Multiphase modelling of the characteristics of close coupled gas atomization

Not withstanding the high demand of metal powder for automotive and High Tech applications, there are still many unclear aspects of the production process. Only recentlyhas supercomputer performance made possible numerical investigation of such phenomena. This thesis focuses on the modelling aspects of primary and secondary atomization. Initially two-dimensional analysis is carried out to investigate the influence of flow parameters (reservoir pressure and gas temperature principally) and nozzle geometry on final powder yielding. Among the different types, close coupled atomizers have the best performance in terms of cost and narrow size distribution. An isentropic contoured nozzle is introduced to minimize the gas flow losses through shock cells: the results demonstrate that it outperformed the standard converging-diverging slit nozzle. Furthermore the utilization of hot gas gave a promising outcome: the powder size distribution is narrowed and the gas consumption reduced. In the second part of the thesis, the interaction of liquid metal and high speed gas near the feeding tube exit was studied. Both axisymmetric andnon-axisymmetric geometries were simulated using a 3D approach. The filming mechanism was detected only for very small metal flow rates (typically obtained in laboratory scale atomizers). When the melt flow increased, the liquid core overtook the adverse gas flow and entered in the high speed wake directly: in this case the disruption isdriven by sinusoidal surface waves. The process is characterized by fluctuating values of liquid volumes entering the domain that are monitored only as a time average rate: it is far from industrial robustness and capability concept. The non-axisymmetric geometry promoted the splitting of the initial stream into four cores, smaller in diameter and easier to atomize. Finally a new atomization design based on the lesson learned from previous cases simulation is presented.

Molecular modelling assisted design and synthesis of cyclothialidine derivatives as DNA gyrase inhibitors

Since cyclothialidine was discovered as the most active DNA gyrase inhibitor in 1994, enormous efforts have been devoted to make it into a commercial medicine by a number of pharmaceutical companies and research groups worldwide. However, no serious breakthrough has been made up to now. An essential problem involved with cyclothialidine is that though it demonstrated the potent inhibition of DNA gyrase, it showed little activity against bacteria. This probably is attributable to its inability to penetrate bacterial cell walls and membranes. We applied the TSAR programme to generate a QSAR equation to the gram-negative organisms. In that equation, LogP is profoundly indicated as the key factor influencing the cyclothialidine activity against bacteria. However, the synthesized new analogues have failed to prove that. In the structure based drug design stage, we designed a group of open chain cyclothialidine derivatives by applying the SPROUT programme and completed the syntheses. Improved activity is found in a few analogues and a 3D pharmacophore of the DNA gyrase B is proposed to lead to synthesis of the new derivatives for development of potent antibiotics.

A hybrid molecular dynamics/fluctuating hydrodynamics method for modelling liquids at multiple scales in space and time

A new 3D implementation of a hybrid model based on the analogy with two-phase hydrodynamics has been developed for the simulation of liquids at microscale. The idea of the method is to smoothly combine the atomistic description in the molecular dynamics zone with the Landau-Lifshitz fluctuating hydrodynamics representation in the rest of the system in the framework of macroscopic conservation laws through the use of a single "zoom-in" user-defined function s that has the meaning of a partial concentration in the two-phase analogy model. In comparison with our previous works, the implementation has been extended to full 3D simulations for a range of atomistic models in GROMACS from argon to water in equilibrium conditions with a constant or a spatially variable function s. Preliminary results of simulating the diffusion of a small peptide in water are also reported.

Multi-threaded parallel numerical modelling of femtosecond pulse propagation in laser machining

Femtosecond laser microfabrication has emerged over the last decade as a 3D flexible technology in photonics. Numerical simulations provide an important insight into spatial and temporal beam and pulse shaping during the course of extremely intricate nonlinear propagation (see e.g. [1,2]). Electromagnetics of such propagation is typically described in the form of the generalized Non-Linear Schrdinger Equation (NLSE) coupled with Drude model for plasma [3]. In this paper we consider a multi-threaded parallel numerical solution for a specific model which describes femtosecond laser pulse propagation in transparent media [4, 5]. However our approach can be extended to similar models. The numerical code is implemented in NVIDIA Graphics Processing Unit (GPU) which provides an effitient hardware platform for multi-threded computing. We compare the performance of the described below parallel code implementated for GPU using CUDA programming interface [3] with a serial CPU version used in our previous papers [4,5]. © 2011 IEEE.

