This paper delves into the application of Uncertainty Quantification (UQ) and Sensitivity Analysis (SA) to address complex, multiscale Global Challenges. Using a Renewable Energy Sources case study, we demonstrate various approaches to incorporate UQ and SA. UQ helps mitigate uncertainties in models and input data, leading to more reliable results. SA identifies the significant influence of specific input parameters on model outputs, aiding in resource allocation and problem-solving. By reducing the number of required parameters, SA can optimize computational resources and accelerate time-to-solution. Additionally, we showcase how UQ and SA can directly contribute to addressing Global Challenges. The paper concludes by discussing the multiscale Uncertainty Quantification and Sensitivity Analysis platform (mUQSA) and its underlying tools, which streamline the implementation of UQ and SA for Global Challenges.

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Fostering Uncertainty Quantification in Global Challenges with mUQSA Toolkit

  • Michał Kulczewski,
  • Bartosz Bosak,
  • Piotr Kopta,
  • Wojciech Szeliga,
  • Tomasz Piontek

摘要

This paper delves into the application of Uncertainty Quantification (UQ) and Sensitivity Analysis (SA) to address complex, multiscale Global Challenges. Using a Renewable Energy Sources case study, we demonstrate various approaches to incorporate UQ and SA. UQ helps mitigate uncertainties in models and input data, leading to more reliable results. SA identifies the significant influence of specific input parameters on model outputs, aiding in resource allocation and problem-solving. By reducing the number of required parameters, SA can optimize computational resources and accelerate time-to-solution. Additionally, we showcase how UQ and SA can directly contribute to addressing Global Challenges. The paper concludes by discussing the multiscale Uncertainty Quantification and Sensitivity Analysis platform (mUQSA) and its underlying tools, which streamline the implementation of UQ and SA for Global Challenges.