G.A.C. Le Roux

Improvements in surrogate models for process synthesis. Application to water network system design

Abstract High accuracy models can be obtained by using different types of surrogate models that accurately approximate equipment phenomenological models and can be used in synthesis problems, leading to faster and more precise solutions. Two types of surrogate models are used to approximate equipment phenomenological models: polynomial and neural network-based. In some cases, these surrogate models are not able to represent more complex equipment. An original methodology to reformulate these models using equations from shortcut equipment design is proposed. A medium-size case study involving fifteen units is presented. The synthesis problem is solved in a short computational time, leading many local solutions. Since several local optima objective function values are very close to each other, the choice of the best configuration among those found should be done qualitatively, because the differences among the objective function values are not significant if compared to the accuracy of equipment cost correlations in the literature.

Performance comparison of parameter estimation techniques for unidentifiable models

Abstract Four different estimation approaches exploiting sensitivities, eigenvalue analysis (rotational discrimination and automatic parameter selection and estimation), reparameterization via differential geometry and the classical nonlinear least squares are assessed in terms of predictivity, robustness and speed. A Monte Carlo methodology is adopted to evaluate the statistical information required to quantify the inherent uncertainty of each approach. The results show that the rotational discrimination method presents the best characteristics among the evaluated methods, since it requires less a priori information than the reparameterization via differential geometry, uses simpler stop criteria than the automatic selection, reduces the overfitting caused by the nonlinear least squares solution and because it estimates parameters with the best predictivity among the methods tested. Additionally, results suggest that assessing the goodness of the estimated parameters solely in the calibration set can be misleading, and that the statistical information obtained from a validation set is more valuable.

Cooperative Weblab: A Tool for Cooperative Learning in Chemical Engineering in a Global Environment

Abstract Weblabs are defined as a set of web-based physical laboratories that allows remote access and control in real time. Since the last decade, Weblabs are being more and more employed in many educational institutions around the world. In Sao Paulo state (Brazil) a “Cluster of Weblabs in Chemical and Biochemical Process Engineering” was implemented. This project has received a grant from FAPESP (State of Sao Paulo Research Agency). The experimental setups are physically placed in laboratories in Sao Paulo, Sao Carlos, Ribeirao Preto and Campinas, that are up to 250 km apart. This paper presents the implementation of two Cooperative Weblab (CW) experiments. The main concept behind the CW is to develop a set of experiments for undergraduate students that should be performed by “mixed teams” located in different institutions at the same time. Collaboration is achieved by gathering participants into working groups that are asked to simultaneously solve a technical problem, for which a weblab experiment is available. This procedure emulates challenges that will frequently take place in their future professional lives. Each group is supervised by a local instructor. Video conference software is used along the experiments (the institutions are connected through a high speed network, named KyaTera). All long the experiments, the students are encouraged to interact, exchange information and opinions on the phenomena that take place during the experimental practice. At the end of the session, the data collected are shared by the students and they produce a unique report for both groups. The use of this approach fosters interest in students. It is clear that the CW offer real benefits to chemical engineering education. It is now necessary to spread the dimension of the cluster and to increase the interaction with groups from other countries.

Dynamics of reactive distillation for the production of ethyl acetate: experiments at a pilot plant and modelling

Abstract In order to understand the complex behaviour of the reactive distillation process and to be able to provide an accurate design of a reactive column, detailed analyses on both continuous and transient regime become necessary. The objective is the definition of a reliable simulation model, based on experimental data obtained from a real pilot-scale plant device for the heterogeneously catalysed esterification of acetic acid and ethanol to form ethyl acetate and water. The choice of the parameters for the continuous equilibrium model was discussed and the simulation results provided good agreement with experimental data, revealing an interesting sensitivity of the catalyst activity to the feed composition. Once column configuration and operational parameters were validated, dynamic experiments were realized so as to interpret the sensitivity of different disturbances. Feed flow rates, reflux ratio and heat duty were perturbed and the consequent open loop transient responses were identified. The assessment of hydrodynamic parameters and the validation of the transient data allow the definition of a reliable dynamic model that represents tendencies and behaviours of the process well. The resulting model is to be applied into a more complex controllability methodology.

Mathematical Modeling for SBO Applications

Modeling and simulation are recognized as extremely valuable tools for developing new materials by increasing efficiently the knowledge on systems. The mathematical tools and methods necessary to build a wide range of models are presented here. Two case studies illustrate the different mathematical approaches introduced: the SDZ photodegradation in SBO and the adsorption in SBO-magnetite particles.

Monte Carlo Assessment of the Arrival Cost Evaluation Method in Moving Horizon Estimation for Chemical Processes

Abstract In this work is to compare the performance of online estimators through a Monte Carlo study. The online estimators compared are the Extended Kalman Filter (EKF), the Unscented Kalman Filter (UKF), and the moving horizon estimator (MHE) with arrival cost estimated by EKF and UKF. These filters were applied to two different systems: a benchmark batch fermentation reactor simulation and an experimental calorimetric reactor. It is shown that the MHE has a better performance in terms of bias, standard deviation and because it did not present any divergence in all the simulations performed.