Pseudo Components Research Articles

In-situ heavy oil upgrading by high temperature oxidation through air injection

Air injection has been widely considered as a technology to enhanced heavy oil recovery on account of the heavy oil upgrading caused by high temperature oxidation during this process. This paper aims at exploring the effects of oxidation thermal processing in a porous media at high temperature from 500 to 540℃ which is the high temperature oxidation range of heavy oil known from TG results, and reaction time from 8 to 16 hours for heavy oil upgrading. It was suggested that the viscosity decreased with the temperature and retention time increased due to getting less ring structure seen from IR Spectrum results. It was observed that the viscosity of heavy oil was reduced 1 to 2 orders of magnitude. Besides, the kinetics of heavy oil upgrading were analysed using five pseudo components including HO (C35+), MO (C15 ~ C35), LO (C5 ~ C14), coke, G (gas products) and successfully predicted the products results with an error of 4.34%, and great correlation to Arrhenius equation. The activation energies obtained are in the range of 44 ~ 215 kJ/mol. This work has great value in revealing the mechanisms of high temperature oxidation heavy oil upgrading and assisting heavy oil production.

A pseudo principal component analysis method for multi-dimensional open-high-low-close data in candlestick chart

As the most widely-used data form in the field of finance, the open-high-low-close (OHLC) data is being collected by all kinds of financial trading systems all the time. This paper puts forward a pseudo-principal component analysis (PCA) for multi-dimensional OHLC data, which can extract their useful information in a comprehensible way for visualization and easy interpretation. Firstly, a novel feature-based representation for OHLC data is proposed, which contains fruitful and explicit economic implications. Next, we define a full set of numerical characteristics and variance-covariance structures for the feature-based OHLC data. Then, the pseudo-PCA procedure for OHLC data is deduced based on the proposed algebraic operators. Finally, the effectiveness and interpretability of the proposed pseudo-PCA method are verified through finite simulations and three typical empirical experiments. This paper enriches the application scenarios of classical PCA and contributes to the multivariate statistical modeling of symbolic data. The proposed applications can serve as models for related studies.

Assessment of the applicability of binary mixture hypothesis to modeling the phase behavior of heavy oil/bitumen-solvent systems for EOR applications

Conventional production methods in heavy oil reservoirs are not efficient primarily due to the high viscosity of the oil. Several methods such as VAPEX and ES-SAGD have been developed to overcome production challenges from these reservoirs, which mainly rely on oil viscosity reduction. Solvent injection dilutes the oil and produces a complex asymmetric mixture. It is difficult to study the phase behavior of oil due to the diversity of its components, and it gets more complicated with the addition of solvent. One of the assumptions to simplify the problem is considering heavy oil as a single pseudo component and investigating the thermophysical properties of binary mixtures with diluents. This study collected and evaluated more than 1000 experimental data on various types of heavy oil/bitumen and several hydrocarbon and non-hydrocarbon solvents. The data were divided into two groups, below and above the critical temperature of the solvent, according to experimental temperatures. Modeling of mixture phase behavior as a binary mixture was performed using the advanced Peng-Robinson equation of state (APR-EoS). EoS tuning to match the experimental data was performed by optimizing the binary interaction coefficients (kij). The results showed that the binary mixture assumption could be used as a practical approach to construct pressure-composition phase diagrams. Optimized values of kij were proposed as two empirical correlations according to the dimensionless ratio Tco/Tcs (oil critical temperature to solvent critical temperature). The model constructed using these correlations showed an average deviation of about 16% compared to experimental data. It is necessary to note that the vapor-liquid-liquid three-phase regions may occur in a heavy oil/bitumen and solvent mixture. But according to the Gibbs phase rule, with two components and three phases in the system, the degree of freedom equals one. So, investigating the effects of pressure change on three-phase regions is not possible using this model.

