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Tesi etd-09012016-163801

Thesis type
Tesi di laurea magistrale
email address
CFD Verification and Validation of Twin Parallel Jets
Corso di studi
relatore Prof. D'Auria, Francesco
Parole chiave
  • CFD
  • Verification
  • Validation
  • Jet
Data inizio appello
Riassunto analitico
A Verification and Validation (V&amp;V) study has been conducted for the ASME V&amp;V30 Subcommittee – First Benchmark Problem: Twin Jets Computational Fluid Dynamics (CFD) Numeric Model Validation. The ASME V&amp;V30 “Verification and Validation in Computational Nuclear System Thermal Fluids Behavior”, provides the practices and procedures for verification and validation of software used to calculate the nuclear system thermal fluid behavior, including system analysis and computational fluid dynamics and the coupling of them. The scope of the first benchmark problem is to investigate the physics and CFD simulation capabilities of two parallel water jets entering in a vertical tank of water. The study of the mixing of two parallel jets is an important thermal hydraulic aspect that can be found in some of the new nuclear systems, like metal-cooled reactors and very high temperature reactors, where great attention is given to some regions of the core coolant system, for example the outlet/inlet plenum, where a not uniform and efficient thermal turbulent mixing of the coolant, coming from different regions of the reactor core at different temperatures, could cause some fluid/structure problems like, thermal striping due to random coolant temperature fluctuations or thermal stratifications caused by an inefficient coolant mixing, leading to high cycle thermal fatigue and potential crack initiation at the surface level of the structure. For these reasons, mixing conditions of the core coolant exit plenum, needs to be accurately evaluated and fully understood. The V&amp;V ultimate goal is validation, defined as the process of determining the degree to which a mathematical model is an accurate representation of the real world, from the prospective of the intended use of the model. Validation must be preceded by code and solution verification. Code verification establishes that the code accurately solves the mathematical model implemented in the code, i.e. the code is free of mistakes and its numerical algorithm is convergent. Solution verification estimates the numerical accuracy of a particular calculation. The estimation of an uncertainty range, within which the simulation modelling error lies, is the primary objective of the validation process and it is accomplished by comparing a simulation results with the available experimental data. There can be no validation without experimental data, with which to compare the results of the simulations.<br>In this study the focus is on the isothermal mixing process of water, coming from two parallel jets, and its scope is to evaluate the sensitivity of the CFD simulation results from the use of different turbulence models and boundary conditions. After the solution verification phase, mainly focused on a mesh sensitivity study, quantitative estimation of the modelling error and the uncertainties of the results, have been evaluated for the model validation part. The next step, which will not be presented in this work, will be the introduction of a temperature difference in the two interacting jets, to better evaluate the influence of thermal turbulent mixing and buoyancy effects. The experimental data velocity field was measured using Particle Image Velocimetry (PIV) and Laser Doppler Anemometry (LDA) and the CFD simulations were conducted using the verified, element-based finite volume CFD code, Ansys-CFX and, for each simulation, the numerical results have been verified by applying Roache’s Grid Convergence Index (GCI), for the estimation of the numerical error uncertainty. In a second phase of this work, the results have been validated by using the approach proposed in the ASME V&amp;V-20 “Standard for Verification and Validation in Computational Fluid Dynamics and Heat Transfer” ASME, for the estimation of the modelling error and its associated uncertainty.<br><br>