Robust model-order reduction of complex biological processes

This paper addresses robust model-order reduction of a high dimensional nonlinear partial differential equation (PDE) model of a complex biological process. Based on a nonlinear, distributed parameter model of the same process which was validated against experimental data of an existing, pilot-scale BNR activated sludge plant, we developed a state-space model with 154 state variables in this work. A general algorithm for robustly reducing the nonlinear PDE model is presented and based on an investigation of five state-of-the-art model-order reduction techniques, we are able to reduce the original model to a model with only 30 states without incurring pronounced modelling errors. The Singular perturbation approximation balanced truncating technique is found to give the lowest modelling errors in low frequency ranges and hence is deemed most suitable for controller design and other real-time applications. (C) 2002 Elsevier Science Ltd. All rights reserved.

Bilinear H 2-optimal Model Order-Reduction with applications to thermal parametric systems

Magdeburg, Univ., Fak. für Mathematik, Diss., 2015

Line-fitting method of model order reduction for elastic multibody systems

Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2015

Model Order Reduction for Determining Bubble Parameters to Attain a Desired Fluid Surface Shape

In this paper, a new methodology for predicting fluid free surface shape using Model Order Reduction (MOR) is presented. Proper Orthogonal Decomposition combined with a linear interpolation procedure for its coefficient is applied to a problem involving bubble dynamics near to a free surface. A model is developed to accurately and efficiently capture the variation of the free surface shape with different bubble parameters. In addition, a systematic approach is developed within the MOR framework to find the best initial locations and pressures for a set of bubbles beneath the quiescent free surface such that the resultant free surface attained is close to a desired shape. Predictions of the free surface in two-dimensions and three-dimensions are presented.

State estimation using model order reduction for unstable systems

The problem of state estimation occurs in many applications of fluid flow. For example, to produce a reliable weather forecast it is essential to find the best possible estimate of the true state of the atmosphere. To find this best estimate a nonlinear least squares problem has to be solved subject to dynamical system constraints. Usually this is solved iteratively by an approximate Gauss–Newton method where the underlying discrete linear system is in general unstable. In this paper we propose a new method for deriving low order approximations to the problem based on a recently developed model reduction method for unstable systems. To illustrate the theoretical results, numerical experiments are performed using a two-dimensional Eady model – a simple model of baroclinic instability, which is the dominant mechanism for the growth of storms at mid-latitudes. It is a suitable test model to show the benefit that may be obtained by using model reduction techniques to approximate unstable systems within the state estimation problem.

Model order reduction for parameterized nonlinear evolution equations

Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Dissertation, 2016

Balancing related model order reduction applied to linear controlled evolution equations with Lévy Noise

Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Dissertation, 2016

Incorporation of Hysteretic Effects in Model-Order Reduction Analysis of Magnetic Devices

The ability to predict the properties of magnetic materials in a device is essential to ensuring the correct operation and optimization of the design as well as the device behavior over a wide range of input frequencies. Typically, development and simulation of wide-bandwidth models requires detailed, physics-based simulations that utilize significant computational resources. Balancing the trade-offs between model computational overhead and accuracy can be cumbersome, especially when the nonlinear effects of saturation and hysteresis are included in the model. This study focuses on the development of a system for analyzing magnetic devices in cases where model accuracy and computational intensity must be carefully and easily balanced by the engineer. A method for adjusting model complexity and corresponding level of detail while incorporating the nonlinear effects of hysteresis is presented that builds upon recent work in loss analysis and magnetic equivalent circuit (MEC) modeling. The approach utilizes MEC models in conjunction with linearization and model-order reduction techniques to process magnetic devices based on geometry and core type. The validity of steady-state permeability approximations is also discussed.

Reduced-order modelling, circuit-level design and SOI fabrication of microelectromechanical resonators

