215 research outputs found
Design and Dynamic Analysis of a Novel Subsea Shuttle Tanker
PhD thesis in Offshore technologyUnderwater pipelines, tanker ships, and liquefied gas carriers have traditionally been employed to transport hydrocarbons between offshore oil and gas facilities and onshore locations. However, both methods come with limitations. Underwater pipelines are costly to install and maintain, while the operation of tanker ships and liquefied gas carriers is heavily dependent on weather conditions, rendering them impractical in severe sea states. As an alternative, a pioneering subsea shuttle tanker (SST) system was proposed as an alternative for offshore transportation. The SST was designed to function at a constant speed and depth beneath the ocean surface, specifically designed for transporting liquid carbon dioxide from existing onshore/offshore sites where carbon dioxide is captured or temporarily stored, to subsea wells for reservoir injection. Nonetheless, the potential applications of the SST extend to being a versatile freight carrier, capable of transporting diverse cargoes such as subsea tools, hydrocarbons, chemicals, and even electricity.
This PhD project unfolds in two phases: design and dynamic analysis.
In the design phase, a baseline design for the SST was formulated based on existing literature. This comprehensive design encompasses critical aspects of SST design and operation, including structural design, hydrostatic stability computations, resistance and propulsion estimations, operational scenarios, and offloading methodologies. Challenges inherent to CO2 SST transportation were scrutinised, involving thermodynamic properties, purity considerations, and hydrate formation of CO2 during various vessel-transportation states. These aspects were explored in relation to cargo sizing, material selection, and energy consumption.
The second phase revolves around dynamic analysis, centred on the derived baseline SST. A manoeuvring model for the SST was constructed as a foundation. Hydrodynamic derivatives were calculated using semi-empirical formulas. Subsequently, the SST’s capability to maintain position during the offloading process was evaluated. A linear quadratic regulator was employed to address the SST’s stationkeeping challenge in stochastic currents, ensuring the vessel remains stationary during offloading. The model was further extended to explore the station-keeping under extreme current conditions, utilising probabilistic methods to predict maximum and minimum depth excursions. These predictions offer valuable insights for cost-effective SST design and operational decision-making.
The study then delved into the SST’s recoverability under undesired malfunctions through the establishment of a safety operating envelope (SOE). This envelope considered potential submersible malfunctions, such as partial flooding, jam-to-rise, and jam-to-dive incidents. By identifying feasible speed and depth ranges from an operational safety perspective, the SOE contributes to a reduction in the designed collapse depth, leading to cost savings in materials and enhanced payload capacity.
Furthermore, computational fluid dynamics (CFD) analysis was conducted to predict pressure, skin friction, drag, and lift forces affecting the SST. This included scenarios of the SST’s near-wall voyage and hovering.
Collectively, the original contributions of this thesis encompass the conceptual design, application of control systems and dynamic analysis of the SST. These contributions pave the way for future exploration in the development of commercial submarine concepts and diverse ocean space utlisation strategies
Grenoble Traffic Lab: An experimental platform for advanced traffic monitoring and forecasting
International audienceThis paper describes the main features of the "Grenoble Traffic Lab" (GTL), a new experimental platform for the collection of traffic data coming from a dense network of wireless sensors installed in the south ring of Grenoble, in France. The main challenges related to the configuration of the platform and data validation are discussed, and two relevant traffic monitoring and forecasting applications are presented to illustrate the operation of GTL
Modeling and Estimation of Biological Plants
Estimating the state of a dynamic system is an essential task for achieving important objectives such as process monitoring, identification, and control. Unlike linear systems, no systematic method exists for the design of observers for nonlinear systems. Although many researchers have devoted their attention to these issues for more than 30 years, there are still many open questions. We envisage that estimation plays a crucial role in biology because of the possibility of creating new avenues for biological studies and for the development of diagnostic, management, and treatment tools. To this end, this thesis aims to address two types of nonlinear estimation techniques, namely, the high-gain observer and the moving-horizon estimator with application to three different biological plants.
After recalling basic definitions of stability and observability of dynamical systems and giving a bird's-eye survey of the available state estimation techniques, we are interested in the high-gain observers. These observers may be used when the system dynamics can be expressed in specific a coordinate under the so-called observability canonical form with the possibility to assign the rate of convergence arbitrarily by acting on a single parameter called the high-gain parameter. Despite the evident benefits of this class of observers, their use in real applications is questionable due to some drawbacks: numerical problems, the peaking phenomenon, and high sensitivity to measurement noise. The first part of the thesis aims to enrich the theory of high-gain observers with novel techniques to overcome or attenuate these challenging performance issues that arise when implementing such observers. The validity and applicability of our proposed techniques have been shown firstly on a simple one-gene regulatory network, and secondly on an SI epidemic model.
