Multi-objective Airfoil Design Using Variable-Fidelity CFD Simulations and Response Surface Surrogates

2014 ◽  
Author(s):  
Slawomir Koziel ◽  
Leifur T. Leifsson
Keyword(s):  
Response Surface ◽  
Cfd Simulations ◽  
Multi Objective ◽  
Variable Fidelity

Optimization of Aqueous Two Phase Extraction of Proteins from Litopenaeus Vannamei Waste by Response Surface Methodology Coupled Multi-Objective Genetic Algorithm

2019 ◽  
Vol 15 (1) ◽  
Author(s):  
P. Saravana Pandian ◽  
S. Sindhanai Selvan ◽  
A. Subathira ◽  
S. Saravanan
Keyword(s):  
Genetic Algorithm ◽  
Molecular Weight ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Litopenaeus Vannamei ◽  
Value Added ◽  
Phase System ◽  
Two Phase ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm

Abstract Waste generated from industrial processing of seafood is an enormous source of commercially valuable proteins. One among the underutilized seafood waste is shrimp waste, which primarily consists of head and carapace. Litopenaeus vannamei (L. vannamei) is the widely cultivated shrimp in Asia and contributes to 90 % of aggregate shrimp production in the world. This work was focused on extraction as well as purification of value-added proteins from L. vannamei waste in a single step aqueous two phase system (ATPS). Polyethylene glycol (PEG) and trisodium citrate system were chosen for the ATPS owing to their adequate partitioning and less toxic nature. Response surface methodology (RSM) was implemented for the optimization of independent process variables such as PEG molecular weight (2000 to 6000), pH (6 to 8) and temperature (25 to 45 °C). The results obtained from RSM were further validated using a Multi-objective genetic algorithm (MGA). At the optimized condition of PEG molecular weight 2000, pH 8 and temperature 35 °C, maximum partition coefficient and protein yield were found to be 2.79 and 92.37 %, respectively. Thus, L. vannamei waste was proved to be rich in proteins, which could be processed industrially through cost-effective non-polluting ATPS extraction, and RSM coupled MGA could be a potential tool for such process optimization.

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