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Multiple exegetically optimization of ultrasonic pretreatment and substrate mixture for biohydrogen and biomethane improvement

Mahmood Mahmoodi-Eshkaftaki and Mohsen Dalvi-Isfahan

Energy, 2024, vol. 292, issue C

Abstract: The aim of this study was to optimize the bio-hydrogen and bio-methane production process by analyzing the effects of substrate mixtures (cow manure: tomato waste) and ultrasonic factors (ultrasonic power and sonication time) on exergy efficiency. A multivariate optimization technique that combined regression modeling and desirability analysis was applied. Different proportions of cow manure and tomato waste (0–100 %) were pretreated with various levels of ultrasonic power (0.08, 0.25, and 0.42 W/mL) and sonication time (15, 30, and 45 min) based on an exergy equilibrium model. The optimal conditions were 0.33 W/mL of ultrasonic power, 23.1 min of sonication time, and a mixture of 2 % cow manure and 98 % tomato waste, which resulted in the highest desirability of the process (=0.687). Under these conditions, the input exergetic parameters (chemical, physical, and total exergies) were the lowest (1.510, 0.559, and 2.062 MJ/kg, respectively), the output exergetic parameters were the highest (0.027, 0.871, and 0.749 MJ/kg, respectively), the exergy efficiency and exergetic improvement potential rate were the highest (43.64 % and 0.73 MJ/kg, respectively), and the exergy destruction was the lowest (1.26 MJ/kg). The experiments were repeated to validate the modeling and optimization processes. The results showed that increasing the ultrasonic factors enhanced exergy efficiency and exergetic potential rate but also increased exergy destruction. A weak ultrasonic pretreatment with a high percentage of cow manure in the mixtures was found to be beneficial for improving plant efficiency and reducing system destruction.

Keywords: Desirability analysis; Exergy destruction; Exergy efficiency; Regression modeling; Multivariate optimization (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:292:y:2024:i:c:s0360544224003086

DOI: 10.1016/j.energy.2024.130537

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