This thesis deals with two important research aspects concerning radio frequency (RF) microresonators and switches. First, a new approach for compact modeling and simulation of these devices is presented. Then, a combined process flow for their simultaneous fabrication on a SOI substrate is proposed. Compact models for microresonators and switches are extracted by applying mathematical model order reduction (MOR) to the devices finite element (FE) description in ANSYS c° . The behaviour of these devices includes forms of nonlinearities. However, an approximation in the creation of the FE model is introduced, which enables the use of linear model order reduction. Microresonators are modeled with the introduction of transducer elements, which allow for direct coupling of the electrical and mechanical domain. The coupled system element matrices are linearized around an operating point and reduced. The resulting macromodel is valid for small signal analysis around the bias point, such as harmonic pre-stressed analysis. This is extremely useful for characterizing the frequency response of resonators. Compact modelling of switches preserves the nonlinearity of the device behaviour. Nonlinear reduced order models are obtained by reducing the number of nonlinearities in the system and handling them as input to the system. In this way, the system can be reduced using linear MOR techniques and nonlinearities are introduced directly in the reduced order model. The reduction of the number of system nonlinearities implies the approximation of all distributed forces in the model with lumped forces. Both for microresonators and switches, a procedure for matrices extraction has been developed so that reduced order models include the effects of electrical and mechanical pre-stress. The extraction process is fast and can be done automatically from ANSYS binary files. The method has been applied for the simulation of several devices both at devices and circuit level. Simulation results have been compared with full model simulations, and, when available, experimental data. Reduced order models have proven to conserve the accuracy of finite element method and to give a good description of the overall device behaviour, despite the introduced approximations. In addition, simulation is very fast, both at device and circuit level. A combined process-flow for the integrated fabrication of microresonators and switches has been defined. For this purpose, two processes that are optimized for the independent fabrication of these devices are merged. The major advantage of this process is the possibility to create on-chip circuit blocks that include both microresonators and switches. An application is, for example, aswitched filter bank for wireless transceiver. The process for microresonators fabrication is characterized by the use of silicon on insulator (SOI) wafers and on a deep reactive ion etching (DRIE) step for the creation of the vibrating structures in single-crystal silicon and the use of a sacrificial oxide layer for the definition of resonator to electrode distance. The fabrication of switches is characterized by the use of two different conductive layers for the definition of the actuation electrodes and by the use of a photoresist as a sacrificial layer for the creation of the suspended structure. Both processes have a gold electroplating step, for the creation of the resonators electrodes, transmission lines and suspended structures. The combined process flow is designed such that it conserves the basic properties of the original processes. Neither the performance of the resonators nor the performance of the switches results affected by the simultaneous fabrication. Moreover, common fabrication steps are shared, which allows for cheaper and faster fabrication.

The port-Hamiltonian framework as a comprehensive approach to model and simulate complex systems

This thesis describes modelling tools and methods suited for complex systems (systems that typically are represented by a plurality of models). The basic idea is that all models representing the system should be linked by well-defined model operations in order to build a structured repository of information, a hierarchy of models. The port-Hamiltonian framework is a good candidate to solve this kind of problems as it supports the most important model operations natively. The thesis in particular addresses the problem of integrating distributed parameter systems in a model hierarchy, and shows two possible mechanisms to do that: a finite-element discretization in port-Hamiltonian form, and a structure-preserving model order reduction for discretized models obtainable from commercial finite-element packages.

Real-time simulation of multibody systems with applications for working mobile vehicles

This dissertation describes an approach for developing a real-time simulation for working mobile vehicles based on multibody modeling. The use of multibody modeling allows comprehensive description of the constrained motion of the mechanical systems involved and permits real-time solving of the equations of motion. By carefully selecting the multibody formulation method to be used, it is possible to increase the accuracy of the multibody model while at the same time solving equations of motion in real-time. In this study, a multibody procedure based on semi-recursive and augmented Lagrangian methods for real-time dynamic simulation application is studied in detail. In the semirecursive approach, a velocity transformation matrix is introduced to describe the dependent coordinates into relative (joint) coordinates, which reduces the size of the generalized coordinates. The augmented Lagrangian method is based on usage of global coordinates and, in that method, constraints are accounted using an iterative process. A multibody system can be modelled as either rigid or flexible bodies. When using flexible bodies, the system can be described using a floating frame of reference formulation. In this method, the deformation mode needed can be obtained from the finite element model. As the finite element model typically involves large number of degrees of freedom, reduced number of deformation modes can be obtained by employing model order reduction method such as Guyan reduction, Craig-Bampton method and Krylov subspace as shown in this study The constrained motion of the working mobile vehicles is actuated by the force from the hydraulic actuator. In this study, the hydraulic system is modeled using lumped fluid theory, in which the hydraulic circuit is divided into volumes. In this approach, the pressure wave propagation in the hoses and pipes is neglected. The contact modeling is divided into two stages: contact detection and contact response. Contact detection determines when and where the contact occurs, and contact response provides the force acting at the collision point. The friction between tire and ground is modelled using the LuGre friction model, which describes the frictional force between two surfaces. Typically, the equations of motion are solved in the full matrices format, where the sparsity of the matrices is not considered. Increasing the number of bodies and constraint equations leads to the system matrices becoming large and sparse in structure. To increase the computational efficiency, a technique for solution of sparse matrices is proposed in this dissertation and its implementation demonstrated. To assess the computing efficiency, augmented Lagrangian and semi-recursive methods are implemented employing a sparse matrix technique. From the numerical example, the results show that the proposed approach is applicable and produced appropriate results within the real-time period.

