929 resultados para Adsorption. Zeolite 13X. Langmuir model. Dynamic modeling. Pyrolysis of sewage sludge
Resumo:
The objective of this study was to produce biofuels (bio-oil and gas) from the thermal treatment of sewage sludge in rotating cylinder, aiming industrial applications. The biomass was characterized by immediate and instrumental analysis (elemental analysis, scanning electron microscopy - SEM, X-ray diffraction, infrared spectroscopy and ICP-OES). A kinetic study on non-stationary regime was done to calculate the activation energy by Thermal Gravimetric Analysis evaluating thermochemical and thermocatalytic process of sludge, the latter being in the presence of USY zeolite. As expected, the activation energy evaluated by the mathematical model "Model-free kinetics" applying techniques isoconversionais was lowest for the catalytic tests (57.9 to 108.9 kJ/mol in the range of biomass conversion of 40 to 80%). The pyrolytic plant at a laboratory scale reactor consists of a rotating cylinder whose length is 100 cm with capable of processing up to 1 kg biomass/h. In the process of pyrolysis thermochemical were studied following parameters: temperature of reaction (500 to 600 ° C), flow rate of carrier gas (50 to 200 mL/min), frequency of rotation of centrifugation for condensation of bio-oil (20 to 30 Hz) and flow of biomass (4 and 22 g/min). Products obtained during the process (pyrolytic liquid, coal and gas) were characterized by classical and instrumental analytical techniques. The maximum yield of liquid pyrolytic was approximately 10.5% obtained in the conditions of temperature of 500 °C, centrifugation speed of 20 Hz, an inert gas flow of 200 mL/min and feeding of biomass 22 g/min. The highest yield obtained for the gas phase was 23.3% for the temperature of 600 °C, flow rate of 200 mL/min inert, frequency of rotation of the column of vapor condensation 30 Hz and flow of biomass of 22 g/min. The non-oxygenated aliphatic hydrocarbons were found in greater proportion in the bio-oil (55%) followed by aliphatic oxygenated (27%). The bio-oil had the following characteristics: pH 6.81, density between 1.05 and 1.09 g/mL, viscosity between 2.5 and 3.1 cSt and highest heating value between 16.91 and 17.85 MJ/ kg. The main components in the gas phase were: H2, CO, CO2 and CH4. Hydrogen was the main constituent of the gas mixture, with a yield of about 46.2% for a temperature of 600 ° C. Among the hydrocarbons formed, methane was found in higher yield (16.6%) for the temperature 520 oC. The solid phase obtained showed a high ash content (70%) due to the abundant presence of metals in coal, in particular iron, which was also present in bio-oil with a rate of 0.068% in the test performed at a temperature of 500 oC.
Resumo:
A direct version of the boundary element method (BEM) is developed to model the stationary dynamic response of reinforced plate structures, such as reinforced panels in buildings, automobiles, and airplanes. The dynamic stationary fundamental solutions of thin plates and plane stress state are used to transform the governing partial differential equations into boundary integral equations (BIEs). Two sets of uncoupled BIEs are formulated, respectively, for the in-plane state ( membrane) and for the out-of-plane state ( bending). These uncoupled systems are joined to formamacro-element, in which membrane and bending effects are present. The association of these macro-elements is able to simulate thin-walled structures, including reinforced plate structures. In the present formulation, the BIE is discretized by continuous and/or discontinuous linear elements. Four displacement integral equations are written for every boundary node. Modal data, that is, natural frequencies and the corresponding mode shapes of reinforced plates, are obtained from information contained in the frequency response functions (FRFs). A specific example is presented to illustrate the versatility of the proposed methodology. Different configurations of the reinforcements are used to simulate simply supported and clamped boundary conditions for the plate structures. The procedure is validated by comparison with results determined by the finite element method (FEM).
