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Messages - atish

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Uncertainty Quantification (quoFEM) / Re: Using quoFEM for GP based Surrogate Modelling and Sensitivity Analysis,
« on: October 31, 2023, 12:05:12 AM »
Many thanks, Sang-ri.

1. I will try to perform the sensitivity analysis on quoFEM as per your instructions. Fingers crossed. Let's see how the sensitivity index values are.
2. For the GP-based surrogate model, could you please suggest which tools will be easier for my case, provided I have no machine learning experience? I am comfortable with Python and MATLAB.

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Uncertainty Quantification (quoFEM) / Re: Using quoFEM for GP based Surrogate Modelling and Sensitivity Analysis,
« on: October 30, 2023, 02:37:26 AM »
Thanks, Sang-ri.

My apologies for the late reply. I have been feeling unwell for the past few days.

1. The dimension of my model input is 50. I have chosen 50 chemical reaction rates whose contribution I would like to inspect. The atmospheric model that I am working on is the Globol Ionosphere Thermosphere Model (GITM), which outputs many parameters, but I will try to focus on baseline parameters such as neutral temperature, nitric oxide density, neutral density, and electron density.  Let's say, for now, my output dimension is 4.

2. No, I have not used quoFEM before. Previously, I tried to use the SALib - Sensitivity Analysis Library in Python to perform Sobol Analysis. The result was not good.

I have 512 simulation data which I obtained when I ran my model using 512 different sets of perturbed reaction rates. Each set of perturbed reaction rates contains 50 reaction rates. I generated these 512 sets of perturbed reaction rates using Monte Carlo simulation.

Regards,
Atish

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Uncertainty Quantification (quoFEM) / Using quoFEM for GP based Surrogate Modelling and Sensitivity Analysis,
« on: October 25, 2023, 04:55:13 AM »
Dear SimCenter Team,

I am a PhD student at the University of New South Wales, Australia. Currently, I am working on a global sensitivity analysis using a high-fidelity atmospheric model. I have considered 50 reaction rates (input parameter) as my input quantity of interest, whose effects I will be quantifying. Using 512 sets of perturbed reaction rates, I tried to run my model and perform sobol analysis. However, my sobol indices are not converging, as I think my sample size is small. Now I have decided to create a surrogate model using the Gaussian Process (GP) Regression method and then perform sobol analysis. I am new to machine learning.

My question:
1. Since my input parameter is 50 and I have 512 output data, can I use quoFEM to perform sensitivity analysis.
2. If not, then can I use quoFEM to create GP based surrogate model.

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