Structure of igniting ethanol and n-heptane spray flames with and without swirl

This paper explores the ignition and subsequent evolution of spray flames in a bluff-body configuration with and without swirl. Ethanol and n-heptane are used to compare the effects of volatility. Ignition is performed by a laser spark. High speed imaging of OH *-chemiluminescence and OH-PLIF collected at 5kHz are used to investigate the behaviour of the flames during the first stages of ignition and the stable flame structure following ignition. Swirl induces a wider and shorter flame, precession, and multiple reaction zones, while the non-swirling flames have a simpler structure. The reaction fronts seem thinner with ethanol than with heptane. The dataset can be used for model validation. © 2012 Elsevier Inc.

Investigation into partially premixed combustion in a light-duty multi-cylinder diesel engine fuelled gasoline and diesel with a mixture of

Partially premixed compression ignition (PPCI) engines operating with a low temperature highly homogeneous charge have been demonstrated previously using conventional diesel fuel. The short ignition delay of conventional diesel fuel requires high fuel injection pressures to achieve adequate premixing along with high levels of EGR (exhaust gas recirculation) to achieve low NOx emissions. Low load operating regions are typified by substantial emissions of CO and HC and there exists an upper operating load limitation due to very high rates of in-cylinder gas pressure rise. In this study mixtures of gasoline and diesel fuel were investigated using a multi-cylinder light duty diesel engine. It was found that an increased proportion of gasoline fuel reduced smoke emissions at higher operating loads through an increase in charge premixing resulting from an increase in ignition delay and higher fuel volatility. The results of this investigation confirm that a combination of fuel properties, exhibiting higher volatility and increased ignition delay, would enable a widening of the low emission operating regime, but that consideration must be given to combustion stability at low operating loads. Copyright © 2007 SAE International.

Chemical vapour deposition of complex ferroic oxide thin films

Herein is presented a novel chemical vapour deposition (CVD) route for the fabrication of oxide ferroelectrics. A versatile layer-by-layer growth mode was developed to prepare naturally super-latticed bismuth based materials belonging to the Aurivillius phase family, with which good control over composition and crystal structure was achieved. In chapter 3, the effect of epitaxial strain on one of the very simple oxide materials TiO2 was studied. It has been found that the ultra-thin TiO2 films demonstrate ferroelectric behaviour when grown on NdGaO3 substrates. TiO2 exists in various crystal phases, but none of them show ferroelectric behaviour. The epitaxial strain due to the substrate, changes the crystal structure from tetragonal to orthorhombic which in turn leads to ferroelectric behaviour. In chapter 4, a unique growth method for multiferroic BiFeO3 (BFO) thin films is shown, where a phase pure BFO thin films can be prepared even in the presence of excess bismuth precursor during the growth process. This type of growth is usually called adsorption controlled growth and can be used for growing various bismuth containing compounds, where the volatility of bismuth can create various types of defects. Chapter 5 describes the growth of Bi4Ti3O12 thin films in a layer-by-layer growth mode. In this section, the effect of Bi and Ti precursor flows on the growth of thin films is discussed and it is shown that how change in precursor flows leads to out-ofphase boundary defects during the layer-by-layer growth mode. In chapter 6, the growth of a compound Bi5Ti3FeO15, which is a 1:1 mixture of BiFeO3 and Bi4Ti3O12, is presented. The growth mechanism of Bi5Ti3FeO15 thin films is presented, where the Fe precursor flow was controlled from zero to the insertion of one full BiFeO3 perovskite unit cell into the Bi4Ti3O12 structure in addition, the effect of iron precursor flow on crystalline properties is demonstrated. The methods presented in this thesis can be adopted to grow ferroelectric and multiferroic films for industrial applications.

Nonparametric estimation of structural models for high-frequency currency market data

Empirical modeling of high-frequency currency market data reveals substantial evidence for nonnormality, stochastic volatility, and other nonlinearities. This paper investigates whether an equilibrium monetary model can account for nonlinearities in weekly data. The model incorporates time-nonseparable preferences and a transaction cost technology. Simulated sample paths are generated using Marcet's parameterized expectations procedure. The paper also develops a new method for estimation of structural economic models. The method forces the model to match (under a GMM criterion) the score function of a nonparametric estimate of the conditional density of observed data. The estimation uses weekly U.S.-German currency market data, 1975-90. © 1995.