Pyrolysis characteristics and kinetic reaction parameters estimation of sassafras wood via thermogravimetric modeling calculation coupled with hybrid optimization methodology

The thermokinetics of sassafras wood pyrolysis were studied via thermogravimetric inverse modeling. Model-free combined with model-fitting methods were used to explore the optimal kinetics. Results indicate the obtained averaged activation energy and pre-exponential factor are 215.12 kJ/mol and 8.65 × 1017s−1, while the reaction model in charge is g(α) = [-ln(1-α)]1/3. In the following, Kissinger-based K–K method was adopted to separate the single reaction kinetics for each pseudo components. The analysis of K–K method provided the basis of the search range for each kinetic parameters. Finally, a new optimization algorithm was put forward, and the multi parallel reactions scheme incorporated into the Grey Wolf Optimization coupled with the Least Squared Fitting procedure was adopted to perform the optimization. The predicted MLR curves based on the simultaneously optimized kinetic parameters fit well with the experimental data not only at heating rates of 10, 20 and 30 K/min, but also at 5 and 40 K/min which were not used in the optimization. Such results indicated the excellent applicability of the optimized parameters and efficiency of the hybrid optimization procedure. Results from the present work could be a guidance for further biomass pyrolysis evaluation under more complex practical scenarios.

Kinetic study of thermal decomposition of sugarcane bagasse pseudo-components at typical pretreatment conditions: Simulations of opportunities towards the establishment of a feasible primary biorefining

A deeper understanding of the kinetic and thermodynamic parameters of thermal degradation of sugarcane bagasse (SCB) is fundamental to defining appropriate conditions for primary biorefining in the production of renewable fuels. In this work, the kinetics of thermal degradation of high polymers of SCB was investigated through thermogravimetric data. Model-free and model-fitting methods were used to calculate apparent activation energies (Ea) and other related reaction parameters. An essential advance of this work is related to the quantitative interpretation of the degradation process (an endothermic and non-spontaneous process) via a multi-stage model governed by diffusion-controlled reactions and order-based models, which helps explain the differences observed in the mass balance of biorefining processes. Based on derivative thermogravimetric curves, three major peaks were associated with pseudo-components (PSE): PSE 1 (hemicelluloses + extractives and lignin), PSE 2 (cellulose + extractives and lignin), and PSE 3 (lignin + extractives and residual holocellulose). For PSE 1, PSE 2, and PSE 3, respectively, Ea ranges of 124–154, 147–153, and 230–530 kJ⋅mol−1 were obtained using the Kissinger-Akahira-Sunose method, and 120–152, 144–150, and 232–545 kJ⋅mol−1 were obtained using the Flynn-Wall-Ozawa method. These data support the calculation of many critical operating parameters of biorefinery processes, such as the minimum pretreatment temperature. SCB biorefining could lead to a degradation of up to 10, 0.5, and 11% of PSE 1, PSE 2, and PSE 3, respectively, at 473.15 K for 200 min.

Comparative insights into flue gas-to-ash characteristics on co-combustion of walnut shell and bio-oil distillation sludge under atmospheric and oxy-fuel condition

The clean recovery of bio-oil distillation sludge (DS) is a pivotal sector to perfect the biomass refinery system in responses to effective waste management and environmentally friendly consensus. This work aimed to comparatively characterize atmospheric and oxy-fuel co-combustion of walnut shell (WS) and DS in terms of (co-)combustion performance, distributed kinetics, flue gas evolution and ash characteristics. The results indicated co-combustion of WS and DS significantly increased the allocated proportion of char combustion stage and improved co-combustion performance, which was reflected in the enhanced four quantitative combustion indices. The fourth pseudo component, corresponded to the char combustion stage, continuously dominated the whole combustion process by adding more fraction of DS to co-combust with WS, whose activation energy was diminished, thereby optimizing the initial reaction energy barrier. In addition, oxy-fuel combustion promoted the recovery and sequestration of CO2, facilitated the formation of CO, and further endowed the conversion of polycyclic aromatic hydrocarbons into phenols rather than aromatics. Although the composition for mixed molten ash presented the decreased contents for easy-slagging minerals, the co-combustion process was still with potential ash fouling risk owing to basically unchanged ash configuration consistent with WS ash. However, the addition of DS to some extent strengthened anti-slagging performance, consequently optimizing the empirical indices of slagging and fouling for mixed ashes. Also, a higher ash content was yielded in oxy-fuel combustion than that in atmospheric combustion owing to the reducibility of CO2, in which the presence of CO2 contributed to the formations of carbonates and low melting-temperature potassium-containing silicates.