The second part of the thesis studies the problem of state estimation using the moving horizon approach. The main advantage of MHE is that information
about the system can be explicitly considered in the form of constraints
and hence improve the estimates. In this work, we focus on estimation for nonlinear plants that can be rewritten in the form of quasi-linear parameter-varying systems with bounded unknown parameters. Moving-horizon estimators are proposed to estimate the state of such systems according to two different formulations, i.e., "optimistic" and "pessimistic". In the former case, we perform estimation by minimizing the least-squares moving-horizon cost with respect to both state variables and parameters simultaneously. In the latter, we minimize such a cost with respect to the state variables after picking up the maximum of the parameters. Under suitable assumptions, the stability of the estimation error given by the exponential boundedness is proved in both scenarios.
Finally, the validity of our obtained results has been demonstrated through three different examples from biological and biomedical fields, namely, an example of one gene regulatory network, a two-stage SI epidemic model, and Amnioserosa cell's mechanical behavior during Dorsal closure
An interactive system for the estimation of emissivity of a wafer in a rapid thermal processing chamber
Rapid thermal processing (RTP) is a method of thermally processing wafers for the manufacture of integrated circuits. During the thermal processing of wafers, it is essential that the wafer temperature follow a pre-specified temperature trajectory and that the temperature across the wafer be uniform especially at high temperatures. To ensure that the above objectives of RTP temperature control be met at any time during the process, the estimation of some parameters of the process is of fundamental importance in the design of the control system.
This thesis demonstrates the implementation of an interactive software system in which the emissivity of wafers in a 3-zone RTP station can be estimated on-line. The simulation of the RTP system is performed to ensure the proper performance of the estimator and the closed loop control system. In addition, it is necessary for the control of temperature uniformity of the wafer to implement simulations of the control system and to experiment with new ways to obtain states and parameters estimations.
The implementation of the system is carried out on a Pentium based PC using LabVIIBW and G Math Toolkit with the full advantages of graphical programming or EL The capabilities of LabYIIEW to directly interface with the system using the data acquisition boards provided motivates the utilization of this software system
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Challenges in Optimization with Complex PDE-Systems (hybrid meeting)
The workshop concentrated on various aspects of optimization problems with systems of nonlinear partial differential equations (PDEs) or variational inequalities (VIs) as constraints. In particular, discussions around several keynote presentations in the areas of optimal control of nonlinear or non-smooth systems, optimization problems with functional and discrete or switching variables leading to mixed integer nonlinear PDE constrained optimization, shape and topology optimization, feedback control and stabilization, multi-criteria problems and multiple optimization problems with equilibrium constraints as well as versions of these problems under uncertainty or stochastic influences, and the respectively associated numerical analysis as well as design and analysis of solution algorithms were promoted. Moreover, aspects of optimal control of data-driven PDE constraints (e.g. related to machine learning) were addressed
DATA-DRIVEN SIMULATIONS OF WILDFIRE SPREAD AT REGIONAL SCALES
Current wildfire spread simulators lack the ability to provide accurate prediction of the active flame burning areas at regional scales due to two main challenges: a modeling challenge associated with providing accurate mathematical representations of the multi-physics multi-scale processes that induce the fire dynamics, and a data challenge associated with providing accurate estimates of the initial fire position and the physical parameters that are required by the fire spread models. A promising approach to overcome these limitations is data assimilation: data assimilation aims at integrating available observations into the fire spread simulator, while accounting for their respective uncertainties, in order to infer a more accurate estimate of the fire front position and to produce a more reliable forecast of the wildfire behavior.
