1. A new method for predicting minimum ignition energy of environmentally friendly working fluids based on microscopic molecular structure.
- Author
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Zhang, Yong, Yang, Zhao, Chen, Yubo, and He, Hongxia
- Subjects
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MOLECULAR structure , *HEAT pipes , *WORKING fluids , *HEAT of combustion , *DENSITY functional theory , *ENERGY conservation , *RANKINE cycle , *DUST explosions - Abstract
The issue of global warming prompts us to consider some questions related to energy supply and use. Organic Rankine Cycles (ORC) is a suitable technology for converting low-grade thermal energy into electrical energy, vital for conserving energy and mitigating emissions. Currently, most environmentally friendly working fluids are characterized by their flammability. Analyzing the minimum ignition energy (MIE) of these working fluids is crucial in guaranteeing secure utilization. This paper introduced a novel approach to predicting the MIE of flammable working fluids using microscopic molecular structure analysis. Firstly, the bond energy of molecules was derived by optimizing the microscopic molecular structure of prevalent combustible agents based on the density functional theory (DFT), which was employed to calculate the heat of combustion. Secondly, a mathematical model for predicting the MIE of combustible working fluids was constructed, drawing inspiration from the energy relationship during combustion. Then, the newly formulated model was used to predict the MIE of propane and nine other combustible working fluids, and the results were compared with the existing data. The results show that the predicted values of the MIE exhibit an impressive accuracy rate exceeding 95%. Finally, the MIE prediction model has been modified to provide higher prediction accuracy. This study is of great significance to ensure the safe application of combustible working fluids and to explore environmentally friendly alternatives. [Display omitted] • A new method for predicting the MIE based on molecular structure was proposed. • The molecular structure was optimized based on density functional theory. • The mathematical model has a prediction accuracy of more than 95 %. • The model can predict the ignition energy of substances outside the database. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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