EM optimization of latent-variable density models

There is currently considerable interest in developing general non-linear density models based on latent, or hidden, variables. Such models have the ability to discover the presence of a relatively small number of underlying `causes' which, acting in combination, give rise to the apparent complexity of the observed data set. Unfortunately, to train such models generally requires large computational effort. In this paper we introduce a novel latent variable algorithm which retains the general non-linear capabilities of previous models but which uses a training procedure based on the EM algorithm. We demonstrate the performance of the model on a toy problem and on data from flow diagnostics for a multi-phase oil pipeline.

GTM: the generative topographic mapping

Latent variable models represent the probability density of data in a space of several dimensions in terms of a smaller number of latent, or hidden, variables. A familiar example is factor analysis which is based on a linear transformations between the latent space and the data space. In this paper we introduce a form of non-linear latent variable model called the Generative Topographic Mapping, for which the parameters of the model can be determined using the EM algorithm. GTM provides a principled alternative to the widely used Self-Organizing Map (SOM) of Kohonen (1982), and overcomes most of the significant limitations of the SOM. We demonstrate the performance of the GTM algorithm on a toy problem and on simulated data from flow diagnostics for a multi-phase oil pipeline.

A hierarchical latent variable model for data visualization

Visualization has proven to be a powerful and widely-applicable tool the analysis and interpretation of data. Most visualization algorithms aim to find a projection from the data space down to a two-dimensional visualization space. However, for complex data sets living in a high-dimensional space it is unlikely that a single two-dimensional projection can reveal all of the interesting structure. We therefore introduce a hierarchical visualization algorithm which allows the complete data set to be visualized at the top level, with clusters and sub-clusters of data points visualized at deeper levels. The algorithm is based on a hierarchical mixture of latent variable models, whose parameters are estimated using the expectation-maximization algorithm. We demonstrate the principle of the approach first on a toy data set, and then apply the algorithm to the visualization of a synthetic data set in 12 dimensions obtained from a simulation of multi-phase flows in oil pipelines and to data in 36 dimensions derived from satellite images.

GTM: A principled alternative to the self-organizing map

The Self-Organizing Map (SOM) algorithm has been extensively studied and has been applied with considerable success to a wide variety of problems. However, the algorithm is derived from heuristic ideas and this leads to a number of significant limitations. In this paper, we consider the problem of modelling the probability density of data in a space of several dimensions in terms of a smaller number of latent, or hidden, variables. We introduce a novel form of latent variable model, which we call the GTM algorithm (for Generative Topographic Mapping), which allows general non-linear transformations from latent space to data space, and which is trained using the EM (expectation-maximization) algorithm. Our approach overcomes the limitations of the SOM, while introducing no significant disadvantages. We demonstrate the performance of the GTM algorithm on simulated data from flow diagnostics for a multi-phase oil pipeline.

GTM: the generative topographic mapping

Latent variable models represent the probability density of data in a space of several dimensions in terms of a smaller number of latent, or hidden, variables. A familiar example is factor analysis which is based on a linear transformations between the latent space and the data space. In this paper we introduce a form of non-linear latent variable model called the Generative Topographic Mapping, for which the parameters of the model can be determined using the EM algorithm. GTM provides a principled alternative to the widely used Self-Organizing Map (SOM) of Kohonen (1982), and overcomes most of the significant limitations of the SOM. We demonstrate the performance of the GTM algorithm on a toy problem and on simulated data from flow diagnostics for a multi-phase oil pipeline.

