Description:
Concrete is arguably one of the most important and widely used materials in the world, responsible for the majority of the industrial revolution due to its unique properties. However, it is susceptible to cracking under internal and external stresses. The generated cracks result in a significant reduction in the concrete lifespan and an increase in maintenance and repair costs. In recent years, the implementation of bacterial-based healing agent in the concrete matrix has emerged as one of the most promising approaches to address the concrete cracking issue. However, the bacterial cells need to be protected from the high pH content of concrete as well as the exerted shear forces during preparation and hardening stages. To address these issues, we propose the magnetic immobilization of bacteria with iron oxide nanoparticles (IONs). In the present study, the effect of the designed bio-agent on mechanical properties of concrete (compressive strength and drying shrinkage) is investigated. The results indicate that the addition of immobilized Bacillus species with IONs in concrete matrix contributes to increasing the compressive strength. Moreover, the precipitates in the bio-concrete specimen were characterized using scanning electron microscope (SEM), X-ray diffraction (XRD), and energy-dispersive X-ray spectroscopy (EDS). The characterization studies confirm that the precipitated crystals in bio-concrete specimen were CaCO3, while no precipitation was observed in the control sample.
Description:
The purpose of this paper is to provide a proper, practical and convenient drilling rate index (DRI) prediction model based on rock material properties. In order to obtain this purpose, 47 DRI tests were used. In addition, the relevant strength properties i.e. uniaxial compressive strength and Brazilian tensile strength were also used and selected as input parameters to predict DRI. Examined simple regression analysis showed that the relationships between the DRI and predictors are statistically meaningful but not good enough for DRI estimation in practice. Moreover, multiple regression, artificial neural network (ANN) and hybrid genetic algorithm (GA)-ANN models were constructed to estimate DRI. Several performance indices i.e. coefficient of determination (R2), root mean square error and variance account for were used for evaluation of performance prediction the proposed methods. Based on these results and the use of simple ranking procedure, the best models were chosen. It was found that the hybrid GA-ANN technique can performed better in predicting DRI compared to other developed models. This is because of the fact that the proposed hybrid model can update the biases and weights of the network connection to train by ANN.
Description:
The purpose of this paper is to provide a proper, practical and convenient drilling rate index (DRI) prediction model based on rock material properties. In order to obtain this purpose, 47 DRI tests were used. In addition, the relevant strength properties i.e. uniaxial compressive strength and Brazilian tensile strength were also used and selected as input parameters to predict DRI. Examined simple regression analysis showed that the relationships between the DRI and predictors are statistically meaningful but not good enough for DRI estimation in practice. Moreover, multiple regression, artificial neural network (ANN) and hybrid genetic algorithm (GA)-ANN models were constructed to estimate DRI. Several performance indices i.e. coefficient of determination (R2), root mean square error and variance account for were used for evaluation of performance prediction the proposed methods. Based on these results and the use of simple ranking procedure, the best models were chosen. It was found that the hybrid GA-ANN technique can performed better in predicting DRI compared to other developed models. This is because of the fact that the proposed hybrid model can update the biases and weights of the network connection to train by ANN.
Description:
Water treatment plants (WTP) in the City of Manaus, Brazil, generate tons of sludge daily, which are then disposed of in landfills and main watercourses, particularly two important Amazonian Rivers: the blackwater Negro River and the pale sandy-colored water Solimoes River. Because WTP-based sludges are rich in silicon and aluminum, they have been employed in the synthesis of geopolymers - alkaline activated inorganic polymers consisting of silicate and aluminosilicate chains. This paper reports the results of a geopolymeric synthesis process in which calcined sludge was explored as a source of silica and alumina. In this research, a laboratory testing program was developed to characterize the waste material generated from a water treatment plant in Manaus, whose intake water is influenced by the above referred rivers. Sample preparation involved kiln drying at 110 degrees C for 8 h, grinding in ball mill for 2 h, and calcination at 750 degrees C for 6 h. The calcined sludge was used as precursor, and potassium hydroxide added as activating alkali. Two geopolymers, one from each sludge source, were prepared following identical procedures. The chemical, compositional, morphological, thermal and mechanical properties of the fresh and hardened geopolymers were characterized. The geopolymers reached uniaxial compressive strengths of over 50 MPa at 28 days. Calcination conveyed more refined properties to the sludge-based geopolymers, akin to metakaolin-based geopolymers. The results presented herein support the technical feasibility of geopolymer synthesis in the lab scale.
Description:
Concrete is the most commonly used construction material because of its various advantages, such as versatility, familiarity, strength, and durability, and it will continue to be in demand far into the future. However, with today’s sensitivity to environmental protection, this material faces unprecedented challenges because of its high greenhouse gas emissions, mainly during cement production. This paper investigates one of the promising cement replacement materials, alkali-activated cement (AAC) concrete. Being produced mainly from byproduct materials and having a comparable structural performance to conventional concrete, AAC concrete can transform the construction industry. Mechanical properties such as compressive and flexural strength and the relationship between them are studied. Different source materials such as fly ash (FA), ground granulated blast furnace slag (GGBS), silica fume (SF), and Metakaolin (MK) are used. The effect of the source materials and the activator solutions on the concrete performance is studied. Furthermore, the freeze-thaw resistance of the concrete is studied. The study results showed that the behavior of AAC depends highly on the source material combinations and type used. The effect of the alkaline solution is also dependent on the source material used. Mixes with higher GGBS content showed the highest strength, while mixes with MK showed the highest flexural strength. The freeze-thaw test results showed that proper design of AAC concrete with lower water content is critical to achieving a good resistance.