Friction Factor Evaluation Using Experimental and Finite Element Methods for Al-4%Cu Preforms

In this study, ring compression tests and finite element (FE) simulations have been utilized to evaluate the friction factor, m, under different lubricating conditions for powder metallurgical (P/M) Al-4%Cu preforms. A series of ring compression tests were carried out to obtain friction factor (m) for a number of lubricating conditions, including zinc stearate, graphite, molybdenum disulfide powder, and unlubricated condition. FE simulations were used to analyze materials deformation, densification, and geometric changes, and to derive the friction calibration curves. The friction factor has been determined for various initial relative densities and different lubricating conditions, and a proper lubricant for cold forging of P/M Al-4%Cu preforms is found. Studies show that the use of lubricants has reduced the friction. However, increase in the number of pores in the preforms leads to excessive friction. The FE simulation results demonstrate a shift in the neutral plane distance from the axis of ring specimen, which occurred due to variations in the frictional conditions and initial relative densities. The load requirement for deformation, effective stress, and effective strain induced, and bulging phenomena obtained by FE simulations have a good agreement with the experimental data.     

Recycled carbon fiber filled polyethylene composites

Composites of recycled carbon fiber (CF) with up to 30 wt % loading with polyethylene (PE) were prepared via melt compounding. The morphology of the composites and the degree of dispersion of the CF in the PE matrix was examined using scanning electron microscopy, and revealed the CF to be highly dispersed at all loadings and strong interfacial adhesion to exist between the CF and PE. Raman and FTIR spectroscopy were used to characterize the surface chemistry and potential bonding sites of recycled CF. Both the Young's modulus and ultimate tensile stress increased with increasing CF loading, but the percentage stress at break was unchanged up to 5 wt % loading, then decreased with further successive addition of CF. The effect of CF on the elastic modulus of PE was examined using the Halpin‐Tsai and modified Cox models, the former giving a better fit with the values determined experimentally. The electrical conductivity of the PE matrix was enhanced by about 11 orders of magnitude on addition of recycled CF with a percolation threshold of 7 and 15 wt % for 500‐μm and 3‐mm thick samples. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

On the computer simulation of the P–C isotherms of ZrFe2 type hydrogen storage materials

This paper deals with computer simulation of the P–C isotherms of some ZrFe₂ type (Zr(Fe_1−xCr_x)₂, Zr_1−xTi_xFe_1.4Cr_0.6, Zr_1−2xMm_xTi_xFe_1.4Cr_0.6 : x00.4) of hydrogen storage materials. A feasible mathematical model has been developed to simulate the P–C isotherms. The randomized variables in the model applied for simulating the P–C isotherms of the above-mentioned ZrFe₂ type hydrogen storage materials correspond to change in enthalpy (ΔH) and entropy (ΔS) of hydride formation. Several ZrFe₂ type materials as in above have been synthesized and their P–C isotherms, enthalpy and entropy change has been evaluated experimentally in order to have input data for simulation. A special software was developed to simulate the P–C isotherms using the said model. A close match between the experimentally observed and simulated P–C isotherms for the above said ZrFe₂ type alloys has been obtained.     

A Genetic Programming Approach to Rainfall-Runoff Modelling

Planning for sustainable development of water resources relies crucially on the data available. Continuous hydrologic simulation based on conceptual models has proved to be the appropriate tool for studying rainfall-runoff processes and for providing necessary data. In recent years, artificial neural networks have emerged as a novel identification technique for the modelling of hydrological processes. However, they represent their knowledge in terms of a weight matrix that is not accessible to human understanding at present. This paper introduces genetic programming, which is an evolutionary computing method that provides a transparent and structured system identification, to rainfall-runoff modelling. The genetic-programming approach is applied to flow prediction for the Kirkton catchment in Scotland (U.K.). The results obtained are compared to those attained using two optimally calibrated conceptual models and an artificial neural network. Correlations identified using data-driven approaches (genetic programming and neural network) are surprising in their consistency considering the relative size of the models and the number of variables included. These results also compare favourably with the conceptual models.     

