Presentation materials
Proper Orthogonal Decomposition (POD)-based model order reduction techniques are a popular choice for multi-query and fast replay applications in CFD, which often require sophisticated extensions for efficient treatment of nonlinearities. Non-intrusive methods which treat the high fidelity model as an external black-box offer a desirable alternative.
We present a non-intrusive approach which...
The aim of the work is to apply the reduced basis method to a two dimensional time dependent convection dominated fluid-structure interaction (FSI) problem.
One basic assumption of the reduced basis method is that the solution manifold
can be well approximated by a sequence of finite dimensional spaces: this mathematical assumption translates in the fact that the...
The trapping of diffusing particles by either a single or a distribution of moving traps is an interesting topic that has been employed to model a variety of different real problems in chemistry, physics and biology. Here we study the dynamics of diffusing particles in a domain with an oscillating bubble. Laboratory experiments provide evidence of a non monotone behavior in time of the...
The aim of this work is to show the applicability of the reduced basis model reduction in non-linear systems undergoing bifurcations. Bifurcation analysis, i.e., following the different bifurcating branches, as well as determining the bifurcation points themselves, is a complex computational task [1, 4]. Reduced Order Models (ROM) can potentially reduce the computational burden by several...
We consider a model-order reduction approach to approximate scalar transport
and mixing in a T-junction using spectral-element-based large-eddy simulation
(LES) for the full-order model. One such LES simulation of 100 convective-time
units can cost hundreds of thousands of core-hours on a supercomputer. For the
reduced-order model, we apply Galerkin projection using POD-generated...
To model the complex dynamics of buoyancy for nuclear thermal-hydraulic studies and other similar industrial problems, a two-way coupling between the momentum equations and the energy equation is required. To simplify the problem, the Boussinesq approximation is often applied by neglecting the effect of local density differences of the fluid, induced by temperature, except for the density...
A Proper Orthogonal Decomposition based Reduced-Order Model (POD-ROM) is presented for parameterized multiphysics computations of the Molten Salt Fast Reactor (MSFR) concept. The reduced-order model is created using the method of snapshots where the training set is obtained by exercising a Full-Order Model (FOM). The steady state model solves the multi-group diffusion k-eigenvalue equations...
Fish farming is increasingly important as the demand on food supplies grows with the world’s population. Limiting the spread of disease within such farms is vital, as the detection of such diseases calls for immediate eradication of the infected farm. Optimal farm placement from the prediction of disease spread could potentially limit the spread of infections within these farms. Previous...
In this work, we present a hybrid approach for the reduction of fluid dynamics flows. The approach proposed is based on mixing the traditional projection Galerkin methods with data-driven techniques. The goal is to reduce complex problems in CFD with special focus on turbulent flows. The data-driven techniques are utilized in approximating certain fluid dynamics variables in the reduced...
In these last months we have been working on the resolution of the parametrized Navier Stokes problem.
In order to apply a reduction method, we started from full order solutions obtained by the use of the OpenFOAM package.
What is new in our work is the effort to follow the SIMPLE algorithm strategy, used in the OpenFOAM full order solvers, also for the reduced problem. The goal is to have a...
Considered as a geophysical fluid, the polluted atmosphere shares the shallow domain characteristics with other natural large-scale fluids such as seas and oceans. This means that its domain is excessively greater horizontally than in the vertical dimension, leading to the classic hydrostatic approximation of the Navier-Stokes equations. We consider the so-called anisotropic model as a...
In continuous casting machinery, the molten metal solidifies in a mold. In order to control the casting process, a proper knowledge of the heat flux between the mold and the metal is crucial. This boundary condition can be estimated using thermocouples measurements inside the mold and solving an inverse problem. In this research we exploit model order reduction techniques to achieve an online...
We are interested in the design of eco-efficient buildings. This involves computing models for several parameters which could be geometrical or physical. Sometimes, each computation could take a long time and this situation is not the most desirable. This reason encourages us to consider the basis reduced method that allow us to obtain a faster solution with a little error.
Dimension reduction techniques confer benefits to parametric studies in a great number of engineering applications. Active subspaces proposed by Trent Russi and developed by Paul Constantine have proven to be a versatile method in this matter for models with an underneath linear trend. Some efforts are directed to possible non-linear extensions. The turning point may come from machine learning...
Optimal flow control problems governed by parametrized partial differential equations are a very powerful mathematical model. They are suitable to describe several complex physical phenomena and they are quite spread in different applications. Although, the computational effort increases when one has to deal with nonlinear and/or time dependent governing equations [3,4,5].
We propose reduced...
This paper presents the enriched Galerkin discretization for modelling fluid flow in fractured porous media using the mixed-dimensional approach. The block structure used to compose this mixed-dimensional problem is presented. The proposed method has been tested against published benchmarks. Moreover, the heterogeneous matrix permeability setting is utilized to assess the enriched Galerkin...
In this work, we will present implementation of reduced order methods for parametrized problems in computational fluid dynamics, with a special attention to inverse problems, such as optimal flow control problems and data assimilation in biomedical sciences.
Our focus will, specifically, be on minimizing the misfit between clinical measurements acquired in coronary artery bypass graft surgery...
