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Articles by Rosli Bin Mohd Yunus
Total Records ( 2 ) for Rosli Bin Mohd Yunus
  Hayder A. Abdul Bari and Rosli Bin Mohd Yunus
  In the present research, Sodium Lauryl Ether Sulphate (SLES) was investigated not only as a drag reducing agent for two phase system (solid-liquid). It is desired to divide the present study into two consequence steps which are, the addition of small amounts of solid particles that can be suspended in liquid used (kerosene), these suspensions may be used as drag reducing agents, then the other step is established by the addition of small quantities of certain surfactant to the suspension transported. The results showed that, percentage drag reduction (Dr%) increases by increasing the suspended particles concentration, suspended particle size, Surfactant concentration and solution velocity (Reynolds No.). Maximum Dr% of 34% was obtained using 1500 ppm of Sand powder suspended in Kerosene and pumped within maximum flow rate. This maximum percentage was increased to 44% by the addition of SLES with concentration up to 600 ppm with the same conditions above.
  Reddy Prasad , Duduku Krishnaiah , Awang Bono , Paulraj Pandiyan , Rosli Bin Mohd Yunus and Naveena Lakshmi
  The application of Artificial Neural Networks in chemical engineering field is being under immense research. One of the physical properties of every material has its own intensity to absorb the sound waves. Carrageenans are water-soluble gums, which occur in certain species of red seaweeds. They are sulfated natural polymers made up of galactose units. Carrageenan consists of a main chain of D-galactose residues linked alternately α - (1→3) and β - (1→4). The decibel frequency analyzer dbFA - 32 has been used for this analysis. The sound signals are captured using the hydrophone. The analog signals are then digitized at different octave frequencies. These are used to generate the frequency power spectrum. The change in the spectrum is proportional to the concentration of the material in the solution. The normalized data is used as a input to a feed forward neural network model. In this study, a simple scheme is proposed to estimate the amount of carrageenan present in a solution using under water acoustics and Artificial Neural Networks. This method is useful for the direct estimation of carrageenan in food, pharmaceutical and cosmetic industries. It can be useful for online measurement of compound in the industries.
 
 
 
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