VOLUME-OF-FLUID CALCULATION OF HEAT OR MASS TRANSFER ACROSS DEFORMING INTERFACES IN TWO-FLUID FLOW

A new volume-of-fluid (VOF)-based numerical method for calculating heat transfer or mass transfer of a species within and between fluids with deforming interfaces is described. The algorithm is tested first against an analytical solution for diffusion from a sphere, and good agreement between theory and calculation is shown. The method is then demonstrated by predicting (a) heat transfer from a rising bubble when the bubble forms a toroidal shape, and (b) mass transfer from a rising drop when the drop phase controls diffusion. The method is shown to be a viable approach for complex interfacial heat/mass transfer.     

Prediction and evaluation of urine and urinary nitrogen and mineral excretion from dairy cattle

Urine excretion is a substantial factor in the amount of manure that needs to be managed, and urinary N can contribute to ammonia volatilization. Development and validation of prediction equations focusing on dietary factors to decrease urine and urinary nutrient excretion will provide information for managing urine and feces separately or for other future technologies. The objective of this study was to develop equations for prediction of urine excretion and excretion of urinary N, Na, and K and to evaluate both new and previously published prediction equations for estimation of urine and urinary nutrient excretion from lactating dairy cows. Data sets from metabolism studies conducted at Washington State University were compiled and evaluated for excretion of minerals. Urine excretion averaged 24.1 kg/d and urinary nitrogen excretion ranged from 63 to 499 g/d in the calibration data set. Regression equations were developed to predict urine excretion, urinary N excretion, and urinary Na and K excretion. Predictors used in the regression equations included milk yield, body weight, dietary crude protein percentage, milk urea nitrogen, and nutrient intakes. Previously published prediction equations were evaluated using data sets from Washington State University and the University of Wisconsin. Mean and linear biases were evaluated by determining the regression of residuals on predicted values. Evaluation and validation of prediction equations are important to develop equations that will more accurately estimate urine and urinary nitrogen excretion from lactating dairy cows.     

A HYBRID MODEL FOR THE MERGING OF JETS IN A COFLOWING AMBIENT FLUID

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Probiotic culture survival and implications in fermented frozen yogurt characteristics

Low-fat ice cream mix was fermented with probiotic-supplemented and traditional starter culture systems and evaluated for culture survival, composition, and sensory characteristics of frozen product. Fermentations were stopped when the titratable acidity reached 0.15% greater than the initial titratable acidity (end point 1) or when the pH reached 5.6 (end point 2). Mix was frozen and stored for 11 wk at -20 degrees C. The traditional yogurt culture system contained the strains Streptococcus salivarius ssp. thermophilus and Lactobacillus delbrueckii ssp. bulgaricus. The probiotic-supplemented system contained the traditional cultures as well as Bifidobacterium longum and Lactobacillus acidophilus. We compared recovery of Bifodobacterium by three methods, a repair-detection system with roll-tubes and plates on modified bifid glucose medium and plates with maltose + galactose reinforced clostridial medium. Culture bacteria in both systems did not decrease in the yogurt during frozen storage. The roll-tube method with modified bifid glucose agar and repair detection system provided at least one-half log10 cfu/ml higher recovery of B. longum compared with recoveries using modified bifid glucose agar or maltose + galactose reinforced clostridial agar on petri plates. No change in concentrations of lactose or protein for products fermented with either culture system occurred during storage. Acid flavor was more intense when product was fermented to pH 5.6, but yogurt flavor was not intensified. The presence of probiotic bacteria in the supplemented system seemed to cause no differences in protein and lactose concentration and sensory characteristics.     

Simulating particle agglomeration in the flash smelting reaction shaft

A steady-state, axi-symmetric, numerical model was developed to investigate the agglomeration of molten particles of sulphide ore in the reaction shaft of a flash smelting process used for extracting copper. The turbulent, particle-laden, gas flow was simulated in conjunction with a population balance model to account for agglomeration. The agglomeration was found to depend primarily on the particle to gas mass loading ratio, and the particle size and turbulence intensity at the shaft inlet. Predictions compared well with the limited experimental data in the literature. Increasing the angle at which the flow enters the shaft from the burner was found to increase agglomeration up to a critical angle at which the flow behaviour changes. The results have implications for the control and reduction of dust levels in the waste gas stream.