Francesc Giralt

Neural virtual sensor for the inferential prediction of product quality from process variables

A predictive Fuzzy ARTMAP neural system and two hybrid networks, each combining a dynamic unsupervised classifier with a different kind of supervised mechanism, were applied to develop virtual sensor systems capable of inferring the properties of manufactured products from real process variables. A new method to construct dynamically the unsupervised layer was developed. A sensitivity analysis was carried out by means of self-organizing maps to select the most relevant process features and to reduce the number of input variables into the model. The prediction of the melt index (MI) or quality of six different LDPE grades produced in a tubular reactor was taken as a case study. The MI inferred from the most relevant process variables measured at the beginning of the process cycle deviated 5% from on-line MI values for single grade neural sensors and 7% for composite neural models valid for all grades simultaneously.

Self-Organizing Map Analysis of Toxicity-Related Cell Signaling Pathways for Metal and Metal Oxide Nanoparticles

The response of a murine macrophage cell line exposed to a library of seven metal and metal oxide nanoparticles was evaluated via High Throughput Screening (HTS) assay employing luciferase-reporters for ten independent toxicity-related signaling pathways. Similarities of toxicity response among the nanoparticles were identified via Self-Organizing Map (SOM) analysis. This analysis, applied to the HTS data, quantified the significance of the signaling pathway responses (SPRs) of the cell population exposed to nanomaterials relative to a population of untreated cells, using the Strictly Standardized Mean Difference (SSMD). Given the high dimensionality of the data and relatively small data set, the validity of the SOM clusters was established via a consensus clustering technique. Analysis of the SPR signatures revealed two cluster groups corresponding to (i) sublethal pro-inflammatory responses to Al2O3, Au, Ag, SiO2 nanoparticles possibly related to ROS generation, and (ii) lethal genotoxic responses due to exposure to ZnO and Pt nanoparticles at a concentration range of 25-100 μg/mL at 12 h exposure. In addition to identifying and visualizing clusters and quantifying similarity measures, the SOM approach can aid in developing predictive quantitative-structure relations; however, this would require significantly larger data sets generated from combinatorial libraries of engineered nanoparticles.

Vortex shedding from a spinning cylinder

An experimental investigation of a two‐dimensional turbulent wake behind a spinning cylinder at Re=9000 is carried out to determine the influence of the rotation on the initial development of the flow. Spectral analysis of the velocity data measured in the near wake shows that for peripheral velocities up to the value of the free‐stream velocity, a distinct Karman vortex activity exists within the wake, whereas for greater peripheral velocities, the Karman activity deteriorates and disappears for values in excess of twice the free‐stream velocity.

Influence of the geometry on the structure of the flow between a pair of corotating disks

Constant-property laminar flow in the space between two coaxial disks corotating in a fixed cylindrical enclosure is investigated numerically over the Reynolds number range 0⩽Re⩽82 380 for interdisk spacing to disk radius aspect ratios in the range 0.05⩽S⩽0.20. Most of the 3D calculations correspond to regions in the (Re, S) map slightly above the 2D–3D transition, where the 2D (axisymmetric) steady flow can bifurcate into two different families of unsteady 3D flow; (a) at sufficiently large values of S or Re, into a flow that is asymmetric with respect to the interdisk midplane; (b) at intermediate values of S and Re, into a flow that displays shift-and-reflect symmetry with respect to the interdisk midplane. Qualitative and quantitative comparisons with previous experimental and numerical results are established. The structure of the 3D flow is analyzed as well as the jumps in wave frequency when it experiences a change in its circumferential wave length. It is shown that each family of 3D flows is char...

Three-dimensional large-eddy motions and fine-scale activity in a plane turbulent wake

A pattern recognition technique has been applied to simultaneously sampled multipoint hot-wire anemometry data obtained in the far wake of a circular cylinder. Data from both the streamwise fluctuating velocity field and the temperature field have been analysed employing a computer code that uses a correlation approach to automatically detect and ensemble average flow patterns and patterns for mean-square fluctuations

Organized motions in a jet in crossflow

An experimental study to identify the structures present in a jet in crossflow has been carried out at a jet-to-crossflow velocity ratio U / U cf = 3.8 and Reynolds number Re = U cf D / v = 6600. The hot-wire velocity data measured with a rake of eight X -wires at x / D = 5 and 15 and flow visualizations using planar laser-induced fluorescence (PLIF) confirm that the well-established pair of counter-rotating vortices is a feature of the mean field and that the upright, tornado-like or Frics vortices that are shed to the leeward side of the jet are connected to the jet flow at the core. The counter-rotating vortex pair is strongly modulated by a coherent velocity field that, in fact, is as important as the mean velocity field. Three different structures – folded vortex rings, horseshoe vortices and handle-type structures – contribute to this coherent field. The new handle-like structures identified in the current study link the boundary layer vorticity with the counter-rotating vortex pair through the upright tornado-like vortices. They are responsible for the modulation and meandering of the counter-rotating vortex pair observed both in video recordings of visualizations and in the instantaneous velocity field. These results corroborate that the genesis of the dominant counter-rotating vortex pair strongly depends on the high pressure gradients that develop in the region near the jet exit, both inside and outside the nozzle.