Sump simulations

Mineral wool insulation material applied to the primary cooling circuit of a nuclear reactor maybe damaged in the course of a loss of coolant accident (LOCA). The insulation material released by the leak may compromise the operation of the emergency core cooling system (ECCS), as it maybe transported together with the coolant in the form of mineral wool fiber agglomerates (MWFA) suspensions to the containment sump strainers, which are mounted at the inlet of the ECCS to keep any debris away from the emergency cooling pumps. In the further course of the LOCA, the MWFA may block or penetrate the strainers. In addition to the impact of MWFA on the pressure drop across the strainers, corrosion products formed over time may also accumulate in the fiber cakes on the strainers, which can lead to a significant increase in the strainer pressure drop and result in cavitation in the ECCS. Therefore, it is essential to understand the transport characteristics of the insulation materials in order to determine the long-term operability of nuclear reactors, which undergo LOCA. An experimental and theoretical study performed by the Helmholtz-Zentrum Dresden-Rossendorf and the Hochschule Zittau/Görlitz1 is investigating the phenomena that maybe observed in the containment vessel during a primary circuit coolant leak. The study entails the generation of fiber agglomerates, the determination of their transport properties in single and multi-effect experiments and the long-term effects that particles formed due to corrosion of metallic containment internals by the coolant medium have on the strainer pressure drop. The focus of this presentation is on the numerical models that are used to predict the transport of MWFA by CFD simulations in the containment sump. Two dispersed phases were conditions to determine the influence of entrained air from a jet on the transport of fibre agglomerates through the sump. The strainer model of A. Grahn was implemented to observe the impact that the accumulation of the fibres have on the pressure drop across the strainers. The geometry considered is similar to the containment sump configurations found in Nuclear Power Plants.

Hydrodynamic modeling of mineral wool fiber suspensions in a two-dimensional channel flow

A consequence of a loss of coolant accident is the damage of adjacent insulation materials (IM). IM may then be transported to the containment sump strainers where water is drawn into the ECCS (emergency core cooling system). Blockage of the strainers by IM lead to an increased pressure drop acting on the operating ECCS pumps. IM can also penetrate the strainers, enter the reactor coolant system and then accumulate in the reactor pressure vessel. An experimental and theoretical study that concentrates on mineral wool fiber transport in the containment sump and the ECCS is being performed. The study entails fiber generation and the assessment of fiber transport in single and multi-effect experiments. The experiments include measurement of the terminal settling velocity, the strainer pressure drop, fiber sedimentation and resuspension in a channel flow and jet flow in a rectangular tank. An integrated test facility is also operated to assess the compounded effects. Each experimental facility is used to provide data for the validation of equivalent computational fluid dynamic models. The channel flow facility allows the determination of the steady state distribution of the fibers at different flow velocities. The fibers are modeled in the Eulerian-Eulerian reference frame as spherical wetted agglomerates. The fiber agglomerate size, density, the relative viscosity of the fluid-fiber mixture and the turbulent dispersion of the fibers all affect the steady state accumulation of fibers at the channel base. In the current simulations, two fiber phases are separately considered. The particle size is kept constant while the density is modified, which affects both the terminal velocity and volume fraction. The relative viscosity is only significant at higher concentrations. The numerical model finds that the fibers accumulate at the channel base even at high velocities; therefore, modifications to the drag and turbulent dispersion forces can be made to reduce fiber accumulation.

Verification and validation of numerical models of the transport of insulation debris

Damage to insulation materials located near to a primary circuit coolant leak may compromise the operation of the emergency core cooling system (ECCS). Insulation material in the form of mineral wool fiber agglomerates (MWFA) maybe transported to the containment sump strainers, where they may block or penetrate the strainers. Though the impact of MWFA on the pressure drop across the strainers is minimal, corrosion products formed over time may also accumulate in the fiber cakes on the strainers, which can lead to a significant increase in the strainer pressure drop and result in cavitation in the ECCS. An experimental and theoretical study performed by the Helmholtz-Zentrum Dresden-Rossendorf and the Hochschule Zittau/Görlitz is investigating the phenomena that maybe observed in the containment vessel during a primary circuit coolant leak. The study entails the generation of fiber agglomerates, the determination of their transport properties in single and multi-effect experiments and the long-term effect that corrosion and erosion of the containment internals by the coolant has on the strainer pressure drop. The focus of this paper is on the verification and validation of numerical models that can predict the transport of MWFA. A number of pseudo-continuous dispersed phases of spherical wetted agglomerates represent the MWFA. The size, density, the relative viscosity of the fluid-fiber agglomerate mixture and the turbulent dispersion all affect how the fiber agglomerates are transported. In the cases described here, the size is kept constant while the density is modified. This definition affects both the terminal velocity and volume fraction of the dispersed phases. Note that the relative viscosity is only significant at high concentrations. Three single effect experiments were used to provide validation data on the transport of the fiber agglomerates under conditions of sedimentation in quiescent fluid, sedimentation in a horizontal flow and suspension in a horizontal flow. The experiments were performed in a rectangular column for the quiescent fluid and a racetrack type channel that provided a near uniform horizontal flow. The numerical models of sedimentation in the column and the racetrack channel found that the sedimentation characteristics are consistent with the experiments. For channel suspension, the heavier fibers tend to accumulate at the channel base even at high velocities, while lighter phases are more likely to be transported around the channel.