Resumo:
The AlMCM-41 material with Si/Al=50 was synthesized by hydrothermal method, using cethyltrimethylammonium as template. The protonic H-AlMCM-41 acid form was obtained by ion exchange with ammonium chloride solution and subsequent calcination. The characterization of the material by several techniques showed that a good-quality MCM-41 material was obtained. High-density polyethylene (HDPE) has been submitted to thermal degradation alone, and in presence of the exchanged H-AlMCM-41 catalyst at a concentration of 1: 1 in mass (H-AlMCM-41/HDPE). The reactor was connected on line to a gas chromatograph connected to a mass spectrometer. This process was evaluated by thermogravimetry (TG), from 350 to 600degreesC, under helium dynamic atmosphere, with heating rates of 5.0; 10.0 and 20.0 degreesC/min. From TG curves, the activation energy, calculated using a multiple heating rate integral kinetic method, decreased from 225.5 KJ.mol(-1), for the pure polymer (HDPE), to 184.7 KJ.mol(-1), in the presence of the catalyst (H-AlMCM-41/HDPE).
Resumo:
One of the most important subjects of debate in the formation of the solar system is the origin of Earth's water. Comets have long been considered as the most likely source of the delivery of water to Earth. However, elemental and isotopic arguments suggest a very small contribution from these objects. Other sources have also been proposed, among which local adsorption of water vapor onto dust grains in the primordial nebula and delivery through planetesimals and planetary embryos have become more prominent. However, no sole source of water provides a satisfactory explanation for Earth's water as a whole. In view of that, using numerical simulations, we have developed a compound model incorporating both the principal endogenous and exogenous theories, and investigating their implications for terrestrial planet formation and water delivery. Comets are also considered in the final analysis, as it is likely that at least some of Earth's water has cometary origin. We analyze our results comparing two different water distribution models, and complement our study using the D/H ratio, finding possible relative contributions from each source and focusing on planets formed in the habitable zone. We find that the compound model plays an important role by showing greater advantage in the amount and time of water delivery in Earth-like planets. © 2013. The American Astronomical Society. All rights reserved.
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
This work investigated the effects of temperature and of rate of heating on the kinetic parameters of pyrolysis of castor beans presscake, a byproduct generated in the biodiesel production process. Pyrolysis process was investigated by thermogravimetric analysis, and parameters were obtained from nonisothermal experiments. The results obtained from the process of thermal decomposition indicated the elimination of humidity and the decomposition of organic components of the biomass. DTG curves showed that the heating rate affects the temperature of maximum decomposition of the material. Kinetic parameters such as activation energy and pre-exponential factor were obtained by model-free methods proposed by Flynn–Wall–Ozawa (FWO), Kissinger–Akahira–Sunose (KAS), and Kissinger. Experimental results showed that the kinetic parameters values of the FWO and KAS methods display good agreement and can be used to understand the mechanism of degradation of the cake. In a generalized way, the results contribute to better understanding of the processes of biomass pyrolysis.
Resumo:
Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.
Generalizing the dynamic field theory of spatial cognition across real and developmental time scales
Resumo:
Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.
Resumo:
We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.
Resumo:
Parallel kinematic structures are considered very adequate architectures for positioning and orienti ng the tools of robotic mechanisms. However, developing dynamic models for this kind of systems is sometimes a difficult task. In fact, the direct application of traditional methods of robotics, for modelling and analysing such systems, usually does not lead to efficient and systematic algorithms. This work addre sses this issue: to present a modular approach to generate the dynamic model and through some convenient modifications, how we can make these methods more applicable to parallel structures as well. Kane’s formulati on to obtain the dynamic equations is shown to be one of the easiest ways to deal with redundant coordinates and kinematic constraints, so that a suitable c hoice of a set of coordinates allows the remaining of the modelling procedure to be computer aided. The advantages of this approach are discussed in the modelling of a 3-dof parallel asymmetric mechanisms.