Insight into the synergistic reaction mechanism of biomass pseudo components and low-density polyethylene for the production of light aromatics through co-catalytic fast pyrolysis over hierarchical HZSM-5

Co-feeding of waste plastics during biomass catalytic fast pyrolysis can improve remarkably the yield of aromatic hydrocarbons. In this work, the simulated biomass by using its model components of cellulose, xylan, and lignin at different proportions was Co-CFP with LDPE to investigate the synergistic reaction mechanism between biomass and low-density polyethylene (LDPE) over hierarchical HZSM-5. Results showed that biomass and its model components were oxygen-enriched feedstock, while LDPE was the hydrogen-enriched feedstock with H/Ceff over 2. The synergistic effect between biomass model components and LDPE was ordered as cellulose and LDPE > xylan and LDPE > lignin and LDPE. Because pyrolysis of cellulose produced higher yield of furans than that of xylan and lignin which acted as the key synergistic compounds in Diels-Alder reaction to form light aromatics. The transfer of hydrogen free radical from the LDPE-derived hydrocarbons to the biomass-derived oxygenates promoted the deoxygenation reaction of oxygenates in hierarchical HZSM-5. Diels-Alder reaction between furans and olefins was the key synergistic reaction which highly improved the yield of hydrocarbon aromatics. In general, the difference of the pyrolysis oxygenated intermediate among the biomass pseudo components resulted in different yields of light aromatics, where cellulose presented highest extent of synergistic reaction to LDPE.

Thermal Debinding Kinetics of Gelcast Ceramic Parts via a Modified Independent Parallel Reaction Model in Comparison with the Multiple Normally Distributed Activation Energy Model.

This work aims to provide useful insights into the thermal debinding kinetics of gelcast ceramic parts, especially for debinding kinetics prediction involving heat preservation. Debinding experiments were conducted in a differential thermogravimetric analyzer at five heating rates (5, 8, 10, 15, and 20 °C/min) in the temperature range of 35–900 °C under an air atmosphere. The conversion (α) and pyrolysis rate (dα/dT) data were simulated using a modified independent parallel reaction (IPR) model and a multiple normally distributed activation energy model (M-DAEM). Their validity was assessed and compared by checking the agreement between the experimental results and the prediction capability. The results showed that both the modified IPR model and M-DAEM had high predictability for thermal debinding kinetics under linear heating conditions. The fitting quality parameters (Fit) were less than 1.406 and 1.01%, respectively. The activation energies (Ei, i = 1, 2, 3, 4, and 5) calculated by the M-DAEM ranged from 153.312 to 217.171 kJ/mol. The relationships between Ei of pseudo components 1 to 5 calculated by the modified IPR model were a function of the conversion rate. The Ei values were E1(α) = 116.750 + 11.153α – 26.772α2 + 4.362α3 kJ/mol, E2(α) = 139.595 – 66.162α + 75.702α2 – 38.041α3 kJ/mol, E3(α) = 190.854 + 135.755α – 214.801α2 + 116.093α3 kJ/mol, E4(α) = 64.068 + 280.086α – 380.270α2 + 264.724α3 kJ/mol, and E5(α) = 188.257 – 77.086α + 74.129α2 – 48.669α3 kJ/mol, respectively. However, it is noteworthy that the α and dα/dT curves predicted by the modified IPR model with a deviation of less than 8% were better than those predicted by the M-DAEM for the linear thermal debinding process with the holding stage. Accordingly, it is believed that the proposed modified IPR model is suitable for describing the thermal debinding kinetics involving the heat preservation of gelcast green parts.

Weighted Blind Source Separation Can Decompose the Frequency Mismatch Response by Deviant Concatenation: An MEG Study.

