Marcelo Farenzena

Fast microwave-assisted pyrolysis of microalgae using microwave absorbent and HZSM-5 catalyst.

Fast microwave-assisted pyrolysis (fMAP) in the presence of a microwave absorbent (SiC) and catalyst (HZSM-5) was tested on a Chlorella sp. strain and on a Nannochloropsis strain. The liquid products were characterized, and the effects of temperature and catalyst:biomass ratio were analyzed. For Chlorella sp., a temperature of 550 °C, with no catalyst were the optimal conditions, resulting in a maximum bio-oil yield of 57 wt.%. For Nannochloropsis, a temperature of 500 °C, with 0.5 of catalyst ratio were shown to be the optimal condition, resulting in a maximum bio-oil yield of 59 wt.%. These results show that the use of microwave absorbents in fMAP increased bio-oil yields and quality, and it is a promising technology to improve the commercial application and economic outlook of microwave pyrolysis technology. Additionally, the use of a different catalyst needs to be considered to improve the bio-oil characteristics.

Growth of microalgae Scenedesmus sp in ethanol vinasse

This study evaluated the feasibility of using vinasse as a nutrient source for microalgae cultivation. The Scenedesmus sp was grown in a medium supplemented with vinasse and process variables were optimized using a factorial design and a Central Composite Design (CCD). The factorial design results showed that it was possible to cultivate microalgae at concentrations of up to 40% of vinasse in the culture medium. The CCD results showed that the light intensity and vinasse concentration influenced the amount of biomass produced.

Tanneries: from waste to sustainability

The aim of this work was to look for an efficient and environmentally safe solution for the leather tanning industry through a problem of non-linear programming. The results were promising and showed a significant potential of wastewater reduction. Reuse of internal streams reduced around 70% wastewater. The solutions obtained could reduce significantly the amount of chemicals and consequently the amount of waste to be treated.

Modified PI Controller for Stiction Compensation

Abstract Stiction is a well known problem of the process performance. Compensate its effect is essential, because most of sticky valves cannot be replaced and they remain working for months or years. The scope of this work is to propose a novel methodology to compensate stiction effects, through the modification of the controller (PI) block in the control loop. The proposed approach is based on the two moves method, however it allows to specify closed loop performances faster than open loop and reject load disturbances efficiently. We assume here that a small offset between process variable and setpoint is accepted, what decreases significantly the valve traveling, comparing with available approaches. The method is described for both setpoint tracking and disturbance rejection. The efficacy is corroborated by a case study, considering setpoint changes and disturbance rejection.

Valve Stiction Evaluation Using Global Optimization

Abstract Abstract Valve stiction is a well known villain in process industry. Quantifying this valve damage is essential to ensure plant stability and profitability. The scope of this work is to propose a new method to compute valve stiction parameters, using a two parameter model, using only routine operating data. The proposed method uses global optimization to evaluate loop and plant parameters. Combining the proposed procedure with an efficient global optimization algorithm, the mean computation time for each valve was about 5 minutes. The method was applied in both simulation and industrial valves, providing reliable results, with relative errors smaller than 3% in all parameters.

Laboratory apparatus to evaluate microalgae production

The application of microalgae for energy purposes and CO2 biomitigation continues to present a number of challenges, including the optimization of culture conditions. The application of experimental designs for microalgae cultivation is difficult, since experiments involving such microorganisms generally last days or weeks. This work proposes a multipurpose laboratory apparatus for the optimization of microalgae experimental conditions that simultaneously enables the evaluation of variables such as temperature, irradiance, photoperiod and CO2 concentration in the aeration stream, as well as variables related to the concentration of culture media nutrients. A case study is also presented in which temperature, concentration of f/2 medium sodium nitrate and the effects of incident light intensity on Nannochloropsis oculata lipid content are evaluated. Experiments were carried out following central composite designs, in batch cultivation within an airlift photobioreactor apparatus. The best experimental result was obtained at 21 oC, 119 mg/L NaNO3 and 137 µE.m-2.s-1, corresponding to 41.8% lipids and 211.9 mg.L-1 final lipid concentrations.

Fast Offshore Wells Model (FOWM): A practical dynamic model for multiphase oil production systems in deepwater and ultra-deepwater scenarios

Abstract This work describes a simplified dynamic model for control and real time applications in offshore deepwater and ultra-deepwater petroleum production systems. Literature about simplified dynamical models, capable of cover the global architecture of an offshore multiphase production system, is scarce. Hence, the proposed model integrates and adapts partial models available in the literature in order to generate a single model of the whole system. The model, designed to represent slugs generated by the casing heading and terrain/riser concomitantly, was evaluated by comparison with a traditional commercial simulator and was also implemented in two actual production systems. As a result, the model showed the capability of capturing complex dynamical behaviors, such as limit cycles, demonstrated to be numerically more stable than similar models in literature, fast enough to be used in real time applications and proved to be adherent to the commercial simulator and actual operating data from Petrobras production systems.

Valve backlash and stiction detection in integrating processes

Valve nonlinearities are responsible for producing limit cycles in the loop and consequently decreasing plant performance. In the case of an integrating plant, once the loop oscillation is detected, the engineer should distinguish between stiction and backlash, but no method is available in the literature to address this class of problem. In this paper, it is proposed a data-driven method to distinguish between loop stiction and backlash for integrating processes. The closed-loop pattern provides enough information to verify when either stiction or backlash is available. The efficacy of the proposed technique is corroborated by simulation case studies.

Evaluation of wavelength selection methods for 2D fluorescence spectra applied to bioprocesses characterization

In biotechnological processes, the productivity and costs depend strongly on the control of the operating conditions. For this reason, sensors that allow the monitoring of variables of interest become quite important. 2D fluorescence spectroscopy is one promising option among those that are being applied for this purpose. In the present work, three methods were evaluated to select the best excitation/emission wavelength pairs of 2D fluorescence spectra to infer product, substrate and cellular concentrations throughout a fermentation using a multiple linear chemometric model: Exhaustive Search (ES), Stepwise Regression and Genetic Algorithm (GA). The Stepwise Regression presented unsatisfying results, while GA always led to good R2 values in short computational times. However, for the proposed problem, the ES showed the best performance, finding the global optimum in a few minutes.

LoopRank: A Novel Tool to Evaluate Loop Connectivity

Abstract Abstract Since the number of loops in refineries or petrochemical plants is very large and the number of loops with poor performance is equally large, to prioritize their maintenance is essential to ensure plant profitability. This work proposes a methodology called LoopRank to compute the importance factor of each loop, aiming to prioritize their maintenance. The algorithm is based on the connection among them, which is computed using partial correlation. The algorithm is based on PageRank , which analyses connections among nodes recursively and computes a rank for each node using partial correlation. The LoopRank assigns an individual score for each loop ranging from 0% to 100%. Based on this score, the loop maintenance can be ranked. The LoopRank algorithm is computationally efficient, thus allowing its industrial large-scale application. The proposed algorithm was applied both on simulation and industrial case studies, providing fruitful results.