Use of an artificial neural network algorithm to predict hydrate dissociation conditions for hydrogen+water and hydrogen+tetra-n-butyl ammonium bromide+water systems

In this communication, a feed-forward artificial neural network algorithm is developed to estimate the hydrate dissociation conditions for the hydrogen+water and hydrogen+tetra-n-butyl ammonium bromide+water systems. To develop this algorithm, the experimental data reported in the literature for hydrate dissociation conditions of the latter two systems with different concentrations of tetra-n-butyl ammonium bromide in aqueous phase below its stoichiometric concentration (i.e., ≈0.037 mole fraction or 0.43 mass fraction) have been used. Independent experimental data (not used in training and developing this algorithm) have been employed to examine the reliability of this method. It is shown that the predicted and the experimental data are in acceptable agreement demonstrating the reliability of this algorithm as a predictive tool.     

Axial impeller selection for anchorage dependent animal cell culture in stirred bioreactors: Methodology based on the impeller comparison at just-suspended speed of rotation

Animal cells, which are nowadays essential for the industrial production of proteinic compounds, are commonly cultivated inside stirred tank bioreactors. In case of anchorage dependent cells, they are usually fixed on microcarriers. The choice of agitation conditions (impeller type, rotational speed…) in this type of process is not an easy task as it has to fulfil three potentially conflicting goals: (1) maintaining microcarriers in complete suspension, (2) homogenizing the culture medium, and (3) limiting mechanical constraints generated by the hydrodynamics on the cells. The aim of this study is to present an original methodology to select the most appropriate axial impeller for this specific application. Seven propellers are preselected on basis of their characteristics available in the literature. Instead of comparing impellers at a given rotational speed or a given power input, they are compared at their respective minimum impeller rotational speed that leads to a complete microcarrier suspension, i.e. at their respective just-suspended speed N_js. They are then compared at higher rotational speeds N, expressed as multiples of N_js. The impeller classification is based on the intensity of mechanical constraints they produced, evaluated from: (1) the macro-shear rate quantified by the spatial derivative of time average velocity fields measured by P.I.V., (2) the micro-shear rate characterized by the ratio between the microcarrier diameter to the average Kolmogorov scale computed from power input measurements, and (3) the impact of microcarrier collisions on cells described via the turbulent collision severity index also computed from power input measurements. Results show that the 125 mm diameter TTP impeller (Mixel) and the 150 mm diameter Elephant Ear impeller (Applikon) produce the smallest mechanical constraints at their just-suspended speed (50 and 20 rpm, respectively). Moreover, the mechanical constraints they produce increase more slowly with the N/N_js ratio than the mechanical constraints produced by other impellers. These propellers are thus even more advantageous if rotational speeds higher than the just-suspended speed have to be used.     

Modeling of Moisture Behavior of Wood Planks in Nonvented Flat Roofs

A computer model was extended and adapted to simulate the hygrothermal behavior of building envelope-wood components. The model was used to predict moisture movement in wood planks forming the decks of nonvented flat roofs insulated with cellulose. The gradient of water potential was considered as the driving force for moisture movement in wood. The model required the determination of convective heat- and mass-transfer coefficients, the sorption curves, the effective water conductivity for different wood species, and the hygrothermal conditions within the assembly to characterize the mass-conservation equation. Once these parameters were integrated in the computer model, this approach was then validated by carrying a simulation of the drying process of wood planks using experimental data from a large-scale test.     

