Speakers: Aida Rashidi and Mahyar Mahdavi Hezaveh
When: April 10th, 2026 at 11:00AM
When: KH A445 (Lincoln) and PKI 160 (Omaha)
Aida Rashidi: Model-Based Estimation of CO2 Generation in Industrial Corn Ethanol Fermentation Process
Abstract: Gas generation in corn ethanol fermentation is highly dynamic, but direct measurement at the individual fermenter level is uncommon in industrial settings, limiting process monitoring and diagnostics. This work develops a dynamic material balance–based framework to estimate CO₂ generation for each fermentation tank using routinely collected plant data. The model integrates liquid-phase measurements with operational information and applies stoichiometric relationships to reconstruct gas profiles. Results will be evaluated against CEMS data, demonstrating the potential of this approach for process monitoring and enabling future data-driven optimization.
Mahyar Mahdavi Hezaveh: Early Detection of Fermentation Infections through Off-Gas Monitoring in Corn Ethanol Production
Abstract: Fermentation in ethanol production is vulnerable to lactic acid bacteria infections, which are often detected only after yield losses occur through periodic liquid-phase testing. This study proposes an early-warning system based on fermenter offgas composition, including carbon dioxide, ethanol vapor, and trace volatile organic compounds (VOCs), which respond rapidly to changes in microbial activity. Pilot-scale fermenter tests using industrial corn mash under both healthy and intentionally infected conditions are conducted to confirm that the off-gas provides a faster detection approach. And improves process control, reduces antibiotic use and energy consumption, and enhances ethanol yield and sustainability.