68 research outputs found
Optimization of the Particle Size in Emulsion Polymerization
No full textIn general, the optimization of polymerization processes focuses on the determination of trade-offs between polydispersity, particle size, polymer composition, number average molar mass, and reaction time with reactor temperature and reactant flow rates as manipulated variables. The foregoing indicates that the implementation of process optimization for the optimal control of emulsion polymerization processes is relying on technological advancement in the areas of mathematical process modeling, soft-sensing, and model-based control. This chapter illustrates some of the most successful approaches and their application to the control of the particle size in emulsion polymerization. Here, the authors illustrate the modeling equations needed to capture the dynamics and evolution of the particle size distribution (PSD) in a semibatch reactor employing a zero-one emulsion polymerization process. The off-line dynamic optimization approach is introduced here to illustrate a strategy that can be followed to develop optimum operation trajectories to achieve a specific PSD shape
Application of evolutionary neural networks and support vector machines to model NOx emissions from gas turbines
No full textEvolutionary artificial neural networks and support vector machines were investigated for the modeling of NOx emissions from gas turbines. For ANN's, a genetic algorithm (GA) with indirect binary encoding was employed to obtain optimal multi-layer perceptron (MLP)-type architectures. The contribution of this research includes the use of an improved GA objective function that takes advantage of the number of effective parameters provided by Bayesian regularization. For SVM's, a GA is also used with a search space covering all hyperparameters, including the choice of the kernel itself. The objective function took advantage of the number of support vectors to yield models that are more capable of generalization and are less computationally expensive. To test the performance of these models, three datasets describing NOx emissions from three different turbines were used. In previous works, these emissions were modeled using a shallow network architecture obtained by trial and error. When the performance of the models was compared, the optimized ANN's reduced the mean squared error (MSE) over testing sets by up to 90%, and optimized SVM's led to a reduction of up to 70%; with the latter's greatest advantage being computational efficiency and consistency with the different GA runs. The GA converged in a period in the order of minutes, which is more efficient than trial-and-error procedures. This work shows that more attention should be given to the influence of machine learning model architectures on the accuracy of PEMS models, as the computational cost of the GA is well justified by the resulting high accuracy. © 2018 Elsevier Lt
Towards a Quantum based GA Search for an Optimal Artificial Neural Networks Architecture and Feature Selection to Model NOx Emissions: A Case Study
No full textRegulating the Residential Solar Boom in Lebanon: Policy Frameworks and Strategic Initiatives for Photovoltaic Transition
No full textThe economic and financial crisis in Lebanon that started in 2019 has exacerbated the shortfalls of the Lebanese energy sector. This is due to the emerging inability to continue funding the imports of fuel oil, the main component that the sector relies on, with hard currencies. Amidst increased and critical power outages, Lebanon has witnessed a significantly observable boom in the installations of distributed solar PV to achieve independence from the failing fuel-powered grids, especially in the residential sector. Installations, however, have been chaotic and unregulated, with the government not playing its role in instating the proper legislative, institutional, and policy environment for these installations to take this transition in a strategic approach. With the current trend, the Lebanese energy sector might be headed in a direction that requires even more reforms down the line. This study aims to assess both the active and dormant laws and institutes that are responsible for regulating distributed solar PV installations and to perform a comparative analysis with other countries across the globe to draw policy recommendations for Lebanon. This study will offer a better understanding of what needs to be done in Lebanon in the upcoming years and aid in instating relevant reforms and policy recommendations
Enhancement of Benzene Emissions in Special Combinations of Electronic Liquid Mixtures
No full textIntroduction—
Electronic nicotine delivery systems (ENDS) are battery-powered smoking devices
introduced to the market as safer alternatives to combustible cigarettes. Upon heating the
electronic liquid (e-liquid), aerosols are released, including several toxicants such as
volatile organic compounds (VOCs). Benzene has been given great attention as a major
component of the VOCs group as it increases cancer risk upon inhalation. In this study,
several basic e-liquids were tested for benzene emissions.
Methods—
Aerosol Lab Vaping Instrument was used to generate aerosols from ENDS comprised of
different e-liquid combinations: vegetable glycerin (VG), propylene glycol (PG), nicotine
(nic), and benzoic acid (BA). The tested mixtures were PG, PG+nic+BA, VG,
VG+nic+BA, 30/70 PG/VG, 30/70PG/VG+nic+BA.
A carboxen polydimethylsiloxane fiber of a solid phase micro-extraction was placed in a
gas cell to trap benzene emitted from ENDS. Collection was done using an online
dynamic/static mode; benzene was adsorbed by the fiber during the puffing process and
for an extra 15 min until reaching equilibrium. Then, using gas chromatography-mass
spectrometry, benzene was quantified.
Results—
Benzene was quantified in VG, but not in PG or PG/VG mixture. However, benzene
concentration increased in all tested mixtures upon the addition of nicotine benzoate salt.
Interestingly, benzene was emitted at the highest concentration when BA was added to
PG. However, lower concentrations were found in the PG/VG and VG mixtures with BA.
