An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Results of the IEA round robin on viscosity and stability of fast pyrolysis bio-oils

An international round robin study of the stability of fast pyrolysis bio-oil was undertaken. Fifteen laboratories in five different countries contributed. Two bio-oil samples were distributed to the laboratories for stability testing and further analysis. The stability test was defined in a method provided with the bio-oil samples. Viscosity measurement was a key input. The change in viscosity of a sealed sample of bio-oil held for 24 h at 80 °C was the defining element of stability. Subsequent analyses included ultimate analysis, density, moisture, ash, filterable solids, and TAN/pH determination, and gel permeation chromatography. The results showed that kinematic viscosity measurement was more generally conducted and more reproducibly performed versus dynamic viscosity measurement. The variation in the results of the stability test was great and a number of reasons for the variation were identified. The subsequent analyses proved to be at the level of reproducibility, as found in earlier round robins on bio-oil analysis. Clearly, the analyses were more straightforward and reproducible with a bio-oil sample low in filterable solids (0.2%), compared to one with a higher (2%) solids loading. These results can be helpful in setting standards for use of bio-oil, which is just coming into the marketplace. © 2012 American Chemical Society.

Production of liquid fuel and activated carbon from mahogany seed by using pyrolysis technology

The renovation of biomass waste in the form of Mahogany seed waste into bio-fuel as well as activated carbon by fixed bed pyrolysis reactor has been taken into consideration in this study. The mahogany seed in particle form is pyrolyzed in an enormously heated fixed bed reactor with nitrogen as the carrier gas. The reactor is heated from 4000C to 6000C using a external heater in which rice husk and charcoal are used as the heater biomass fuel. Reactor bed temperature, running time and feed particle size have been varied to get the optimum operating conditions of the system. The parameters are found to influence the product yields to a large extent. A maximum liquid and char yield are 49 wt. % and 35 wt. % respectively obtained at a reactor bed temperature 5000C when the running time is 90 minutes. Acquired pyrolyzed oil at these optimal process conditions were analyzed for some of their properties as an alternative fuel. The oil possesses comparable flame temperature, favorable flash point and reasonable viscosity along with somewhat higher density. The kinematic viscosity of the derived fuel is 3.8 cSt and density is 1525 kg/m3. The higher calorific value is found 32.4 MJ/kg which is significantly higher than other biomass derived fuel. Moderate adsorption capacity of the prepared activated carbon in case of methyl blue & tea water was also revealed.

Influence of fatty acid structure on fuel properties of algae derived biodiesel

Physical and chemical properties of biofuel are influenced by structural features of fatty acid such as chain length, degree of unsaturation and branching of the chain. A simple and reliable calculation method to estimate fuel property is therefore needed to avoid experimental testing which is difficult, costly and time consuming. Typically in commercial biodiesel production such testing is done for every batch of fuel produced. In this study 9 different algae species were selected that were likely to be suitable for subtropical climates. The fatty acid methyl esters (FAMEs) of all algae species were analysed and the fuel properties like cetane number (CN), cold filter plugging point (CFPP), kinematic viscosity (KV), density and higher heating value (HHV) were determined. The relation of each fatty acid with particular fuel property is analysed using multivariate and multi-criteria decision method (MCDM) software. They showed that some fatty acids have major influences on the fuel properties whereas others have minimal influence. Based on the fuel properties and amounts of lipid content rank order is drawn by PROMETHEE-GAIA which helped to select the best algae species for biodiesel production in subtropical climates. Three species had fatty acid profiles that gave the best fuel properties although only one of these (Nannochloropsis oculata) is considered the best choice because of its higher lipid content.