The mismatch response (MMR) is thought to be a neurophysiological measure of novel auditory detection that could serve as a translational biomarker of various neurological diseases. When recorded with electroencephalography (EEG) or magnetoencephalography (MEG), the MMR is traditionally extracted by subtracting the event-related potential/field (ERP/ERF) elicited in response to “deviant” sounds that occur randomly within a train of repetitive “standard” sounds. However, there are several problems with such a subtraction, which include increased noise and the neural adaptation problem. On the basis of the original theory underlying MMR (i.e., the memory-comparison process), the MMR should be present only in deviant epochs. Therefore, we proposed a novel method called weighted-BSST/k, which uses only the deviant response to derive the MMR. Deviant concatenation and weight assignment are the primary procedures of weighted-BSST/k, which maximize the benefits of time-delayed correlation. We hypothesized that this novel weighted-BSST/k method highlights responses related to the detection of the deviant stimulus and is more sensitive than independent component analysis (ICA). To test this hypothesis and the validity and efficacy of the weighted-BSST/k in comparison with ICA (infomax), we evaluated the methods in 12 healthy adults. Auditory stimuli were presented at a constant rate of 2 Hz. Frequency MMRs at a sensor level were obtained from the bilateral temporal lobes with the subtraction approach at 96–276 ms (the MMR time range), defined based on spatio-temporal cluster permutation analysis. In the application of the weighted-BSST/k, the deviant responses were given a constant weight using a rectangular window on the MMR time range. The ERF elicited by the weighted deviant responses demonstrated one or a few dominant components representing the MMR that fitted well with that of the sensor space analysis using the conventional subtraction approach. In contrast, infomax or weighted-infomax revealed many minor or pseudo components as constituents of the MMR. Our single-trial, contrast-free approach may assist in using the MMR in basic and clinical research, and it opens a new and potentially useful way to analyze event-related MEG/EEG data.

Enhanced symplectic geometry mode decomposition and its application to rotating machinery fault diagnosis under variable speed conditions

Tacholess order tracking (TLOT) has been one of the most powerful and applicable rotating machinery fault diagnosis methods. However, it is still a challenge to accurately estimate the instantaneous phase of the reference shaft under variable speed conditions. Although current available signal decomposition methods can deal with non-stationary vibration signal, they are probably interfered by some tough problems, such as prior knowledge requirement or heavy computational burden. In this paper, the aforementioned problems are addressed and an adaptive harmonic components extraction framework is proposed. Firstly, the vibration signal is low-pass filtered and down-sampled for computation speed acceleration. Harmonic components are subsequently extracted by enhanced symplectic geometry mode decomposition (ESGMD), which is based on Cramer-von Mises criterion. Secondly, surrogate data test is applied for pseudo components identification, thereby interferences induced by background noise can be filtered out adaptively. Finally, Hilbert transform is applied to obtain the instantaneous phase of the decomposed fundamental harmonic component, and thereby TLOT is conducted to realize fault diagnosis. The effectiveness of the proposed method has been validated by both simulated and experimental tests. The results exhibit that the proposed method outperforms conventional approaches in harmonic components extraction for rotating machinery fault diagnosis under variable speed conditions.

Simulation of the deasphalting process of crude oils: Models development and extraction conditions analysis

Heavy crude oils are under constant investigation due to light oil exhaustion. So, its use is compulsory to meet the world energy demand. Heavy crude oils present several drawbacks as high content of metals, heteroatoms, and asphaltenes, and, therefore, upgrading processes are becoming essential. A deasphalting process, conventionally used for vacuum residue upgrading, can be an interesting pretreatment to eliminate the heavier phases and ease the crude processing in conventional refining facilities. Most of the models developed for deasphalting simulation show problems to be implemented in simulation software packages. In this work, a versatile deasphalting simulation method is developed, composed by the definition of a synthetic crude oil model, formed by discrete pseudo components, and a deasphalting model approaching the process to a liquid-liquid extraction based on the thermodynamic model modified UNIFAC (Dortmund). Both models were satisfactorily validated. The deasphalting method was used to explore the solvent/crude ratio, extraction temperatures, and alternative solvents in substitution of conventional light paraffins. Higher extraction temperatures did not enhance remarkably the deasphalting process and the optimum solvent to crude ratio depends on the solvent type. Alcohols were found as promising compounds as their use is recommended by some studies and they showed great deasphalting results. • A discrete pseudocomponent-based crude oil model is developed. • A deasphalting model is proposed using a liquid-liquid equilibrium extraction and the modified UNIFAC (Dortmund) model. • The solvent selection is better from extraction yield+asphaltene reduction than from selectivity+partition coefficients. • Alcohols are found as alternative sustainable solvents for deasphalting use.