Controladores robustos do tipo LQG/LTR de ordem reduzida para sistemas MIMO com saídas independentes de seus modos não dominantes

O objetivo principal desta dissertação é apresentar uma solução eficiente, prática e de simples implementação para um problema recorrente em projetos de controladores robustos multivariáveis do tipo LQG/LTR: a elevada ordem que estes controladores podem obter dependendo das complicações apresentadas pelo sistema dificultando para que este possa ser controlado de maneira satisfatória. Para que esta meta seja alcançada, é apresentada uma técnica de redução do modelo de sistemas com metodologia bastante descomplicada, dispensando qualquer necessidade de complexas programações para a sua utilização. Esta metodologia porém, é somente aplicável a uma classe bastante específica de sistema. Em suma, o sistema deve possuir variáveis de estado desacopladas do restante do sistema, ou seja, variáveis que não sofram influências de outras e que também não provoquem grande efeito nas saídas do sistema. Foi escolhido um sistema multivariável de sexta ordem, com duas entradas e duas saídas para que a técnica de redução de ordem de modelo seja testada. Este sistema possui as características especiais mencionadas anteriormente bem como exige o projeto de compensador dinâmico e a adição de integradores às suas saídas para que seja controlado adequadamente. Este trabalho pretende apresentar o procedimento de todo o projeto mencionado, desde a obtenção de um modelo de ordem reduzida até a implementação do controlador LQG/LTR. Em seguida, o controlador obtido é testado através de diversas simulações e os resultados encontrados são discutidos para a avaliação da eficácia e da praticidade do método proposto para obtenção de controladores de ordem reduzida.

Nonlinear/electromagnetic co-simulation of microwaves and millimeter-waves links

The Ph.D. thesis describes the simulations of different microwave links from the transmitter to the receiver intermediate-frequency ports, by means of a rigorous circuit-level nonlinear analysis approach coupled with the electromagnetic characterization of the transmitter and receiver front ends. This includes a full electromagnetic computation of the radiated far field which is used to establish the connection between transmitter and receiver. Digitally modulated radio-frequency drive is treated by a modulation-oriented harmonic-balance method based on Krylov-subspace model-order reduction to allow the handling of large-size front ends. Different examples of links have been presented: an End-to-End link simulated by making use of an artificial neural network model; the latter allows a fast computation of the link itself when driven by long sequences of the order of millions of samples. In this way a meaningful evaluation of such link performance aspects as the bit error rate becomes possible at the circuit level. Subsequently, a work focused on the co-simulation an entire link including a realistic simulation of the radio channel has been presented. The channel has been characterized by means of a deterministic approach, such as Ray Tracing technique. Then, a 2x2 multiple-input multiple-output antenna link has been simulated; in this work near-field and far-field coupling between radiating elements, as well as the environment factors, has been rigorously taken into account. Finally, within the scope to simulate an entire ultra-wideband link, the transmitting side of an ultrawideband link has been designed, and an interesting Front-End co-design technique application has been setup.

Comparación de un nuevo método de aceleración de análisis dinámicos con métodos de reducción de modelos

