Conditional Moment Closure for Turbulent Premixed Flames

The conditional moment closure (CMC) method has been successfully applied to various non-premixed combustion systems in the past, but its application to premixed flames is not fully tested and validated. The main difficulty is associated with the modeling of conditional scalar dissipation rate of the conditioning scalar, the progress variable. A simple algebraic model for the conditional dissipation rate is validated using DNS results of a V-flame. This model along with the standard k- turbulence modeling is used in computations of stoichiometric pilot stabilized Bunsen flames using the RANS-CMC method. A first-order closure is used for the conditional mean reaction rate. The computed non reacting and reacting scalars are in reasonable agreement with the experimental measurements and are consistent with earlier computations using flamelets and transported PDF methods. Sensitivity to chemical kinetic mechanism is also assessed. The results suggest that the CMC may be applied across the regimes of premixed combustion.

Kernel conditional quantile estimation via reduction revisited

Quantile regression refers to the process of estimating the quantiles of a conditional distribution and has many important applications within econometrics and data mining, among other domains. In this paper, we show how to estimate these conditional quantile functions within a Bayes risk minimization framework using a Gaussian process prior. The resulting non-parametric probabilistic model is easy to implement and allows non-crossing quantile functions to be enforced. Moreover, it can directly be used in combination with tools and extensions of standard Gaussian Processes such as principled hyperparameter estimation, sparsification, and quantile regression with input-dependent noise rates. No existing approach enjoys all of these desirable properties. Experiments on benchmark datasets show that our method is competitive with state-of-the-art approaches. © 2009 IEEE.

Using sub-word-level information for confidence estimation with conditional random field models

The task of word-level confidence estimation (CE) for automatic speech recognition (ASR) systems stands to benefit from the combination of suitably defined input features from multiple information sources. However, the information sources of interest may not necessarily operate at the same level of granularity as the underlying ASR system. The research described here builds on previous work on confidence estimation for ASR systems using features extracted from word-level recognition lattices, by incorporating information at the sub-word level. Furthermore, the use of Conditional Random Fields (CRFs) with hidden states is investigated as a technique to combine information for word-level CE. Performance improvements are shown using the sub-word-level information in linear-chain CRFs with appropriately engineered feature functions, as well as when applying the hidden-state CRF model at the word level.

The process of making the business case for technology: A sales and marketing perspective for technologists

Technological investment is a key driver of innovation and the evaluation of technology potential is becoming increasingly important in this context. There is a range of approaches and tools for developing an understanding of the value of technology. However the process of communicating this potential to possible customers is not well documented in terms of theory and practice and falls outside the skill set of many technologists. This paper seeks to integrate the concepts of marketing and consultative selling into making business cases for new technologies. It describes an exploratory study which results in an outline process activity model for technologists wishing to build an effective business case for securing investment internally or when selling a technology externally. Following a review of literature, we suggest that there is potential to learn from market research and consultative sales techniques, and propose a five step process. The work has been industrially validated and forms a novel foundation for further development. © 2012 Elsevier Inc.

Computations of turbulent lean premixed combustion using conditional moment closure

Conditional Moment Closure (CMC) is a suitable method for predicting scalars such as carbon monoxide with slow chemical time scales in turbulent combustion. Although this method has been successfully applied to non-premixed combustion, its application to lean premixed combustion is rare. In this study the CMC method is used to compute piloted lean premixed combustion in a distributed combustion regime. The conditional scalar dissipation rate of the conditioning scalar, the progress variable, is closed using an algebraic model and turbulence is modelled using the standard k-e{open} model. The conditional mean reaction rate is closed using a first order CMC closure with the GRI-3.0 chemical mechanism to represent the chemical kinetics of methane oxidation. The PDF of the progress variable is obtained using a presumed shape with the Beta function. The computed results are compared with the experimental measurements and earlier computations using the transported PDF approach. The results show reasonable agreement with the experimental measurements and are consistent with the transported PDF computations. When the compounded effects of shear-turbulence and flame are strong, second order closures may be required for the CMC. © 2013 Copyright Taylor and Francis Group, LLC.

Algorithm Studies on How to Obtain a Conditional Nonlinear Optimal Perturbation (CNOP)

The conditional nonlinear optimal perturbation (CNOP), which is a nonlinear generalization of the linear singular vector (LSV), is applied in important problems of atmospheric and oceanic sciences, including ENSO predictability, targeted observations, and ensemble forecast. In this study, we investigate the computational cost of obtaining the CNOP by several methods. Differences and similarities, in terms of the computational error and cost in obtaining the CNOP, are compared among the sequential quadratic programming (SQP) algorithm, the limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, and the spectral projected gradients (SPG2) algorithm. A theoretical grassland ecosystem model and the classical Lorenz model are used as examples. Numerical results demonstrate that the computational error is acceptable with all three algorithms. The computational cost to obtain the CNOP is reduced by using the SQP algorithm. The experimental results also reveal that the L-BFGS algorithm is the most effective algorithm among the three optimization algorithms for obtaining the CNOP. The numerical results suggest a new approach and algorithm for obtaining the CNOP for a large-scale optimization problem.

The Sales Process Practice of Food and Drink SMEs - A Holistic Conceptual Framework: Steps, dimensions, barriers and enablers.

Purpose –The research examines the sales process practised by SMEs, and barriers and enablers that hinder and support effective selling practices from the selling organisation’s perspective in Scottish-based Food and Drink firms. Design/methodology approach - – The paper adopts an interpretivist perspective with qualitative data gathered through face-to-face semi-structured interviews. 20 people involved in selling activities were interviewed from 15 SMEs across Scotland. Thematic analysis established key findings regarding the sales process practice. Findings – Five themes emerged that affect the operationalisation of the selling process: the owner manager has considerable involvement in the sales process, SMEs with some degree of sales knowledge take a more systematic approach, SMEs lack awareness of how CRM technology can assist them, power is tipped in favour of the buyer and, the geographic location of the SME places constraints on how SMEs conduct business Research limitation/implication – Thematic analysis was chosen over other more traditional methods due to the lack of relevant quantitative data. The phenomenon of the research and research methodology means that it will not be possible to repeat this study and replicate its findings. However, the process that has been adopted does provide a basis for future research. Originality/value - The paper identifies areas where future research is required in the field alongside suggestions where policy makers and government business agencies might focus intervention to assist SMEs improve delivery of the sales process and selling effectiveness

US Foreign Sales Corporations, Export Tax Credits and the WTO

Rhodes, Mark. 'US Foreign Sales Corporations, Export Tax Credits and the WTO', in: 'The WTO and the Regulation of International Trade: Recent Trade Disputes between the European Union and the United States', (Cheltenham: Edward Elgar Publishing, 2005), pp.177-189 RAE2008