Investigation of non-isothermal pyrolysis kinetics of waste industrial hemp stem by three-parallel-reaction model

The evaluation of pyrolysis kinetics for waste industrial hemp stem (IHS) is essential to achieve the high-value utilization of agricultural waste. In present study, firstly, non-isothermal pyrolysis experiments of IHS were performed at different heating rates using a thermogravimetric analyzer. Then, the kinetic triplets (apparent activation energy, pre-exponential factor, and reaction mechanism) of the three pseudo components for IHS (hemicellulose, cellulose, and lignin) were determined by a three-parallel-reaction model. Moreover, the pyrolysis products were also characterized via FTIR and SEM. The results showed that the apparent activation energies of hemicellulose, cellulose and lignin were 86.523, 113.257 and 197.961 kJ/mol, respectively; the pre-exponential factors were 6.887 × 107, 8.179 × 109 and 1.801 × 1015 s−1, respectively; and the reaction mechanism functions were f(α) = α1.35629(1-α)0.34832[-ln(1-α)]−1.20128, f(α) = α3.42900(1-α)0.01288[-ln(1-α)]-2.84445, f(α) = α0.68738(1-α)3.09313[-ln(1-α)]-1.58522, respectively. The release temperature for volatile products of IHS pyrolysis was mainly between 440 and 840 K. IHS as an agricultural waste is a suitable feedstock to produce renewable energy.

A novel time-delayed correlation method decomposes mismatch response without using subtraction.

The mismatch response (MMR) is thought to be a neurophysiological measure of novel auditory detection that could serve as a translational biomarker of various neurological diseases. When recorded with electroencephalography (EEG) or magnetoencephalography (MEG), the MMR is traditionally extracted by subtracting the event-related potential/field (ERP/ERF) elicited in response to "deviant" sounds that occur randomly within a train of repetitive "standard" sounds. To overcome the limitations of this subtraction procedure, we propose a novel method which we call weighted-BSST/k, which uses only the deviant response to derive the MMR. We hypothesized that this novel weighted-BSST/k method highlights responses related to the detection of the deviant stimulus and is more sensitive than independent component analysis (ICA). To test this hypothesis and the validity and efficacy of the weighted-BSST/k in comparison with ICA (infomax), we evaluated the methods in 12 healthy adults. Auditory stimuli were presented at a constant rate of 2 Hz. Frequency MMRs at a sensor level were obtained from the bilateral temporal lobes with the subtraction approach at 96-276 ms (the MMR time range), defined on the basis of spatio-temporal cluster permutation analysis. In the application of the weighted-BSST/k, the deviant responses were given a constant weight on the MMR time range. The ERF elicited by the weighted deviant responses demonstrated one or a few dominant components representing the MMR with a high signal-to-noise ratio and similar topography to that of the sensor space analysis using the subtraction approach. In contrast, infomax or weighted-infomax revealed many minor or pseudo components as constituents of the MMR. Our new approach may assist in using the MMR in basic and clinical research.Clinical Relevance-Our proposed method opens a new and potentially useful way to analyze event-related MEG/EEG data.

Analytical and numerical modeling for the assessment of CO2 storage in the Pariñas geological formation - Talara, Peru

This research evaluates the CO2 storage capacity of the Pariñas Formation belonging to the Talara basin in Peru through analytical modeling based on mass balance equations and numerical modeling using IMEX CMG. Pariñas Formation has several depleted hydrocarbon reservoirs that presents favorable conditions for CO2 geological storage. It has an average porosity of 17.6% and a permeability of 640 mD in the horizontal direction consisting of sandstones with interspersed lutites layers. The study evaluates the depleted Bellavista oil deposits involving CO2 storage capacity estimation with CO2 and reservoir fluid (oil and water) interaction. It involves numerical modeling based on the reservoirs properties and CO2 injection simulation not exceeding the fracture pressure of the reservoir rock. This approach is the first one carried out in Peru and provides the chance to evaluate the CO2 storage capacity in a hydrocarbon reservoir in this part of the world, as a strategy to mitigate future global change impacts. The results indicate a storage capacity of 35.37 million tons of CO2, approximately. Besides, the sandstone reservoir of the Pariñas geological formation has adequate characteristics to serve as a CO2 storage reservoir. C30+ pseudo component shows greater sensitivity in its properties (temperature and critical pressure) adjusting the fluid properties with the experimental data (saturation pressure, viscosity and minimum miscibility pressure).