La dinámica estructural estudia la respuesta de una estructura ante cargas o fenómenos variables en el tiempo. En muchos casos, estos fenómenos requieren realizar análisis paramétricos de la estructura considerando una gran cantidad de configuraciones de diseño o modificaciones de la estructura. Estos cambios, ya sean en fases iniciales de diseño o en fases posteriores de rediseño, alteran las propiedades físicas de la estructura y por tanto del modelo empleado para su análisis, cuyo comportamiento dinámico se modifica en consecuencia. Un caso de estudio de este tipo de modificaciones es la supervisión de la integridad estructural, que trata de identificar la presencia de daño estructural y prever el comportamiento de la estructura tras ese daño, como puede ser la variación del comportamiento dinámico de la estructura debida a una delaminación, la aparición o crecimiento de grieta, la debida a la pérdida de pala sufrida por el motor de un avión en vuelo, o la respuesta dinámica de construcciones civiles como puentes o edificios frente a cargas sísmicas. Si a la complejidad de los análisis dinámicos requeridos en el caso de grandes estructuras se añade la variación de determinados parámetros en busca de una respuesta dinámica determinada o para simular la presencia de daños, resulta necesario la búsqueda de medios de simplificación o aceleración del conjunto de análisis que de otra forma parecen inabordables tanto desde el punto de vista del tiempo de computación, como de la capacidad requerida de almacenamiento y manejo de grandes volúmenes de archivos de datos. En la presente tesis doctoral se han revisado los métodos de reducción de elementos .nitos más habituales para análisis dinámicos de grandes estructuras. Se han comparado los resultados de casos de estudio de los métodos más aptos, para el tipo de estructuras y modificaciones descritas, con los resultados de aplicación de un método de reducción reciente. Entre los primeros están el método de condensación estática de Guyan extendido al caso con amortiguamiento no proporcional y posteriores implementaciones de condensaciones dinámicas en diferentes espacios vectoriales. El método de reducción recientemente presentado se denomina en esta tesis DACMAM (Dynamic Analysis in Complex Modal space Acceleration Method), y consiste en el análisis simplificado que proporciona una solución para la respuesta dinámica de una estructura, calculada en el espacio modal complejo y que admite modificaciones estructurales. El método DACMAM permite seleccionar un número reducido de grados de libertad significativos para la dinámica del fenómeno que se quiere estudiar como son los puntos de aplicación de la carga, localizaciones de los cambios estructurales o puntos donde se quiera conocer la respuesta, de forma que al implementar las modificaciones estructurales, se ejecutan los análisis necesarios sólo de dichos grados de libertad sin pérdida de precisión. El método permite considerar alteraciones de masa, rigidez, amortiguamiento y la adición de nuevos grados de libertad. Teniendo en cuenta la dimensión del conjunto de ecuaciones a resolver, la parametrización de los análisis no sólo resulta posible, sino que es también manejable y controlable gracias a la sencilla implementación del procedimiento para los códigos habituales de cálculo mediante elementos .nitos. En el presente trabajo se muestra la bondad y eficiencia del método en comparación con algunos de los métodos de reducción de grandes modelos estructurales, verificando las diferencias entre sí de los resultados obtenidos y respecto a la respuesta real de la estructura, y comprobando los medios empleados en ellos tanto en tiempo de ejecución como en tamaño de ficheros electrónicos. La influencia de los diversos factores que se tienen en cuenta permite identificar los límites y capacidades de aplicación del método y su exhaustiva comparación con los otros procedimientos. ABSTRACT Structural dynamics studies the response of a structure under loads or phenomena which vary over time. In many cases, these phenomena require the use of parametric analyses taking into consideration several design configurations or modifications of the structure. This is a typical need in an engineering o¢ ce, no matter the structural design is in early or final stages. These changes modify the physical properties of the structure, and therefore, the finite element model to analyse it. A case study, that exempli.es this circumstance, is the structural health monitoring to predict the variation of the dynamical behaviour after damage, such as a delaminated structure, a crack onset or growth, an aircraft that suffers a blade loss event or civil structures (buildings or bridges) under seismic loads. Not only large structures require complex analyses to appropriately acquire an accurate solution, but also the variation of certain parameters. There is a need to simplify the analytical process, in order to bring CPU time, data .les, management of solutions to a reasonable size. In the current doctoral thesis, the most common finite element reduction methods for large structures are reviewed. Results of case studies are compared between a recently proposed method, herein named DACMAM (Dynamic Analysis in Complex Modal space Acceleration Method), and different condensation methods, namely static or Guyan condensation and dynamic condensation in different vectorial spaces. All these methods are suitable for considering non-classical damping. The reduction method DACMAM consist of a structural modification in the complex modal domain which provides a dynamic response solution for the reduced models. This process allows the selection of a few degrees of freedom that are relevant for the dynamic response of the system. These d.o.f. are the load application points, relevant structural points or points in which it is important to know the response. Consequently, an analysis with structural modifications implies only the calculation of the dynamic response of the selected degrees of freedom added, but with no loss of information. Therefore, mass, stiffness or damping modifications are easily considered as well as new degrees of freedom. Taking into account the size of the equations to be solved, the parameterization of the dynamic solutions is not only possible, but also manageable and controllable due to the easy implementation of the procedure in the standard finite element solvers. In this thesis, the proposed reduction method for large structural models is compared with other published model order reduction methods. The comparison shows and underlines the efficiency of the new method, and veri.es the differences in the response when compared with the response of the full model. The CPU time, the data files and the scope of the parameterization are also addressed.