Flow transitions in laminar Rayleigh–Bénard convection in a cubical cavity at moderate Rayleigh numbers

Abstract A three-dimensional numerical study of the natural convection in a cubical cavity heated from below is reported at moderate Rayleigh numbers for three Prandtl numbers Pr = 0.71, 10 and 130. The six walls are considered rigid and immobile, with isothermal horizontal plates and adiabatic lateral walls. The Boussinesq approximation for the variation of physical properties is assumed. Seven different structures, four single roll-type, two four roll-type and a toroidal roll, and several flow transitions have been identified in the steady and laminar regime for Ra ⩽ 6×104 and Pr ⩽ 130. Both, the dynamic and heat transfer characteristics of these seven structures are discussed. The effects of slightly changing the aspect ratio or tilting the cavity on the stability of the different structures are also analyzed. There is general agreement between the predicted average Nusselt number and available correlations for Rayleigh–Benard convection in rectangular enclosures and between two horizontal plates.

A Fuzzy ARTMAP Based on Quantitative Structure-Property Relationships (QSPRs) for Predicting Aqueous Solubility of Organic Compounds

Quantitative structure-property relationships (QSPRs) for estimating aqueous solubility of organic compounds at 25 degrees C were developed based on a fuzzy ARTMAP and a back-propagation neural networks using a heterogeneous set of 515 organic compounds. A set of molecular descriptors, developed from PM3 semiempirical MO-theory and topological descriptors (first-, second-, third-, and fourth-order molecular connectivity indices), were used as input parameters to the neural networks. Quantum chemical input descriptors included average polarizability, dipole moment, resonance energy, exchange energy, electron-nuclear attraction energy, and nuclear-nuclear (core-core) repulsion energy. The fuzzy ARTMAP/QSPR correlated aqueous solubility (S, mol/L) for a range of -11.62 to 4.31 logS with average absolute errors of 0.02 and 0.14 logS units for the overall and validation data sets, respectively. The optimal 11-13-1 back-propagation/QSPR model was less accurate, for the same solubility range, and exhibited larger average absolute errors of 0.29 and 0.28 logS units for the overall and validation sets, respectively. The fuzzy ARTMAP-based QSPR approach was shown to be superior to other back-propagation and multiple linear regression/QSPR models for aqueous solubility of organic compounds.

Natural convection in a cubical cavity heated from below at low rayleigh numbers

Abstract Natural convection in a cubical cavity heated from below is examined by means of the three-dimensional computation of the time dependent Navier-Stokes and energy transport equations in the range of Rayleigh numbers 3500 ⩽Ra ⩽ 10 000. The Boussinesq approximation has been used to model buoyancy effects on momentum transfer. Four different stable convective structures occur with orientation and flow circulation dictated by the combined effect of the four adiabatic confining lateral walls. Three of these structures are typical single rolls with their axis of rotation or vorticity horizontal and either parallel to two opposite vertical walls, structures S1 and S3, or orientated towards two opposite vertical edges (S2). The fourth structure (S4) is a nearly toroidal roll with the descending motion aligned with the four vertical edges and the single ascending current along the vertical axis of the enclosure. The effect of the Rayleigh number and the type of flow structure on heat transfer rates at the top and bottom plates is also reported. For the single roll-type structures the surface averaged Nusselt number increases with a power of the Rayleigh number that changes within the range studied from 0.7 to 0.4. A similar trend is observed for the toroidal roll but in this case heat transfer rates are 65% lower. The distribution of local heat transfer coefficients at the top and bottom surfaces agrees with the topology of the flow patterns portrayed with the aid of the second invariant of the velocity gradient and the modulus of the cross product of the corresponding velocity and vorticity fields.

Neural Network Based Quantitative Structural Property Relations (QSPRs) for Predicting Boiling Points of Aliphatic Hydrocarbons

Quantitative structural property relations (QSPRs) for boiling points of aliphatic hydrocarbons were derived using a back-propagation neural network and a modified Fuzzy ARTMAP architecture. With the back-propagation model, the selected molecular descriptors were capable of distinguishing between diastereomers. The QSPRs were obtained from four valance molecular connectivity indices (1chiv,2chiv,3chiv,4chiv), a second-order Kappa shape index (2kappa), dipole moment, and molecular weight. The inclusion of dipole moment proved to be particularly useful for distinguishing between cis and trans isomers. A back-propagation 7-4-1 architecture predicted boiling points for the test, validation, and overall data sets of alkanes with average absolute errors of 0.37% (1.65 K), 0.42% (1.73 K), and 0.37% (1.54 K), respectively. The error for the test and overall data sets decreased to 0.19% (0.81 K) and 0.31% (1.30 K), respectively, using the modified Fuzzy ARTMAP network. A back-propagation alkene model, with a 7-10-1 architecture, yielded predictions with average absolute errors for the test, validation, and overall data sets of 1.96% (6.79 K), 1.83% (6.45 K), and 1.25% (4.42 K), respectively. Fuzzy ARTMAP reduced the errors for the test and overall data sets to 0.19% (0.73 K) and 0.25% (0.95 K), respectively. The back-propagation composite model for aliphatic hydrocarbons, with a 7-9- architecture, yielded boiling points with average absolute errors for the test, validation, and overall set of 1.74% (6.09 K), 1.25% (4.68 K), and 1.37% (4.85 K), respectively. The error for the test and overall data sets using the Fuzzy ARTMAP composite model decreased to 0.84% (1.15 K) and 0.35% (1.35 K), respectively. Performance of the QSPRs, developed from a simple set of molecular descriptors, displayed accuracy well within the range of expected experimental errors and of better accuracy than other regression analysis and neural network-based boiling points QSPRs previously reported in the literature.