Corn to Ethanol: Design, Simulate and Statistical Optimization for Sustainable Biofuel Production

Abstract

Ahmed Nazmus Sakib and Mushaida Haque

This study presents a systematic approach to the design, simulation, and statistical optimization of a corn-to-ethanol plant, a crucial facet of biofuel production in the United States. The report encompasses a historical overview of bio-ethanol, emphasizing its significance in the context of escalating energy demands and environmental considerations. Key aspects of plant development, including feed treatment processing, product separation, and economic and environmental implications, are examined. Utilizing the PRO-II process simulator and Design Expert software, a generic model simulation and optimization results for a major corn- ethanol process are presented. The dry grind process, the predominant method for ethanol production from corn, is scrutinized, affirming bioethanol as a profitable and environmentally viable option. The study employs response surface methodology (RSM) for statistical optimization, specifically focusing on the crucial fermentation step. Through experimental setups with central composite design, the study analyzes variables such as pH, temperature, and substrate concentration to enhance ethanol production. The simulation achieves 92 wt% ethanol purity from 90 g/L starch, demonstrating significant production efficiency. Statistical validation shows pH, temperature, and substrate concentration significantly impact ethanol yield, affirmed by substantial F-values and p-values. Optimal conditions identified for maximizing yield include pH 5.24-5.52, temperature 30- 31°C, and substrate concentration 158-163 g/L.This research contributes to the ongoing advancements in plant design and optimization strategies, essential for bolstering the sustainability and competitiveness of corn-to-ethanol production in the United States and globally.

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