Resumo:
Analytical pyrolysis was used to investigate the formation of diketopiperazines (DKPs) which are cyclic dipeptides formed from the thermal degradation of proteins. A quali/quantitative procedure was developed combining microscale flash pyrolysis at 500 °C with gas chromatography-mass spectrometry (GC-MS) of DKPs trapped onto an adsorbent phase. Polar DKPs were silylated prior to GC-MS. Particular attention was paid to the identification of proline (Pro) containing DKPs due to their greater facility of formation. The GC-MS characteristics of more than 80 original and silylated DKPs were collected from the pyrolysis of sixteen linear dipeptides and four model proteins (e.g. bovine serum albumin, BSA). The structure of a novel DKP, cyclo(pyroglutamic-Pro) was established by NMR and ESI-MS analysis, while the structures of other novel DKPs remained tentative. DKPs resulted rather specific markers of amino acid sequence in proteins, even though the thermal degradation of DKPs should be taken into account. Structural information of DKPs gathered from the pyrolysis of model compounds was employed to the identification of these compounds in the pyrolysate of proteinaceous samples, including intrinsecally unfolded protein (IUP). Analysis of the liquid fraction (bio-oil) obtained from the pyrolysis of microalgae Nannochloropsis gaditana, Scenedesmus spp with a bench scale reactor showed that DKPs constituted an important pool of nitrogen-containing compounds. Conversely, the level of DKPs was rather low in the bio-oil of Botryococcus braunii. The developed micropyrolysis procedure was applied in combination with thermogravimetry (TGA) and infrared spectroscopy (FT-IR) to investigate surface interaction between BSA and synthetic chrysotile. The results showed that the thermal behavior of BSA (e.g. DKPs formation) was affected by the different form of doped synthetic chrysotile. The typical DKPs evolved from collagen were quantified in the pyrolysates of archaeological bones from Vicenne Necropolis in order to evaluate their conservation status in combination with TGA, FTIR and XRD analysis.
Resumo:
Biodiesel represents a possible substitute to the fossil fuels; for this reason a good comprehension of the kinetics involved is important. Due to the complexity of the biodiesel mixture a common practice is the use of surrogate molecules to study its reactivity. In this work are presented the experimental and computational results obtained for the oxidation and pyrolysis of methane and methyl formate conducted in a plug flow reactor. The work was divided into two parts: the first one was the setup assembly whilst, in the second one, was realized a comparison between the experimental and model results; these last was obtained using models available in literature. It was started studying the methane since, a validate model was available, in this way was possible to verify the reliability of the experimental results. After this first study the attention was focused on the methyl formate investigation. All the analysis were conducted at different temperatures, pressures and, for the oxidation, at different equivalence ratios. The results shown that, a good comprehension of the kinetics is reach but efforts are necessary to better evaluate kinetics parameters such as activation energy. The results even point out that the realized setup is adapt to study the oxidation and pyrolysis and, for this reason, it will be employed to study a longer chain esters with the aim to better understand the kinetic of the molecules that are part of the biodiesel mixture.
Resumo:
A diesel oxidation catalyst (DOC) with a catalyzed diesel particulate filter (CPF) is an effective exhaust aftertreatment device that reduces particulate emissions from diesel engines, and properly designed DOC-CPF systems provide passive regeneration of the filter by the oxidation of PM via thermal and NO2/temperature-assisted means under various vehicle duty cycles. However, controlling the backpressure on engines caused by the addition of the CPF to the exhaust system requires a good understanding of the filtration and oxidation processes taking place inside the filter as the deposition and oxidation of solid particulate matter (PM) change as functions of loading time. In order to understand the solid PM loading characteristics in the CPF, an experimental and modeling study was conducted using emissions data measured from the exhaust of a John Deere 6.8 liter, turbocharged and after-cooled engine with a low-pressure loop EGR system and a DOC-CPF system (or a CCRT® - Catalyzed Continuously Regenerating Trap®, as named by Johnson Matthey) in the exhaust system. A series of experiments were conducted to evaluate the performance of the DOC-only, CPF-only and DOC-CPF configurations at two engine speeds (2200 and 1650 rpm) and various loads on the engine ranging from 5 to 100% of maximum torque at both speeds. Pressure drop across the DOC and CPF, mass deposited in the CPF