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G. Mohan Ganesh

Bio: G. Mohan Ganesh is an academic researcher from VIT University. The author has contributed to research in topics: Structural engineering & Composite number. The author has an hindex of 1, co-authored 4 publications receiving 5 citations.

Papers
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Journal ArticleDOI
TL;DR: In this article, the use of pozzolanic material like Metakaolin (MK) as a mineral admixture and non-pozzolastic material like Waste Marble Powder (WMP) as filler material.

18 citations

Book ChapterDOI
19 Feb 2020
TL;DR: In this article, the optimization of mix proportion design has been determined by adopting the proposed rational mix design method or Japanese method with necessary modifications in consonance with the guidelines of EFNARC.
Abstract: Self-Compacting Concrete (SCC) is a special type of concrete recognized for placing in congested reinforced structures without any application of external vibration. Self compactibility can be determined by the properties of material constituents and the design of mix proportions. The absence of an approved code in India on mix design proportions and characteristics of material constituents to achieve compactibility in SCC has necessitated to determine a method for mix design of SCC. Though some researchers have carried out investigations to determine a proper mix design for producing SCC. In this investigation, the optimization of mix proportion design has been determined by adopting the proposed rational mix design method or Japanese method with necessary modifications in consonance with the guidelines of EFNARC. A suitable mix using the marginal aggregates was selected and numerous trial mixes (sixty-five) were carried out with the varying mix parameters like binder content, water-binder ratio, fine aggregate-coarse aggregate ratio, percentage of superplasticizer and viscosity modifying admixtures. The test results of this study are presented in this paper and a successful attempt has been made to determine the suitable mix design for producing SCC.

4 citations

DOI
01 Jan 2020
TL;DR: In this paper, Bacillus pumilus and Bacillus flexus were identified through 16-srRNA gene sequencing and an experiment on cylinder and prisms cast was performed to evaluate the strength of concrete with the influence of bacteria.
Abstract: In recent years, concrete has become an important versatile construction material. This paper evaluates the strength obtained by concrete with the influence of bacteria. The bacterial strains were isolated from calcareous sludge and urea ware house. The bacterial strains were identified through 16srRNA gene sequencing as Bacillus pumilus and Bacillus flexus. Using these strains, an experiment on cylinder and prisms cast was performed. Compressive strength, split tensile and flexural tests were conducted at the age of 7, 28 and 56 days with ultrasonic pulse velocity and rebound hammer. The results were compared with Bacillus cohnii MTCC 3616 obtained from microbial type culture collection and gene bank, Chandigarh, India. Based on the experimental results, the improvement in the mechanical strength is due to the deposition of calcite crystals on the bacterial cell surfaces within the pores which enhanced the strength of concrete and reduced porosity and permeability.

3 citations

Journal ArticleDOI
TL;DR: In this paper , the axial capacities of pultruded fiber-reinforced polymer (PFRP) composite channel columns were investigated using finite element (FE) models.
Abstract: This article reports the finite element (FE) investigation of the axial capacities of pultruded fiber-reinforced polymer (PFRP) composite channel columns. The nonlinear finite element model (FEM) was developed by using the ABAQUS package for glass fiber-reinforced polymer (GFRP) composite channel columns, which included geometric and initial geometric imperfections. The developed FEMs were verified against an experimental result available in the literature for GFRP channel columns. The validated FEMs were used to carry out the parametric study comprising 61 FE models to investigate the effect of different geometries, plate slenderness and the length of members on the axial capacities of GFRP pultruded channel columns. The results obtained from the parametric study were used to examine the accuracy of the current Italian guidelines, American pre-standard and the Direct Strength Method (DSM) proposed in the literature for GFRP channel profiles. Based on the obtained results, the suitability of the current design guidelines is assessed and, also, a new set of design equations is proposed to estimate the axial capacity of the pultruded GFRP channel columns. The new proposed set of reliable design equations witnessed a less scattered and a high degree of accuracy in determining the axial load capacity of the pultruded GFRP composite channel columns.

