Volume 14, Issue 6 - Special Issue: First International Energy Conference, IEC 2015, Guest Editors: Carlos O. Castillo-Araiza and Margarita González-Brambila

In this paper, we derive mathematical models for mass transfer and reaction taking place in first-generation bioreactors to convert non-food starch into bioethanol. Given the hierarchical nature of the system, we identified three scale levels ranging from inside bagasse fibers (the pore scale) where the reaction occurs, up to the bioreactor itself (macroscopic scale) where the various products obtained from this reaction are monitored. We derive a macroscopic model at the reactor scale by systematically upscaling the relevant information from the pore scale using the method of volume averaging. A salient feature of the model is that the effective medium coefficients involved are predicted by solving ancillary closure problems in representative unit cells of the different levels of scale. The predictions of the model in terms of CO 2 production as well as cellular growth were validated with a close agreement with available experimental data. This work enhances our understanding of the relevance of transport phenomena taking place at the different scales in a bioreactor and may become an aid in design and operation applications of bioethanol production systems.

This study is aimed at giving some insights on kinetics, adsorption and partitioning of ethyl acetate during a single well tracer test. Synthetic formation water, an specific crude oil and a silicate-dolomite rock were used during experiments performed in laboratory and bench scale systems. Independent sets of experiments were designed to calculate the partition coefficient of ethyl acetate between the formation water and the oil, to develop a kinetic model for the hydrolysis of ethyl acetate, and to derive isotherm and kinetic models for the adsorption of ethyl acetate on the rock. These tracer experiments were evaluated at a concentration range (100–300 mmol.L −1 ) similar to that supposed to be used in the single well tracer method. All parameters determined from these experiments were validated describing observations from stirred batch and column systems, in which kinetic, adsorption and partitioning phenomena occurred at the same time. Pseudo-heterogeneous models, accounting for three phases namely the formation water, the rock and the oil, were applied to elucidate the interaction of the different mechanisms involved in these set-ups. Main results are summarized as follows: (i) partition coefficients ( K EA ) were apparent varying from ca. 5–8 because of thermodynamic constraints; (ii) kinetic models for the hydrolysis of ethyl acetate were developed under acid and basic conditions since at neutral ones there were negligible conversions; (iii) the combined Langmuir-Freundlich isotherm and the Langmuir kinetics were the most suitable models describing equilibrium and adsorption rate observations, respectively; (iv) the studied rock adsorbed significant amounts of ethyl acetate, leading to a maximum adsorption capacity (q EAm ) of ca. 7.0 mmol.g −1 at studied operating conditions; (v) the adsorption kinetic model rather than the simplified isotherm model seems necessary to describe this phenomenon from the single well test evaluating ethyl acetate as the tracer; and (vi) partition, hydrolysis and adsorption parameters evaluated from independent experiments allowed us to describe observations from both stirred batch and column systems. These results disclose the importance of accounting for partition, hydrolysis and adsorption mechanisms in a single well method using ethyl acetate as the tracer.

Conversion of biomass-derived syngas to ethanol has recently received significant attention because of strong demands for alternative and renewable energy sources; therefore glycerol has been suggested as promising raw material for obtaining ethanol in two consecutive steps. In this work, a thermodynamic study of glycerol dry reforming to produce syngas and subsequent ethanol production, as two-step process, was evaluated by means of the method of Gibbs free energy minimization. The effect of parameters such as reaction temperature, CO 2 /glycerol ratio (CGR), and pressure (P) on system performance was investigated. Reactions were simulated between 700–1,500 K and CGR range of 0–5, at 1 atm pressure. Calculations were performed with Aspen Plus 8.4, using Peng–Robinson thermodynamic method for properties estimation. Optimum conditions for syngas and ethanol production were determined, in order to prevent carbon deposition and methane formation. At temperatures above 900 K and CGR<1, between 3 and 7 mole of H 2 /mole of glycerol can be generated. Results indicated that the addition of CO 2 to the glycerol dry reforming reactor favored syngas and ethanol synthesis. The maximum yield obtained was 1 mole of ethanol per mole of glycerol at CGR≥2. Simulations indicate that temperature and CGR are essential factors for determining the process efficiency of the production of ethanol from syngas. These results suggest that glycerol wasted from biodiesel manufacturing should be useful as efficient raw material for syngas and ethanol production.

