Katarzyna Bizon

ANN-based Virtual Sensor for On-line Prediction of In-cylinder Pressure in a Diesel Engine

Abstract This study presents the process design and tune-up of robust artificial neural networks (ANN) to be used as virtual sensors for the diagnosis of a three-cylinder Diesel engine operating at various conditions. Particularly, a feed-forward neural network based on radial basis functions (RBF) is employed. The use of different radial basis functions, and their relevant parameters, is investigated in detail, with their effect on the network accuracy. The RBF network is validated using data not included in training, showing good correspondence between measured and reconstructed pressure signal. The accuracy of the predicted pressure signals is analyzed in terms of mean square error and in terms of a number of pressure-derived parameters. Results are promising in terms of performance and accuracy, both for the predicted pressure signals and for the pressure-derived engine parameters that can be used in a closed loop engine control system.

Fractal structure of iterative time profiles of a tubular chemical reactor with recycle

The scope of the paper is the theoretical analysis of the time rate in which a chemical reactor reaches a stable stationary state or stable temperature and concentration oscillations of the fluid flux. The method used for the analysis is based on the so-called iterative time profiles, demonstrating a chaotic and fractal nature of some of the profiles. The results were presented in the form of two and three-dimensional graphs.

Numerical assessment of accurate measurements of laminar flame speed

In combustion, the laminar flame speed constitutes an important parameter that reflects the chemistry of oxidation for a given fuel, along with its transport and thermal properties. Laminar flame speeds are used (i) in turbulent models used in CFD codes, and (ii) to validate detailed or reduced mechanisms, often derived from studies using ideal reactors and in diluted conditions as in jet stirred reactors and in shock tubes. End-users of such mechanisms need to have an assessment of their capability to predict the correct heat released by combustion in realistic conditions. In this view, the laminar flame speed constitutes a very convenient parameter, and it is then very important to have a good knowledge of the experimental errors involved with its determination. Stationary configurations (Bunsen burners, counter-flow flames, heat flux burners) or moving flames (tubes, spherical vessel, soap bubble) can be used. The spherical expanding flame configuration has recently become popular, since it can be used...

Spectral reduction on empirically derived orthogonal basis of the dynamical model of a Circulating Fluidized Bed Combustor

Abstract Spectral reduction of the 1-D distributed dynamic model of a circulating fluidized bed combustor (CFBC) in isothermal operation is presented. The continuum model is first approximated by a finite–difference method to provide a “reference” solution. Then, Proper Orthogonal Decomposition (POD) with Galerkin projection is introduced to derive a reduced order model (ROM). The POD modes are then tested in the low-order approximation of the system evolution. POD–based models prove to be effective, being able to reproduce steady–state with as little as four basis functions and computing speed-up in the order of 104.

Assessment of a POD method for the dynamical analysis of a catalyst pellet with simultaneous chemical reaction, adsorption and diffusion: Uniform temperature case

Abstract A model reduction method applied to the dynamic model of a single isothermal catalyst pellet with simultaneous chemical reaction, diffusion and adsorption is presented. The model of the pellet accounts for both internal and external resistances to mass transfer, and variable bulk gas concentration. The reduction of the model was performed by means of proper orthogonal decomposition (POD). Accuracy and computational efficiency of the reduced order model (ROM) were discussed for two kinetic models, i.e. a first order chemical kinetics and a Langmuir–Hinshelwood kinetics. To improve the computational efficiency of the model described by the Langmuir–Hinshelwood equation, the non-linear terms were approximated by a discrete empirical interpolation method (DEIM). High accuracy and efficiency of the proposed reduction approach was demonstrated.

POD reduced order dynamical model of non-isothermal Circulating Fluidized Bed Combustor

Abstract This paper presents the spectral reduction of the 1-D distributed dynamic model of a non-isothermal Circulating Fluidized Bed Combustor (CFBC). The continuum model is first approximated by a finite-difference method and integrated in time by means of Adams-Moulton method to provide a “reference” solution. Then, Proper Orthogonal Decomposition (POD) is introduced, coupled with a spectral penalty method, to derive a reduced order model (ROM). The penalty method deals with the variable boundary conditions which characterize the original model. The numerical performance of the proposed approach is evaluated.