On pressure modes in ice-induced vibrations using multivariate analysis

Pressures at the ice-structure interface during model-scale ice-structure interaction are often measured with tactile sensors. Resulting datasets usually include large volume of data along with some measurement error and noise; therefore, it is inherently hard to extract the hidden fluctuating pressures in the system. Identifying the...

A semi-continuous formulation for goal-oriented reduced-order models

Modern computational and experimental techniques can represent the detailed dynamics of complex systems using large numbers of degrees of freedom. To facilitate human interpretation or the optimal design of control systems, however, reduced-order models (ROMs) are required. Conventional reduced-order modeling techniques, such as those based on...

POD-DEIM model order reduction for strain softening viscoplasticity

We demonstrate a Model Order Reduction technique for a system of nonlinear equations arising from the Finite Element Method (FEM) discretization of the three-dimensional quasistatic equilibrium equation equipped with a Perzyna viscoplasticity constitutive model. The procedure employs the Proper Orthogonal Decomposition-Galerkin (POD-G) in...

Use of reduced-order models in well control optimization

Many aspects of reservoir management can be expected to benefit from the application of computational optimization procedures. The focus of this review paper is on well control optimization, which entails the determination of well settings, such as flow rates or bottom hole pressures, that maximize a particular objective function. As is the case...

A modified POD procedure with patterns in time for parameter estimation

Proper orthogonal decomposition (POD) is a well established model order reduction technique, however its efficiency is limited for advection dominated model. In this report, we explore a modified proper orthogonal decomposition procedure with patterns in time instead of the usual patterns in space. This modified procedure is more suitable for...

Characteristics of flow through orifices in pipes: An experimental investigation

Orifice plates are key components used for flow measurement and control in several industries. For instance, they find applications in gas and liquid circuits of lithography machines, nuclear power plants and aerospace propulsion systems. They are used typically either for measuring flow-rate or to introduce a pressure drop for purposes of flow...

Nonlinear Model Order Reduction using POD/DEIM for Optimal Control of Burgers' Equation

The model-order reduction techniques Proper Orthogonal Decomposition (POD) and Discrete Empirical Interpolation Method (DEIM) have been applied for the optimal control of Burgers' equation. Accuracy and performance of the reduced models have been studied in detail for different values of the viscosity parameter and different sizes of the...

3D flow organization and dynamics in subsonic jets: Aeroacoustic source analysis by tomographic PIV

To meet the increasingly stringent noise regulation, aircraft manufacturers are searching for solutions to jet noise. This, which constitutes a significant amount of the total noise emitted by civil aircrafts, is generated by the mixing processes between the exhaust flow leaving the engine and the atmosphere. A detailed understanding of such...

Model-Reduced Gradient Based Production Optimization: Computational Analysis of POD-Based Model-Order Reduction in the Context of Production Optimization

Reduced-order modelling procedures, seen as an alternative to the classical gradient based approach, in which the adjoint of the tangent linear approximation of the forward model is replaced by the adjoint of a linear approximation of a reduced forward model. Proper orthogonal decomposition is used to compute the reduced model, by using the...

Model-reduced gradient-based history matching

Gradient-based history matching algorithms can be used to adapt the uncertain parameters in a reservoir model using production data. They require, however, the implementation of an adjoint model to compute the gradients, which is usually an enormous programming effort. We propose a new approach to gradient-based history matching which is based...

Unsteady Flow Organization of a Shock Wave/Boundary Layer Interaction

A fundamental experimental study is carried out to investigate the unsteady flow organization of an incident shock wave/turbulent boundary layer interaction at Mach 2.1. Planar and tomographic particle image velocimetry (PIV) are used in combination with data processing using the proper orthogonal decomposition (POD), complemented with hot-wire...

Use of POD in control of flow through porous media

During the design of development concepts for the exploitation of oil and gas reservoirs, frequent use is made of numerical simulation of the flow of multi-phase fluids through porous rock. Recently, increased attention has been paid to systematic optimization of well positions and operating parameters (rates, pressures) over the life of the...

Model reduction by proper orthogonal decomposition for lambda-omega systems

Proper orthogonal decomposition (POD) is a powerful technique for model reduction of linear and non-linear systems. It is based on a Galerkin type discretization with basis elements created from the system itself. In this work POD is used to derive low-order models for a so-called lambda-omega system that is a universal model to investigate two...

Use of POD in control of flow through porous media

During the design of development concepts for the exploitation of oil and gas reservoirs, frequent use is made of numerical simulation of the flow of multi-phase fluids through porous rock. Recently, increased attention has been paid to systematic optimization of well positions and operating parameters (rates, pressures) over the life of the...

Numerical investigation of the aerodynamic noise from a forward-facing step

In the present study, aerodynamic noise from a forward-facing step is numerically investigated for Reynolds number based on the step height, Reh=8,000 and flow Mach number, M=0.03. A three-dimensional flow over the forward-facing step is calculated by the incompressible large eddy simulation (LES), while its acoustic field is solved by the...

Model reduction by proper orthogonal decomposition for estimation of scalar parameters in elliptic PDEs

Proper orthogonal decomposition (POD) is a powerful technique for model reduction of linear and non-linear systems. It is based on a Galerkin type discretization with basis elements created from the system itself. In this work POD is applied to estimate scalar parameters in elliptic partial differential equations. The parameter estimation is...