Which persistent organic pollutants can we map in soil using a large spacing systematic soil monitoring design? A case study in Northern France

Persistent organic pollutants (POPs) impact upon human and animal health and the wider environment. It is important to determine where POPs are found and the spatial pattern of POP variation. The concentrations of 90 molecules which are members of four families of POPs and two families of herbicides were measured within a region of Northern France as part of the French National Soil Monitoring Network (RMQS: Réseau de Mesures de la Qualité des Sols). We also gather information on five covariates (elevation, soil organic carbon content, road density, land cover and population density) which might influence POP concentrations. The study region contains 105 RMQS observation sites arranged on a regular square grid with spacing of 16 km. The observations include hot-spots at sites of POP application, smaller concentrations where POPs have been dispersed and observations less than the limit of quantification (LOQ) where the soil has not been impacted by POPs. Fifty nine of the molecules were detected at less than 50 sites and hence the data were unsuitable for spatial analyses. We represent the variation of the remaining 31 molecules by various linear mixed models which can include fixed effects (i.e. linear relationships between the molecule concentrations and covariates) and spatially correlated random effects. The best model for each molecule is selected by the Akaike Information Criterion. For nine of the molecules, spatial correlation is evident and hence they can potentially be mapped. For four of these molecules, the spatial correlation cannot be wholly explained by fixed effects. It appears that these molecules have been transported away from their application sites and are now dispersed across the study region with the largest concentrations found in a heavily populated depression. More complicated statistical models and sampling designs are required to explain the distribution of the less dispersed molecules.     

A fuzzy constraint-based approach to data reconciliation in material flow analysis

Data reconciliation consists in modifying noisy or unreliable data in order to make them consistent with a mathematical model (herein a material flow network). The conventional approach relies on least-squares minimization. Here, we use a fuzzy set-based approach, replacing Gaussian likelihood functions by fuzzy intervals, and a leximin criterion. We show that the setting of fuzzy sets provides a generalized approach to the choice of estimated values, that is more flexible and less dependent on oftentimes debatable probabilistic justifications. It potentially encompasses interval-based formulations and the least squares method, by choosing appropriate membership functions and aggregation operations. This paper also lays bare the fact that data reconciliation under the fuzzy set approach is viewed as an information fusion problem, as opposed to the statistical tradition which solves an estimation problem.     

Ruthenium‐Catalyzed One‐Pot Tandem Isomerization–Transfer Hydrogenation Reactions of γ‐Trifluoromethylated Allylic Alcohols and β‐Trifluoromethylated Enones

The ruthenium–2‐propanol combination was found to transform γ‐trifluoromethylated allylic alcohols and β‐trifluoromethylated enones into the corresponding saturated alcohols in excellent yields via a one‐pot tandem process involving isomerization and transfer hydrogenation(s). High stereospecificity was demonstrated and evidence for two mechanistic pathways is provided. The method was applied to a rapid synthesis of trifluoromethylated citronellol.     

Polytope-based computation of polynomial ranges

Polynomial ranges are commonly used for numerically solving polynomial systems with interval Newton solvers. Often ranges are computed using the convex hull property of the tensorial Bernstein basis, which is exponential size in the number n of variables. In this paper, we consider methods to compute tight bounds for polynomials in n variables by solving two linear programming problems over a polytope. We formulate a polytope defined as the convex hull of the coefficients with respect to the tensorial Bernstein basis, and we formulate several polytopes based on the Bernstein polynomials of the domain. These Bernstein polytopes can be defined by a polynomial number of halfspaces. We give the number of vertices, the number of hyperfaces, and the volume of each polytope for n=1,2,3,4, and we compare the computed range widths for random n-variate polynomials for n?10. The Bernstein polytope of polynomial size gives only marginally worse range bounds compared to the range bounds obtained with the tensorial Bernstein basis of exponential size.     

Multiple-relaxation-time lattice Boltzmann models in three dimensions

This article provides a concise exposition of the multiple-relaxation-time lattice Boltzmann equation, with examples of 15-velocity and 19-velocity models in three dimensions. Simulation of a diagonally lid-driven cavity flow in three dimensions at Re = 500 and 2000 is performed. The results clearly demonstrate the superior numerical stability of the multiple-relaxation-time lattice Boltzmann equation over the popular lattice Bhatnagar-Gross-Krook equation.