A hierarchical reduction method with selective targets for combustion modeling of large Hydrocarbons: A case study of 1, 3, 5-Trimethylbenzene skeletal mechanism. (15th August 2023)

• Record Type: Journal Article
• Authors: Tuo, Chenyu; Hui, Xin; Sung, Chih-Jen
• Is Part Of: Fuel. Volume 346(2023)
• Publication Date: 2023-08-15
• Subjects: 1, 3, 5-trimethylbenzene -- Mechanism reduction -- Skeletal mechanism -- Hierarchical sensitivity analysis -- Selective reduction target; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2023.128277
• Languages: English
• ISSNs: 0016-2361

Abstract

Highlights: A reduction method based on the hierarchical sensitive analysis (HSA) is proposed. The HSA method has good efficiency and accuracy for large hydrocarbons. A skeletal mechanism of 1, 3, 5-trimethylbenzene (135TMB) is generated by HSA method. The 135TMB skeletal mechanism agrees well with the detailed mechanism. Abstract: A novel hierarchical method of skeletal reduction for detailed hydrocarbon reaction mechanisms is proposed and applied to generate a skeletal mechanism of 1, 3, 5-trimethylbenzene (135TMB) which is relevant to practical fuels and their surrogates. The proposed reduction method is based on the hierarchical sensitivity analysis (HSA) implemented in a top-to-bottom manner in terms of carbon levels with selective reduction targets, such as autoignition delay time, laminar flame speed, flame extinction, speciation, etc. These reduction targets can be selected based on the desired combustion phenomena to be simulated and are only validated at their corresponding carbon levels where the respective chemistries are dominating. In contrast to the conventional global sensitivity analysis (GSA) in which species and reactions are randomly evaluated, HSA evaluates species and reactions following the oxidation sequence of fuel molecule, and therefore is able to generate skeletal mechanisms as compact as possible with significantly higher efficiency than GSA. In addition, quasi-steady-state approximation and reaction lumping are integrated in the current reduction process. Low-temperature reaction pathway is also optimized with reaction rates tuned using a particle swarm algorithm to better predict species fractions in the low-to-intermediate temperature regime. As such, based on the detailed 135TMB mechanism of Diévart et al. (2013) with 450 species and 4569 reactions, a skeletal mechanism with 46 species and 197 reactions has been successfully generated including both high- and low-temperature reaction pathways. Extensive validations of the resulting skeletal mechanism are performed against the detailed mechanism predictions and the literature experimental data over a wide range of conditions, and good agreements are observed. These results not only show the accuracy and reliability of the present skeletal 135TMB mechanism but also demonstrate the effectiveness and reduction efficiency of the proposed hierarchical reduction method.