The main objective of the present study is to design and evaluate suitable algorithms for regional-scale wildfire spread simulations, which are able to properly handle the variations in wildfire spread due to the significant spatial heterogeneity in the model inputs and to the temporal changes in the wildfire behavior. First we developed a grid-based spatialized parameter estimation approach where the estimation targets are the spatially-varying input model parameters. Then we proposed an efficient and robust method to compute the discrepancy between the observed and simulated fire fronts, which is based on a front shape similarity measure inspired from image processing theory. The new method is demonstrated in the context of Luenberger observer-based state estimation strategy. Finally we developed a dual state-parameter estimation method where we estimate both model state and model parameters simultaneously in order to retrieve more accurate physical values of model parameters and achieve a better forecast performance in terms of fire front positions. All these efforts aim at designing algorithmic solutions to overcome the difficulties associated with spatially-varying environmental conditions and potentially complex fireline shapes and topologies. It paves the way towards real-time monitoring and forecasting of wildfire dynamics at regional scales
State estimators in soft sensing and sensor fusion for sustainable manufacturing
State estimators, including observers and Bayesian filters, are a class of model-based algorithms for estimating variables in a dynamical system given sensor measurements of related system states. They can be used to derive fast and accurate estimates of system variables which cannot be measured directly (’soft sensing’) or for which only noisy, intermittent, delayed, indirect or unreliable measurements are available, perhaps from multiple sources (’sensor fusion’). In this paper we introduce the concepts and main methods of state estimation and review recent applications in improving the sustainability of manufacturing processes. It is shown that state estimation algorithms can play a key role in manufacturing systems to accurately monitor and control processes to improve efficiencies, lower environmental impact, enhance product quality, improve the feasibility of processing more sustainable raw materials, and ensure safer working environments for humans. We discuss current and emerging trends in using state estimation as a framework for combining physical knowledge with other sources of data for monitoring and control of distributed manufacturing systems
Model-based measurement and control of fluidised bed spray granulation processes
Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2012von Andreas Büc
Performance indicators for the dynamics modeling and control of PEMFC systems
Society is gradually becoming aware that the current energy industry, based on the
use of fossil fuels, is inefficient, highly polluting and has a finite supply. Within the
scientific community, there are indications that hydrogen (H2) as an energy vector,
obtained from renewable energy sources, can represent a viable option to mitigate
the problems associated with hydrocarbon combustion. In this context, the change
from the current energy industry to a new structure with a significant involvement of
H2 facilitates the introduction of fuel cells as elements of energy conversion. Polymer
Electrolyte Membrane Fuel Cells (PEMFC) are gaining increased attention as viable
energy conversion devices for a wide range of applications from automotive,
stationary to portable. In order to optimize performance, these systems require active
control and thus in-depth knowledge of the system dynamics which include fluid
mechanics, thermal dynamics and reaction kinetics. One of the main issues, with
respect to proper control of these systems, is the understanding of the water
transport mechanisms through the membrane and the liquid water distribution. The
thesis is based on the publication of nine international journal articles that are divided
into 4 sub-topics: Dynamic fuel cell modeling, fuel cell system control-oriented
analysis, identification of parameters and performance indicators and finally, fault
and failure detection and system diagnosis. In the sub-topic of Dynamic Fuel cell
modeling, experimentally validated Computational Fluid Dynamics (CFD) modeling is
used to relate the effects of the physical phenomena associated with fluid mechanics
and thermal dynamics, that occur inside the fuel cell [Alonso, 2009][Strahl, 2011], to
water distribution. However, since these CFD models cannot be directly used for
control, control-oriented models [Kunusch, 2008][Kunusch, 2011] have been
developed in parallel. As well, another study is done in [Serra, 2006] which includes
a controllability analysis of the system for future development and application of
efficient controllers. The results of the above mentioned studies are limited because
either they do not incorporate an electrochemical model or the model is not experimentally validated. Moreover, these models do not take into account the
voltage losses due to liquid water inside the fuel cell. Therefore, there is a need to
properly relate the relevant effects of fluid mechanics and thermal dynamics,
including liquid water, to the fuel cell voltage. Primarily, methodologies are needed to
determine the relevant indicators associated to the effect of water on the fuel cell
performance. The works published in [Husar, 2008] and [Husar, 2011] treats
experimental parameter identification, mainly focused on water transport through the
membrane and fuel cell voltage loss indicators respectively. The implementation of
the indicators indirect measurement methodology provides an experimental way for
the isolation of three main types of voltage losses in the fuel cell: activation, mass
transport and ohmic losses. Additionally since these voltage loss indicators relate the
fuel cell operating conditions to the fuel cell voltage, they can be utilized to calibrate
and validate CFD models as well as employed in novel control strategies. On the
other hand, to develop reliable systems, the controller should not only take into
account performance variables during standard operation but should also be able to
detect failures and take the appropriate actions. A preliminary study on failure
indicators is presented in [Husar 2007] and fault detection methodologies are
described in [de Lira 2011]. As a whole, the compilation of articles represented in this
thesis applies a comprehensive experimental approach which describes the
implementation of novel methodologies and experimental procedures to characterize
and model the PEMFC and their associated systems taking into consideration
control oriented goals.La societat s'està adonant que la indústria energètica actual, basada en l'ús de
combustibles fòssils, és ineficient, molt contaminant i té un subministrament limitat.