Leap Aided Modelling (LAM) in Blender

L'evoluzione tecnologica e l'utilizzo crescente della computer grafica in diversi settori stanno suscitando l'interesse di sempre più persone verso il mondo della modellazione 3D. I software di modellazione, tuttavia, si presentano spesso inadeguati all'utilizzo da parte di utenti senza esperienza, soprattutto a causa dei comandi di navigazione e modellazione poco intuitivi. Dal punto di vista dell'interazione uomo-computer, questi software devono infatti affrontare un grande ostacolo: il rapporto tra dispositivi di input 2D (come il mouse) e la manipolazione di una scena 3D. Il progetto presentato in questa tesi è un addon per Blender che consente di utilizzare il dispositivo Leap Motion come ausilio alla modellazione di superfici in computer grafica. L'obiettivo di questa tesi è stato quello di progettare e realizzare un'interfaccia user-friendly tra Leap e Blender, in modo da potere utilizzare i sensori del primo per facilitare ed estendere i comandi di navigazione e modellazione del secondo. L'addon realizzato per Blender implementa il concetto di LAM (Leap Aided Modelling: modellazione assistita da Leap), consentendo quindi di estendere le feature di Blender riguardanti la selezione, lo spostamento e la modifica degli oggetti in scena, la manipolazione della vista utente e la modellazione di curve e superfici Non Uniform Rational B-Splines (NURBS). Queste estensioni sono state create per rendere più veloci e semplici le operazioni altrimenti guidate esclusivamente da mouse e tastiera.

Unstructured grid modelling of offshore wind farm impacts on seasonally stratified shelf seas

Shelf seas comprise approximately 7% of the world’s oceans and host enormous economic activity. Development of energy installations (e.g. Offshore Wind Farms (OWFs), tidal turbines) in response to increased demand for renewable energy requires a careful analysis of potential impacts. Recent remote sensing observations have identified kilometrescale impacts from OWFs. Existing modelling evaluating monopile impacts has fallen into two camps: small-scale models with individually resolved turbines looking at local effects; and large-scale analyses but with sub-grid scale turbine parameterisations. This work straddles both scales through a 3D unstructured grid model (FVCOM): wind turbine monopiles in the eastern Irish Sea are explicitly described in the grid whilst the overall grid domain covers the south-western UK shelf. Localised regions of decreased velocity extend up to 250 times the monopile diameter away from the monopile. Shelf-wide, the amplitude of the M2 tidal constituent increases by up to 7%. The turbines enhance localised vertical mixing which decreases seasonal stratification. The spatial extent of this extends well beyond the turbines into the surrounding seas. With significant expansion of OWFs on continental shelves, this work highlights the importance of how OWFs may impact coastal (e.g. increased flooding risk) and offshore (e.g. stratification and nutrient cycling) areas.

Unstructured grid modelling of offshore wind farm impacts on seasonally stratified shelf seas

Shelf seas comprise approximately 7% of the world’s oceans and host enormous economic activity. Development of energy installations (e.g. Offshore Wind Farms (OWFs), tidal turbines) in response to increased demand for renewable energy requires a careful analysis of potential impacts. Recent remote sensing observations have identified kilometrescale impacts from OWFs. Existing modelling evaluating monopile impacts has fallen into two camps: small-scale models with individually resolved turbines looking at local effects; and large-scale analyses but with sub-grid scale turbine parameterisations. This work straddles both scales through a 3D unstructured grid model (FVCOM): wind turbine monopiles in the eastern Irish Sea are explicitly described in the grid whilst the overall grid domain covers the south-western UK shelf. Localised regions of decreased velocity extend up to 250 times the monopile diameter away from the monopile. Shelf-wide, the amplitude of the M2 tidal constituent increases by up to 7%. The turbines enhance localised vertical mixing which decreases seasonal stratification. The spatial extent of this extends well beyond the turbines into the surrounding seas. With significant expansion of OWFs on continental shelves, this work highlights the importance of how OWFs may impact coastal (e.g. increased flooding risk) and offshore (e.g. stratification and nutrient cycling) areas.