Conclusions—
Both VG and BA are sources of benzene. Enhanced emission, however, is mostly noticed
when BA is mixed with PG and not VG
Solar pyrolysis of waste rubber tires using photoactive catalysts
No full textThe solar pyrolysis of waste tire rubber was investigated with the application of heterogeneous photocatalysts including TiO2, Pd/TiO2, Pt/TiO2, Pd-Pt/TiO2, and Bi2O3/SiO2/TiO2. Experiments were performed at temperatures ranging between 550 and 570 °C under solar irradiations of 950–1050 W/m2. The gas yield from non-catalytic solar pyrolysis was at 20% while the use of TiO2 catalyst increased the gas yield to 27%. Doping of TiO2 with noble metals and Bi2O3/SiO2 metal oxides enhanced further the cracking ability of the catalyst. Bi2O3/SiO2/TiO2 gave a 32% gas yield. The highest gas yields of 40% and 41% were achieved over Pd-Pt/TiO2 and Pd/TiO2 catalysts, respectively. Catalyst characterization by BET, SEM, EDX and XRD showed the role of metal doping in altering the morphology of TiO2, resulting in nanocrystallites, larger pore volume and higher surface area. Both, Pd and Bi influenced the photocatalytic properties of TiO2 improving cracking activity during pyrolysis of waste rubber. © 2018 Elsevier Lt
Numerical solution of the population balance equation under turbulent flow conditions -
No full textThesis. M.S. American University of Beirut. Computational Sciences Program, 2018. T:6815$Advisor : Dr. Fouad Azizi, Associate Professor, Chemical and Petroleum Engineering ; Committee members : Dr. Mazen Al Ghoul, Professor, Chemistry ; Dr. Joseph Zeaiter, Associate Professor, Chemical and Petroleum Engineering.Includes bibliographical references (leaves 81-97)In this work, the algorithm developed by Azizi and Al Taweel (2011) to solve the population balance equation using the sampling approach and the moving grid technique will be used to solve the population balance equation under various operating conditions. Two models will be employed to simulate turbulently flowing gas-liquid systems, namely, the models of Coulaloglou and Tavlarides (1977), and Wang et al. (2003). The models will be used to simulate the two-phase flow in pipes equipped with static mixers that exhibit regions of low, moderate, and high energy dissipation, where the conditions change drastically in very short times. The model constants used in the model of Coulaloglou and Tavlarides (1977) will first be optimized. The simulation results will then be compared to experimental results for validation.
Pyrolysis of waste tires: A modeling and parameter estimation study using Aspen Plus®
No full textThis paper presents a simulation flowsheet model of a waste tire pyrolysis process with feed capacity of 150 kg/h. A kinetic rate-based reaction model is formulated in a form implementable in the simulation package Aspen Plus, giving the flowsheet model the capability to predict more than 110 tire pyrolysis products as reported in experiments by Laresgoiti et al. (2004) and Williams (2013) for the oil and gas products respectively. The simulation model is successfully validated in two stages: firstly against experimental data from Olazar et al. (2008) by comparing the mass fractions for the oil products (gas, liquids (non-aromatics), aromatics, and tar) at temperatures of 425, 500, 550 and 610 °C, and secondly against experimental results of main hydrocarbon products (C7 to C15) obtained by Laresgoiti et al. (2004) at temperatures of 400, 500, 600, and 700 °C. The model was then used to analyze the effect of pyrolysis process temperature and showed that increased temperatures led to chain fractions from C10 and higher to decrease while smaller chains increased; this is attributed to the extensive cracking of the larger hydrocarbon chains at higher temperatures. The utility of the flowsheet model was highlighted through an energy analysis that targeted power efficiency of the process determined through production profiles of gasoline and diesel at various temperatures. This shows, through the summation of the net power gain from the plant for gasoline plus diesel that the maximum net power lies at the lower temperatures corresponding to minimum production of gasoline and maximum production of diesel. This simulation model can thus serve as a robust tool to respond to market conditions that dictate fuel demand and prices while at the same time identifying optimum process conditions (e.g. temperature) driven by process economics. © 2016 Elsevier Lt
Pyrolysis of olive cake with catalytic upgrading of volatile products
No full textSAPO-34 and 1 mol% MeSAPO-34 (metal-modified catalysts, Me = Ni, Fe) were synthesized and tested for the catalytic pyrolysis of olive cake at 500 °C under inert conditions. The characterization of the catalysts was performed using XRD, BET, SEM, EDX, FT-IR, and TGA. MeSAPO catalysts demonstrated a chabazite cubic structure identical to the parent catalyst, with lower surface areas and particle sizes, and less water retention. The use of catalysts increased gas yield from 39 to 66% and decreased the oil yield from 39 to 10%. Biochar yield was maintained around 25%, and the solid samples showed an increase in carbonization as shown in the SEM and EDX results. Liquid GC-MS analysis indicated that SAPO was more selective towards alkane and amine products, whereas metal-modified catalysts favored the production of alkenes, acids, and phenols. Similarly, the analysis of the gas samples revealed the presence of light olefins and light oxygenated compounds which varied with the type of catalyst used. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature
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