Simulation and optimization of continuous catalytic reforming: Reducing energy cost and coke formation

Continuous catalytic naphtha reformers are one of the main refinery units producing hydrogen. Reliable and comprehensive modeling of such a complex and integrated refinery unit plays a pivotal role in optimization to increase the efficiency of the process. A reaction network with 26 pseudo components and 58 reactions, considering coke formation and catalyst activity, was proposed to predict the outlet compositions of reactors in more detail. The whole unit, including reaction and purification sections, was simulated to cover all products. NOMAD optimizer, with the mesh adaptive direct search algorithm, is used to minimize energy costs. Non-linear constraints were defined to guarantee the quality of the final products. The optimized decision variables reduced the energy cost by 13.5%, mainly caused by a significant decline in natural gas consumption. The simulation also indicated an increase of 4800 ton/y in reformate production, which the product is rich in aromatics. By contrast, LPG, hydrogen-rich gas, and coke production dropped by nearly 4355, 321, and 127 ton/y, respectively. The coke production decline can significantly increase the catalyst lifetime and decrease the operating cost of the catalyst regeneration unit.

Combustion Behavior of Algal Biochars Obtained at Different Pyrolysis Heating Rates.

In this work, the combustion performance of Chlorella vulgaris (CV), Dunaliella salina (DS), and Haematococcus pluvialis (HP) algal biochars was analyzed based on the multicomponent method. The biochars were obtained via nonisothermal pyrolysis of raw algal biomasses at three different heating rates (i.e., 30, 40, and 50 °C/min), and biochar combustion was performed from 200 to 700 °C at a heating rate of 5 °C/min. The complex oxidative reaction of algal biochar was resolved into combined reactions of multiple pseudo-components based on the peak deconvolution method using a bi-Gaussian model. The activation energies (Ea) for each pseudo-component (PC) of all biochar samples were calculated by the Coats–Redfern isoconversional method and four kinetic models (i.e., diffusion, nucleation, order-based, and shrinking core models). The results showed that the highest Ea values were predicted by the diffusion model. Except that the Ea for the first PC of CV biochar decreased by 16.45%, the Ea values for all other biochar samples generally increased with increasing the pyrolysis heating rate. Moreover, when the diffusion model was used, the Ea for the second PC of CV biochar increased by 50.87%, that for the first PC of DS biochar increased by 16.85%, and those for the first and third PCs of HP biochar increased by 4.66 and 11.66%, respectively. In addition, the combustibility index (Sn) was evaluated based on the ignition and burnout temperatures as well as the mean and maximum weight loss rates. Generally, the combustion performance of all biochar samples was good at a low temperature but deteriorated toward a high temperature. As the pyrolysis heating rate increases, an overall increase in the combustion quality was also seen for the second PC of CV biochar and the first PCs of DS and HP biochars because their Sn increased from 2.70 × 10–15 to 3.07 × 10–15 °C–5, 2.53 × 10–13 to 3.88 × 10–13 °C–5, and 3.00 × 10–13 to 3.26 × 10–13 °C–5, respectively.

Kinetic study and Modeling of heavy Naphtha Catalytic Reforming process in AL-Daura Refinery

In the present work, kinetics and modeling of heavy naphtha catalytic reforming process in Al-Daura refinery-Midland refineries Company were studied. A proposed reaction scheme involving (15 pseudo components) connected together by a network of 30 reactions for components in the C6-C8+ range have been modeled. In the present work, kinetics and modeling of heavy naphtha catalytic reforming process in AL-Daura refinery-Midland refineries Company were studied. A proposed reaction scheme involving (15 pseudo components) connected together by a network of 30 reactions for components in the C6-C8+ range have been modeled. The proposed model has been solved numerically using the 4th order Runge–Kutta approach. Alteration of components and temperature, with time and reactor length was evaluated. Results showed that the rate of formation of aromatics is becoming slower as the reactants proceed to the third reactor. The catalytic reaction rates in the reformer are well represented by the Hougen-Watson Langmur-Hinshelwood (HWLH) type form. The deactivation of catalyst causes the reactor behavior to continue changing over a longer period of time. This clearly seems to pay off in the scenario where coke deposition plays such a major role. It was also found that the rate of coke formation increases with the progress from first to the last bed, so keeping a decreasing inlet temperature profile from first to the last bed would lead to more uniform coke content in each bed. The production rate of reformate has a negative impact on the octane number. Temperature drop across the first reactor (~ 45oC) is larger than the temperature drops across the other two reactors (10-12oC). This could be related to the endothermic reaction rate which is faster in the first reactor. The results show that perfect agreement of temperatures, compositions, and fractions molar flow rate at the exit of the third reactor is obtained between predicted values and industrial values.This confirmed the reliability of the present model.