A model is developed to study the transient behavior of a non-isothermal, non-adiabatic packed-bed reactor during VOC (toluene) oxidation with air on a mixed-oxide catalyst via Mars-van Krevelen kinetic scheme. The aim is to find a safe reactor design and operating conditions for VOC elimination, which has been collected in a battery of adsorption units from dilute VOC streams. Once each adsorption column is saturated, a non-isothermal desorption takes place, and the gas stream exiting the sequence of VOC desorption columns feeds continuously the catalytic reactor for VOC elimination. The reactor model describes a 2D two-phase system interacting through the gas-solid interphase, including convection and axial and radial dispersions of mass and heat. The simulations show that the gas flow velocity, and reactor and particle diameters, are key parameters to achieve a safe design, and that traveling reaction fronts in the packed-bed exist when a series of reversible stepwise changes are performed in the concentration and temperature at the feed, as a result of the transient balance between heat generation and heat elimination along the packed-bed. When comparing the perturbation in VOC concentration at the feed versus those in temperature, a large parametric sensitivity is observed for the latter case without the presence of multiple steady states. Due to the uncertainty in the values of the effective heat transport parameters, transient responses of different magnitude are observed for the same operating conditions when using heat transport parameter of different magnitude.

This work proposes a substrate feeding strategy for a bioprocess integrated with a biomass estimator based in nonlinear filtering techniques. The performance of the proposed estimator and the substrate strategy are illustrated for the δ-endotoxin production of Bacillus thuringiensis ( Bt ) in batch and fed batch cultures. Nonlinear filtering techniques constitutes an adequate option as estimation tool because of the strongly nonlinear dynamics of this bioprocess and also due to nature of the uncertainties and perturbations that cannot be supposed Gaussians distributed. Biomass estimation is performed from substrate and dissolved oxygen. Substrate feeding strategy is intended to obtain high product concentration. Simulations results along with their experimental verifications demonstrate the acceptable performance of the proposed biomass estimator and the substrate feeding strategy.

Living cells, type of substrate, enzymatic hydrolysis play an important role in the efficiency of ethanol production; however, the kinetic parameters of biochemical reactions necessary for modelling these processes are often not accessible directly through experiments. In this context, for the implementation of suitable operational strategies, it is necessary to have kinetic models able to describe the process as realistically as possible. This paper proposes a comparative study of two nonlinear techniques for parametric identification of a kinetic model for ethanol production from recycled paper sludge in order to improve process performance. The parameters of the model are optimized by two methods: using the Levenberg–Marquardt optimization approach and Genetic Algorithms. The performances of both techniques are evaluated using a numerical simulation. The optimal value of these parameters have been obtained based on Genetic Algorithm. Finally, the effect of parametric adjustment and dilution rate on productivity was demonstrated by changing the batch operation to the continuous operating model. The maximum ethanol concentration was about 13.25 g/l in batch process and about 13.9 g/l at Dilution rate: 0.005 1/h corresponding to a productivity of 0.327 in continuous process.

In this work, the effect of the mixed Al 2 O 3 -TiO 2 oxide (Al/Ti=2, named AT2) support on the support-metal interaction in oxide state, its influence on MoS 2 dispersion and its impact on the hydrodeoxygenation of phenol reaction was studied. In contrast with CoMo/Al 2 O 3 catalysts, the use of Al 2 O 3 -TiO 2 as support tuned favorably the support-metal interaction, increasing the availability of easily reducible CoO X and MoO X species with octahedral coordination, which are recognized as precursors of the active phase. The lower support-metal interaction strength caused a decrease in the dispersion of MoS 2 phase. Even so, the sulfided CoMo/AT2 catalyst reached 85 % higher catalytic activity in the hydrodeoxygenation of phenol than CoMo/Al 2 O 3 . These increases were explained in terms of the formation of a higher amount of active CoMoS phase, and it is consistent with the increased availability of cobalt promoter for the decoration of MoS 2 edges. CoMo/AT2 catalyst was more resistant to inhibition by CS 2 than CoMo/Al 2 O 3 in direct deoxygenation route and hydrodeoxygenation of phenol.