Numerical models used for the modelling of the transport of fibrous insulation debris

Mineral wool insulation material applied to the primary cooling circuit of a nuclear reactor maybe damaged in the course of a loss of coolant accident (LOCA). The insulation material released by the leak may compromise the operation of the emergency core cooling system (ECCS), as it maybe transported together with the coolant in the form of mineral wool fiber agglomerates (MWFA) suspensions to the containment sump strainers, which are mounted at the inlet of the ECCS to keep any debris away from the emergency cooling pumps. In the further course of the LOCA, the MWFA may block or penetrate the strainers. In addition to the impact of MWFA on the pressure drop across the strainers, corrosion products formed over time may also accumulate in the fiber cakes on the strainers, which can lead to a significant increase in the strainer pressure drop and result in cavitation in the ECCS. Therefore, it is essential to understand the transport characteristics of the insulation materials in order to determine the long-term operability of nuclear reactors, which undergo LOCA. An experimental and theoretical study performed by the Helmholtz-Zentrum Dresden-Rossendorf and the Hochschule Zittau/Görlitz1 is investigating the phenomena that maybe observed in the containment vessel during a primary circuit coolant leak. The study entails the generation of fiber agglomerates, the determination of their transport properties in single and multi-effect experiments and the long-term effects that particles formed due to corrosion of metallic containment internals by the coolant medium have on the strainer pressure drop. The focus of this presentation is on the numerical models that are used to predict the transport of MWFA by CFD simulations. A number of pseudo-continuous dispersed phases of spherical wetted agglomerates can represent the MWFA. The size, density, the relative viscosity of the fluid-fiber agglomerate mixture and the turbulent dispersion all affect how the fiber agglomerates are transported. In the cases described here, the size is kept constant while the density is modified. This definition affects both the terminal velocity and volume fraction of the dispersed phases. Only one of the single effect experimental scenarios is described here that are used in validation of the numerical models. The scenario examines the suspension and horizontal transport of the fiber agglomerates in a racetrack type channel. The corresponding experiments will be described in an accompanying presentation (see abstract of Seeliger et al.).

E-business adoption and its impact on performance

Organizations today face intense competitive and economic pressures leading to large scale transformation of existing business operations and transactions. In addition, organizations have adopted automated business processes to deal with partners and customers. E-business diffusion is a multi-phase process, moving from initiation through to routinisation and an insight into the adoption processes helps organizations to adopt e-business more effectively. It is imperative that organizations effectively manage the e-business environment, and all associated changes to accommodate the changing relationships with customers and business partners and more importantly, to improve performance. This chapter discusses the process of e-business implementation, usage and diffusion (routinisation stage) on business performance. © 2010, IGI Global.

A Cognitive Science Reasoning in Recognition of Emotions in Audio-Visual Speech

In this report we summarize the state-of-the-art of speech emotion recognition from the signal processing point of view. On the bases of multi-corporal experiments with machine-learning classifiers, the observation is made that existing approaches for supervised machine learning lead to database dependent classifiers which can not be applied for multi-language speech emotion recognition without additional training because they discriminate the emotion classes following the used training language. As there are experimental results showing that Humans can perform language independent categorisation, we made a parallel between machine recognition and the cognitive process and tried to discover the sources of these divergent results. The analysis suggests that the main difference is that the speech perception allows extraction of language independent features although language dependent features are incorporated in all levels of the speech signal and play as a strong discriminative function in human perception. Based on several results in related domains, we have suggested that in addition, the cognitive process of emotion-recognition is based on categorisation, assisted by some hierarchical structure of the emotional categories, existing in the cognitive space of all humans. We propose a strategy for developing language independent machine emotion recognition, related to the identification of language independent speech features and the use of additional information from visual (expression) features.