Face recognition using a unified 3D morphable model

We address the problem of 3D-assisted 2D face recognition in scenarios when the input image is subject to degradations or exhibits intra-personal variations not captured by the 3D model. The proposed solution involves a novel approach to learn a subspace spanned by perturbations caused by the missing modes of variation and image degradations, using 3D face data reconstructed from 2D images rather than 3D capture. This is accomplished by modelling the difference in the texture map of the 3D aligned input and reference images. A training set of these texture maps then defines a perturbation space which can be represented using PCA bases. Assuming that the image perturbation subspace is orthogonal to the 3D face model space, then these additive components can be recovered from an unseen input image, resulting in an improved fit of the 3D face model. The linearity of the model leads to efficient fitting. Experiments show that our method achieves very competitive face recognition performance on Multi-PIE and AR databases. We also present baseline face recognition results on a new data set exhibiting combined pose and illumination variations as well as occlusion.

Historic Building Information Modelling: il caso della Rocca di San Felice sul Panaro

Il Building Information Modelling nasce da un processo di integrazione sostenibile, basato sull'interoperabilità dei processi. La caratteristica vincente è la circolarietà delle informazioni: ogni informazione è gestita come parametro di un ricco e complesso modello parametrico dell'edificio; la geometria, i materiali, i costi ed i tempi sono gestiti come parametri internamente collegati e quindi variabili di uno stesso sistema. Nel caso di beni storici, la maggior parte degli edifici possiede vincoli intrinseci che influenzano tali parametri. I materiali non possono essere scelti liberamente, in quanto parte di un organismo esistente, la geometria dell'edificio è definita e difficilmente sarà variata negli interventi di recupero. Nella presente tesi si applica il metodo CLOUD2FEM al mondo dell'Historic Building Information Modelling (HBIM) concentrandosi sullo studio della Rocca Estense di San Felice sul Panaro, colpita dal sisma dell'Emilia e attualmente inagibile. La procedura CLOUD2FEM permette di trasformare le informazioni ricavate dal laser scanner in mesh chiuse e regolari, generando in modo semi-automatico un modello FEM 3D. Nel caso di costruzioni complesse, la cui geometria non può essere ricondotta a modelli semplificati, è necessario valutare l'attendibilità del modello strutturale. Nel caso in esame, la validazione è stata condotta mediante il confronto del danno rilevato con il danno simulato. La flessibilità del modello permette di aggiungere dettagli inizialmente non rilevati: ogni informazione è inserita nel modello attraverso un parametro differente, al fine di eseguire analisi sullo stato di fatto e su futuri stati di progetto con semplice aggiornamento dei parametri.

Modelling continuum mechanics phenomena using three dimensional unstructured meshes on massively parallel processors

The difficulties encountered in implementing large scale CM codes on multiprocessor systems are now fairly well understood. Despite the claims of shared memory architecture manufacturers to provide effective parallelizing compilers, these have not proved to be adequate for large or complex programs. Significant programmer effort is usually required to achieve reasonable parallel efficiencies on significant numbers of processors. The paradigm of Single Program Multi Data (SPMD) domain decomposition with message passing, where each processor runs the same code on a subdomain of the problem, communicating through exchange of messages, has for some time been demonstrated to provide the required level of efficiency, scalability, and portability across both shared and distributed memory systems, without the need to re-author the code into a new language or even to support differing message passing implementations. Extension of the methods into three dimensions has been enabled through the engineering of PHYSICA, a framework for supporting 3D, unstructured mesh and continuum mechanics modeling. In PHYSICA, six inspectors are used. Part of the challenge for automation of parallelization is being able to prove the equivalence of inspectors so that they can be merged into as few as possible.

