This research focuses on developing a comprehensive framework for designing and modeling experiments in the presence of multiple sources of competing prior knowledge. In particular, methodology is proposed for process optimization in high-cost, low-resource experimental settings where the underlying response function can be highly non-linear. In the first part of this research, an initial experimental design criteria is proposed for optimization problems by combining multiple, potentially competing, sources of prior information--engineering models, expert opinion, and data from past experimentation on similar, non-identical systems. New methodology is provided for incorporating and combining conjectured models and data into both the initial modeling and design stages. The second part of this research focuses on the development of a batch sequential design procedure for optimizing high-cost, low-resource experiments with complicated response surfaces. The success in the proposed approach lies in melding a flexible, sequential design algorithm with a powerful local modeling approach. Batch experiments are designed sequentially to adapt to balance space-filling properties and the search for the optimal operating condition. Local model calibration and averaging techniques are introduced to easily allow incorporation of statistical models and engineering knowledge, even if such knowledge pertains to only subregions of the complete design space. The overall process iterates between adapting designs, adapting models, and updating engineering knowledge over time. Applications to nanomanufacturing are provided throughout.

Les réseaux de distribution d’eau consistent en de grandes infrastructures réparties dans l’espace qui assurent la distribution d’eau potable en quantité et en qualité suffisantes. Les modèles mathématiques de ces systèmes sont caractérisés par un grand nombre de variables d’état et de paramètres dont la plupart sont incertains. Les temps de calcul peuvent s’avérer conséquents pour les réseaux de taille importante et la propagation d’incertitude par des méthodes de Monte Carlo. Par conséquent, les deux principaux objectifs de cette thèse sont l’étude des techniques de modélisation à ordre réduit par projection ainsi que la propagation spectrale des incertitudes des paramètres. La thèse donne tout d’abord un aperçu des méthodes mathématiques utilisées. Ensuite, les équations permanentes des réseaux hydrauliques sont présentées et une nouvelle méthode de calcul des sensibilités est dérivée sur la base de la méthode adjointe. Les objectifs spécifiques du développement de modèles d’ordre réduit sont l’application de méthodes basées sur la projection, le développement de stratégies d’échantillonnage adaptatives plus efficaces et l’utilisation de méthodes d’hyper-réduction pour l’évaluation rapide des termes résiduels non linéaires. Pour la propagation des incertitudes, des méthodes spectrales sont introduites dans le modèle hydraulique et un modèle hydraulique intrusif est formulé. Dans le but d’une analyse plus efficace des incertitudes des paramètres, la propagation spectrale est ensuite évaluée sur la base du modèle réduit. Les résultats montrent que les modèles d’ordre réduit basés sur des projections offrent un avantage considérable par rapport à l’effort de calcul. Bien que l’utilisation de l’échantillonnage adaptatif permette une utilisation plus efficace des états système pré-calculés, l’utilisation de méthodes d’hyper-réduction n’a pas permis d’améliorer la charge de calcul. La propagation des incertitudes des paramètres sur la base des méthodes spectrales est comparable aux simulations de Monte Carlo en termes de précision, tout en réduisant considérablement l’effort de calcul. / Water distribution systems are large, spatially distributed infrastructures that ensure the distribution of potable water of sufficient quantity and quality. Mathematical models of these systems are characterized by a large number of state variables and parameter. Two major challenges are given by the time constraints for the solution and the uncertain character of the model parameters. The main objectives of this thesis are thus the investigation of projection based reduced order modelling techniques for the time efficient solution of the hydraulic system as well as the spectral propagation of parameter uncertainties for the improved quantification of uncertainties. The thesis gives an overview of the mathematical methods that are being used. This is followed by the definition and discussion of the hydraulic network model, for which a new method for the derivation of the sensitivities is presented based on the adjoint method. The specific objectives for the development of reduced order models are the application of projection based methods, the development of more efficient adaptive sampling strategies and the use of hyper-reduction methods for the fast evaluation of non-linear residual terms. For the propagation of uncertainties spectral methods are introduced to the hydraulic model and an intrusive hydraulic model is formulated. With the objective of a more efficient analysis of the parameter uncertainties, the spectral propagation is then evaluated on the basis of the reduced model. The results show that projection based reduced order models give a considerable benefit with respect to the computational effort. While the use of adaptive sampling resulted in a more efficient use of pre-calculated system states, the use of hyper-reduction methods could not improve the computational burden and has to be explored further. The propagation of the parameter uncertainties on the basis of the spectral methods is shown to be comparable to Monte Carlo simulations in accuracy, while significantly reducing the computational effort.