Cited by
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Journal ArticleDOI
TL;DR: In this article , the results of axial compression tests on a total of 429 concrete mixtures with marble aggregates were compiled by paying special attention to reporting all test variables (form and content of marble wastes, water-cement ratio, cement content, proportion of coarse and fine aggregates in all aggregates) affecting the concrete strength.
Abstract: The use of marble wastes in concrete mixtures, causing air and water pollution, has been promoted in the academic and practical spheres of the construction industry. Although the effects of various forms (powder, fine, coarse and mixed) of this waste on the concrete compressive strength has been subject to a decent number of studies in the literature, the difficulties in reaching specific conclusions on the effect of each test parameter constitute a major restraint for the proliferation of the use of marble wastes in the concrete industry. Most of these studies are far from underscoring all of the parameters affecting the concrete compressive strength. Due to the urgent need in the literature for comprehensive studies on concrete mixtures with marble wastes, the results of the axial compression tests on a total of 429 concrete mixtures with marble aggregates were compiled by paying special attention to reporting all test variables (form and content of marble wastes, water–cement ratio, cement content, proportion of coarse and fine aggregates in all aggregates) affecting the concrete strength. In this context, multivariate regression analyses were carried out on the existing test results. These regression analyses yielded to relationships between the change in concrete compressive strength and the test parameters for each and every form of marble waste (powder, fine and coarse aggregate). The study indicated that independent from the form of marble wastes (as powder, fine aggregate or coarse aggregate), aggregate replacements of up to 50% can yield to significant changes in the concrete compressive strength. In addition, the analytical estimates from the developed equations exhibited a high correlation (a least r value of 0.91) with the experimental results from the previous studies, yielding to rather low error values (RMSE value is 5.06 MPa at max). For this reason, the developed equations can consistently predict the changes in concrete compressive strength with varying amounts and forms of the marble aggregates as well as the other test variables.

42 citations

Journal ArticleDOI
TL;DR: In this article, the use of pozzolanic material like Metakaolin (MK) as a mineral admixture and non-pozzolastic material like Waste Marble Powder (WMP) as filler material.

18 citations

Journal ArticleDOI
TL;DR: In this article , the authors compared the environmental impacts of green and conventional concrete, initially, they compared the physical and chemical properties of materials, fresh and hardened properties of concrete for all the mixes, based on test results, LCA models are prepared by using SimaPro software and the Ecoinvent database.

16 citations

Journal ArticleDOI
TL;DR: In this article , a machine learning prediction model using the Python programming language was proposed to estimate the compressive strength of a green concrete mix that includes construction and demolition waste and FA.
Abstract: Purpose Utilization of sustainable materials is a global demand in the construction industry. Hence, this study aims to integrate waste management and artificial intelligence by developing an artificial neural network (ANN) model to predict the compressive strength of green concrete. The proposed model allows the use of recycled coarse aggregate (RCA), recycled fine aggregate (RFA) and fly ash (FA) as partial replacements of concrete constituents. Design/methodology/approach The model is constructed, trained and validated using python through a set of experimental data collected from the literature. The model’s architecture comprises an input layer containing seven neurons representing concrete constituents and two neurons as the output layer to represent the 7- and 28-days compressive strength. The model showed high performance through multiple metrics, including mean squared error (MSE) of 2.41 and 2.00 for training and testing data sets, respectively. Findings Results showed that cement replacement with 10% FA causes a slight reduction up to 9% in the compressive strength, especially at early ages. Moreover, a decrease of nearly 40% in the 28-days compressive strength was noticed when replacing fine aggregate with 25% RFA. Research limitations/implications The research is limited to normal compressive strength of green concrete with a range of 25 to 40 MPa. Practical implications The developed model is designed in a flexible and user-friendly manner to be able to contribute to the sustainable development of the construction industry by saving time, effort and cost consumed in the experimental testing of materials. Social implications Green concrete containing wastes can solve several environmental problems, such as waste disposal problems, depletion of natural resources and energy consumption. Originality/value This research proposes a machine learning prediction model using the Python programming language to estimate the compressive strength of a green concrete mix that includes construction and demolition waste and FA. The ANN model is used to create three guidance charts through a parametric study to obtain the compressive strength of green concrete using RCA, RFA and FA replacements.

13 citations

Journal ArticleDOI
TL;DR: In this paper , the use of marble dust (MD) and granulated blast furnace slag (GBFS) in the production of self-compacting concrete (SCC) is explored.
Abstract: Self-compacting concrete (SCC) is a special, highly fluid type of concrete that is produced using chemical additives. It is easier to pour and reduces defects arising from workability. Waste marble dust is generated during the production of marble using different methods, or during the cutting of marble in processing plants; however, the uncontrolled disposal of waste marble dust in nature is associated with some environmental problems. Cement and concrete technology is a field with potential for the utilization of these large amounts of waste. The present study explores the use of marble dust (MD) (an industrial waste generated in abundance around the province of Bilecik) and granulated blast furnace slag (GBFS) (another industrial waste product) in the production of SCC. In this study, MD and GBFS are used as fine materials in SCC mixtures, and the rheological and workability properties and other hardened concrete properties of the produced SCC specimens are tested. Additional tests are conducted to identify the durability of the specimens to sulfate attack, as well as their freeze–thaw and abrasion resistance, followed by microstructure tests to identify the effects of MD and GBFS on bond structure. The late-age performances of MD and GBFS were then examined based on the results of the durability tests. The presented results revealed improvements in the fresh and hardened properties of SCC produced using MD and GBFS.

6 citations