Master's Proposal: Pavan Patel

Fri Nov 19 2021 10:00 PM
MK317 and BlueJeans

You're invited to attend a


Master's Proposal 




Pavan Patel

(Advisor: Prof. Suresh Menon)



"Uncertainty Quantification of DIMP Kinetics in a Shocktube"


Friday, November 19
10:00 a.m.
Montgomery Knight Building 317


Designing explosives that can effectively destroy stockpiles of chemical warfare agents, such as sarin, requires a detailed understanding of its decomposition kinetics at high temperatures. Performing experiments with sarin, however, is difficult due its toxicity. Instead, simulants such as DIMP, whose chemical properties are similar to that of sarin, can be used. A modified DIMP kinetics model with 1350 reactions and 131 species was developed recently at the University of Central Florida (UCF) using shocktube experiments. Predictions made using this mechanism compare well with experiments. However, this is not a sufficient condition to trust a prediction made at any other condition. Uncertainty analyses can help assess the ability to make reliable predictions with a given chemical kinetics mechanism. Uncertainties associated with the DIMP kinetics model, primarily from model inputs such as rate parameters, need to be propagated through the model to quantify the variability in predictions. For this thesis, uncertainty quantification methods are proposed to quantify the effect of initial pressure, temperature, composition, and kinetic rate parameter uncertainties on the destruction time of DIMP in a shocktube. Large prediction uncertainties under certain conditions indicate the need for improved rate parameter values. In order to improve the predictive capability, of the DIMP kinetics mechanism, a Bayesian inference framework that reduces uncertainties in the rate parameters of the most influential reactions is proposed.


  • Prof. Suresh Menon – School of Aerospace Engineering (advisor)
  • Prof. Wenting Sun – School of Aerospace Engineering
  • Prof. Jerry Seitzman – School of Aerospace Engineering


MK317 and BlueJeans