Effects of Different Coatings, Primers, and Additives on Corrosion of Steel Rebars.

In this research, methods of increasing the corrosion resistance of reinforced concrete were experimentally investigated. The study used silica fume and fly ash at optimized percentages of 10 and 25% by cement weight, polypropylene fibers at a ratio of 2.5% by volume of concrete, and a commercial corrosion inhibitor, 2-dimethylaminoethanol (Ferrogard 901), at 3% by cement weight. The corrosion resistance of three types of reinforcements, mild steel (STt37), AISI 304 stainless steel, and AISI 316 stainless steel, was investigated. The effects of various coatings, including hot-dip galvanizing, alkyd-based primer, zinc-rich epoxy primer, alkyd top coating, polyamide epoxy top coating, polyamide epoxy primer, polyurethane coatings, a double layer of alkyd primer and alkyd top coating, and a double layer of epoxy primer and alkyd top coating, were evaluated on the reinforcement surface. The corrosion rate of the reinforced concrete was determined through results of accelerated corrosion and pullout tests of steel-concrete bond joints and stereographic microscope images. The samples containing pozzolanic materials, the corrosion inhibitor, and a combination of the two showed significant improvement in corrosion resistance by 7.0, 11.4, and 11.9 times, respectively, compared to the control samples. The corrosion rate of mild steel, AISI 304, and AISI 316 decreased by 1.4, 2.4, and 2.9 times, respectively, compared to the control sample; however, the presence of polypropylene fibers reduced the corrosion resistance by 2.4 times compared to the control.

Optimized Alkali-Activated Slag-Based Concrete Reinforced with Recycled Tire Steel Fiber.

This study employed Taguchi-Grey relational analysis to optimize the influences of binder content, the molarity of sodium hydroxide (SH) solution, alkaline solution to binder content (Al/Bi) ratio, water to alkali-activated solids (W/S) ratio, and sodium silicate to sodium hydroxide solution (SS/SH) ratio on the workability, setting time, and compressive strength of alkali-activated slag-based concrete (AASC). Then, the recycled tire steel fibers (RTSF) were introduced into the optimized mixture in different dosages, and the physical and mechanical properties of fiber-reinforced AASC (FR-AASC) were evaluated. RTSF inclusion negatively affected the workability and increased the density while slightly reducing the water absorption. Additionally, the compressive strength and flexural behavior of FR-AASC improved by increasing the RTSF content. The analysis of images taken from flexural specimens through the Digital Image Correlation technique (DIC) revealed that higher RTSF dosage caused a curved macro crack with several branches alongside, leading to a better post-cracking performance in terms of strength and toughness.

Coal tailings as a soil conditioner: evaluation of tailing properties and effect on tomato plants.

The global coal industry yields a vast amount of tailings waste, and the utilisation of these tailings necessitates innovative efforts contributing to the United Nations Sustainable Development Goals. One of such novel initiatives is to reuse coal tailings (CT) safely, ecofriendly, and cost-effectively in agroecosystems as a soil conditioner to enhance the productivity of lands. This study aimed to evaluate the potential utilisation of coal tailings waste in the soil amelioration to improve plant performance. The physico-chemical characteristics of coal tailings from two Australian mining sites (CT1 and CT2) showed that the tailings samples are alkaline with loamy and loamy sand textures, respectively. The tailings have ~ 3% of macronutrients, high carbon (C), and low heavy metals and metalloids (As, Cd, Se, Cu, Zn, and Pb). The germination rate of tomato seeds was improved in the low-rate CT treatment. Greenhouse tomato plants exhibited an increase in leaf's K, Ca, and Mg contents in CT1 and CT2 treatments. More importantly, the CT treatment-induced accumulation of heavy metals in plants was mostly insignificant in both CT treatments. Therefore, we highlight the potential application of coal tailings as a soil conditioner because of the beneficial effect of improved carbon and nutrients (N, P, K, Mg, and Ca) in tomato leaves. Further amendment of the coal tailings should focus on the adjustment of pH and the addition of other beneficial materials for the improvement of soil properties for crops in both the greenhouse and the field.

Properties of Lime-Cement Concrete Containing Various Amounts of Waste Tire Powder under Different Ground Moisture Conditions.

