BITS Faculty Publications

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Author: search.filters.author.Gupta, RajivSubject: search.filters.subject.Compressive strength

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    Evaluation of use of bottom ash in cement masonry and concrete regarding their mechanical properties
    (IAAM-VBRI Press, 2018) Gupta, Rajiv
    Large quantities of ash are generated every year by the various manufacturing industries as a waste by-product. This study aims to utilize waste by-product in concrete and to reduce its cost by replacing cement in parts with bottom ash. This research presents the results of the experimental investigations to study the use of bottom ash as partial replacement for cement in concrete and masonry units. Bottom ash is the coarser material, which falls into furnace bottom and constitutes about 20% of total ash content. The strength development for various percentage replacements (5-15%) of cement with bottom ash has been compared to control specimens of concrete and masonry.
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    Group Method of Data Handling Algorithms to Predict Compressive Strength of Concrete Based on Absorbed Extraterrestrial Solar Radiations
    (Scientific Net, 2016-04) Gupta, Rajiv
    The present study applies group method of data handling (GMDH) to predict compressive strength of normal strength concrete based on experimentally determined weight, ultrasonic pulse velocity and extraterrestrial solar radiations absorbed by concrete specimen. GMDH are widely used as mathematical modelling and non-linear regression algorithms, and are assumed as specific type of supervised artificial neural networks. Concrete being a multi-phase porous and non-linear material justifies usage of such algorithm as GMDH employs the idea of natural selection to control size, complexity and accuracy of networks being used for various applications like function approximation, non-linear regression and pattern recognition. The effectiveness of algorithm is validated when 60%, 70%, 80% and 100% of normalized and non-normalized data is used for training. GMDH being an intelligent algorithm with ability of learning and adaptation can be conveniently used as an appropriate prediction tool for non-linear complex systems like concrete.
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    Compressive Strength Characteristics of Normal Strength Concrete Cured Using Colored Polythene Sheets
    (Scientific Net, 2013-04) Gupta, Rajiv
    Concrete performance is severely influenced when placed in extreme environmental conditions and hence certain measures are required to control it. The present paper proposes covering the structural members with colored polythene sheets which serves dual purpose of curing. Polythene sheets do not allow appreciable loss of water by evaporation and thus they do not delay or prevent hydration besides providing optimum temperature and humidity conditions for strength development and being water conservative. In present study concrete cubes were wrapped using five different colored polythene sheets for a period of 7-days. The study incorporates prevailing environmental conditions by relating effect of curing, including conventional methods like sprinkling and ponding on compressive strength of concrete at varied atmospheric temperatures, relative humidity and influence of available solar radiation. Significant compressive strength characteristics like initial tangent modulus and strain at peak stress are also determined for cubes at a period of 7-, 28-, and 180-days. The quality assessment of concrete cubes cast was carried out using ultrasonic pulse velocity test results. The study aims at developing a knowledge base to design an extensive decision making algorithm that identifies appropriate curing method in prevailing environmental conditions.
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    Concrete compressive strength prediction using ultrasonic pulse velocity through artificial neural networks
    (Elsiever, 2006-05) Gupta, Rajiv
    Numerous attempts to use ultrasonic pulse velocity (UPV) as a measure of compressive strength of concrete has been made due to obvious advantages of non-destructive testing methods. The present study is conducted for prediction of compressive strength of concrete based on weight and UPV for two different concrete mixtures (namely M20 and M30) involving specimens of two different sizes and shapes as a result of need for rapid test method for predicting long-term compressive strength of concrete. The prediction is done using multiple regression analysis and artificial neural networks. A comparison between two methods depicts that artificial neural networks can be used to predict the compressive strength of concrete effectively. The results are plotted as experimentally evaluated compressive strength versus predicted strength through both methods of analysis.
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    A Study on Application of Pickling Sludge in Pavements Tiles
    (RTESE, 2019-06) Verma, Sanjay Kumar; Gupta, Rajiv; Singhal, Anupam; Devi, Anuradha
    Spent pickling liquor disposal is not safe according to US K062 the Environmental Protection Agency (EPA) and Hazardous Waste (Management &Handling) Rule, 1989. In the normal practice pickling sludge is being disposed off on both sides of roads and railway tracks to fill low-lying areas. This may cause a severe problem of ground water contamination. In the present study, an attempt has been made to examine the potential of utilizing Solidification and stabilization (S/S) pickling sludge in pavement tiles as a substitute to cement to avoid disposal problem. The results of this work showed that the compressive strength of pavement tiles increases by replacing cement with pickling sludge up to 10%. As per US EPA TCLP test, heavy metal (Fe, Cr, and Ni) concentrations are below detectable limit in the leachate of pavement tiles at 28 days of curing. Thus, sludge-cement pavement tiles can be safely used on the footpath. Reusing pickling sludge as the raw materials of the pavement will not only solve the disposal problem, but also decrease the producing cost of pavement.