Adaptive Mixture Modelling Metropolis Methods for Bayesian Analysis of Non-linear State-Space Models.

We describe a strategy for Markov chain Monte Carlo analysis of non-linear, non-Gaussian state-space models involving batch analysis for inference on dynamic, latent state variables and fixed model parameters. The key innovation is a Metropolis-Hastings method for the time series of state variables based on sequential approximation of filtering and smoothing densities using normal mixtures. These mixtures are propagated through the non-linearities using an accurate, local mixture approximation method, and we use a regenerating procedure to deal with potential degeneracy of mixture components. This provides accurate, direct approximations to sequential filtering and retrospective smoothing distributions, and hence a useful construction of global Metropolis proposal distributions for simulation of posteriors for the set of states. This analysis is embedded within a Gibbs sampler to include uncertain fixed parameters. We give an example motivated by an application in systems biology. Supplemental materials provide an example based on a stochastic volatility model as well as MATLAB code.

Bayesian Analysis of Latent Threshold Dynamic Models

We discuss a general approach to dynamic sparsity modeling in multivariate time series analysis. Time-varying parameters are linked to latent processes that are thresholded to induce zero values adaptively, providing natural mechanisms for dynamic variable inclusion/selection. We discuss Bayesian model specification, analysis and prediction in dynamic regressions, time-varying vector autoregressions, and multivariate volatility models using latent thresholding. Application to a topical macroeconomic time series problem illustrates some of the benefits of the approach in terms of statistical and economic interpretations as well as improved predictions. Supplementary materials for this article are available online. © 2013 Copyright Taylor and Francis Group, LLC.

Numerical solutions of certain nonlinear models in European options on a distributed computing environment

Financial modelling in the area of option pricing involves the understanding of the correlations between asset and movements of buy/sell in order to reduce risk in investment. Such activities depend on financial analysis tools being available to the trader with which he can make rapid and systematic evaluation of buy/sell contracts. In turn, analysis tools rely on fast numerical algorithms for the solution of financial mathematical models. There are many different financial activities apart from shares buy/sell activities. The main aim of this chapter is to discuss a distributed algorithm for the numerical solution of a European option. Both linear and non-linear cases are considered. The algorithm is based on the concept of the Laplace transform and its numerical inverse. The scalability of the algorithm is examined. Numerical tests are used to demonstrate the effectiveness of the algorithm for financial analysis. Time dependent functions for volatility and interest rates are also discussed. Applications of the algorithm to non-linear Black-Scholes equation where the volatility and the interest rate are functions of the option value are included. Some qualitative results of the convergence behaviour of the algorithm is examined. This chapter also examines the various computational issues of the Laplace transformation method in terms of distributed computing. The idea of using a two-level temporal mesh in order to achieve distributed computation along the temporal axis is introduced. Finally, the chapter ends with some conclusions.

The determinants of business performance of estate agency in England and Wales

Purpose: This paper seeks to investigate the factors influencing the business performance of estate agency in England and Wales. Design/methodology/approach: The paper investigates the effect of housing market, company size and pricing policy on business performance in the estate agency sector in England and Wales. The analysis uses the survey data of Woolwich Cost of Moving Survey (a survey of transactions costs sponsored by the Woolwich/Barclays Bank) from 2003 to 2005 to test the hypothesis that the business performance of estate agency is affected by industry characteristics and firm factors. Findings: The empirical analysis indicates that the business performance of estate agency is subject to market environment volatility such as market uncertainty, housing market liquidity and house price changes. The firm factors such as firm size and the level of agency fee have no explanatory power in explaining business performance. The level of agency fee is positively associated with firm size, market environment and liquidity. Research limitations/implications: The research is limited to the data received and is based on a research project on transaction costs designed prior to this analysis. Originality/value: There is little other research that investigates the factors determining the business performance of estate agency, using consecutive data of three years across England and Wales. The findings are useful for practitioners and/or managers to allocate resources and adjust their business strategy to enhance business performance in the estate agency sector.

