Ramiro Rico-Martínez

This research presents the prediction of temperatures in the chamber of a solar dryer using artificial neural networks (ANN). The dryer is a forced-flow type and indirect. Climatic conditions, temperatures, airflow, and geometric parameters were considered to build the ANN model. The model was a feed-forward network trained using a backpropagation algorithm and Levenberg–Marquardt optimization. The configuration of the optimal neural network to carry out the verification and validation processes was nine neurons in the input layer, one in the output layer, and two hidden layers of thirteen and twelve neurons each (9-13-12-1). The percentage error of the predictive model was below 1%. The predictive model has been successfully tested, achieving a predictor with good capabilities. This consistency is reflected in the relative error between the predicted and experimental temperatures. The error is below 0.25% for the model’s verification and validation. Moreover, this model could be the basis for developing a powerful real-time operation optimization tool and the optimal design for indirect solar dryers to reduce cost and time in food-drying processes.

Ohmic heating, also known as electrical resistance heating, is a novel process of pasteurization that has several advantages including homogeneous heating, low heating time, high inactivation of microorganisms, and organoleptic and nutritional properties. Furthermore, mathematical tools allow for quick and low-cost analysis of behaviors with various operating parameters. This study aimed to improve the ohmic pasteurization process of the mango pulp using computational fluid dynamics (CFD) and response surface methodology (RSM), using the experimental properties of mango pulp. The generated mathematical model is an accurate tool for predicting ohmic pasteurization behavior in an industrial environment; it presents a 4.4% standard deviation error in the experimental data. Furthermore, the arrangement and intensity of the added voltage analysis suggested operating variables with better pasteurization performance. Another observation was that the production speed was related to the voltage intensities of the inlet speed in a non-proportional manner. Additionally, operation at a low inlet velocity may be more susceptible to thermal damage, whereas operation at a high inlet velocity requires a particular proportion of voltage insertion to ensure adequate heat distribution.

A solar chimney configuration consisting of three air flow channels divided by two metallic plate, placed in the center of the chimney between two acrylic covers, leading to symmetric air flow, is proposed as an alternative for the design of natural ventilation systems for buildings in tropical and subtropical climatic zones The solar chimney dimensions are 2.0 m height, 1.0 m width, and gap between channels of 0.30 m. These dimensions are appropriate for the design of ventilation systems for residential buildings in central México. A Numerical simulation using the global mass and energy balances in steady state was utilized to evaluate the efficacy of the proposed configuration. The temperature profiles, calculated for a typical hot day in a tropical region, reveal that the configuration is more efficient than the single channel chimney, achieving thermal efficiency values near 75%. This solar chimney configuration can be used with better results than the traditional design as an alternative for natural ventilation systems in residential buildings without a significant increase in the cost of the residence investment.

A conventional approach to solving stochastic optimal control problems with time-dependent uncertainties involves the use of the stochastic maximum principle (SMP) technique. For large-scale problems, however, such an algorithm frequently leads to convergence complexities when solving the two-point boundary value problem resulting from the optimality conditions. An alternative approach consists of using continuous random variables to capture uncertainty through sampling-based methods embedded within an optimization strategy for the decision variables; such a technique may also fail due to the computational intensity involved in excessive model calculations for evaluating the objective function and its derivatives for each sample. This paper presents a new approach to solving stochastic optimal control problems with time-dependent uncertainties based on BONUS (Better Optimization algorithm for Nonlinear Uncertain Systems). The BONUS has been used successfully for non-linear programming problems with static uncertainties, but we show here that its scope can be extended to the case of optimal control problems with time-dependent uncertainties. A batch reactor for biodiesel production was used as a case study to illustrate the proposed approach. Results for a maximum profit problem indicate that the optimal objective function and the optimal profiles were better than those obtained by the maximum principle.

We present the first theoretical comparison between ketene dimerization in gas phase and ketene dimerization in solution. Density functional theory (DFT) calculations on the ketene dimerization were carried out considering the following product dimers: diketene (d-I), 1,3-cyclobutanedione (d-II), 2,4-dimethylene-1,3-dioxetane (d-III), and 2-methyleneoxetan-3-one (d-IV). All structures were optimized at the PW86x+PBEc/DZP level of theory. Based on these geometries, a total of 58 meta and hybrid functionals were used to evaluate the heat of dimerization. The MPW1K functional was found to fit the experimental data best and subsequently used in the final analyses for all energy calculations. It was found on both kinetic and thermodynamic grounds that only d-I and d-II are formed during ketene dimerization in gas phase and solution. In gas phase, d-I is favored over d-II by 2 kcal/mol. However, the dimerization barrier for d-I is 1 kcal/mol higher than for d-II. Solvation makes dimerization more favorable. On the enthalpic surface this is due to a favorable interaction between the dimer dipole moment and solvent molecules. The dimer is stabilized further on the Gibbs energy surface by an increase of the dimerization entropy in solution compared to gas phase. The species d-I remains the most stable dimer in solution by 1 kcal/mol. Kinetically, the dimerization barriers for the relevant species d-I and d-II are cut in half by solvation, due to both favorable dimer−dipole/solvent interactions (ΔH^⧧, ΔG^⧧) and an increase in the activation entropies (ΔS^⧧). While the dimerization barrier for d-II is lowest for the gas phase and toluene, the barrier for d-I formation becomes lowest for the more polar solvent acetone by 1 kcal/mol as d-I dimerization has the most polar transition state.

In this work is studied the effect of a noncommercial enzyme preparation on xanthophyll extraction from marigold flower (Tagetes erecta). The enzymatic extract was synthesized by endogenous microorganisms previously isolated and identified as Flavobacterium IIb, Acinetobacter anitratus, and Rhizopus nigricans. The results show that the extraction yield depends directly on the extent of the enzymatic hydrolysis of cell walls in the flower petals and that it is possible to reach yields in excess of those previously reported for treatments with commercially available enzymes (29.3 g/kg of dry weight). HPLC analysis of the product indicates that the original xanthophyll profile is not altered. The enhanced extraction system appears to be very competitive when compared to the traditional process and current alternatives.

Endogenous microorganisms isolated from the marigold flower (Tagetes erecta) were studied to understand the events taking place during its ensilage. Studies of the cellulase enzymatic activity and the ensilage process were undertaken. In both studies, the use of approximate second-order models and multiple lineal regression, within the context of an experimental mixture design using the response surface methodology as optimization strategy, determined that the microorganisms Flavobacterium IIb, Acinetobacter anitratus, and Rhizopus nigricans are the most significant in marigold flower ensilage and exhibit high cellulase activity. A mixed culture comprised of 9.8% Flavobacterium IIb, 41% A. anitratus, and 49.2% R. nigricans used during ensilage resulted in an increased yield of total xanthophylls extracted of 24.94 g/kg of dry weight compared with 12.92 for the uninoculated control ensilage. Keywords: Marigold flower; ensilage; starter inoculum; mixed culture