Diseño y desarrollo de un modelo booleano probabilístico de regulación genética en el simulador de colonias bacterianas GRO

Resulta interesante comprender como microorganismos sencillos como la bacteria Escherichia coli poseen mecanismos no tan simples para responder al entorno en el que está gestionada por complicadas redes de regulación formadas por genes y proteínas, donde cada elemento de la red genética debe tomar parte en armonía, en el momento justo y la cantidad adecuada para dar lugar a la respuesta celular apropiada. La biología sintética es un nuevo área de la biología y la tecnología que fusiona la biolog ía molecular, la ingeniería genética y las herramientas computacionales, para crear sistemas biológicos con funcionalidades novedosas. Los sistemas creados sintéticamente son ya una realidad, y cada vez se acumulan más trabajos alrededor del mundo que muestran su factibilidad. En este campo no solo se hacen pequeñas modificaciones en la información genética, sino que también se diseñan, manipulan e introducen circuitos genéticos a los organismos. Actualmente, se hace un gran esfuerzo para construir circuitos genéticos formados por numerosos genes y caracterizar la interacción de los mismos con otras moléculas, su regulaci ón, expresión y funcionalidad en diferentes organismos. La mayoría de los proyectos de biología sintética que se han desarrollado hasta ahora, se basan en el conocimiento actual del funcionamiento de los organismos vivos. Sin embargo, la información es numerosa y creciente, por lo que se requiere de herramientas computacionales y matem áticas para integrar y hacer manejable esta gran cantidad de información. El simulador de colonias bacterianas GRO posee la capacidad de representar las dinámicas más simples del comportamiento celular, tales como crecimiento, división y comunicación intercelular mediante conjugación, pero carece de la capacidad de simular el comportamiento de la colonia en presencia de un circuito genético. Para ello, se ha creado un nuevo módulo de regulación genética que maneja las interaciones entre genes y proteínas de cada célula ejecutando respuestas celulares específicas. Dado que en la mayoría de los experimentos intervienen colonias del orden de 105 individuos, es necesario un módulo de regulación genética simplificado que permita representar de la forma más precisa posible este proceso en colonias de tales magnitudes. El módulo genético integrado en GRO se basa en una red booleana, en la que un gen puede transitar entre dos estados, on (expresado) o off (reprimido), y cuya transición viene dada por una serie de reglas lógicas.---ABSTRACT---It is interesting to understand how simple organisms such as Escherichia coli do not have simple mechanisms to respond to the environment in which they find themselves. This response is managed by complicated regulatory networks formed by genes and proteins, where each element of the genetic network should take part in harmony, at the right time and with the right amount to give rise to the appropriate cellular response. Synthetic biology is a new area of biology and technology that combines molecular biology, genetic engineering and computational tools to create biological systems with novel features. The synthetically created systems are already a reality, and increasingly accumulate work around the world showing their feasibility. In this field not only minor changes are made in the genetic information but also genetic circuits designed, manipulated and introduced into the organisms. Currently, it takes great effort to build genetic circuits formed by numerous genes and characterize their interaction with other molecules, their regulation, their expression and their function in different organisms. Most synthetic biology projects that have been developed so far are based on the current knowledge of the functioning of living organisms. However, there is a lot of information and it keeps accumulating, so it requires computational and mathematical tools to integrate and manage this wealth of information. The bacterial colonies simulator, GRO, has the ability to represent the simplest dynamics of cell behavior, such as growth, division and intercellular communication by conjugation, but lacks the ability to simulate the behavior of the colony in the presence of a genetic circuit. To this end, a new genetic regulation module that handles interactions between genes and proteins for each cell running specific cellular responses has been created. Since most experiments involve colonies of about 105 individuals, a simplified genetic module which represent cell dynamics as accurately and simply as possible is needed. The integrated genetic GRO module is based on a Boolean network, in which a gene can be in either of two states, on (expressed) or off (repressed), and whose transition is given by a set of logical rules.

Computational Schemes for Optimizing Domains of Attraction in Dynamical Systems

In this paper, several computational schemes are presented for the optimal tuning of the global behavior of nonlinear dynamical sys- tems. Specifically, the maximization of the size of domains of attraction associated with invariants in parametrized dynamical sys- tems is addressed. Cell Mapping (CM) tech- niques are used to estimate the size of the domains, and such size is then maximized via different optimization tools. First, a ge- netic algorithm is tested whose performance shows to be good for determining global maxima at the expense of high computa- tional cost. Secondly, an iterative scheme based on a Stochastic Approximation proce- dure (the Kiefer-Wolfowitz algorithm) is eval- uated showing acceptable performance at low cost. Finally, several schemes combining neu- ral network based estimations and optimiza- tion procedures are addressed with promising results. The performance of the methods is illus- trated with two applications: first on the well-known van der Pol equation with stan- dard parametrization, and second the tuning of a controller for saturated systems.