Dins de la comunitat cientÃfica, hi ha indicis que el hidrogen (H2) com vector
energètic, obtingut a partir de fonts d'energia renovables, pot representar una opció
viable per a mitigar els problemes associats amb la combustió d'hidrocarburs. En
aquest context, el canvi de la indústria energètica actual a una nova estructura amb
una important participació de el hidrogen exigeix la introducció de les piles de
combustible com elements de conversió d'energia. Les piles de combustible de
membrana polimèrica (PEMFC) estan tenint cada vegada més atenció com a
dispositius viables de conversió d'energia per a una à mplia gamma d'aplicacions
com automoció, estacionà ries o portà tils. Amb la finalitat d'optimitzar el seu
rendiment, les piles PEM requereixen un control actiu i per tant un coneixement
profund de la dinà mica del sistema, que inclou la mecà nica de fluids, la dinà mica
tèrmica i la cinètica de les reaccions. Un dels temes principals relacionat amb el
control adequat d'aquests sistemes és la comprensió dels mecanismes de transport
d'aigua a través de la membrana i la distribució d'aigua lÃquida. Aquesta tesi es basa
en nou articles publicats en revistes internacionals que es divideixen en 4 subtemes:
la modelització dinà mica de piles de combustible, l'anà lisi orientada al control
del sistema, la identificació de parà metres i d’indicadors de funcionament i,
finalment, la detecció de fallades i la diagnosi dels sistemes. En el sub-tema de la
modelització dinà mica de piles PEM, la modelització basada en la Dinà mica de
Fluids Computacional (CFD) amb validació experimental s'ha utilitzat per a
relacionar els efectes dels fenòmens fÃsics de la mecà nica de fluids i de la dinà mica
tèrmica que es produeixen dintre de la pila [Alonso, 2009] [ Strahl, 2011] amb la
distribució d'aigua. No obstant això, com aquests models CFD no poden ser utilitzats
directament per al control, s'han desenvolupat models orientats a control [Kunusch,
2008] [Kunusch, 2011] en paral·lel. A més, en un altre estudi [Serra, 2006] s'inclou una anà lisi de control·labilitat del sistema per al desenvolupament i aplicació futurs
de controladors eficaços. Però els resultats dels estudis esmentats anteriorment són
limitats, ja sigui perquè no incorporen un model electroquÃmic o bé perquè no han
estat validats experimentalment. A més, cap dels models té en compte les pèrdues
de tensió degudes a l'aigua lÃquida dins de la pila de combustible. Per tant, hi ha una
necessitat de relacionar adequadament els efectes rellevants de la mecà nica de
fluids i de la dinà mica tèrmica, incloent l'aigua lÃquida, amb el voltatge de la pila de
combustible. Principalment, són necessà ries metodologies per a determinar els
indicadors rellevants associats a aquest efecte de l'aigua sobre el rendiment de la
pila de combustible. Els treballs publicats en [Husar, 2008] i [Husar, 2011] tracten la
identificació experimental de parà metres, centrada en el transport d'aigua a través
de la membrana i els indicadors de pèrdua de tensió, respectivament. L'aplicació
d'una proposta de metodologia de mesura indirecte dels indicadors permet
l'aïllament dels tres tipus principals de pèrdues de voltatge en la pila de combustible:
l'activació, el transport de massa i les pèrdues ohmiques. Aquests indicadors de
pèrdua de tensió relacionen les condicions d'operació amb el voltatge de la pila de
combustible i per tant poden ser utilitzats per a calibrar i validar models CFD, aixÃ
com per a definir noves estratègies de control. D'altra banda, per a aconseguir
sistemes fiables, el controlador no només ha de considerar els indicadors de
funcionament de l'operació normal, sinó que també ha de detectar possibles fallades
per a poder prendre les accions adequades en cas de fallada. Un estudi preliminar
sobre indicadors de fallades es presenta en [Husar 2007] i una metodologia de
detecció de fallades completa es descriu en [Lira de 2011]. En el seu conjunt, el
compendi d'articles que formen aquesta tesi segueix un enfocament experimental i
descriu la implementació de noves metodologies i procediments experimentals per a
la caracterització i el modelatge de piles PEM i els sistemes associats amb objectius
orientats al control eficient d'aquests sistemes.La sociedad se ésta dando cuenta de que la industria energética actual, basada en
el uso de combustibles fósiles, es ineficiente, muy contaminante y tiene un
suministro limitado. Dentro de la comunidad cientÃfica, hay indicios de que el
hidrógeno (H2) como vector energético, obtenido a partir de fuentes de energÃa
renovables, puede representar una opción viable para mitigar los problemas
asociados con la combustión de hidrocarburos. En este contexto, el cambio de la
industria energética actual a una nueva estructura con una importante participación
de H2 exige la introducción de pilas de combustible como elementos de conversión
de energÃa. Las pilas de combustible de membrana polimérica (PEMFC) están
ganando cada vez más atención como dispositivos viables de conversión de energÃa
para una amplia gama de aplicaciones como automoción, estacionarias o portátiles.