Microalgal species selection for biodiesel production based on fuel properties derived from fatty acid profiles

Physical and chemical properties of biodiesel are influenced by structural features of the fatty acids, such as chain length, degree of unsaturation and branching of the carbon chain. This study investigated if microalgal fatty acid profiles are suitable for biodiesel characterization and species selection through Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) analysis. Fatty acid methyl ester (FAME) profiles were used to calculate the likely key chemical and physical properties of the biodiesel [cetane number (CN), iodine value (IV), cold filter plugging point, density, kinematic viscosity, higher heating value] of nine microalgal species (this study) and twelve species from the literature, selected for their suitability for cultivation in subtropical climates. An equal-parameter weighted (PROMETHEE-GAIA) ranked Nannochloropsis oculata, Extubocellulus sp. and Biddulphia sp. highest; the only species meeting the EN14214 and ASTM D6751-02 biodiesel standards, except for the double bond limit in the EN14214. Chlorella vulgaris outranked N. oculata when the twelve microalgae were included. Culture growth phase (stationary) and, to a lesser extent, nutrient provision affected CN and IV values of N. oculata due to lower eicosapentaenoic acid (EPA) contents. Application of a polyunsaturated fatty acid (PUFA) weighting to saturation led to a lower ranking of species exceeding the double bond EN14214 thresholds. In summary, CN, IV, C18:3 and double bond limits were the strongest drivers in equal biodiesel parameter-weighted PROMETHEE analysis.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Effect of temperature and moisture on high pressure lipid/oil extraction from microalgae

Commercially viable carbon–neutral biodiesel production from microalgae has potential for replacing depleting petroleum diesel. The process of biodiesel production from microalgae involves harvesting, drying and extraction of lipids which are energy- and cost-intensive processes. The development of effective large-scale lipid extraction processes which overcome the complexity of microalgae cell structure is considered one of the most vital requirements for commercial production. Thus the aim of this work was to investigate suitable extraction methods with optimised conditions to progress opportunities for sustainable microalgal biodiesel production. In this study, the green microalgal species consortium, Tarong polyculture was used to investigate lipid extraction with hexane (solvent) under high pressure and variable temperature and biomass moisture conditions using an Accelerated Solvent Extraction (ASE) method. The performance of high pressure solvent extraction was examined over a range of different process and sample conditions (dry biomass to water ratios (DBWRs): 100%, 75%, 50% and 25% and temperatures from 70 to 120 ºC, process time 5–15 min). Maximum total lipid yields were achieved at 50% and 75% sample dryness at temperatures of 90–120 ºC. We show that individual fatty acids (Palmitic acid C16:0; Stearic acid C18:0; Oleic acid C18:1; Linolenic acid C18:3) extraction optima are influenced by temperature and sample dryness, consequently affecting microalgal biodiesel quality parameters. Higher heating values and kinematic viscosity were compliant with biodiesel quality standards under all extraction conditions used. Our results indicate that biodiesel quality can be positively manipulated by selecting process extraction conditions that favour extraction of saturated and mono-unsaturated fatty acids over optimal extraction conditions for polyunsaturated fatty acids, yielding positive effects on cetane number and iodine values. Exceeding biodiesel standards for these two parameters opens blending opportunities with biodiesels that fall outside the minimal cetane and maximal iodine values.

Investigation of the effects of the fatty acid profile on fuel properties using a Multi-Criteria Decision Analysis

The structural features of fatty acids in biodiesel, including degree of unsaturation, percentage of saturated fatty acids and average chain length, influence important fuel properties such as cetane number, iodine value, density, kinematic viscosity, higher heating value and oxidation stability. The composition of fatty acid esters within the fuel should therefore be in the correct ratio to ensure fuel properties are within international biodiesel standards such as ASTM 6751 or EN 14214. This study scrutinises the influence of fatty acid composition and individual fatty acids on fuel properties. Fuel properties were estimated based on published equations, and measured according to standard procedure ASTM D6751 and EN 14214 to confirm the influences of the fatty acid profile. Based on fatty acid profile-derived calculations, the cetane number of the microalgal biodiesel was estimated to be 11.6, but measured 46.5, which emphasises the uncertainty of the method used for cetane number calculation. Multi-criteria decision analysis (MCDA), PROMETHEE-GAIA, was used to determine the influence of individual fatty acids on fuel properties in the GAIA plane. Polyunsaturated fatty acids increased the iodine value and had a negative influence on cetane number. Kinematic viscosity was negatively influenced by some long chain polyunsaturated fatty acids such as C20:5 and C22:6 and some of the more common saturated fatty acids C14:0 and C18:0. The positive impact of average chain length on higher heating value was also confirmed in the GAIA plane

