Estimating strength properties of geopolymer self-compacting concrete using machine learning techniques

There has been a persistent drive for sustainable development in the concrete industry. While there are series of encouraging experimental research outputs, yet the research field requires a standard framework for the material development. In this study, the strength characteristics of geopolymer self-compacting concrete made by addition of mineral admixtures, have been modelled with both genetic programming (GEP) and the artificial neural networks (ANN) techniques. The study adopts a 12M sodium hydroxide and sodium silicate alkaline solution of ratio to fly ash at 0.33 for geopolymer reaction. In addition to the conventional material (river sand), fly ash was partially replaced with silica fume and granulated blast furnace slag. Various properties of the concrete, filler ability and passing ability of fresh mixtures, and compressive, split-tensile and flexural strength of hardened concrete were determined. The model developmentinvolved using raw materials and fresh mix properties as predictors, and strength properties as response. Results shows that the use of the admixtures enhanced both the fresh and hardened properties of the concrete. Both GEP and ANN methods exhibited good prediction of the experimental data, with minimal errors. However, GEP models can be preferred as simple equations are developed from the process, while ANN is only a predictor

10 - Mineralogy and interfacial transition zone features of recycled aggregate concrete

The intrinsic features of cementitious composites depend largely on the constituent materials compositions. The former is also known to be responsible for the overall mechanical performance of the composite materials. This chapter reported the mineralogy of recycled aggregate concrete (RAC) as affected by the concrete compositions. The processes involved in the microstructural development, mineralogy, and concept of interfacial transition zones in RAC were described. The influence of supplementary cementitious materials on the mineralogy modifications in RAC is also reported. The study also discussed microscale analysis of RAC using scanning electron microscope and the various hydration products commonly found in RAC

Engineered uses of nanomaterials for sustainable cementitious composites

Over several decades ago, the use of nanomaterials has become attractive, as it has provided solutions to numerous engineering problems. For instance, biomaterials (optoelectrical materials, tissue-engineering scaffolds, and supercapacitors), have been developed from algal cells, which are subsequently used in medicine, heavy metal absorbents, and biosensors. In this chapter, the various engineered uses of nanomaterials for sustainable cementitious composites are reported. Emphasis was laid on to nanomaterials uses in the construction field, with a holistic view of types and specific applications. Nanotechnology has brought significant development to the construction field. Nanomaterials, such as ureolytic or nonureolytic bacteria and nano-silica, are used for modifying the interfacial transition zone of recycled aggregate and recycled aggregate concrete. Such modifications influence a reduction in water permeability of the composite matrix and also enhance the specific gravity of aggregates. By this technology, microscale features of cementitious composites are also modified. The hydration mechanism is improved with biogenic calcite. Nanoengineered cementitious composites, having appreciable mechanical and durability characteristics, have been developed using this technology

Self-compacting concrete blended with fly ash and ground granulated blast furnace slag

This research study was performed on the self-compacting concrete (SCC) mixture blended with 5%, 10%, 15%, and 20% of fly ash (FA) and 5%, 10%, 15%, and 20% of ground granulated blast furnace slag (GGBFS) individually and with a combination of FA and GGBFS, that is, 5% (2.5% FA and 2.5% GGBFS), 10% (5% FA and 5% GGBFS), 15% (7.5% FA and 7.5% GGBFS), and 20% (10% FA and 10% GGBFS) by the weight of Portland cement. The main theme of this research work is to determine the fresh properties in terms of filling ability (slump flow, V�Funnel and T50 flow), passing ability (J-Ring and L-box), and sieve segregation test of SCC mixture and hardened properties in terms of compressive, split tensile, and flexural strengths and permeability of SCC mixture. However, the concrete specimens were prepared at 0.40 water– cement ratio, and these specimens were tested at 28 and 90 days. The results showed that the fresh properties of SCC mixture blended with FA and GGBFS provide better results with addition of a superplasticizer and hardened properties of SCC mixture are enhanced while utilizing 5% of GGBFS and 5% of FA by the weight of PC at 28 and 90 days, respectively

Estimating strength properties of geopolymer self-compacting concrete using machine learning techniques

tThere has been a persistent drive for sustainable development in the concrete industry.While there are series of encouraging experimental research outputs, yet the research fieldrequires a standard framework for the material development. In this study, the strengthcharacteristics of geopolymer self-compacting concrete made by addition of mineral admix-tures, have been modelled with both genetic programming (GEP) and the artificial neuralnetworks (ANN) techniques. The study adopts a 12M sodium hydroxide and sodium sili-cate alkaline solution of ratio to fly ash at 0.33 for geopolymer reaction. In addition to theconventional material (river sand), fly ash was partially replaced with silica fume and gran-ulated blast furnace slag. Various properties of the concrete, filler ability and passing abilityof fresh mixtures, and compressive, split-tensile and flexural strength of hardened concretewere determined. The model development involved using raw materials and fresh mix prop-erties as predictors, and strength properties as response. Results shows that the use of theadmixtures enhanced both the fresh and hardened properties of the concrete. Both GEP andANN methods exhibited good prediction of the experimental data, with minimal errors.However, GEP models can be preferred as simple equations are developed from the process,while ANN is only a predictor

Thermal insulation and mechanical characteristics of cement mortar reinforced with mineral wool and rice straw fibers

Building insulation is an essential requirement for buildings located in areas of varying temperature conditions. However, the conventional building insulation techniques accrue high cost and consume resources. This work aimed to evaluate the use of mineral wool and rice straw to improve Portland cement mortar’s thermal insulating properties. Samples of 40x40x160 mm mortar were produced with cement and sand, but varying mineral wool and rice straw constituents from 0 to 50% in weight. Water absorption, flexural and compressive strengths, thermal conductivity were performed in samples with and without mineral wool and rice straw addition.The microstructure of mortars was analyzed using scanning electron microscopy (SEM). It was observed that reinforcing mortars with mineral wool and rice straw fibers yielded a significant drop in the mortar’s thermal conductivity, improving their insulative abilities. Although the addition of fibers, in turn, deferred the mechanical performance in some mixes, however, it was not too significant or below workable standards. The performed tests prove the feasibility of adopting the selected fibers for insulating Portland cement mortars

Influence of fiber type on the performance of reinforced concrete beams made of waste aggregates : experimental, numerical, and cost analyses

The structural performance of concrete structures requires swelling the bending and shear characteristics of reinforced concrete (RC) beams. The bending characteristics of RC beams consisting of waste granite aggregate (WGA), steel fibers (SF), polypropylene fibers (PF), and glass fibers (GF) are assessed in this research. Twenty-one 2,000 mm×200 mm×250 mm RC beams were cast and tested. WGA was sorted and utilized instead of natural coarse aggregates (NA), with three mass replacement fractions: 0%, 50%, and 100%. Besides, SF, PF, and GF were utilized separately at three fractions of 0%, 0.5%, and 1%. Beams were loaded under a four-point bending arrangement, and the ultimate bending resistance, deformability, stiffness and crack development were recorded and assessed. Also, an evaluation of experimental results and existing design standards in terms of maximum crack width has been carried out. Moreover, a cost-sensitivity examination has been made to analyze the effectiveness of using various fibers in terms of cost. Experiments revealed that the impact of PF on enhancing the load-bearing capability of beams with WGA was greater than that of strengthened with SF and GF. However, the impact of GF on the ultimate deformability of WGA RC beam samples was superior to that of PF and SF. PF has a greater influence on enhancing the flexural capacity of RC beams than SF; nevertheless, SF has a greater influence on deformation. The ductility and deformability of RC beams were substantially enhanced when GF was introduced in specimens made with WGA