Mapping Ireland’s Energy Pathways: Characterizing and Catalyzing Transition

In 2015 Ireland has arguably begun to make its first bold steps in confronting the challenges of energy transition, with the objective of a “low carbon, climate resilient and environmentally sustainable economy by the end of the
year 2050” expressed in the 2015 Climate Action and Low Carbon Development Bill and the 2015 Energy Bill acknowledging that energy transformation relied on a new breed of ‘energy citizens’. These represent the first formal articulation of Ireland’s ambition to engage in a radical, long-term and far-reaching transition process, and raises a myriad of questions over how this can be operationalised, resourced and whether it can maintain political momentum. A range of perspectives on these issues is provided in the growing body of literature on transition theories (Rotmans et al 2001, Markard et al 2012) and the inter-disciplinary EPA-funded CC Transitions project, based at Queen’s University Belfast, represents an attempt to translate this into the context of Ireland’s institutions and technological profile. By relating this to international research on sustainability transitions, which conceptualises transitions as multi-level, multi-phase and multi-actor processes, this paper will explore the opportunities of alternative pathways that could take Ireland towards a more progressing, inclusive and effective low carbon future. Drawing on a number of case studies it will highlight some of the capacities for transition required in Irish society: where these exist, how they are being built or enabled, and the barriers to wider social change.

Impacts des dépositions atmosphériques de fer sur les assemblages phytoplanctoniques et la production de diméthylsulfure dans le Pacifique Nord-Est contemporain et dans le contexte de l’acidification des océans

La croissance du phytoplancton est limitée par les faibles concentrations de fer (Fe) dans près de 40% de l’océan mondial. Le Pacifique subarctique Nord-Est représente une de ces zones limitées en fer et désignées High Nutrient - Low Chlorophyll (HNLC). Cet écosystème, dominé par des cellules de petite taille telles les prymnésiophytes, est caractérisé par de très faibles concentrations estivales de chlorophylle a et de fortes concentrations de macronutriments. Il a été maintes fois démontré que les ajouts de fer, sous différentes formes chimiques (habituellement FeSO4), dans les zones HNLC, stimulent la croissance et modifient la structure des communautés planctoniques en favorisant la croissance des cellules de grande taille, notamment les diatomées. Ces effets sur la communauté planctonique ont le potentiel d’influencer les grands mécanismes régulateurs du climat, tels la pompe biologique de carbone et la production de diméthylsulfure (DMS). Les poussières provenant des déserts du nord de la Chine sont reconnues depuis longtemps comme une source sporadique importante de fer pour le Pacifique Nord-Est. Malgré leur importance potentielle, l’influence directe exercée par ces poussières sur l’écosystème planctonique de cette zone HNLC n’a jamais été étudiée. Il s’agit d’une lacune importante puisque le fer associé aux poussières est peu soluble dans l’eau de mer, que la proportion biodisponible n’est pas connue et que les poussières peuvent avoir un effet inhibiteur chez le phytoplancton. Cette thèse propose donc, dans un premier temps, de mesurer pour la première fois l’effet de la fertilisation de la communauté planctonique du Pacifique Nord-Est par un gradient de concentrations de poussières désertiques naturelles. Cette première expérimentation a démontré que le fer contenu dans les poussières asiatiques est biodisponible et qu’une déposition équivalente à celles prenant place au printemps dans le Pacifique Nord-Est peut résulter en une stimulation significative de la prise de nutriments et de la croissance du phytoplancton. Mes travaux ont également montré que l’ajout de 0,5 mg L-1 de poussières peut résulter en la production d’autant de biomasse algale que l’ajout de FeSO4, l’espèce chimique utilisée lors des expériences d’enrichissement en fer à grande échelle. Cependant, les ajouts de FeSO4 favorisent davantage les cellules de petite taille que les ajouts de poussières, observation démontrant que le FeSO4 n’est pas un proxy parfait des poussières asiatiques. Dans un deuxième temps, je me suis intéressée à une source alternative de fer atmosphérique, les cendres volcaniques. Mon intérêt pour cette source de fer a été attisé par les observations d’une floraison spectaculaire dans le Pacifique Nord-Est, ma région d’étude, associée à l’éruption de 2008 du volcan Kasatochi dans les îles Aléoutiennes. Forte de mon expérience sur les poussières, j’ai quantifié l’effet direct de ces cendres volcaniques sur la communauté planctonique du Pacifique Nord-Est. Mes résultats ont montré que le fer contenu dans les cendres volcaniques est également biodisponible pour le phytoplancton. Ils ont également montré que cette source de fer peut être aussi importante que les poussières désertiques dans la régulation de la croissance du phytoplancton dans cette partie de l’océan global à l’échelle millénaire. Dans un troisième temps, j’ai estimé comment l’acidification des océans modulera les réponses des communautés planctoniques aux dépositions naturelles de fer mises en évidence lors de mes expériences précédentes. Pour ce faire, j’ai effectué des enrichissements de poussière dans de l’eau de mer au pH actuel de 8.0 et dans l’eau de mer acidifiée à un pH de 7.8. Mes résultats ont montré une diminution du taux de croissance du phytoplancton dans le milieu acidifié mais pas de changement notable dans la structure de la communauté. Les ajouts de poussières et de cendres, de même que les variations de pH, n’ont pas eu d’effet significatif sur la production de DMS et de son précurseur le diméthylsulfoniopropionate (DMSP), probablement en raison de la courte durée (4 jours) des expériences. L’ensemble des résultats de cette thèse montre que le fer contenu dans diverses sources atmosphériques naturelles est biodisponible pour le phytoplancton du Pacifique Nord-Est et que des taux de déposition réalistes peuvent stimuler la croissance de manière notable dans les premiers jours suivant une tempête désertique ou une éruption volcanique. Finalement, les résultats de mes expériences à stresseurs multiples Fer/acidification suggèrent une certaine résistance des communautés phytoplanctoniques à la diminution du pH prédite d’ici la fin du siècle pour les eaux de surface des océans.