Magnetorotational instability driven dynamos at low magnetic Prandtl numbers

Numerical simulations of the magnetorotational instability (MRI) with zero initial net flux in a non-stratified isothermal cubic domain are used to demonstrate the importance of magnetic boundary conditions. In fully periodic systems the level of turbulence generated by the MRI strongly decreases as the magnetic Prandtl number (Pm), which is the ratio of kinematic viscosity and magnetic diffusion, is decreased. No MRI or dynamo action below Pm=1 is found, agreeing with earlier investigations. Using vertical field conditions, which allow magnetic helicity fluxes out of the system, the MRI is found to be excited in the range 0.1

Shear alignment of a disordered lamellar mesophase

The shear alignment of an initially disordered lamellar phase is examined using lattice Boltzmann simulations of a mesoscopic model based on a free-energy functional for the concentration modulation. For a small shear cell of width 8 lambda, the qualitative features of the alignment process are strongly dependent on the Schmidt number Sc = nu/D (ratio of kinematic viscosity and mass diffusion coefficient). Here, lambda is the wavelength of the concentration modulation. At low Schmidt number, it is found that there is a significant initial increase in the viscosity, coinciding with the alignment of layers along the extensional axis, followed by a decrease at long times due to the alignment along the flow direction. At high Schmidt number, alignment takes place due to the breakage and reformation of layers because diffusion is slow compared to shear deformation; this results in faster alignment. The system size has a strong effect on the alignment process; perfect alignment takes place for a small systems of width 8 lambda and 16 lambda, while a larger system of width 32 lambda does not align completely even at long times. In the larger system, there appears to be a dynamical steady state in which the layers are not perfectly aligned-where there is a balance between the annealing of defects due to shear and the creation due to an instability of the aligned lamellar phase under shear. We observe two types of defect creation mechanisms: the buckling instability under dilation, which was reported earlier, as well as a second mechanism due to layer compression.

Prediction of reaeration rates in square, stirred tanks

Experiments were conducted on the oxygen transfer coefficient, k(L)a(20), through surface aeration in geometrically similar square tanks, with a rotor of diameter D fitted with six flat blades. An optimal geometric similarity of various linear dimensions, which produced maximum k(L)a(20) for any rotational speed of rotor N by an earlier study, was maintained. A simulation equation uniquely correlating k = k(L)a(20)(nu/g(2))(1/3) (nu and g are kinematic viscosity of water and gravitational constant, respectively), and a parameter governing the theoretical power per unit volume, X = (ND2)-D-3/(g(4/3)nu(1/3)), is developed. Such a simulation equation can be used to predict maximum k for any N in any size of such geometrically similar square tanks. An example illustrating the application of results is presented. Also, it has been established that neither the Reynolds criterion nor the Froude criterion is singularly valid to simulate either k or K = k(L)a(20)/N, simultaneously in all the sizes of tanks, even through they are geometrically similar. Occurrence of "scale effects" due to the Reynolds and the Froude laws of similitude on both k and K are also evaluated.

Continuous distribution kinetics for ultrasonic degradation of poly(methyl methacrylate)

Ultrasonic degradation of poly(methyl methacrylate) (PMMA) was carried out in several solvents and some mixtures of solvents. The time evolution of molecular weight distribution (MWD), determined by gel permeation chromatography, is analysed by continuous distribution kinetics. The rate coefficients for polymer degradation are determined for each solvent. The variation of rate coefficients is correlated with the vapour pressure of the solvent, kinematic viscosity of the solution and solvent-polymer interaction parameters. The vapour pressure and the kinematic viscosity of the solution are found to be more critical than other parameters (such as the Huggins and Flory-Huggins constants) in determining the degradation rates. (C) 2001 Society of Chemical Industry.

