**Are you an EPFL student looking for a semester project?**

Work with us on data science and visualisation projects, and deploy your project as an app on top of GraphSearch.

Person# Diogo Filipe Mateus Rodrigues

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related units

Loading

Courses taught by this person

Loading

Related research domains

Loading

Related publications

Loading

People doing similar research

Loading

Related units (5)

Courses taught by this person

No results

Related research domains (28)

Chemical reaction

A chemical reaction is a process that leads to the chemical transformation of one set of chemical substances to another. Classically, chemical reactions encompass changes that only involve the posit

Heat transfer

Heat transfer is a discipline of thermal engineering that concerns the generation, use, conversion, and exchange of thermal energy (heat) between physical systems. Heat transfer is classified into v

Mathematical optimization

Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternative

People doing similar research (126)

Related publications (21)

Loading

Loading

Loading

Dominique Bonvin, Diogo Filipe Mateus Rodrigues

For the investigation of complex reaction systems, it has been proposed to decouple the various rate processes using a linear time-invariant transformation that is constructed from knowledge of stoichiometry, reaction enthalpies, inlet compositions and temperatures, and initial conditions, that is, without any kinetic information. The resulting transformed system is expressed in terms of vessel extents. The transformation uses a heat balance that is written in terms of reaction enthalpies evaluated at some reference temperature. This paper revisits the transformation to vessel extents using an enthalpy balance instead of the heat balance. In this transformation, the reaction enthalpies are not used explicitly. However, it is shown that, provided a not very restrictive assumption holds, the enthalpy balance equation is equivalent to the heat balance equation written with constant reaction enthalpies at some reference temperature. The two transformations to vessel extents are compared, first formally and then numerically via a simulated CSTR example. (C) 2019 Elsevier Ltd. All rights reserved.

Dominique Bonvin, Diogo Filipe Mateus Rodrigues

This paper discusses the use of parsimonious input parameterization for the dynamic optimization of reaction systems. This parameterization is able to represent the optimal inputs with only a few parameters. In the context of batch, semibatch, and continuous reactors, the method takes advantage of the concept of extents to allow the analytical computation of adjoint-free optimal control laws. It is shown that this computation can be performed in a systematic way for all types of arcs in the solution, thereby resulting in a finite set of plausible arc sequences. For each arc sequence, the optimal values of the input parameters are computed via numerical optimization. The results are illustrated via simulated examples of reaction systems.

Julien Léo Billeter, Dominique Bonvin, Diogo Filipe Mateus Rodrigues

For lumped homogeneous reaction systems, this paper presents a kinetic model identification scheme that provides maximum-likelihood parameter estimates and guarantees convergence to global optimality. The use of the extent-based incremental approach allows one to (i) identify each reaction individually, and (ii) reduce the number of parameters to be identified via optimization to the ones that appear non-linearly in the investigated rate law. The approach results in maximum-likelihood parameter estimation if the experimental extents are uncorrelated and the rate estimates used to compute the modeled extents are unbiased. Furthermore, the identification problem can be rearranged via Taylor series expansion as a polynomial optimization problem. This optimization problem is then reformulated as a convex optimization problem that can be solved efficiently to global optimality. Different aspects of the approach are demonstrated via simulated examples. (C) 2018 Elsevier Ltd. All rights reserved.