at the end of loading, upstream and downstream gaseous and particulate emissions, and particle size distributions were measured at different times during the experiments to characterize the pressure drop and filtration efficiency of the DOCCPF system as functions of loading time. Pressure drop characteristics measured experimentally across the DOC-CPF system showed a distinct deep-bed filtration region characterized by a non-linear pressure drop rise, followed by a transition region, and then by a cake-filtration region with steadily increasing pressure drop with loading time at engine load cases with CPF inlet temperatures less than 325 °C. At the engine load cases with CPF inlet temperatures greater than 360 °C, the deep-bed filtration region had a steep rise in pressure drop followed by a decrease in pressure drop (due to wall PM oxidation) in the cake filtration region. Filtration efficiencies observed during PM cake filtration were greater than 90% in all engine load cases. Two computer models, i.e., the MTU 1-D DOC model and the MTU 1-D 2-layer CPF model were developed and/or improved from existing models as part of this research and calibrated using the data obtained from these experiments. The 1-D DOC model employs a three-way catalytic reaction scheme for CO, HC and NO oxidation, and is used to predict CO, HC, NO and NO2 concentrations downstream of the DOC. Calibration results from the 1-D DOC model to experimental data at 2200 and 1650 rpm are presented. The 1-D 2-layer CPF model uses a ‘2-filters in series approach’ for filtration, PM deposition and oxidation in the PM cake and substrate wall via thermal (O2) and NO2/temperature-assisted mechanisms, and production of NO2 as the exhaust gas mixture passes through the CPF catalyst washcoat. Calibration results from the 1-D 2-layer CPF model to experimental data at 2200 rpm are presented. Comparisons of filtration and oxidation behavior of the CPF at sample load-cases in both configurations are also presented. The input parameters and selected results are also compared with a similar research work with an earlier version of the CCRT®, to compare and explain differences in the fundamental behavior of the CCRT® used in these two research studies. An analysis of the results from the calibrated CPF model suggests that pressure drop across the CPF depends mainly on PM loading and oxidation in the substrate wall, and also that the substrate wall initiates PM filtration and helps in forming a PM cake layer on the wall. After formation of the PM cake layer of about 1-2 µm on the wall, the PM cake becomes the primary filter and performs 98-99% of PM filtration. In all load cases, most of PM mass deposited was in the PM cake layer, and PM oxidation in the PM cake layer accounted for 95-99% of total PM mass oxidized during loading. Overall PM oxidation efficiency of the DOC-CPF device increased with increasing CPF inlet temperatures and NO2 flow rates, and was higher in the CCRT® configuration compared to the CPF-only configuration due to higher CPF inlet NO2 concentrations. Filtration efficiencies greater than 90% were observed within 90-100 minutes of loading time (starting with a clean filter) in all load cases, due to the fact that the PM cake on the substrate wall forms a very efficient filter. A good strategy for maintaining high filtration efficiency and low pressure drop of the device while performing active regeneration would be to clean the PM cake filter partially (i.e., by retaining a cake layer of 1-2 µm thickness on the substrate wall) and to completely oxidize the PM deposited in the substrate wall. The data presented support this strategy.
Resumo:
Dynamic models for electrophoresis are based upon model equations derived from the transport concepts in solution together with user-inputted conditions. They are able to predict theoretically the movement of ions and are as such the most versatile tool to explore the fundamentals of electrokinetic separations. Since its inception three decades ago, the state of dynamic computer simulation software and its use has progressed significantly and Electrophoresis played a pivotal role in that endeavor as a large proportion of the fundamental and application papers were published in this periodical. Software is available that simulates all basic electrophoretic systems, including moving boundary electrophoresis, zone electrophoresis, ITP, IEF and EKC, and their combinations under almost exactly the same conditions used in the laboratory. This has been employed to show the detailed mechanisms of many of the fundamental phenomena that occur in electrophoretic separations. Dynamic electrophoretic simulations are relevant for separations on any scale and instrumental format, including free-fluid preparative, gel, capillary and chip electrophoresis. This review includes a historical overview, a survey of current simulators, simulation examples and a discussion of the applications and achievements of dynamic simulation.