Orientadores: Rubens Maciel Filho, Liliane Maria Ferrareso Lona / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica / Made available in DSpace on 2018-08-04T02:31:19Z (GMT). No. of bitstreams: 1 MendozaMarin_FlorentinoLazaro_D.pdf: 8929110 bytes, checksum: 9041b9e7f02f9a324fa10cde9a962f54 (MD5) Previous issue date: 2004 / Resumo: O modelo determinístico e processo homopolimerização na emulsão do estireno são aplicados em reator tubular contínuo sem e com deflectores angulares internos sob condição isotérmica e não isotérmica. Os resultados de modelagem e simulação foram realizados a estado estacionário, modelo unidimensional, coordenada cilíndrica, fluxo pistão laminar completamente desenvolvido, modelo Smith-Ewart para estimar a conversão do monômero, cinética química de Arrhenius corno modelo de velocidade finita laminar para computar a geração química. O objetivo é modelar, simular e analisar o comportamento do reator de homopolimerização na emulsão do estireno com deflectores angulares inclinados internos, e comparar com reator tubular. Os métodos experimental e matemático-dedutivo foram aplicados para obter resultados, por meio de programação computacional, usando Dinâmica de Fluido Computacional através do método de volumes finitos. As seguintes variáveis como temperatura de reação constante e variável, reator tubular sem e com deflectores, temperatura de alimentação, diâmetro de reator, processo adiabático e exotérmico, calor de reação constante e velocidade axial completamente desenvolvida foram investigados. Os efeitos de conversão de monômero, área transversal interna, temperatura axial, concentração do polímero, radicais e iniciador, outros corno densidade de polímero e monômero, perda de carga e queda de pressão foram determinados e simulados. Os produtos foram caracterizados com Número de Partículas (nucleação homogênea e heterogênea), distribuição de peso molecular, tamanho de partículas de polímero e distribuição de viscosidade. Estes resultados foram validados com resultados da literatura sob condição igualou aproximada. Os resultados sob condições não isotérmicas foram melhores que os resultados isotérmicos em termos de caracterização do polímero. Isso mostra que o desenho alternativo proposto (com deflectores) permite obter o polímero com propriedades melhores em termos de número de partículas, distribuição de peso molecular, distribuição do tamanho de partículas e viscosidade / Abstract: Deterministic model and emulsion homopolymerization process of styrene are applied in continuous tubular reactor without and with internal angular baffles under isothermic and no isothermic conditions. The modeling and simulation results were approximate to steady state, one-dimensional model, cylindrical coordinate, fully developed laminar plug flow, Smith-Ewart model to estimate the monomer conversion, Arrhenius chemical kinetics as laminar finite-rate model to compute chemical source. The objective is to model, simulate and to analyze the emulsion homopolymerization reactor performance of styrene with internal-inc1ined angular baffles, and to compare with continuous tubular reactor. The experimental and mathematical-deductive methods were applied to obtain results, by means of computational programming, using Computational Fluid Dynamics (program code), finite volume method. The following variables such as constant and variable reaction temperature, tubular reactor without and with baffles, feed temperature, reactor diameter, adiabatic and exothermic process, constant reaction heat and fully developed axial velocity were investigated. The monomer conversion, internal transversal are a, axial temperature, concentration of polymer, radicals and initiator, others as density of polymer and monomer, head loss and pressure drop effects were determined and simulated. The products were characterized by partic1es number (homogeneous and heterogeneous nuc1eation), molecular weight distribution, polymer partic1es size and polymer viscosity distribution. These results were validated with literature results under same or approximate condition. The results under no isothermic conditions were better than isothermic results in terms of polymer characterization. It is shown that the proposed alternative design (with baffles) allow to obtain the polymer with better properties in terms of number of partic1es, molecular weight distribution, particle size distribution and viscosity / Doutorado / Desenvolvimento de Processos Químicos / Mestre em Engenharia Química

Adaptation enables a reaction to a changing environment. For traditional software development, that means changing the design and implementation of the software in a potentially complex and expensive process. If requirements are not known until the runtime of a software system, this system must be able to cope with changes during its runtime. For this, self-adaptive systems (SAS) were created. They have internal knowledge about themselves and their environment to reason about changes and take appropriate actions. Many approaches aiming to build such systems have been published since the start of the research area at the beginning of the 21st century. However, it is difficult to find an appropriate approach, even when all requirements of a scenario the system should be built for are known. If no suitable approach can be found, software developers have to built a new system leading to high development costs and potentially inefficient solutions due to the complexity of the system. This thesis follows two goals: (1) To make approaches building SAS more comparable through a feature model describing features of SAS, and (2) to provide a novel way of specifying SAS concisely using reference attribute grammars (RAGs) providing efficient systems. RAGs originate from the research field of compiler construction and enable the concise description of parts of the internal knowledge mentioned above as well as of the computation of the actions to cope with recognised changes. To make RAGs fully usable, this thesis presents two extensions: Relational RAGs enable the efficient handling of relations required for knowledge graphs, and Connected RAGs let RAG-based system communicate with other external systems to both recognise changes and execute actions. To evaluate the novel approaches, a classification of 30 approaches for the feature model and several case studies in the areas smart home, robotics, and system orchestration were conducted. It can be shown, that significantly less code is required to specify SAS. To specify the computation, 14.5 % to 28.7 % less code was required, whereas in another case study only 6.3 % of the total code was manually written and the rest was generated. The efficiency is similar to the best comparable approaches for graph queries. Furthermore, using additional optimizations (incremental evaluation), the execution time can be shown to be faster by a factor of 167.88 less albeit being sometimes by 50.0 % slower for very small workloads and specific queries. In a more realistic, extrapolated experiment, using incremental evaluation creates speed-up factors between 6.63 and 44.93. With the contributions in this thesis, existing approaches can be selected more precisely, new approaches can classify themselves within the research area, and the development of self-adaptive systems is possible using RAG-based systems.