Experimental and Modeling Study on the Thermal Decomposition of Jet Propellant-10

Vandewiele, Nick; Magoon, Gregory R.; Geem, Kevin Van; Reyniers, Marie-Françoise; Green, William; Marin, Guy

doi:10.1021/ef500936m

Cited by 50 publications

(51 citation statements)

References 60 publications

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“…The shock tube experiments confirm the presence of 2CC during pyrolysis and oxidation (see Supporting Material). This is also supported by experimental data presented by Vandewiele et al [34], where many unidentified C 9 and C 10 species with similar volatility to JP-10 were found at low conversion. The species undergo bond scissions which lead to the formation of two radicals that initiate the radical mechanism.…”

Section: The Reaction Networksupporting

confidence: 87%

“…A second validation for the model compares our predictions with the JP-10 pyrolysis flow tube experimental data reported by Vandewiele et al [34]. These experiments were obtained in a bench scale setup recently used for studies on butanol and aromatic hydrocarbons.…”

Section: Pyrolysis Flow Tube Speciationmentioning

confidence: 68%

“…11. Experimentally measured (data points) and simulated concentration profiles (lines) as a function of temperature for the pyrolysis of JP-10 as reported by Vandewiele et al [34]. Experimental conditions: 10 mol% JP-10 diluted in N 2 , P = 0.14 MPa, mass flow rate of JP-10 = 2.33 Â 10 À2 g s À1 .…”

Section: Ignition Delaysmentioning

confidence: 98%

“…OH sensitivity analysis was performed for the model at stoichiometric conditions (1500 K and 7 atm for a 0.20 mol% feed [34]. Experimental conditions: 7 mol% JP-10 diluted in N 2 , P = 0.14 MPa, mass flow rate of JP-10 = 2.33 Â 10 À2 g s À1 .…”

Section: Ignition Delaysmentioning

confidence: 99%

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JP-10 combustion studied with shock tube experiments and modeled with automatic reaction mechanism generation

Gao

Vandeputte

Yee

et al. 2015

Combustion and Flame

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a b s t r a c tThis work presents shock tube experiments and kinetic modeling efforts on the pyrolysis and combustion of JP-10. The experiments were performed at 6-8 atm using 2000 ppm of JP-10 over a temperature range of 1000-1600 K for pyrolysis and oxidation equivalence ratios from 0.14 to 1.0. This work distinguishes itself from previous studies as GC/MS was used to identify and quantify the products within the shocked samples, enabling the tracking of product yield dependence on equivalence ratio as well as identifying several new intermediates that form during JP-10's decomposition. A detailed, comprehensive model of JP-10's combustion and pyrolysis kinetics was constructed with the help of RMG, an open-source reaction mechanism generation software package. The resulting model, which includes 691 species reacting in 15,518 reactions, was extensively validated against the shock tube experimental dataset as well as newly published flow tube pyrolysis data from Ghent. Most of the important rate coefficients were computed using quantum chemistry. The model succeeds in identifying all major pyrolysis and combustion products and captures key trends in the product distribution. Simulated ignition delays agree within a factor of 4 with most experimental ignition delay data gathered from literature. The presented experimental work and modeling efforts yield new insights on JP-10's complex decomposition and oxidation chemistry and identify key pathways towards aromatics formation.

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Section: The Reaction Networksupporting

confidence: 87%

Section: Pyrolysis Flow Tube Speciationmentioning

confidence: 68%

Section: Ignition Delaysmentioning

confidence: 98%

Section: Ignition Delaysmentioning

confidence: 99%

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JP-10 combustion studied with shock tube experiments and modeled with automatic reaction mechanism generation

Gao

Vandeputte

Yee

et al. 2015

Combustion and Flame

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“…First, the Ghent experiments isolated a number of products containing a five-membered ring, such as methylcyclopentadiene (C 6 H 8 ) and ethenylcyclopentene (C 7 H 10 ), 18 cf. Figure 7.…”

Section: Energy and Fuelsmentioning

confidence: 99%

Kinetic Modeling of Jet Propellant-10 Pyrolysis

et al. 2014

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A detailed kinetic model for the thermal decomposition of the advanced fuel Jet-Propellant 10 (JP-10) was constructed using a combination of automated mechanism generation techniques and ab initio calculations. Rate coefficients for important unimolecular initiation routes of exo-TCD were calculated using the multireference method CAS-PT2, while rate coefficients for the various primary decompositions of the exo-TCD-derived monoradicals were obtained using CBS-QB3. Rateof-production analysis showed the importance of four dominating JP-10 decomposition channels. The model predictions agree well with five independent experimental data sets for JP-10 pyrolysis that cover a wide range of operating conditions (T = 300− 1500 K, P = 300 Pa−1.7 × 10 5 Pa, dilution = 0.7−100 mol% JP-10, conversion = 0−100%) without any adjustment of the model parameters. A significant part of the model comprises secondary conversion routes to aromatic and polyaromatic hydrocarbons and could thus be used to assess the tendency for deposit formation in fuel-rich zones of endothermic fuel applications.

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Automatic Mechanism and Kinetic Model Generation for Gas‐ and Solution‐Phase Processes: A Perspective on Best Practices, Recent Advances, and Future Challenges

Vijver

Vandewiele

Bhoorasingh

et al. 2015

Int J of Chemical Kinetics

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113

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Completely automated mechanism generation of detailed kinetic models is within reach in the coming decade. The recent developments in this field of chemical reaction engineering are anticipated to lead to some groundbreaking discoveries in the future, extending our fundamental understanding and resolving many of today's society problems such as energy production and conversion, emission reduction, greener chemical production processes, etc. In the present review, the focus is on the core of these automated mechanism generation for gas‐phase and solution‐phase processes that is on how the reaction kinetics and thermodynamic and transport properties of species are estimated and calculated starting from the fundamental elements of the software. With tasks such as the definition of reaction rules and reaction families, the unambiguous representation of species, and the choice of different termination criteria, generating a good reaction mechanism is still not as simple as pressing a “run” button. One of the main challenges that still needs to be overcome is how to deal with data scarcity and the combination with affordable computational chemistry calculations seems the logical step forward. The best practices are illustrated in a butane pyrolysis case study, which also exposes the challenges in the field of automatic kinetic model generation.

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Experimental and Modeling Study on the Thermal Decomposition of Jet Propellant-10

Cited by 50 publications

References 60 publications

JP-10 combustion studied with shock tube experiments and modeled with automatic reaction mechanism generation

JP-10 combustion studied with shock tube experiments and modeled with automatic reaction mechanism generation

Kinetic Modeling of Jet Propellant-10 Pyrolysis

Automatic Mechanism and Kinetic Model Generation for Gas‐ and Solution‐Phase Processes: A Perspective on Best Practices, Recent Advances, and Future Challenges

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