Toward the development of a verification, validation, and uncertainty quantification framework for granular and multiphase flows-Part 1: Screening study and sensitivity analysis

Aytekin Gel, Avinash Vaidheeswaran, Jordan Musser, Charles H. Tong

Research output: Contribution to journalArticle

Abstract

Establishing the credibility of computational fluid dynamics (CFD) models for multiphase flow applications is increasingly becoming a mainstream requirement. However, the established verification and validation (V&V) Standards have been primarily demonstrated for single phase flow applications. Studies to address their applicability for multiphase flows have been limited. Hence, their application may not be trivial and require a thorough investigation. We propose to adopt the ASME V&V 20 Standard and explore its applicability for multiphase flows through several extensions by introducing some of the best practices. In the current study, the proposed verification, validation, and uncertainty quantification (VVUQ) framework is presented and its preliminary application is demonstrated using the simulation of granular discharge through a conical hopper commonly employed in several industrial processes. As part of the proposed extensions to the V&V methodology, a detailed survey of subject matter experts including CFD modelers and experimentalists was conducted. The results from the survey highlighted the need for a more quantitative assessment of importance ranking in addition to a sensitivity study before embarking on simulation and experimental campaigns. Hence, a screening study followed by a global sensitivity was performed to identify the most influential parameters for the CFD simulation as the first phase of the process, which is presented in this paper. The results show that particle-particle coefficients of restitution and friction are the most important parameters for the granular discharge flow problem chosen for demonstration of the process. The identification of these parameters is important to determine their effect on the quantities of interest and improve the confidence level in numerical predictions.

Original languageEnglish (US)
Article number031001
JournalJournal of Verification, Validation and Uncertainty Quantification
Volume3
Issue number3
DOIs
StatePublished - Sep 1 2018
Externally publishedYes

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Modeling and Simulation
  • Statistics and Probability

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