Analysis of internal helically finned tubes for parabolic trough design by CFD tools

This paper has analysed the effect of the utilization of internal finned tubes for the design of parabolic trough collectors with computational fluid dynamics tools. Our numerical approach has been qualified with the computational estimation of reported experimental data regarding phenomena involved in finned tube applications and solar irradiation of parabolic trough collector. The application of finned tubes to the design of parabolic trough collectors must take into account features as the pressure losses, thermal losses and thermo-mechanical stress and thermal fatigue. Our analysis shows an improvement potential in parabolic trough solar plants efficiency by the application of internal finned tubes.

The PiLLoW/Ciao library for INTERNET/WWW programming using computational logic systems

We discuss from a practical point of view a number of issues involved in writing Internet and WWW applications using LP/CLP systems. We describe PiLLoW, an Internet and WWW programming library for LP/CLP systems which we argüe significantly simplifies the process of writing such applications. PiLLoW provides facilities for generating HTML structured documents, producing HTML forms, writing form handlers, accessing and parsing WWW documents, and accessing code posted at HTTP addresses. We also describe the architecture of some application classes, using a high-level model of client-server interaction, active modules. Finally we describe an architecture for automatic LP/CLP code downloading for local execution, using generic browsers. The PiLLoW library has been developed in the context of the &-Prolog and CIAO systems, but it has been adapted to a number of popular LP/CLP systems, supporting most of its functionality.

Lagrangian tools and the assessment of the predictive capacity of geophysical data sets

We examine, with recently developed Lagrangian tools, altimeter data and numerical simulations obtained from the HYCOM model in the Gulf of Mexico. Our data correspond to the months just after the Deepwater Horizon oil spill in the year 2010. Our Lagrangian analysis provides a skeleton that allows the interpretation of transport routes over the ocean surface. The transport routes are further verified by the simultaneous study of the evolution of several drifters launched during those months in the Gulf of Mexico. We find that there exist Lagrangian structures that justify the dynamics of the drifters, although the agreement depends on the quality of the data. We discuss the impact of the Lagrangian tools on the assessment of the predictive capacity of these data sets.

Development of Shape-Optimization Tools for the Aerodynamic Design of Turbomachinery Blades

The aim of this work is to develop an automated tool for the optimization of turbomachinery blades founded on an evolutionary strategy. This optimization scheme will serve to deal with supersonic blades cascades for application to Organic Rankine Cycle (ORC) turbines. The blade geometry is defined using parameterization techniques based on B-Splines curves, that allow to have a local control of the shape. The location in space of the control points of the B-Spline curve define the design variables of the optimization problem. In the present work, the performance of the blade shape is assessed by means of fully-turbulent flow simulations performed with a CFD package, in which a look-up table method is applied to ensure an accurate thermodynamic treatment. The solver is set along with the optimization tool to determine the optimal shape of the blade. As only blade-to-blade effects are of interest in this study, quasi-3D calculations are performed, and a single-objective evolutionary strategy is applied to the optimization. As a result, a non-intrusive tool, with no need for gradients definition, is developed. The computational cost is reduced by the use of surrogate models. A Gaussian interpolation scheme (Kriging model) is applied for the estimated n-dimensional function, and a surrogate-based local optimization strategy is proved to yield an accurate way for optimization. In particular, the present optimization scheme has been applied to the re-design of a supersonic stator cascade of an axial-flow turbine. In this design exercise very strong shock waves are generated in the rear blade suction side and shock-boundary layer interaction mechanisms occur. A significant efficiency improvement as a consequence of a more uniform flow at the blade outlet section of the stator is achieved. This is also expected to provide beneficial effects on the design of a subsequent downstream rotor. The method provides an improvement to gradient-based methods and an optimized blade geometry is easily achieved using the genetic algorithm.

