Large-scale processes that are modeled using differential algebraic equations based on mass and energy balance calculations at times require excessive computation time to simulate. Depending on the complexity of the model, these simulations may require many iterations to converge and in some cases they may not converge at all. Application of a storage and retrieval technique, named in situ adaptive tabulation or ISAT is proposed for faster convergence of process simulation models. Comparison with neural networks is performed, and better performance using ISAT for extrapolation is shown. In particular, the requirement of real-time dynamic simulation is discussed for operating training simulators (OTS). Integration of ISAT to a process simulator (CHEMCAD®) using the input-output data only is shown. A regression technique based on partial least squares (PLS) is suggested to approximate the sensitivity without accessing the first-principles model. Different record distribution strategies to build an ISAT database are proposed and better performance using the suggested techniques is shown for different case studies. A modified ISAT algorithm (mISAT) is described to improve the retrieval rate, and its performance is compared with the original approach in a case study. State estimation is a key requirement of many process control and monitoring strategies. Different nonlinear state estimation techniques studied in the past are discussed with their relative advantages/disadvantages. A robust state estimation technique like moving horizon estimation (MHE) has a trade-off between accuracy of state estimates and the computational cost. Implementation of MHE based ISAT is shown for faster state estimation, with an accuracy same as that of MHE. Flowsheet optimization aims to optimize an objective or cost function by changing various independent process variables, subject to design and model constraints. Depending on the nonlinearity of the process units, an optimization routine can make a number of calls for flowsheet (simulation) convergence, thereby making the computation time prohibitive. Storage and retrieval of the simulation trajectories can speed-up process optimization, which is shown using a CHEMCAD® flowsheet. Online integration of an ISAT database to solve the simulation problem along with an outer-loop consisting of the optimization routine is shown using the sequential-modular approach. / text

[pt] O desenvolvimento de modelos computacionais para simulação de escoamentos reativos operando em regime de turbulencia requer a soluçao das equações diferenciais parciais que representam os balanços de massa, quantidade de movimento linear, espécies químicas e energia. Além disso, as reações químicas do modelo necessitam de um mecanismo cinético detalhado para descrição dos fenomenos físico-químicos associados. Um dos maiores desafios encontrados é a rigidez da simulação numérica desses modelos e a natureza não linear do termo de produção das espécies químicas. Esta dissertação apresenta uma revisão das principais técnicas disponíveis na literatura para o desenvolvimento de modelos reduzidos de cinética química, em particular para a combustão, bem como de técnicas para solução eficiente dos modelos de escoamentos reativos. Após uma apresentação da formulação matemática associada, a metodologia denominada tabulação adaptativa in situ (ISAT) é implementada e avaliada quanto a sua acurácia, eficiencia e uso de memória na simulação de alguns modelos de reator homogeneo agitado. Avalia-se a combustão de misturas de monóxido de carbono/oxigenio e metano/ar cujos mecanismos cinéticos tem 4 e 53 espécies, 3 and 325 reações respectivamente. Os resultados destassimulações indicam que a presente implementação da técnica ISAT tem erro relativo global inferior a 1%. Além disso, a técnica ISAT propiciou ganhos, em termos de tempo computacional, de at´e 80% quando comparado a simulação direta da cinética detalhada. Entretanto, em termos de utilização da memória, a implementação desenvolvida da técnica ISAT se mostrou excessivamente exigente. / [en] The development of computational models for the numerical simulation of chemically reacting flows operating in the turbulent regime requires the solution of partial differential equations that represent the balance of mass, linear momentum, chemical species and energy. Moreover, the chemical reactions of the model may require a detailed reaction mechanism for the description of the physicochemical phenomena involved. One of the biggest challenges is the stiffness of the numerical simulation of these models and the nonlinear nature of species rate of reaction. This dissertation presents an overview of the main techniques available in the literature for the development of reduced models of chemical kinetics, particularly for the combustion, as well as the techniques for efficient computation of the chemically reacting flows models. After a presentation of the associated mathematical formulation, the methodology dubbed in situ adaptive tabulation (ISAT) is implemented and its accuracy, efficiency and memory usage are evaluated in the simulation of homogeneous stirred reactor models. The combustion of carbon monoxide with oxygen and methane with air mixtures is considered, which detailed reaction mechanisms involve 4 and 53 species, 3 and 325 reactions respectively. The results of these simulations indicate that the development implementation of the ISAT technique has a absolute global error of less than 1%. Moreover, the ISAT technique provided gains, in terms of computational time, of up to 80% when compared to the direct integration of the full chemical kinetics. However, in terms of memory usage the present implementation of ISAT technique was found to be excessively demanding.