Comprehensive kinetic study of Imperata Cylindrica pyrolysis via Asym2sig deconvolution and combined kinetics

This study examined the non-isothermal kinetics of the slow pyrolysis of Imperata Cylindrica (IC). Pyrolysis conditions were developed under the pure N2 flow and non-isothermal conditions at the heating rates of 2.5, 5, 10, and 17.5 K/min and over the temperature range of 303–1173 K. The IC pyrolysis profiles could be identified into three parallel reactions, each of which corresponded to pseudo-hemicelluloses (P-Hem), pseudo-cellulose (P-Cell), and pseudo-lignin (P-Lig) decomposition. A systematic kinetic study of the pyrolysis of IC via thermogravimetric analysis (TGA) deconvolution using Asymmetric Double Sigmoidal (Asym2sig), Friedman differential iso-conversional and combined kinetics of biomass pseudo-components was carried out. The kinetics parameters of pseudo components fitted well with the pyrolysis experimental data for all the heating rates. Differential master-plots showed that the reaction mechanisms for pseudo hemicellulose (P-Hem) and pseudo cellulose (P-Cell) were diffusional and order based, and high order based (3rd order) for the pseudo lignin (P-Lig). Mechanism of P-Hem, P-Cell and P-Lig could be further reconstructed to Sestak and Berggren model of fα=α-0.98751-α1.325-ln⁡(1-α)0.0209,fα=α0.33131-α1.4731-ln⁡(1-α)0.0215 and fα=α-2.95511-α2.7642-ln⁡(1-α)0.0074, respectively. The combined kinetic reported the activation energies of pseudo-components were as 194.709 kJ/mol, 179.968 kJ/mol and 219.226 kJ/mol for P-Hem, P-Cell and P-Lig, respectively.

Gearbox fault diagnosis method based on the fusion of EEMD and improved Elman-NN

In connection with the complex operating conditions of gearbox, multiple vibration excitation sources, and difficulty in extracting vibration signal fault features, a novel method of gearbox fault diagnosis is proposed. based on the fusion of EEMD and improved Elman neural network (Elman-NN) is developed. The wavelet packet is utilized to denoise the collected vibration signals of four different types of gearboxes: broken teeth, cracks, wear, and normal, and then use the EEMD method to decompose the denoised vibration signals, and use the correlation coefficient criterion means to carry out the IMF pseudo component elimination, and then get a more effective signal. Calculate the energy feature of the effective signal and use it as the enter feature of the Elman-NN. Based on standard Elman-NN, a self-feedback factor β is added to construct a reformed Elman-NN. Experimental results indicate that compared with the standardized Elman-NN, the improved Elman-NN has higher diagnostic accuracy and diagnostic efficiency.

Fuzzy logic control of a catalytic naphtha unit

This work examines the fuzzy logic-based control of a catalytic reformer. The control process requires development of an exact process model valid over a wide range of operating conditions. Two control methods, proportional integral derivative (PID) and Fuzzy-PID, were applied to determine the optimal operating conditions. The output temperature from the feedback fuzzy controller was sent to the PID controllers as a setpoint in the heating system loop, and two fuzzy logic systems, one in the forward path and one in the feedback path were developed to give setpoints for temperature control loops in the four reactors. A fuzzy logic-based optimal control scheme was established to increase the aromatics yield, subject to constraints on the inlet temperature of the reactors. A rigorous kinetic model was then developed by expressing the heat and mass balances under unsteady state conditions. This model was used to determine the temperature and concentration profiles of three main hydrocarbons, naphthenes, paraffins, and aromatics, across the four reactors. A reaction scheme involving 27 pseudo components connected using a network of 71 reactions for components in a wide range of carbon numbers was thus modelled. The simulation results for the model were compared with previous studies to validate the model, and good agreement was found between the reformate composition of the proposed model and the plant reformate composition and temperature. The simulation results also showed that the PID –Fuzzy controller is accurate but that it requires additional time to reach a steady state value.