Production of biodiesel from waste fryer grease using mixed methanol/ethanol system

Transesterification of waste fryer grease (WFG) containing 5–6 wt.% free fatty acid (FFA) was carried out with methanol, ethanol, and mixtures of methanol/ethanol maintaining the oil to alcohol molar ratio of 1:6, and initially with KOH as a catalyst. Mixtures of methanol and ethanol were used for transesterification in order to use the better solvent property of ethanol and rapid equilibrium using methanol. Formation of soap by reaction of FFA present in WFG with KOH instigated difficulty in the separation of glycerol from biodiesel ester. To untangle this problem, two-stage (acid and alkali catalyzed) method was used for biodiesel synthesis. More than 90% ester was obtained when two-stage method was used compared to ∼ 50% ester in single stage alkaline catalyst. In the case of mixed alcohol, a relatively smaller amount of ethyl esters was formed along with methyl esters. Acid value, viscosity, and cetane number of all the esters prepared from WFG were within the range of the ASTM standard. Esters obtained from WFG showed good performance as a lubricity additive.     

Strength evaluation of granite block samples with different predictive models

Over the last decade, application of soft computing techniques has rapidly grown up in different scientific fields, especially in rock mechanics. One of these cases relates to indirect assessment of uniaxial compressive strength (UCS) of rock samples with different artificial intelligent-based methods. In fact, the main advantage of such systems is to readily remove some difficulties arising in direct assessment of UCS, such as time-consuming and costly UCS test procedure. This study puts an effort to propose four accurate and practical predictive models of UCS using artificial neural network (ANN), hybrid ANN with imperialism competitive algorithm (ICA–ANN), hybrid ANN with artificial bee colony (ABC–ANN) and genetic programming (GP) approaches. To reach the aim of the current study, an experimental database containing a total of 71 data sets was set up by performing a number of laboratory tests on the rock samples collected from a tunnel site in Malaysia. To construct the desired predictive models of UCS based on training and test patterns, a combination of several rock characteristics with the most influence on UCS has been used as input parameters, i.e. porosity (n), Schmidt hammer rebound number (R), p-wave velocity (V_p) and point load strength index (Is(50)). To evaluate and compare the prediction precision of the developed models, a series of statistical indices, such as root mean squared error (RMSE), determination coefficient (R²) and variance account for (VAF) are utilized. Based on the simulation results and the measured indices, it was observed that the proposed GP model with the training and test RMSE values 0.0726 and 0.0691, respectively, gives better performance as compared to the other proposed models with values of (0.0740 and 0.0885), (0.0785 and 0.0742), and (0.0746 and 0.0771) for ANN, ICA–ANN and ABC–ANN, respectively. Moreover, a parametric analysis is accomplished on the proposed GP model to further verify its generalization capability. Hence, this GP-based model can be considered as a new applicable equation to accurately estimate the uniaxial compressive strength of granite block samples.

     

Synthesis of Biodiesel from Canola Oil Using Heterogeneous Base Catalyst

A series of alkali metal (Li, Na, K) promoted alkali earth oxides (CaO, BaO, MgO), as well as K₂CO₃ supported on alumina (Al₂O₃), were prepared and used as catalysts for transesterification of canola oil with methanol. Four catalysts such as K₂CO₃/Al₂O₃ and alkali metal (Li, Na, K) promoted BaO were effective for transesterification with >85 wt% of methyl esters. ICP-MS analysis revealed that leaching of barium in ester phase was too high (~1,000 ppm) when BaO based catalysts were used. As barium is highly toxic, these catalysts were not used further for transesterification of canola oil. Optimization of reaction conditions such as molar ratio of alcohol to oil (6:1–12:1), reaction temperature (40–60 °C) and catalyst loading (1–3 wt%) was performed for most efficient and environmentally friendly K₂CO₃/Al₂O₃ catalyst to maximize ester yield using response surface methodology (RSM). The RSM suggested that a molar ratio of alcohol to oil 11.48:1, a reaction temperature of 60 °C, and catalyst loading 3.16 wt% were optimum for the production of ester from canola oil. The predicted value of ester yield was 96.3 wt% in 2 h, which was in agreement with the experimental results within 1.28%.     

Study of Tire Particle Mixing in a Moving and Stirred Bed Vacuum Pyrolysis Reactor

The paper studies the motion of scrap tire shreds in a moving and stirred bed vacuum pyrolysis reactor. The reactor configuration is a novel concept. The pattern and the residence time distribution (RTD) of the particle motion in the reactor were investigated using tracers, for different feed rates and blade speeds. It was shown that the particle motion in the reactor is plug flow nature with intermediate dispersion (σ² = 0.02—0.055). The mean residence time is in the range of 7—23 min, depending on the speed of the blades and the feed rate. The ratio of mean particle speed and the speed of blades v_m/v_b varied between 0.03 and 0.07.     