Non uniform embedding based on relevance analysis with reduced computational complexity: application to the detection of pathologies from biosignal recordings

Nonlinear analysis tools for studying and characterizing the dynamics of physiological signals have gained popularity, mainly because tracking sudden alterations of the inherent complexity of biological processes might be an indicator of altered physiological states. Typically, in order to perform an analysis with such tools, the physiological variables that describe the biological process under study are used to reconstruct the underlying dynamics of the biological processes. For that goal, a procedure called time-delay or uniform embedding is usually employed. Nonetheless, there is evidence of its inability for dealing with non-stationary signals, as those recorded from many physiological processes. To handle with such a drawback, this paper evaluates the utility of non-conventional time series reconstruction procedures based on non uniform embedding, applying them to automatic pattern recognition tasks. The paper compares a state of the art non uniform approach with a novel scheme which fuses embedding and feature selection at once, searching for better reconstructions of the dynamics of the system. Moreover, results are also compared with two classic uniform embedding techniques. Thus, the goal is comparing uniform and non uniform reconstruction techniques, including the one proposed in this work, for pattern recognition in biomedical signal processing tasks. Once the state space is reconstructed, the scheme followed characterizes with three classic nonlinear dynamic features (Largest Lyapunov Exponent, Correlation Dimension and Recurrence Period Density Entropy), while classification is carried out by means of a simple k-nn classifier. In order to test its generalization capabilities, the approach was tested with three different physiological databases (Speech Pathologies, Epilepsy and Heart Murmurs). In terms of the accuracy obtained to automatically detect the presence of pathologies, and for the three types of biosignals analyzed, the non uniform techniques used in this work lightly outperformed the results obtained using the uniform methods, suggesting their usefulness to characterize non-stationary biomedical signals in pattern recognition applications. On the other hand, in view of the results obtained and its low computational load, the proposed technique suggests its applicability for the applications under study.

Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems

Emotion is generally argued to be an influence on the behavior of life systems, largely concerning flexibility and adaptivity. The way in which life systems acts in response to a particular situations of the environment, has revealed the decisive and crucial importance of this feature in the success of behaviors. And this source of inspiration has influenced the way of thinking artificial systems. During the last decades, artificial systems have undergone such an evolution that each day more are integrated in our daily life. They have become greater in complexity, and the subsequent effects are related to an increased demand of systems that ensure resilience, robustness, availability, security or safety among others. All of them questions that raise quite a fundamental challenges in control design. This thesis has been developed under the framework of the Autonomous System project, a.k.a the ASys-Project. Short-term objectives of immediate application are focused on to design improved systems, and the approaching of intelligence in control strategies. Besides this, long-term objectives underlying ASys-Project concentrate on high order capabilities such as cognition, awareness and autonomy. This thesis is placed within the general fields of Engineery and Emotion science, and provides a theoretical foundation for engineering and designing computational emotion for artificial systems. The starting question that has grounded this thesis aims the problem of emotion--based autonomy. And how to feedback systems with valuable meaning has conformed the general objective. Both the starting question and the general objective, have underlaid the study of emotion, the influence on systems behavior, the key foundations that justify this feature in life systems, how emotion is integrated within the normal operation, and how this entire problem of emotion can be explained in artificial systems. By assuming essential differences concerning structure, purpose and operation between life and artificial systems, the essential motivation has been the exploration of what emotion solves in nature to afterwards analyze analogies for man--made systems. This work provides a reference model in which a collection of entities, relationships, models, functions and informational artifacts, are all interacting to provide the system with non-explicit knowledge under the form of emotion-like relevances. This solution aims to provide a reference model under which to design solutions for emotional operation, but related to the real needs of artificial systems. The proposal consists of a multi-purpose architecture that implement two broad modules in order to attend: (a) the range of processes related to the environment affectation, and (b) the range or processes related to the emotion perception-like and the higher levels of reasoning. This has required an intense and critical analysis beyond the state of the art around the most relevant theories of emotion and technical systems, in order to obtain the required support for those foundations that sustain each model. The problem has been interpreted and is described on the basis of AGSys, an agent assumed with the minimum rationality as to provide the capability to perform emotional assessment. AGSys is a conceptualization of a Model-based Cognitive agent that embodies an inner agent ESys, the responsible of performing the emotional operation inside of AGSys. The solution consists of multiple computational modules working federated, and aimed at conforming a mutual feedback loop between AGSys and ESys. Throughout this solution, the environment and the effects that might influence over the system are described as different problems. While AGSys operates as a common system within the external environment, ESys is designed to operate within a conceptualized inner environment. And this inner environment is built on the basis of those relevances that might occur inside of AGSys in the interaction with the external environment. This allows for a high-quality separate reasoning concerning mission goals defined in AGSys, and emotional goals defined in ESys. This way, it is provided a possible path for high-level reasoning under the influence of goals congruence. High-level reasoning model uses knowledge about emotional goals stability, letting this way new directions in which mission goals might be assessed under the situational state of this stability. This high-level reasoning is grounded by the work of MEP, a model of emotion perception that is thought as an analogy of a well-known theory in emotion science. The work of this model is described under the operation of a recursive-like process labeled as R-Loop, together with a system of emotional goals that are assumed as individual agents. This way, AGSys integrates knowledge that concerns the relation between a perceived object, and the effect which this perception induces on the situational state of the emotional goals. This knowledge enables a high-order system of information that provides the sustain for a high-level reasoning. The extent to which this reasoning might be approached is just delineated and assumed as future work. This thesis has been studied beyond a long range of fields of knowledge. This knowledge can be structured into two main objectives: (a) the fields of psychology, cognitive science, neurology and biological sciences in order to obtain understanding concerning the problem of the emotional phenomena, and (b) a large amount of computer science branches such as Autonomic Computing (AC), Self-adaptive software, Self-X systems, Model Integrated Computing (MIC) or the paradigm of models@runtime among others, in order to obtain knowledge about tools for designing each part of the solution. The final approach has been mainly performed on the basis of the entire acquired knowledge, and described under the fields of Artificial Intelligence, Model-Based Systems (MBS), and additional mathematical formalizations to provide punctual understanding in those cases that it has been required. This approach describes a reference model to feedback systems with valuable meaning, allowing for reasoning with regard to (a) the relationship between the environment and the relevance of the effects on the system, and (b) dynamical evaluations concerning the inner situational state of the system as a result of those effects. And this reasoning provides a framework of distinguishable states of AGSys derived from its own circumstances, that can be assumed as artificial emotion.