Lime-cement concrete (LCC) is a non-structural concrete in which lime and cement are used as the main binders. However, although LCC has many applications in reducing the settlement of foundations and providing a support layer for shallow foundations, little research has been conducted to evaluate its behaviour in various moisture conditions. Previous researchers have studied the feasibility of using waste tires in conventional concrete to alleviate their negative environmental impacts. However, in field projects, rubber has not been widely used because its application leads to the strength reduction of concrete. In the case of LCC, attaining high strengths is not required and thus application of waste tire particles sounds reasonable. This research evaluated the impact of various rubber powder contents on the fresh, geotechnical and durability properties of LCC at different saturation degrees induced by the capillary action and groundwater level increment, which has not been studied before. The results of more than 320 tests showed that the application of tire powder increases workability and decreases the water absorption of LCC. Moreover, all 60-day cured specimens exposed to 100% saturation degree experienced a strength reduction of less than 10% by using rubber powder contents varying from 0 to 20%. Moreover, increasing the saturation degree from 0 to 100% decreased the average compressive strength by 13.5 and 22% for 60-day cured samples of two different mix designs. The results of this research confirm that LCC containing up to 10% rubber powder could be promisingly used underneath or close to the groundwater table without its strength and geotechnical properties being jeopardized due to rubber employment and/or exposure to ground moisture.

Fresh, Mechanical, and Durability Properties of Self-Compacting Mortar Incorporating Alumina Nanoparticles and Rice Husk Ash.

This paper presents a comprehensive evaluation on self-compacting (SC) mortars incorporating 0, 1, 3, and 5% alumina nanoparticles (NA) as well as 0% and 30% rice husk ash (RHA) used as Portland cement replacement. To evaluate the workability, mechanical, and durability performance of SC mortars incorporating NA and RHA, the fresh properties (slump flow diameter and V-funnel flow time), hardened properties (compressive strength, flexural strength, and ultrasonic pulse velocity), and durability properties (water absorption, rapid chloride permeability, and electrical resistivity) were determined. The results indicated that the addition of NA and RHA has negligible effect on the workability and water absorption rate of the SC mortars. However, significant compressive and flexural strength development was observed in the SC mortars treated with NA or the combination of NA and RHA. The introduction of RHA and NA also reduced the rapid chloride permeability and enhanced the electrical resistivity of the SC mortars significantly. It is concluded that the coexistence of 30% RHA and 3% NA as cement replacement in SC mortars can provide the best mechanical and durability performance.

Mechanical Properties of Recycled Aggregate Concretes Containing Silica Fume and Steel Fibres.

In this study, the impact of steel fibres and Silica Fume (SF) on the mechanical properties of recycled aggregate concretes made of two different types of Recycled Coarse Aggregates (RCA) sourced from both low- and high-strength concretes were evaluated through conducting 60 compressive strength tests. The RCAs were used as replacement levels of 50% and 100% of Natural Coarse Aggregates (NCA). Hook-end steel fibres and SF were also used in the mixtures at the optimised replacement levels of 1% and 8%, respectively. The results showed that the addition of both types of RCA adversely affected the compressive strength of concrete. However, the incorporation of SF led to compressive strength development in both types of concretes. The most significant improvement in terms of comparable concrete strength and peak strain with ordinary concrete at 28 days was observed in the case of using a combination of steel fibres and SF in both recycled aggregate concretes, especially with RCA sourced from high strength concrete. Although using SF slightly increased the elastic modulus of both recycled aggregate concretes, a substantial improvement in strength was observed due to the reinforcement with steel fibre and the coexistence of steel fibre and SF. Moreover, existing models to predict the elastic modulus of both non-fibrous and fibrous concretes are found to underestimate the elastic modulus values. The incorporation of SF changed the compressive stress-strain curves for both types of RCA. The addition of steel fibre and SF remarkably improved the post-peak ductility of recycled aggregates concretes of both types, with the most significant improvement observed in the case of RCA sourced from a low-strength parent concrete. The existing model to estimate the compressive stress-strain curve for steel fibre-reinforced concrete with natural aggregates was found to reasonably predict the compressive stress-strain behaviour for steel fibres-reinforced concrete with recycled aggregate.

Seismic response prediction of FRC rectangular columns using intelligent fuzzy-based hybrid metaheuristic techniques.

This research study focused on the dynamic response and mechanical performance of fiber-reinforced concrete columns using hybrid numerical algorithms. Whereas test data has non-linearity, an artificial intelligence (AI) algorithm has been incorporated with different metaheuristic algorithms. About 317 datasets have been applied from the real test results to detect the promising factor of strength subjected to the seismic loads. Adaptive neuro-fuzzy inference system (ANFIS) was carried out as an AI beside the combination of particle swarm optimization (PSO) and genetic algorithm (GA). Extreme Machine Learning (ELM) was also performed in order to approve the obtained results. According to the findings, it is demonstrated that ANFIS-PSO predicts the lateral load with promising evaluation indexes [R2 (test) = 0.86, R2 (train) = 0.90]. Mechanical performance prediction was also carried out in this study, and the results showed that ELM predicts the compressive strength with promising evaluation indexes [R2 (test) = 0.66, R2 (train) = 0.86]. Finally, both ANFIS-GA and ANFIS-PSO techniques illustrated a reliable performance for prediction, which encourage scholars to replace costly and time-consuming experimental tests with predicting utilities.