Effect of solvent on the ultrasonic degradation of poly(vinyl acetate)

The ultrasonic degradation of poly(vinyl acetate) was carried out in six different solvents and two mixtures of solvents. The evolution of molecular weight distribution (MWD) with time was determined with gel permeation chromatography. The observed MWDs were analyzed by continuous distribution kinetics. A stoichiometric kernel that accounts for preferential mid-point breakage of the polymer chains was used. The degradation rate coefficient of the polymer in each solvent was determined from the model. The variations of rate coefficients were correlated with vapor pressure of the solvent, the Flory–Huggins polymer–solvent interaction parameter and the kinematic viscosity of the solution. A lower saturation vapor pressure resulted in higher degradation rates of the polymer. The degradation rate increased with increasing kinematic viscosity.

Chapman-Enskog analysis for finite-volume formulation of lattice Boltzmann equation

The classical Chapman-Enskog expansion is performed for the recently proposed finite-volume formulation of lattice Boltzmann equation (LBE) method D.V. Patil, K.N. Lakshmisha, Finite volume TVD formulation of lattice Boltzmann simulation on unstructured mesh, J. Comput. Phys. 228 (2009) 5262-5279]. First, a modified partial differential equation is derived from a numerical approximation of the discrete Boltzmann equation. Then, the multi-scale, small parameter expansion is followed to recover the continuity and the Navier-Stokes (NS) equations with additional error terms. The expression for apparent value of the kinematic viscosity is derived for finite-volume formulation under certain assumptions. The attenuation of a shear wave, Taylor-Green vortex flow and driven channel flow are studied to analyze the apparent viscosity relation.

After transition in a soft-walled microchannel

In comparison to the flow in a rigid channel, there is a multifold reduction in the transition Reynolds number for the flow in a microchannel when one of the walls is made sufficiently soft, due to a dynamical instability induced by the fluid-wall coupling, as shown by Verma & Kumaran (J. Fluid Mech., vol. 727, 2013, pp. 407-455). The flow after transition is characterised using particle image velocimetry in the x-y plane, where x is the streamwise direction and y is the cross-stream coordinate along the small dimension of the channel of height 0.2-0.3 mm. The flow after transition is characterised by a mean velocity profile that is flatter at the centre and steeper at the walls in comparison to that for a laminar flow. The root mean square of the streamwise fluctuating velocity shows a characteristic sharp increase away from the wall and a maximum close to the wall, as observed in turbulent flows in rigid-walled channels. However, the profile is asymmetric, with a significantly higher maximum close to the soft wall in comparison to that close to the hard wall, and the Reynolds stress is found to be non-zero at the soft wall, indicating that there is a stress exerted by fluid velocity fluctuations on the wall. The maximum of the root mean square of the velocity fluctuations and the Reynolds stress (divided by the fluid density) in the soft-walled microchannel for Reynolds numbers in the range 250-400, when scaled by suitable powers of the maximum velocity, are comparable to those in a rigid channel at Reynolds numbers in the range 5000-20 000. The near-wall velocity profile shows no evidence of a viscous sublayer for (y upsilon(*)/nu) as low as two, but there is a logarithmic layer for (y upsilon(*)/nu) up to approximately 30, where the von Karman constants are very different from those for a rigid-walled channel. Here, upsilon(*) is the friction velocity, nu is the kinematic viscosity and y is the distance from the soft surface. The surface of the soft wall in contact with the fluid is marked with dye spots to monitor the deformation and motion along the fluid-wall interface. Low-frequency oscillations in the displacement of the surface are observed after transition in both the streamwise and spanwise directions, indicating that the velocity fluctuations are dynamically coupled to motion in the solid.