Conservation of Computational Scientific Execution Environments for Workflow-based Experiments Using Ontologies

La reproducibilidad de estudios y resultados científicos es una meta a tener en cuenta por cualquier científico a la hora de publicar el producto de una investigación. El auge de la ciencia computacional, como una forma de llevar a cabo estudios empíricos haciendo uso de modelos matemáticos y simulaciones, ha derivado en una serie de nuevos retos con respecto a la reproducibilidad de dichos experimentos. La adopción de los flujos de trabajo como método para especificar el procedimiento científico de estos experimentos, así como las iniciativas orientadas a la conservación de los datos experimentales desarrolladas en las últimas décadas, han solucionado parcialmente este problema. Sin embargo, para afrontarlo de forma completa, la conservación y reproducibilidad del equipamiento computacional asociado a los flujos de trabajo científicos deben ser tenidas en cuenta. La amplia gama de recursos hardware y software necesarios para ejecutar un flujo de trabajo científico hace que sea necesario aportar una descripción completa detallando que recursos son necesarios y como estos deben de ser configurados. En esta tesis abordamos la reproducibilidad de los entornos de ejecución para flujos de trabajo científicos, mediante su documentación usando un modelo formal que puede ser usado para obtener un entorno equivalente. Para ello, se ha propuesto un conjunto de modelos para representar y relacionar los conceptos relevantes de dichos entornos, así como un conjunto de herramientas que hacen uso de dichos módulos para generar una descripción de la infraestructura, y un algoritmo capaz de generar una nueva especificación de entorno de ejecución a partir de dicha descripción, la cual puede ser usada para recrearlo usando técnicas de virtualización. Estas contribuciones han sido aplicadas a un conjunto representativo de experimentos científicos pertenecientes a diferentes dominios de la ciencia, exponiendo cada uno de ellos diferentes requisitos hardware y software. Los resultados obtenidos muestran la viabilidad de propuesta desarrollada, reproduciendo de forma satisfactoria los experimentos estudiados en diferentes entornos de virtualización. ABSTRACT Reproducibility of scientific studies and results is a goal that every scientist must pursuit when announcing research outcomes. The rise of computational science, as a way of conducting empirical studies by using mathematical models and simulations, have opened a new range of challenges in this context. The adoption of workflows as a way of detailing the scientific procedure of these experiments, along with the experimental data conservation initiatives that have been undertaken during last decades, have partially eased this problem. However, in order to fully address it, the conservation and reproducibility of the computational equipment related to them must be also considered. The wide range of software and hardware resources required to execute a scientific workflow implies that a comprehensive description detailing what those resources are and how they are arranged is necessary. In this thesis we address the issue of reproducibility of execution environments for scientific workflows, by documenting them in a formalized way, which can be later used to obtain and equivalent one. In order to do so, we propose a set of semantic models for representing and relating the relevant information of those environments, as well as a set of tools that uses these models for generating a description of the infrastructure, and an algorithmic process that consumes these descriptions for deriving a new execution environment specification, which can be enacted into a new equivalent one using virtualization solutions. We apply these three contributions to a set of representative scientific experiments, belonging to different scientific domains, and exposing different software and hardware requirements. The obtained results prove the feasibility of the proposed approach, by successfully reproducing the target experiments under different virtualization environments.