Simulations of droplet dispersion in the wakes of cylinders and icing tunnel spray bars

Simulations of droplet dispersion behind cylinder wakes and downstream of icing tunnel spray bars were conducted. In both cases, a range of droplet sizes were investigated numerically with a Lagrangian particle trajectory approach while the turbulent air flow was investigated with a hybrid Reynolds-Averaged Navier-Stokes/Large-Eddy Simulations approach scheme. In the first study, droplets were injected downstream of a cylinder at sub-critical conditions (i.e. with laminar boundary layer separation). A stochastic continuous random walk (CRW) turbulence model was used to capture the effects of sub-grid turbulence. Small inertia droplets (characterized by small Stokes numbers) were affected by both the large-scale and small-scale vortex structures and closely followed the air flow, while exhibiting a dispersion consistent with that of a scalar flow field. Droplets with intermediate Stokes numbers were centrifuged by the vortices to the outer edges of the wake, yielding an increased dispersion. Large Stokes number droplets were found to be less responsive to the vortex structures and exhibited the least dispersion. Particle concentration was also correlated with vorticity distribution which yielded preferential bias effects as a function of different particle sizes. This trend was qualitatively similar to results seen in homogenous isotropic turbulence, though the influence of particle inertia was less pronounced for the cylinder wake case. A similar study was completed for droplet dispersion within the Icing Research Tunnel (IRT) at the NASA Glenn Research Center, where it is important to obtain a nearly uniform liquid water content (LWC) distribution in the test section (to recreate atmospheric icing conditions).. For this goal, droplets are diffused by the mean and turbulent flow generated from the nozzle air jets, from the upstream spray bars, and from the vertical strut wakes. To understand the influence of these three components, a set of simulations was conducted with a sequential inclusion of these components. Firstly, a jet in an otherwise quiescent airflow was simulated to capture the impact of the air jet on flow turbulence and droplet distribution, and the predictions compared well with experimental results. The effects of the spray bar wake and vertical strut wake were then included with two more simulation conditions, for which it was found that the air jets were the primary driving force for droplet dispersion, i.e. that the spray bar and vertical strut wake effects were secondary.