Polyester nanocomposite fibers with improved flame retardancy and thermal stability

Polyester (PET) nanocomposite fibers were spun by adding master batches of linear low‐density polyethylene (LLDPE) loaded with Montmorillonite (MMT) nanoclay after compatibilizing the PET and LLDPE. The spun fibers showed increased thermal stability as well as flame retardancy, which increased progressively with the amount of nanoclay loaded into the fiber. There is slight decrease in tensile strength of the fiber accompanied by decrease in elongation % indicating addition of nanoclay makes the filaments stiffer. The onset of crystallization temperature occurred at higher temperature in case of composite fibers than on the neat PET fiber because of nucleating effect of nanoclay. The dyeability of the fibers was not affected and also had very little impact on the flame retardancy of the fiber. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers     

Formulation and characterisation of nanosuspensions of BCS class II and IV drugs by combinative method

Drug nanocrystals are known to increase the solubility of Biopharmaceutics Classification System (BCS) class II and IV drugs. SmartCrystals are the second generation nanocrystals with particle size of less than 100 nm and increased the stability and solubility of drug and drug product. The combinative methods adopted for the preparation of SmartCrystals are reported to shorten the processing time to reduce the particle size of the drug. This study was carried out with the aim to prepare nanosuspensions of aprepitant and ibuprofen using two pretreatment methods, precipitation and ball milling in a combination of high-pressure homogenisation (HPH). Ball milling and precipitation resulted in nanosuspensions having a particle size less than 1 µ, which were subjected to high HPH. HPH further led to a reduction in the particle size. However, the precipitation method failed to reduce the size of ibuprofen particles to 1 µ.     

Simplified loss analysis and comparison of full-bridge,full-range-ZVS DC-DC converters

The loss of zero-voltage-switching (ZVS) of active switches has been a serious limitation of full-bridge (FBZVS) converters. Many techniques have been proposed in the past to extend the range of ZVS operation over the wider and also the full range of operation. However, in these techniques ZVS is achieved at the expense of additional conduction loss in active switches and losses in the auxiliary components. In this paper, the analysis for the additional losses in various full-range FBZVS DC-DC converters and their comparative evaluation is reported. Closed form expressions are derived for average value of device currents and losses. The loss curves for various topologies are plotted and compared. The analytical results are found to be consistent with the experimental efficiency tests performed on 500 W, 100 kHz prototype. It is concluded that a recently proposed new topology has the least penalty of additional losses.     

The reliability of the diagnostic features in patients with narcolepsy

This study determined the test-retest reliability of the polysomnographic findings in narcolepsy. The diagnosis of narcolepsy was based on clinical symptoms and polysomnographic signs. Control subjects were screened before participation and were split based on their screening multiple sleep latency test (MSLT) into high- and low-MSLT groups. Subjects completed two polysomnographic evaluations with at least 5 days between laboratory tests. Narcoleptics had lower sleep efficiencies and high stage 1% when compared to the low MSLT control group. They had more awakenings and less stage 2% than the control groups. Narcoleptics had a shorter latency to 1 when compared to the high-MSLT group but comparable to that of the low-MSLT group. Narcoleptics had a higher number of sleep-onset rapid eye movement periods (SOREMPs) than both control groups. The MSLT scores were stable across the two evaluations and showed a statistically significant correlation. Twenty-eight of the 30 narcoleptic subjects had two or more SOREMPs on reevaluation. None of the controls had multiple SOREMPs. Thus, multiple SOREMPs were shown to be a reliable finding in patients with narcolepsy.     

Modelling the Effective Thermal Conductivity in Polydispersed Bed Systems: A Unified Approach using the Linear Packing Theory and Unit Cell Model

A comprehensive, unified approach, using the Linear Packing Theory and Unit Cell Model, is proposed for calculating of the effective thermal conductivity of polydispersed packed beds. In this new approach, the effect of packing density is incorporated by the use of (i) an initial porosity to take into account the packing of mono‐sized particles, and (ii) the packing size ratio as a measure of the particle‐particle interaction. The proposed approach was validated with the experimental measurements of binary and ternary beds. This new approach demonstrates that the effective thermal conductivity of beds composed of polydispersed particles can be simulated for any composition without the need to measure the in situ porosity.