Computational and Experimental Modelling of Mooring Lines Dynamics for Offshore Floating Wind Turbines

El cálculo de cargas de aerogeneradores flotantes requiere herramientas de simulación en el dominio del tiempo que consideren todos los fenómenos que afectan al sistema, como la aerodinámica, la dinámica estructural, la hidrodinámica, las estrategias de control y la dinámica de las líneas de fondeo. Todos estos efectos están acoplados entre sí y se influyen mutuamente. Las herramientas integradas se utilizan para calcular las cargas extremas y de fatiga que son empleadas para dimensionar estructuralmente los diferentes componentes del aerogenerador. Por esta razón, un cálculo preciso de las cargas influye de manera importante en la optimización de los componentes y en el coste final del aerogenerador flotante. En particular, el sistema de fondeo tiene gran impacto en la dinámica global del sistema. Muchos códigos integrados para la simulación de aerogeneradores flotantes utilizan modelos simplificados que no consideran los efectos dinámicos de las líneas de fondeo. Una simulación precisa de las líneas de fondeo dentro de los modelos integrados puede resultar fundamental para obtener resultados fiables de la dinámica del sistema y de los niveles de cargas en los diferentes componentes. Sin embargo, el impacto que incluir la dinámica de los fondeos tiene en la simulación integrada y en las cargas todavía no ha sido cuantificada rigurosamente. El objetivo principal de esta investigación es el desarrollo de un modelo dinámico para la simulación de líneas de fondeo con precisión, validarlo con medidas en un tanque de ensayos e integrarlo en un código de simulación para aerogeneradores flotantes. Finalmente, esta herramienta, experimentalmente validada, es utilizada para cuantificar el impacto que un modelos dinámicos de líneas de fondeo tienen en la computación de las cargas de fatiga y extremas de aerogeneradores flotantes en comparación con un modelo cuasi-estático. Esta es una información muy útil para los futuros diseñadores a la hora de decidir qué modelo de líneas de fondeo es el adecuado, dependiendo del tipo de plataforma y de los resultados esperados. El código dinámico de líneas de fondeo desarrollado en esta investigación se basa en el método de los Elementos Finitos, utilizando en concreto un modelo ”Lumped Mass” para aumentar su eficiencia de computación. Los experimentos realizados para la validación del código se realizaron en el tanque del École Céntrale de Nantes (ECN), en Francia, y consistieron en sumergir una cadena con uno de sus extremos anclados en el fondo del tanque y excitar el extremo suspendido con movimientos armónicos de diferentes periodos. El código demostró su capacidad para predecir la tensión y los movimientos en diferentes posiciones a lo largo de la longitud de la línea con gran precisión. Los resultados indicaron la importancia de capturar la dinámica de las líneas de fondeo para la predicción de la tensión especialmente en movimientos de alta frecuencia. Finalmente, el código se utilizó en una exhaustiva evaluación del efecto que la dinámica de las líneas de fondeo tiene sobre las cargas extremas y de fatiga de diferentes conceptos de aerogeneradores flotantes. Las cargas se calcularon para tres tipologías de aerogenerador flotante (semisumergible, ”spar-buoy” y ”tension leg platform”) y se compararon con las cargas obtenidas utilizando un modelo cuasi-estático de líneas de fondeo. Se lanzaron y postprocesaron más de 20.000 casos de carga definidos por la norma IEC 61400-3 siguiendo todos los requerimientos que una entidad certificadora requeriría a un diseñador industrial de aerogeneradores flotantes. Los resultados mostraron que el impacto de la dinámica de las líneas de fondeo, tanto en las cargas de fatiga como en las extremas, se incrementa conforme se consideran elementos situados más cerca de la plataforma: las cargas en la pala y en el eje sólo son ligeramente modificadas por la dinámica de las líneas, las cargas en la base de la torre pueden cambiar significativamente dependiendo del tipo de plataforma y, finalmente, la tensión en las líneas de fondeo depende fuertemente de la dinámica de las líneas, tanto en fatiga como en extremas, en todos los conceptos de plataforma que se han evaluado. ABSTRACT The load calculation of floating offshore wind turbine requires time-domain simulation tools taking into account all the phenomena that affect the system such as aerodynamics, structural dynamics, hydrodynamics, control actions and the mooring lines dynamics. These effects present couplings and are mutually influenced. The results provided by integrated simulation tools are used to compute the fatigue and ultimate loads needed for the structural design of the different components of the wind turbine. For this reason, their accuracy has an important influence on the optimization of the components and the final cost of the floating wind turbine. In particular, the mooring system greatly affects the global dynamics of the floater. Many integrated codes for the simulation of floating wind turbines use simplified approaches that do not consider the mooring line dynamics. An accurate simulation of the mooring system within the integrated codes can be fundamental to obtain reliable results of the system dynamics and the loads. The impact of taking into account the mooring line dynamics in the integrated simulation still has not been thoroughly quantified. The main objective of this research consists on the development of an accurate dynamic model for the simulation of mooring lines, validate it against wave tank tests and then integrate it in a simulation code for floating wind turbines. This experimentally validated tool is finally used to quantify the impact that dynamic mooring models have on the computation of fatigue and ultimate loads of floating wind turbines in comparison with quasi-static tools. This information will be very useful for future designers to decide which mooring model is adequate depending on the platform type and the expected results. The dynamic mooring lines code developed in this research is based in the Finite Element Method and is oriented to the achievement of a computationally efficient code, selecting a Lumped Mass approach. The experimental tests performed for the validation of the code were carried out at the `Ecole Centrale de Nantes (ECN) wave tank in France, consisting of a chain submerged into a water basin, anchored at the bottom of the basin, where the suspension point of the chain was excited with harmonic motions of different periods. The code showed its ability to predict the tension and the motions at several positions along the length of the line with high accuracy. The results demonstrated the importance of capturing the evolution of the mooring dynamics for the prediction of the line tension, especially for the high frequency motions. Finally, the code was used for an extensive assessment of the effect of mooring dynamics on the computation of fatigue and ultimate loads for different floating wind turbines. The loads were computed for three platforms topologies (semisubmersible, spar-buoy and tension leg platform) and compared with the loads provided using a quasi-static mooring model. More than 20,000 load cases were launched and postprocessed following the IEC 61400-3 guideline and fulfilling the conditions that a certification entity would require to an offshore wind turbine designer. The results showed that the impact of mooring dynamics in both fatigue and ultimate loads increases as elements located closer to the platform are evaluated; the blade and the shaft loads are only slightly modified by the mooring dynamics in all the platform designs, the tower base loads can be significantly affected depending on the platform concept and the mooring lines tension strongly depends on the lines dynamics both in fatigue and extreme loads in all the platform concepts evaluated.

