Development of a compact and robust Polyoxymethylene Dimethyl Ether 3 reaction mechanism for internal combustion engines

Lin, Qinjie; Tay, Kun Lin; Zhou, Dezhi; Yang, Wenming

doi:10.1016/j.enconman.2019.02.007

Cited by 53 publications

(48 citation statements)

References 60 publications

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“…Given the complexity of engine simulations, the size of these mechanisms makes simulation largely intractable, requiring the development of a reduced mechanism. Two simplified mechanisms were proposed by Ren et al 35 and Lin et al 18 Both employed the model of He et al 33 as a basis, using different methodologies for selecting key species and reactions of PODE 3 . Additional reactions were added by both for modeling the combustion of a PRF carrier fuel.…”

Section: Methodsmentioning

confidence: 99%

“…As a demonstration of the proposed knowledge graph-based approach, the starting mechanism of Lin et al 18 is selected due to its relatively small size. This is the mechanism generated by selecting reactions from the wider He et al 33 mechanism prior to any further calibration to experimental results.…”

Section: Methodsmentioning

confidence: 99%

“…This was chosen to simplify the process for a proof-of-concept framework demonstration and as the main focus of this work is to demonstrate a knowledge graph-based approach. There is an existing precedent for works adjusting the pre-exponential factors alone, 18 with large hypercubes of potential values. This approach is further justified when reduced mechanisms are optimized as some reaction pathways and species are already not present within the mechanism.…”

Section: Methodsmentioning

confidence: 99%

“…A demonstration of this is performed on a reduced poly(oxymethylene)dimethyl ether 3 (PODE n , where n = 3) mechanism. 18 This alternative fuel, with a molecular formula of CH 3 O(CH 2 O) 3 CH 3 , is deliberately chosen for its current interest as a fuel additive to help with the push for cleaner and more efficient vehicles. The additive has been demonstrated to lower soot emissions and improve combustion efficiency in engines.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Automated Calibration of a Poly(oxymethylene) Dimethyl Ether Oxidation Mechanism Using the Knowledge Graph Technology

Bai

Geeson

Farazi

et al. 2021

J. Chem. Inf. Model.

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In this paper, we develop a knowledge graph-based framework for the automated calibration of combustion reaction mechanisms and demonstrate its effectiveness on a case study of poly(oxymethylene)dimethyl ether (PODE n , where n = 3) oxidation. We develop an ontological representation for combustion experiments, OntoChemExp, that allows for the semantic enrichment of experiments within the J-Park simulator (JPS, theworldavatar.com ), an existing cross-domain knowledge graph. OntoChemExp is fully capable of supporting experimental results in the Process Informatics Model (PrIMe) database. Following this, a set of software agents are developed to perform experimental result retrieval, sensitivity analysis, and calibration tasks. The sensitivity analysis agent is used for both generic sensitivity analyses and reaction selection for subsequent calibration. The calibration process is performed as a sampling task, followed by an optimization task. The agents are designed for use with generic models but are demonstrated with ignition delay time and laminar flame speed simulations. We find that calibration times are reduced, while accuracy is increased compared to manual calibration, achieving a 79% decrease in the objective function value, as defined in this study. Further, we demonstrate how this workflow is implemented as an extension of the JPS.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Automated Calibration of a Poly(oxymethylene) Dimethyl Ether Oxidation Mechanism Using the Knowledge Graph Technology

Bai

Geeson

Farazi

et al. 2021

J. Chem. Inf. Model.

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show abstract

“…In this study, the 2-butanone raw reduced mechanism is built using the [44][45][46] decoupling method. The main step to build a reduced mechanism is as follow:…”

Section: Mechanism Constructionmentioning

confidence: 99%

A New Machine Learning Algorithm to Optimize A Reduced Mechanism of 2-Butanone and the Comparison with Other Algorithms

Wang¹,

Liu²,

Jia³

et al. 2019

ES Mater.Manuf.

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View Article Online 2-butanone (methyl ethyl ketone) has been identified as a potential alternative fuel and fuel tracer in recent studies. In this work, a reduced mechanism containing 50 species and 190 reactions for 2-butanone is developed for the first time. The raw reduced mechanism is built in three parts using decoupling methodology, a reduced CC sub-mechanism, a reduced CC sub-mechanism and a detailed H /CO/C sub-4 n 2 3 2 1 mechanism. Subsequently, the self-adaptive differential evolution algorithm of machine learning is proposed for optimizing the reaction rates of 31 reactions in the CC sub-mechanism to predict the ignition delay times and laminar flame speeds in constant volume bombs. The 4 n optimized reduced mechanism is validated by the ignition delay times in shock tubes and laminar flame speeds in constant volume bombs. The results of the optimized reduced mechanism are similar to those of the detailed mechanism, which show it is reliable. Moreover, the performance of the self-adaptive differential evolution algorithm is much better than the genetic algorithm and the particle swarm optimization.

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Fully Automated Kinetic Models Extend our Understanding of Complex Reaction Mechanisms

Rihm

Bai

Pascazio

et al. 2023

Chemie Ingenieur Technik

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Die Automatisierung von Erstellung und Kalibrierung mikrokinetischer Modelle befähigt Forscher zur detaillierten Analyse von Reaktionsmechanismen sowie der Multiskalenmodellierung von Reaktoren auf Basis von Ab‐initio‐Berechnungen. Am Beispiel elektrochemischer CO2‐Reduktion wird deutlich, dass dies eine strukturierte und standardisierte Darstellung skalenübergreifender Konzepte erfordert. Massive Fortschritte wurden in diesem Bereich durch dynamische Wissensgraphen erzielt, wobei erste Teilerfolge im Bereich der Mechanismuserzeugung, quantenmechanischen Berechnungen sowie Kalibrierung mit Experimentaldaten zu vermelden sind.

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Development of a compact and robust Polyoxymethylene Dimethyl Ether 3 reaction mechanism for internal combustion engines

Cited by 53 publications

References 60 publications

Automated Calibration of a Poly(oxymethylene) Dimethyl Ether Oxidation Mechanism Using the Knowledge Graph Technology

Automated Calibration of a Poly(oxymethylene) Dimethyl Ether Oxidation Mechanism Using the Knowledge Graph Technology

A New Machine Learning Algorithm to Optimize A Reduced Mechanism of 2-Butanone and the Comparison with Other Algorithms

Fully Automated Kinetic Models Extend our Understanding of Complex Reaction Mechanisms

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