Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Monte Carlo and Active Subspace Identification methods are combined with first- and second-order adjoint sensitivities to perform (forward) uncertainty quantification analysis of the thermo-acoustic stability of two annular combustor configurations. This method is applied to evaluate the risk factor, i.e., the probability for the system to be unstable. It is shown that the adjoint approach reduces the number of nonlinear-eigenproblem calculations by as much as the Monte Carlo samples.
['Luca Magri', 'Michaël Bauerheim', 'Franck Nicoud', 'Matthew P. Juniper']
I am writing a research paper on a idea Stability analysis of thermo-acoustic nonlinear eigenproblems in annular combustors. I am writing a research paper on a idea Part II. I am writing a research paper on a idea Uncertainty quantification
[{"from": "human", "value": "I am writing a research paper on a idea Stability analysis of thermo-acoustic nonlinear eigenproblems in annular combustors. I am writing a research paper on a idea Part II. I am writing a research paper on a idea Uncertainty quantification"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Monte Carlo and Active Subspace Identification methods are combined with first- and second-order adjoint sensitivities to perform (forward) uncertainty quantification analysis of the thermo-acoustic stability of two annular combustor configurations. This method is applied to evaluate the risk factor, i.e., the probability for the system to be unstable. It is shown that the adjoint approach reduces the number of nonlinear-eigenproblem calculations by as much as the Monte Carlo samples."}]