Concise dynamic model to accurately calculate the hydrogen yield during the reaction process. (6th October 2021)

• Record Type: Journal Article
• Authors: Lan, Yang; Changshi, Liu
• Is Part Of: International journal of hydrogen energy. Volume 46:Number 69(2021)
• Page Start: 34381
• Page End: 34388
• Publication Date: 2021-10-06
• Subjects: Model -- Hydrogen production -- Time -- Total amount hydrogen -- Fit; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2021.08.007
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: Estimation of hydrogen production rate and the total amount hydrogen during any reaction process require an accurate and concise dynamic model to describe the variation of hydrogen production rate with reaction time. There must be two comprehensive features of such model, the first one is that the hydrogen production rate calculated by this model is zero at the initial time is zero and the second one is that the integration of this model over time result in an explicit function. In this paper, we present a comprehensive model which meets above two requirements via amendments to the shifted logistic model. The model is validated against measured results through comparison of 25 experimental and theoretical hydrogen production rate. The experimentally validated model is used to calculate the total amount hydrogen during each reaction process. The impact of some experimental conditions on the total hydrogen production was mathematically explained for the first time, and this result reveal the excellent predictive ability of framework suggested in this paper. In addition, that is for an experimental condition history, predictions are achieved by developing a set of "secondary models" that describe some experimental conditions dependence of the "primary models" parameters. The method to obtain the parameters in "secondary models" described in this paper indicated that another major departure from the conventional models is the notion that the "secondary models" do not need to follow any preconceived formula and that they can be derived solely from the observed growth patterns. The presented framework can help the hydrogen production industry. Highlights: Dynamic model to calculate hydrogen production rate by time was provided. The total amount hydrogen can be estimated via this concise dynamic model. The impact of experimental conditions on hydrogen production was explained. A set of "secondary models" of parameters were developed. Very good application results were achieved.