Publications by authors named "Rahmath Ulla Baig"

In this study, the effects of incorporating cerium oxide into diesel and WPO blends were investigated to determine the potential of the blend as a fuel additive. The study aimed to assess engine-performance, emission, and combustion properties of the blend. The experiments utilized a single-cylinder diesel engine, and researchers prepared two different blends of WPO with 25% WPO in diesel and 50% WPO in diesel.

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This study delves into the influence of incorporating alumina (AlO) nanoparticles with waste cooking oil (WCO) biofuels in a gasoline engine that employs premixed fuel. During the suction phase, gasoline blends with atmospheric air homogeneously at the location of the inlet manifold. The biodiesel, enhanced with AlO nanoparticles and derived from WCO, is subsequently directly infused into the combustion chamber at 23° before the top dead center.

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The traditional way to machine hybrid composites is hard because they tend to break, have a high retraction, have a high service temperature, and have an uneven surface irregularity. For high-strength fiber/metal composite constructions, alternative machining methods have drawn interest as a solution to these problems. Current research focuses on enhancing the Abrasive Water Jet Machining process by optimizing its variables using a composite material of epoxy reinforced with silicon carbide, stainless steel wire mesh, and Kevlar.

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Geopolymer is the alternative to current construction material trends. In this paper, an attempt is made to produce a sustainable construction composite material using geopolymer. Ground granulated blast furnace slag (GGBS)-based geopolymer concrete was prepared and tested for different alkaline to binder ratios (A/B).

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This study investigates the effects of red mud on the performance of geopolymer concrete in regard to fresh and mechanical properties. Red mud was used as a binder, and GGBS replaced the binder. Different proportions of red mud ranging from 0 to 30% with an interval of 2% and activator agents such as KOH and KSiO for various alkaline-to-binder ratios such as 0.

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Background And Objective: Streptococcus mutans is the primary initiator and most common organism associated with dental caries. Prediction of post-Streptococcus mutans favours in the selection of appropriate caries excavation method which eventually results in meliorate caries-free cavity preparation for restoration. The objective of this study is to predict the post-Streptococcus mutans prior to dental caries excavation based on pre- Streptococcus mutans using iOS App developed on Artificial Neural Network (ANN) model.

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