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A. O. Arinkoola

Publications (4)

Optimization of Operating Conditions Affecting Microbiologically Influenced Corrosion of Mild Steel Exposed to Crude Oil Environments Using Response Surface Methodology

K. K. Salam, S. E. Agarry, A. O. Arinkoola & I. O. Shoremekun · Biotechnology Journal International · 2015

In this study, the influence of four operating parameters (pH, salinity, nitrate concentration and immersion time) and their interactions on the microbiologically influenced corrosion (MIC) rate of mild steel in simulated crude oil environments were investigated by response surfa...

Open access Research Article 10.9734/BBJ/2015/16810

Effect of Activation on Clays and Carbonaceous Materials in Vegetable Oil Bleaching: State of Art Review

Akinwande B. Aishat, Salawudeen T. Olalekan, A. O. Arinkoola & Jimoh M. Omolola · Current Journal of Applied Science and Technology · 2014

The use of clay and its minerals in vegetable oil purification has been tremendous. It has been discovered that surface modification or activation of this distinct adsorbent greatly increases its adsorptive capacity. Similarly, seed hulls also known as carbonaceous materials are...

Open access Research Article 10.9734/BJAST/2015/11942

Development of Optimum Operating Parameters for Bioelectricity Generation from Sugar Wastewater Using Response Surface Methodology

M. O. Aremu, E. O. Oke, A. O. Arinkoola & K. K. Salam · Journal of Scientific Research and Reports · 2014

Two response surface methodologies involving historical data designs have been successfully developed with the aim of predicting optimum operating parameters for bioelectricity generation from sugar wastewater. The regression models evaluated the effect of waste water concentrati...

Open access Research Article 10.9734/JSRR/2014/10402

Fuzzy Sequential Forward Search for Oil Formation Volume Factor Predictive Tool Factor for Niger Delta Crude Oil

K. K. Salam, D. O. Araromi, A. O. Arinkoola & S. S. Ikiensikimama · Current Journal of Applied Science and Technology · 2013

Accurate prediction of fluid properties is essentials for all reservoir engineering calculations such as estimation of reserves, well testing analysis and in numerical reservoir simulation. Oil formation volume factor is one of the properties that can either be gotten from empiri...

Open access Research Article 10.9734/BJAST/2014/2280