Con el fin de optimizar su rendimiento, las pilas PEM requieren un control activo y
por lo tanto un conocimiento profundo de la dinámica del sistema, que incluye la
mecánica de fluidos, la dinámica térmica y la cinética de las reacciones. Uno de los
temas principales relacionado con el control adecuado de estos sistemas, es la
comprensión de los mecanismos de transporte de agua a través de la membrana y
la distribución de agua lÃquida. Esta tesis se basa en la publicación de nueve
artÃculos en revistas internacionales que se dividen en 4 sub-temas: el modelado
dinámico de pilas de combustible, el análisis orientado a control del sistema, la
identificación de parámetros e indicadores de desempeño y, por último, la detección
de fallos y la diagnosis. En el sub-tema de la modelización dinámica de pilas PEM,
el modelado basado en Dinámica de Fluidos Computacional (CFD) con validación
experimental se ha utilizado para relacionar los efectos de los fenómenos fÃsicos de
la mecánica de fluidos y la dinámica térmica que se producen dentro de la pila
[Alonso, 2009] [ Strahl, 2011] con la distribución de agua. Sin embargo, como estos modelos CFD no pueden ser utilizados directamente para el control, modelos
orientados a control [Kunusch, 2008] [Kunusch, 2011] se han desarrollado en
paralelo. Además, en otro estudio [Serra, 2006] se incluye un análisis de
controlabilidad del sistema para el futuro desarrollo y aplicación de controladores
eficaces. Pero los resultados de los estudios mencionados anteriormente son
limitados, ya sea porque no incorporan un modelo electroquÃmico o bien porque no
son validados experimentalmente. Además, ninguno de los modelos tiene en cuenta
las pérdidas de tensión debidas al agua lÃquida dentro de la pila de combustible. Por
lo tanto, hay una necesidad de relacionar adecuadamente los efectos relevantes de
la mecánica de fluidos y la dinámica térmica, incluyendo el agua lÃquida, con la
tensión de la pila de combustible. Principalmente, son necesarias metodologÃas para
determinar los indicadores relevantes asociados al efecto del agua sobre el
rendimiento de la pila de combustible. Los trabajos publicados en [Husar, 2008] y
[Husar, 2011] tratan la identificación experimental de parámetros, centrada en el
transporte de agua a través de la membrana y los indicadores de pérdida de tensió,
respectivamente. La aplicación de una metodologÃa propuesta de medición indirecta
de los indicadores permite el aislamiento de los tres tipos principales de pérdidas de
tensión en la pila de combustible: la activación, el transporte de masa y las pérdidas
óhmicas. Éstos indicadores de pérdida de tensión relacionan las condiciones de
operación con la tensión de la pila de combustible y por lo tanto pueden ser
utilizados para calibrar y validar modelos CFD, asà como para definir nuevas
estrategias de control. Por otro lado, para conseguir sistemas fiables, el controlador
no sólo debe considerar los indicadores de desempeño de la operación regular, sino
que también debe detectar posibles fallos para poder tomar las acciones adecuadas
en caso de fallo. Un estudio preliminar sobre indicadores de fallos se presenta en
[Husar 2007] y una metodologÃa de detección de fallos completa se describe en [Lira
de 2011]. En su conjunto, el compendio de artÃculos que forman esta tesis sigue un
enfoque experimental y describe la implementación de nuevas metodologÃas y
procedimientos experimentales para la caracterización y el modelado de pilas PEM
y los sistemas asociados con objetivos orientados al control eficiente de estos
sistemas
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