Less of a Puzzle: a new look at the forward forex market

The two-country monetary model is extended to include a consumption externality with habit persistence. The model is simulated using the artificial economy methodology. The 'puzzles' in the forward market are re-examined. The model is able to account for: (a) the low volatility of the forward discount; (b) the higher volatility of expected forward speculative profit; (c) the even higher volatility of the spot return; (d) the persistence in the forward discount; (e) the martingale behavior of spot exchange rates; and (f) the negative covariance between the expected spot return and expected forward speculative profit. It is unable to account for the forward market bias because the volatility of the expected spot return is too large relative to the volatility of the expected forward speculative profit.

Choice and use of standards for dynamic headspace trapping and application to the analysis of the volatiles of baked potato

When attempting to quantify the volatile components of a food isolated by dynamic headspace trapping onto an adsorbent, the analyst has to select the most appropriate compounds to use as standards and at which stage of the analysis to add them. Factors to be borne in mind include the volatility of the standard, the response of the GC detector, and whether to add the standard to the sample or to the adsorbent trap. This chapter considers the issues and describes the application of one chosen method to the quantitation of the volatile components of baked potato.

Towards an understanding of the causes and effects of software requirements change: two case studies

Changes to software requirements not only pose a risk to the successful delivery of software applications but also provide opportunity for improved usability and value. Increased understanding of the causes and consequences of change can support requirements management and also make progress towards the goal of change anticipation. This paper presents the results of two case studies that address objectives arising from that ultimate goal. The first case study evaluated the potential of a change source taxonomy containing the elements ‘market’, ‘organisation’, ‘vision’, ‘specification’, and ‘solution’ to provide a meaningful basis for change classification and measurement. The second case study investigated whether the requirements attributes of novelty, complexity, and dependency correlated with requirements volatility. While insufficiency of data in the first case study precluded an investigation of changes arising due to the change source of ‘market’, for the remainder of the change sources, results indicate a significant difference in cost, value to the customer and management considerations. Findings show that higher cost and value changes arose more often from ‘organisation’ and ‘vision’ sources; these changes also generally involved the co-operation of more stakeholder groups and were considered to be less controllable than changes arising from the ‘specification’ or ‘solution’ sources. Results from the second case study indicate that only ‘requirements dependency’ is consistently correlated with volatility and that changes coming from each change source affect different groups of requirements. We conclude that the taxonomy can provide a meaningful means of change classification, but that a single requirement attribute is insufficient for change prediction. A theoretical causal account of requirements change is drawn from the implications of the combined results of the two case studies.

Why and how FDI stocks are a biased measure of MNE affiliate activity

Many international business (IB) studies have used foreign direct investment (FDI) stocks to measure the aggregate value-adding activity of multinational enterprises (MNE) affiliates in host countries. We argue that FDI stocks are a biased measure of that activity, because the degree to which they overestimate or underestimate affiliate activity varies systematically with host-country characteristics. First, most FDI into countries that serve as tax havens generate no actual productive activity; thus FDI stocks in such countries overestimate affiliate activity. Second, FDI stocks do not include locally raised external funds, funds widely used in countries with well-developed financial markets or volatile exchange rates, resulting in an underestimation of affiliate activity in such countries. Finally, the extent to which FDI translates into affiliate activity increases with affiliate labor productivity, so in countries where labor is more productive, FDI stocks also result in an underestimation of affiliate activity. We test these hypotheses by first regressing affiliate value-added and affiliate sales on FDI stocks to calculate a country-specific mismatch, and then by regressing this mismatch on a host country's tax haven status, level of financial market development, exchange rate volatility, and affiliate labor productivity. All hypotheses are supported, implying that FDI stocks are a biased measure of MNE affiliate activity, and hence that the results of FDI-data-based studies of such activity need to be reconsidered. [ABSTRACT FROM AUTHOR]