Heat transfer performance investigation of nanofluids flow in pipe

Different types of base fluids, such as water, engine oil, kerosene, ethanol, methanol, ethylene glycol etc. are usually used to increase the heat transfer performance in many engineering applications. But these conventional heat transfer fluids have often several limitations. One of those major limitations is that the thermal conductivity of each of these base fluids is very low and this results a lower heat transfer rate in thermal engineering systems. Such limitation also affects the performance of different equipments used in different heat transfer process industries. To overcome such an important drawback, researchers over the years have considered a new generation heat transfer fluid, simply known as nanofluid with higher thermal conductivity. This new generation heat transfer fluid is a mixture of nanometre-size particles and different base fluids. Different researchers suggest that adding spherical or cylindrical shape of uniform/non-uniform nanoparticles into a base fluid can remarkably increase the thermal conductivity of nanofluid. Such augmentation of thermal conductivity could play a more significant role in enhancing the heat transfer rate than that of the base fluid. Nanoparticles diameters used in nanofluid are usually considered to be less than or equal to 100 nm and the nanoparticles concentration usually varies from 5% to 10%. Different researchers mentioned that the smaller nanoparticles concentration with size diameter of 100 nm could enhance the heat transfer rate more significantly compared to that of base fluids. But it is not obvious what effect it will have on the heat transfer performance when nanofluids contain small size nanoparticles of less than 100 nm with different concentrations. Besides, the effect of static and moving nanoparticles on the heat transfer of nanofluid is not known too. The idea of moving nanoparticles brings the effect of Brownian motion of nanoparticles on the heat transfer. The aim of this work is, therefore, to investigate the heat transfer performance of nanofluid using a combination of smaller size of nanoparticles with different concentrations considering the Brownian motion of nanoparticles. A horizontal pipe has been considered as a physical system within which the above mentioned nanofluid performances are investigated under transition to turbulent flow conditions. Three different types of numerical models, such as single phase model, Eulerian-Eulerian multi-phase mixture model and Eulerian-Lagrangian discrete phase model have been used while investigating the performance of nanofluids. The most commonly used model is single phase model which is based on the assumption that nanofluids behave like a conventional fluid. The other two models are used when the interaction between solid and fluid particles is considered. However, two different phases, such as fluid and solid phases is also considered in the Eulerian-Eulerian multi-phase mixture model. Thus, these phases create a fluid-solid mixture. But, two phases in the Eulerian-Lagrangian discrete phase model are independent. One of them is a solid phase and the other one is a fluid phase. In addition, RANS (Reynolds Average Navier Stokes) based Standard κ-ω and SST κ-ω transitional models have been used for the simulation of transitional flow. While the RANS based Standard κ-ϵ, Realizable κ-ϵ and RNG κ-ϵ turbulent models are used for the simulation of turbulent flow. Hydrodynamic as well as temperature behaviour of transition to turbulent flows of nanofluids through the horizontal pipe is studied under a uniform heat flux boundary condition applied to the wall with temperature dependent thermo-physical properties for both water and nanofluids. Numerical results characterising the performances of velocity and temperature fields are presented in terms of velocity and temperature contours, turbulent kinetic energy contours, surface temperature, local and average Nusselt numbers, Darcy friction factor, thermal performance factor and total entropy generation. New correlations are also proposed for the calculation of average Nusselt number for both the single and multi-phase models. Result reveals that the combination of small size of nanoparticles and higher nanoparticles concentrations with the Brownian motion of nanoparticles shows higher heat transfer enhancement and thermal performance factor than those of water. Literature suggests that the use of nanofluids flow in an inclined pipe at transition to turbulent regimes has been ignored despite its significance in real-life applications. Therefore, a particular investigation has been carried out in this thesis with a view to understand the heat transfer behaviour and performance of an inclined pipe under transition flow condition. It is found that the heat transfer rate decreases with the increase of a pipe inclination angle. Also, a higher heat transfer rate is found for a horizontal pipe under forced convection than that of an inclined pipe under mixed convection.