Browsing by Subject "Process optimization"

Now showing 1 - 2 of 2

Open Access
Highly sensitive determination of 2, 4, 6-trinitrotoluene and related byproducts using a diol functionalized column for high performance liquid chromatography
(Public Library of Science, 2014) Gumuscu, B.; Erdogan, Z.; Güler, Mustafa O.; Tekinay, T.
In this work, a new detection method for complete separation of 2,4,6-trinitrotoluene (TNT); 2,4-dinitrotoluene (2,4-DNT); 2,6-dinitrotoluene (2,6-DNT); 2-aminodinitrotoluene (2-ADNT) and 4-aminodinitrotoluene (4-ADNT) molecules in high-performance liquid-chromatography (HPLC) with UV sensor has been developed using diol column. This approach improves on cost, time, and sensitivity over the existing methods, providing a simple and effective alternative. Total analysis time was less than 13 minutes including column re-equilibration between runs, in which water and acetonitrile were used as gradient elution solvents. Under optimized conditions, the minimum resolution between 2,4-DNT and 2,6-DNT peaks was 2.06. The recovery rates for spiked environmental samples were between 95-98%. The detection limits for diol column ranged from 0.78 to 1.17 μg/L for TNT and its byproducts. While the solvent consumption was 26.4 mL/min for two-phase EPA and 30 mL/min for EPA 8330 methods, it was only 8.8 mL/min for diol column. The resolution was improved up to 49% respect to two-phase EPA and EPA 8330 methods. When compared to C-18 and phenyl-3 columns, solvent usage was reduced up to 64% using diol column and resolution was enhanced approximately two-fold. The sensitivity of diol column was afforded by the hydroxyl groups on polyol layer, joining the formation of charge-transfer complexes with nitroaromatic compounds according to acceptor-donor interactions. Having compliance with current requirements, the proposed method demonstrates sensitive and robust separation. © 2014 Gumuscu et al.
Open Access
Modeling and optimization of multi-scale machining operations
(2012) Yılmaz, Fevzi
Minimization of production time, cost and energy while improving the part quality is the main goal in manufacturing. In order to be competitive in today’s global markets, it is crucial to develop high precision machine tools and maintain high productive operation of the machine tools through intelligent and effective selection of machining parameters. A recent shift in manufacturing industry is towards the production of high value added micro parts which are mainly used in biomedical and electronics industries. However, the knowledge base for micro machining operations is quite limited compared to macro scale machining processes. Metal cutting, which allows production of parts with complex shapes made from engineering materials, constitutes a large portion in all manufacturing activities and expected to remain so in upcoming years. In this thesis, modeling and optimization of macro scale turning and micro scale milling operations have been considered. A well known multi pass turning problem from the literature is used as a benchmark tool to test the performances of Particle Swarm Optimization (PSO) technique and nonlinear optimization algorithms. It is shown that acceptable results can be obtained through PSO in short time. Micro scale milling operation is thoroughly investigated through experimental techniques where the influences of machining parameters on the process outputs (machining forces, surface quality, and tool life) have been investigated and factors affecting the process outputs are identified. A minimum unit cost optimization problem is formulated based on the pocketing operation and machining strategies are proposed for different machining scenarios using PSO technique.