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Author: search.filters.author.Ram Chandar, R.C.Subject: search.filters.subject.statistical analysis

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    Experimental and Statistical Evaluations of Strength Properties of Concrete with Iron Ore Tailings as Fine Aggregate
    (American Society of Civil Engineers (ASCE) onlinejls@asce.org 1801 Alexander Bell DriveGEO Reston VA 20191 Alabama, 2020) Gayana, G.B.; Ram Chandar, R.C.
    Iron ore tailings (IOT) are the by-products of iron ore beneficiation, and these tailings are disposed of in several tons annually in quarries, landfills, and tailings dams, causing environmental issues. Various researchers have attempted to study the properties of IOT and the use of them in concrete as a building material. The present research aims to investigate the potential use of alccofine, a microfine particle of slag, as a cement replacement and IOT as fine aggregates in concrete. Experimental results indicated that the concrete workability decreased with an increase in the IOT-alccofine content and the maximum compressive strength (CS) obtained was 70.00, 68.67, and 65 MPa respectively at 40%, 30%, and 20% IOT-alccofine dosage for varying water-to-cement (w/c) ratios of 0.35, 0.40, and 0.45 respectively. Similarly, the flexural strength (FS) and splitting tensile strength (STS) increased with an increase in IOT-alccofine content. A statistically fitted multiple regression analysis was performed for all the mechanical properties to evaluate the significant level of concrete containing alccofine and IOT in concrete. These prediction models have high accuracy and low bias and the validation process represented that the equations can perform excellently in predicting the IOT-alccofine concrete properties. © 2019 American Society of Civil Engineers.
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    Integrated Slope Monitoring System for Slope Stability Over Old Underground Galleries During Surface Mining Operations Using Internet of Things
    (Springer Science and Business Media Deutschland GmbH, 2023) Dorthi, K.; Ram Chandar, R.C.
    Surface mining methods have been adopted to extract the coal which is in the form of pillars and roof in old underground coal workings. There are slope failures associated with the extraction method. Conventional slope monitoring systems are available but require physical presence of the person at the site and the readout units which are physically connected to the base units and generally such monitoring is done only during day light. Radar-based systems are being used to monitor the broad area through rain, dust, smoke and operate during both day and night. They provide accurate results, but they are high-cost and require a skilled person for operating in the field. Hence, an investigation taken up to assess the stability of the slope stability over old underground coal workings by using wireless sensor networks (WSNs) and internet of things (IoT). In this paper, monitoring of slope stability using a low cost wireless sensor networks is discussed. An integrated wireless data acquisition system is developed to assess the slope stability and it is validated with conventional instrument and numerical modeling approach. The variation in between integrated slope monitoring system (ISMS) to data logger and numerical modeling is around 3.03%–19%. Statistical analysis results revealed that there is a good correlation between field observations and modeling studies. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.