The coiled flow inverter (CFI) is an enhanced heat exchanger. This device uses the principle of flow inversion to increase heat transfer and has potential for industrial applications. A mathematical model based on experimental and numerical data was developed for the case of single phase flow with water as working fluids. This model includes (ε-NTU) Effectiveness Number of Transfer Units curves, Nusselt correlations, for this specific neither parallel nor counter flow setup. A range of Reynolds numbers from 2,000 to 18,000 in the tube side, and 500 to 2,000 in the shell side was considered. The coiled flow inverter is made of coils and 90◦ bends, inserted in a closed shell. The shell side is cylindrical. The average temperatures at input and output of the heat exchanger were reported for different tube and shell side flow rates. Overall heat-transfer coefficients (U f ) were calculated as well as the Number of Transfer Units (NTU) and Effectiveness (ε) at various process conditions. A Nusselt correlation was proposed for the shell side of this configuration. The ε-NTU curves of the selected heat exchanger have a high resemblance to the parallel flow tube heat exchanger, with a maximum of 2.1 % error. The coiled flow inverter has increases of 200 %, 300 % and 500 %, respectively for effectiveness, number of transfer units and overall heat transfer coefficient compared to a regular parallel flow heat exchanger at the same conditions. Correlations for the CFI in its shell were proposed. This heat exchanger provides higher U f , reduces cumbersomeness and length of piping.

The effectiveness factor (EF) is a useful tool for the study of heterogeneous reaction systems, such as catalytic particles, where interactions of reaction-diffusion processes are involved. For simplicity, the study of EF is achieved on steady state operation (SSEF), but recent studies have suggested that EF can increase on dynamic operation conditions, especially when diffusive transport does not follow the Fick’s law. In this paper, a study about the effect of anomalous diffusion on the dynamic effectiveness factor (DEF) in catalytic particles is presented. For this, it is considered a generalized Cattaneo-type diffusion model described by differential equations of fractional order applied at rectangular, cylindrical and spherical geometries of the catalytic particles, which is analyzed in the frequency space by means the Fourier transform method. Numerical results, based on Bode and Nyquist diagrams, show the conditions and regions where the DEF values are largest than SSEF.

A pilot scale Upflow Anaerobic Contactor (UAC), based on upflow sludge blanket principle, was designed to treat vinasse waste obtained from beet molasses fermentation. An assessment of the anaerobic digestion of vinasse was carried out for the production of biogas as a source of energy. Average Organic loading rate (OLR) was around 7.5 gCOD/m 3 /day in steady state, increasing upto 8.1 gCOD/m 3 /day. The anaerobic digestion was conducted at mesophilic (30–37 °C) temperature and a stable operating condition was achieved after 81 days with average production of 65 % methane which corresponded to a maximum biogas production of 85 l/day. The optimal performance of UAC was obtained at 87 % COD removal, which corresponded to a hydraulic retention time of 16.67 days. The biogas production increased gradually with OLR, corresponding to a maximum 6.54 gCOD/m 3 /day (7.4 % increase from initial target). A coupled Artificial Neural Network-Differential Evolution (ANN-DE) methodology was formulated to predict chemical oxygen demand (COD), total suspended solids (TSS) and volatile fatty acids (VFA) of the effluent along with the biogas production. The method incorporated a DE approach for the efficient tuning of ANN meta -parameters such as number of nodes in hidden layer, input and output activation function and learning rate. The model prediction indicated that it can learn the nonlinear complex relationship between the parameters and able to predict the output of the contactor with reasonable accuracy. The utilization of the coupled ANN-DE model provided significant improvement to the study and helps to study the parametric effect of influential parameters on the reactor output.