Low cost 3D global instability analysis and flow sensitivity based on dynamic mode decomposition and high-order numerical tools

We explore the recently developed snapshot-based dynamic mode decomposition (DMD) technique, a matrix-free Arnoldi type method, to predict 3D linear global flow instabilities. We apply the DMD technique to flows confined in an L-shaped cavity and compare the resulting modes to their counterparts issued from classic, matrix forming, linear instability analysis (i.e. BiGlobal approach) and direct numerical simulations. Results show that the DMD technique, which uses snapshots generated by a 3D non-linear incompressible discontinuous Galerkin Navier?Stokes solver, provides very similar results to classical linear instability analysis techniques. In addition, we compare DMD results issued from non-linear and linearised Navier?Stokes solvers, showing that linearisation is not necessary (i.e. base flow not required) to obtain linear modes, as long as the analysis is restricted to the exponential growth regime, that is, flow regime governed by the linearised Navier?Stokes equations, and showing the potential of this type of analysis based on snapshots to general purpose CFD codes, without need of modifications. Finally, this work shows that the DMD technique can provide three-dimensional direct and adjoint modes through snapshots provided by the linearised and adjoint linearised Navier?Stokes equations advanced in time. Subsequently, these modes are used to provide structural sensitivity maps and sensitivity to base flow modification information for 3D flows and complex geometries, at an affordable computational cost. The information provided by the sensitivity study is used to modify the L-shaped geometry and control the most unstable 3D mode.