Extended balancing of continuous LTI systems: a structure-preserving approach

In this article, we treat extended balancing for continuous-time linear time-invariant systems. We take a dissipativity perspective, thus, resulting in a characterization in terms of linear matrix inequalities. This perspective is useful for determining a priori error bounds. In addition, we address the problem of structure-preserving model...

Model Reduction for Interactive Geometry Processing

The research field of geometry processing is concerned with the representation, analysis, modeling, simulation and optimization of geometric data. In this thesis, we introduce novel techniques and efficient algorithms for problems in geometry processing, such as the modeling and simulation of elastic deformable objects, the design of tangential...

Real-time Control of Combined Water Quantity & Quality in Open Channels

Fresh water supply and flood protection are two central issues in water management. Society needs more and more fresh water and a safe water system to guarantee a better life. A more severe climate will result in more droughts and extreme storms. As a consequence, salt water intrusion will increase. Therefore, clean and fresh water is becoming...

Dynamic Substructuring Methodologies for Integrated Dynamic Analysis of Wind Turbines

Model Reduction in Chemical Engineering: Case studies applied to process analysis, design and operation

During the last decades, models have become widely used for supporting a broad range of chemical engineering activities, such as product and process design and development, process monitoring and control, real time optimization of plant operation or supply chain management. Although tremendous advancements continue to take place in 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...

Impact of Thermodynamic Principles in Systems Biology

It is shown that properties of biological systems which are relevant for systems biology motivated mathematical modelling are strongly shaped by general thermodynamic principles such as osmotic limit, Gibbs energy dissipation, near equilibria and thermodynamic driving force. Each of these aspects will be demonstrated both theoretically and...

System-Theoretical Model Reduction for Reservoir Simulation and optimization

This thesis is concerned with low-order modelling of heterogeneous reservoir systems for the purpose of efficient simulation and optimization of flooding processes with multiple injection and production (smart) wells. Typically, one is initially equipped with a physics-based ('white-box') model consisting of O(103-106) equations and parameters...

Model inversion of transient nonlinear groundwater flow models using model reduction

Despite increasing computational resources many high?dimensional applications are impractical for model inversions. In this paper, two methods are presented that are promising for high?dimensional model inversion. The methods draw on proper orthogonal decomposition (POD) and yield reduced models that describe a truncated behavior of the original...

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...

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...

Model reduction for dynamic real-time optimization of chemical processes

The value of models in process industries becomes apparent in practice and literature where numerous successful applications are reported. Process models are being used for optimal plant design, simulation studies, for off-line and online process optimization. For online optimization applications the computational load is a limiting factor. The...

Inverse modeling of groundwater flow using model reduction

Numerical groundwater flow models often have a very high number of model cells (greater than a million). Such models are computationally very demanding, which is disadvantageous for inverse modeling. This paper describes a low?dimensional formulation for groundwater flow that reduces the computational burden necessary for inverse modeling. The...