Two‐phase flow behavior in microtube reactors during biodiesel production from waste cooking oil

Flow patterns in the course of transesterification of waste cooking oil (WCO), sunflower oil (SFO) with water and/or oleic acid as a model of WCO, and pure SFO in the presence of a KOH catalyst in microtubes were investigated. FAME yield for the transesterification of WCO reached more than 89% in the microtube reactors with a residence time of 252 s at 333 K. The flow patterns when using WCO were changed from a liquid–liquid slug flow at the inlet region to a parallel flow at the middle region, and then to a homogeneous liquid flow at the outlet region as the reaction proceeded at 333 K. Fine droplets containing glycerol and methanol generally formed in oil slugs when using pure SFO, but were almost unobservable when using WCO. The soap produced from free fatty acids was considered to be the main factor affecting the flow patterns of WCO and SFO. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

A semi-Markovian model for low-cycle elastic-plastic fatigue crack growth

Elastic-plastic fatigue crack growth is described by a continuous time semi-Markovian stochastic process. The load on the member is considered to be deterministic and the resistance is assumed to be random. Crack growth resistance is described by an equation employing the J-integral. Quantities of interest that can be obtained from this model include emergency statistics and probability distributions on the time to reach a critical crack length. The model is tested with fatigue crack propagation data for A533B pressure vessel steel. The results indicate that the model underpredicts the mean first-passage time at the start of a test but predicts it well in the mid-ranges and towards the end of the test; the variance of the process is better predicted for specimens that undergo large plasticity than those with low plasticity.     

THE EFFECTS OF STRESS RATIO, COMPRESSIVE PEAK STRESS AND MAXIMUM STRESS LEVEL ON FATIGUE BEHAVIOUR OF 2024-T3 ALUMINIUM ALLOY

Abstract— Fatigue crack growth behaviour of 2024-T3 aluminium alloy is investigated as a function of stress ratio, compressive peak stress and maximum stress level. It is found that as the stress ratio and the magnitude of the compressive peak stress are increased, the threshold stress intensity range decreased linearly. Intermediate and near threshold growth rate data are analysed with different formulae for effective stress intensity range. The data covered different values of stress ratio, compressive peak stress and maximum stress level. A formula for the crack opening stress level is introduced as a function of stress ratio, compressive peak stress and maximum stress level. The formula permitted a good correlation between crack growth data for both positive stress ratio and negative compressive peak stress values. Using the new formula, intermediate and near threshold crack growth data for the 2024-T3 aluminium alloy yielded a unique crack growth rate vs effective stress intensity range curve for all stress ratio and compressive peak stress values investigated. This suggests that for the 2024-T3 aluminium alloy the crack growth rate vs effective stress intensity range curve does not depend on stress ratio, compressive peak stress, or maximum stress level. The significance of the new equation and the crack growth rate versus effective stress intensity range curve is that they allow a designer to find crack growth rate vs stress intensity range data for the 2024-T3 aluminium alloy in both intermediate and near threshold regions for the particular stress ratio, compressive peak stress and maximum stress level conditions of the component under investigation.     

Scalable Parallel Algorithms for FPT Problems

Algorithmic methods based on the theory of fixed-parameter tractability are combined with powerful computational platforms to launch systematic attacks on combinatorial problems of significance. As a case study, optimal solutions to very large instances of the NP-hard vertex cover problem are computed. To accomplish this, an efficient sequential algorithm and various forms of parallel algorithms are devised, implemented, and compared. The importance of maintaining a balanced decomposition of the search space is shown to be critical to achieving scalability. Target problems need only be amenable to reduction and decomposition. Applications in high throughput computational biology are also discussed.