Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Palanisamy, T.Subject: search.filters.subject.Compressive strength

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    Prediction of Compressive Strength and Workability Characteristics of Self-compacting Concrete Containing Fly Ash Using Artificial Neural Network
    (Springer Science and Business Media Deutschland GmbH, 2023) Netam, N.; Palanisamy, T.
    This study aims to propose an artificial neural network (ANN) model for predicting the properties of self-compacting concrete (SCC). SCC has enhanced properties such as very high workability and it can go through very tight spaces between reinforcements without any application of vibration. To get the desired strength and workability, it is necessary to understand the parameters determining the nature and properties of SCC and the relationships involved among those parameters. In this study binder content, water to binder ratio, fly ash percentage, coarse aggregate, fine aggregate, and superplasticizer content are chosen as input parameters, and output results from the model are slump flow value, L-box ratio, V-funnel time, and compressive strength. An ANN model is constructed and its architecture is selected by evaluating the performance of a network with a different number of neurons for the optimum results. Then this model is trained, tested, and validated through a database of experimental test results gathered from various literature. The accuracy of this model is evaluated by evaluation matrices such as R and MSE. To check the efficiency, the current model comparison was made with an existing data envelopment analysis model (DEA). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Examining the Effect of Diverse Calcium Sources on Cement Mortar Using Bacillus Subtilis Through MICP: A Preliminary Investigation
    (Springer Science and Business Media Deutschland GmbH, 2024) Hosamane, C.C.; Chaudhary, P.; Palanisamy, T.
    Calcite, a crystal form of calcium carbonate, plays a crucial role in Microbially Induced Calcium Carbonate Precipitation (MICP). In this process, bacteria aid in forming calcite crystals, strengthening materials like mortar. Bacteria interact with calcium ions, causing calcite to precipitate, thus enhancing the strength and durability of the cement matrix. This study presents a method to improve cement mortar properties through MICP. Gram-positive Bacillus subtilis bacteria were introduced into cubes containing four different calcium sources: calcium chloride, calcium hydroxide, calcium lactate, and calcium oxide. After curing for 7, 14, and 28 days, calcium carbonate quantification, EDTA testing, and compressive strength testing were conducted on the mortar cubes. Results showed that cubes with calcium chloride exhibited peak compressive strengths of approximately 37.4 MPa, 45.7 MPa, and 58 MPa after each respective curing duration. This highlights the superior performance of cubes with CaCl2 compared to other calcium sources. The increase in strength and decrease in water absorption is attributed to the proliferation of calcite crystals within the cement matrix voids, confirmed by microstructural analyses using scanning electron microscopy (SEM). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.