In this paper, a novel control algorithm to increase biohydrogen production in a continuous reactor using the sulphate-reducing bacteria Desulfovibrio alaskensis with lactate as carbon source is proposed. This work was conducted via numerical simulations, based on an experimentally corroborated kinetic model, considered as a benchmark of the system. A bifurcation analysis to identify the reactor’s steady-state performance was done in order to identify feasible operating regions. The proposed controller cancels the upper bounds of the reactor, imposing a finite-time convergence to the selected set point. The closed-loop stability of the reactor is analysed via the dynamic of the regulation error. Finally, numerical experiments were conducted in order to compare the dynamic behaviour of the proposed closed-loop system versus its open-loop counterpart and a well-tuned classical PI controller one. The proposed methodology increases the hydrogen productivity controlling with a satisfactory performance the biomass concentration, which is considered as the control output.

Nowadays ethanol is considered an alternative to liquid fossil fuels, as a product of fermentation of sugars by Saccharomyces cerevisiae and other microorganisms. It is very important in the food, pharmaceutical and chemical industries. Prior studies show that the addition of certain amount of zeolite induces an increase in the ethanol/glucose yield. In this work, the effect of zeolite on the carbon flux of S. cerevisiae in different culture conditions is reported. An explanation for the effect of the zeolite on the yeast metabolism is offered. Results show a 20 % increase in yield, thus lowering production costs and improving the use of raw materials, which would increase the possibilities of using alcohol as biofuel.

The plans for developing the electrical sector in México are reviewed and compared with the targets set up for emissions and for participation of clean energies in the electrical generation considering a time horizon up to year 2050. The options required to meet the targets are discussed, with particular emphasis on the necessity for CCS. The electrical sector in México is one of fast growth, with the installed capacity essentially doubling over the next 15 years. This growth has to be compatible with the commitments that the country has made to reduce Green House Gas (GHG) emissions. Sector’s development strategy includes new technologies such as renewables, nuclear energy and Carbon Capture and Storage (CCS), in amounts larger than the minimum values established in the legislation. It is also concluded that CCS will be a necessity for Mexico. It is proposed that the energy policies to be established should be accompanied by industrial development policies, in order to maximize the participation of the Mexican Industry in the supply chain of the energy systems.

Plastic solid waste (PSW) presents challenges and opportunities to society regardless of their sustainability awareness and technological advances. A special emphasis is paid on waste generated from polyolefin sources, which makes up a great percentage of our daily commodities’ plastic products. In Mexico 7.6 millions of tons of plastic in 2012 were wasted, which low density polyethylene LDPE, and high density polyethylene HDPE were the most abundant. Increasing cost, and decreasing space of landfills are forcing considerations of alternative options for PSW disposal. Years of research, study and testing have resulted in a number of treatment, recycling and recovery methods for plastics that can be economically, and environmentally viable. The following work studies the possibilities of polyethylene recycling. Nowadays, non-catalytic thermal cracking (Pyrolysis) is receiving renewed attention, due to the fact of added value on a crude oil barrel and its very valuable yielded products, but a fact remains that advanced thermo-chemical recycling of polyolefin still lacks the proper design, and kinetic background to target certain desired products and/or chemicals. On the other hand some research have shown a good performance that can be used in a real plant. ASPEN Plus is used to simulate a non-catalytic thermal cracking process. The process behavior of simulation is similar to the experimental data from other authors. Using gibbs free energy to identify the chemical equilibrium in system, its global minimization allows identifying the amount of substances present in the process. The simulation results demonstrate that it could be produced 49 % and 34 % wt of ethylene and propylene respectively from gas yield at 850 °C. Then scale the plant to produce ethylene and propylene from the pyrolysis and ethanol from a direct hydration of ethylene. Aspen Process Economics Analyzer is used in order to find the feasibility of the pyrolysis and ethanol production. The total sales/total production cost ratio obtained for the integrated process approaches was 2.55.

A CFD model of a copper-ceria based micro-reactor for the CO preferential oxidation reaction is developed. Simulations are performed by changing the thermal conductivity of the support and the oxygen inlet concentration. It is found that the value of the wall thermal conductivity has a significant role on the temperature profiles, hot-spot and selectivity. On increasing the O 2 content, the CO selectivity decreases. An increase of the oxygen content anticipates the activation of the H 2 oxidation, thus competing with CO oxidation. Conversely, at low values of the O 2 content, the H 2 oxidation is activated only after an almost complete CO oxidation is obtained. From the results it appears that the temperature control and management in the reactor is a key for increasing the CO selectivity at high CO conversion.