix, it appears that the replacement ratio of RCA and the volume of the residual mortar in RCA directly affect the modulus of elasticity as well as the compressive strength of concrete. However, for the modified EMV mix, the modulus of elasticity of the concrete may be increased to be equivalent to the companion concrete with natural aggregate by controlling the new mortar volume so that the total mortar volume remains the same regardless of the RCA replacement ratio. It was observed that the smaller new volume requirement makes the RCA paving concrete more environmentally friendly and economically profitable.

The goal of this work is to show how machine learning models, such as the random forest, neural network, gradient boosting, and AdaBoost models, can be used to forecast the fatigue life (N) of plain concrete under uniaxial compression. Here, we developed our final machine learning model by generating the following three data files from the original data used in the work of Zhang et al.: (a) grouped data with the same input variable value and different output variable logN value, (b) data excluding outliers selected by three or more outlier detection methods; (c) average data excluding outliers, created by averaging the grouped data after excluding outliers from among the grouped data. Excluding the sustained strength of the concrete variable, originally treated as the seventh input variable in the work of Zhang et al., resulted in improving the determination coefficient (R²) values. Moreover, the gradient boosting model showed a high R² value at 0.753, indicating a high accuracy in predicting outcomes. Further analysis using data excluding outliers shows that the R² value increased to 0.803. Moreover, the average data excluding outliers provided the best R² value at 0.915. Finally, a permutation feature importance (PFI) analysis was carried out to determine the strength of the relationship between the feature and the target value for the gradient boosting model. The analysis results showed that the maximum stress level (S_max) and loading frequency (f) were the most significant input variables, followed by compressive strength (f′_c) and maximum to minimum stress ratio (R). Shape and height to width ratio (h/w) were the features with a non-significant influence on the model. This trend was previously confirmed by a Pearson and Spearman correlation analysis.

To evaluate the effect of the mix proportioning method on drying shrinkage and freeze-and-thaw resistance of recycled concrete aggregate (RCA) concrete, two series of concrete mixes were made using the modified equivalent mortar volume (EMV) method and the conventional ACI method. In this study, different sources of RCAs were manufactured from on-site plants on air bases and at a commercial recycling plant. Keeping the total mortar at the same level, concrete mixes were proportioned by the modified EMV method, using different scale factors: S = 1 (with RCA substitution of 23%), S = 2 (with RCA substitution of 47%), and S = 3 (with RCA substitution of 73%). It was assumed that the residual mortar volume in the RCA concrete was represented in the sum of the volume of mortar and the volume of aggregate, in variance to the scale factors. Test results showed that the modified EMV method for all the mixes yielded the drying shrinkage property of the RCA concrete comparable to that of the companion concrete with natural coarse aggregate. On the other hand, it was observed in the freeze-and-thaw test that the modified EMV method could be marginally applied to the limited condition with S = 2.

The decrease in the quality of recycled aggregate due to an increase in the number of recycling is a primary factor that limits the multi-recycling of concrete. This degradation adversely affects concrete performance; thus, the characteristics of recycled aggregate should be considered during the mix design stage, but little research has taken that into account. This study investigates the effect of the equivalent mortar volume (EMV) mix design on some physical, mechanical and durability properties of concrete made of multiple recycled coarse aggregates at 50% and 100% replacement ratios compared to concrete made by the conventional mix design (CMD). The results showed that the performances of concrete by the CMD decreased with an increasing number of recycling cycles. The properties of EMV-based concrete deteriorated with an increase in the number of recycling cycles at 100% replacement ratio due to poor workability caused by a shortage of fresh mortar. However, at 50% replacement, the EMV-based concrete exhibited similar performance across the three cycles of recycling, as well as improved properties over natural aggregate concrete. This study demonstrated that an appropriate mix design and optimal aggregate replacement ratio can offset the property loss of multiple recycled aggregate concrete.

Residual mortar attached to recycled concrete aggregate (RCA) always leads to a decrease in Young’s modulus and an increase in the drying shrinkage of RCA concrete, mainly due to an increase of total mortar volume. To overcome this inherent problem, the modified and equivalent mortar volume (EMV) methods were proposed by researchers. Despite the comparable test results, both models are still subject to the slump loss problem. Thus, under the same W/C (water to cement ratio) ratio and slump condition, this study assessed the influence of the modified EMV mix method on RCA concrete properties. A total of six mixes were proportioned using the modified EMV method with three different RCAs. Test results show that the concrete mixed with RCA produced from old PC concrete sleepers exhibited compressive strength, Young’s modulus, and flexural strength values within 2% variation, equivalent to those values of the companion natural aggregate concrete. In other mixes, compressive strength was found to decrease to 11–20%. It was observed that for 100% replacement of RCA mix, Young’s modulus increased to 10% and drying shrinkage increased to 8% only, while for 50% replacement of RCA mix, Young’s modulus decreased to 8% and drying shrinkage dropped to 4%.

This study aims to show the effect of a modified equivalent mortar volume (EMV) method on the flexural performance of recycled concrete aggregate (RCA). To verify this, an experimental study was carried out firstly by testing fresh and hardened material properties of RCA concrete specimens made by two different mixture design methods, i.e., the modified EMV method and the conventional American Concrete Institute (ACI) method. The flexural performance of five reinforced recycled concrete (RRC) beams mixed with different mixture designs was then investigated. Test results confirmed that the elastic moduli of the RCA concrete specimens made using the modified EMV method are greater than those of the conventional ACI mixture, while the drying shrinkage tended to decrease. The ultimate strengths of RRC beams mixed with the modified EMV method are as much as five percent greater than that achieved with the conventional ACI mixture.