Solar magnetic carpet III: coronal modelling of synthetic magnetograms

This article is the third in a series working towards the construction of a realistic, evolving, non-linear force-free coronal-field model for the solar magnetic carpet. Here, we present preliminary results of 3D time-dependent simulations of the small-scale coronal field of the magnetic carpet. Four simulations are considered, each with the same evolving photospheric boundary condition: a 48-hour time series of synthetic magnetograms produced from the model of Meyer et al. ( Solar Phys. 272, 29, 2011). Three simulations include a uniform, overlying coronal magnetic field of differing strength, the fourth simulation includes no overlying field. The build-up, storage, and dissipation of magnetic energy within the simulations is studied. In particular, we study their dependence upon the evolution of the photospheric magnetic field and the strength of the overlying coronal field. We also consider where energy is stored and dissipated within the coronal field. The free magnetic energy built up is found to be more than sufficient to power small-scale, transient phenomena such as nanoflares and X-ray bright points, with the bulk of the free energy found to be stored low down, between 0.5 - 0.8 Mm. The energy dissipated is currently found to be too small to account for the heating of the entire quiet-Sun corona. However, the form and location of energy-dissipation regions qualitatively agree with what is observed on small scales on the Sun. Future MHD modelling using the same synthetic magnetograms may lead to a higher energy release.

Analysis and modelling of immune cell behaviour in lymph nodes based on multi-photon imaging

This thesis presents quantitative studies of T cell and dendritic cell (DC) behaviour in mouse lymph nodes (LNs) in the naive state and following immunisation. These processes are of importance and interest in basic immunology, and better understanding could improve both diagnostic capacity and therapeutic manipulations, potentially helping in producing more effective vaccines or developing treatments for autoimmune diseases. The problem is also interesting conceptually as it is relevant to other fields where 3D movement of objects is tracked with a discrete scanning interval. A general immunology introduction is presented in chapter 1. In chapter 2, I apply quantitative methods to multi-photon imaging data to measure how T cells and DCs are spatially arranged in LNs. This has been previously studied to describe differences between the naive and immunised state and as an indicator of the magnitude of the immune response in LNs, but previous analyses have been generally descriptive. The quantitative analysis shows that some of the previous conclusions may have been premature. In chapter 3, I use Bayesian state-space models to test some hypotheses about the mode of T cell search for DCs. A two-state mode of movement where T cells can be classified as either interacting to a DC or freely migrating is supported over a model where T cells would home in on DCs at distance through for example the action of chemokines. In chapter 4, I study whether T cell migration is linked to the geometric structure of the fibroblast reticular network (FRC). I find support for the hypothesis that the movement is constrained to the fibroblast reticular cell (FRC) network over an alternative 'random walk with persistence time' model where cells would move randomly, with a short-term persistence driven by a hypothetical T cell intrinsic 'clock'. I also present unexpected results on the FRC network geometry. Finally, a quantitative method is presented for addressing some measurement biases inherent to multi-photon imaging. In all three chapters, novel findings are made, and the methods developed have the potential for further use to address important problems in the field. In chapter 5, I present a summary and synthesis of results from chapters 3-4 and a more speculative discussion of these results and potential future directions.

Computational modelling of non-equilibrium condensing steam flows in low-pressure steam turbines

The steam turbines play a significant role in global power generation. Especially, research on low pressure (LP) steam turbine stages is of special importance for steam turbine man- ufactures, vendors, power plant owners and the scientific community due to their lower efficiency than the high pressure steam turbine stages. Because of condensation, the last stages of LP turbine experience irreversible thermodynamic losses, aerodynamic losses and erosion in turbine blades. Additionally, an LP steam turbine requires maintenance due to moisture generation, and therefore, it is also affecting on the turbine reliability. Therefore, the design of energy efficient LP steam turbines requires a comprehensive analysis of condensation phenomena and corresponding losses occurring in the steam tur- bine either by experiments or with numerical simulations. The aim of the present work is to apply computational fluid dynamics (CFD) to enhance the existing knowledge and understanding of condensing steam flows and loss mechanisms that occur due to the irre- versible heat and mass transfer during the condensation process in an LP steam turbine. Throughout this work, two commercial CFD codes were used to model non-equilibrium condensing steam flows. The Eulerian-Eulerian approach was utilised in which the mix- ture of vapour and liquid phases was solved by Reynolds-averaged Navier-Stokes equa- tions. The nucleation process was modelled with the classical nucleation theory, and two different droplet growth models were used to predict the droplet growth rate. The flow turbulence was solved by employing the standard k-ε and the shear stress transport k-ω turbulence models. Further, both models were modified and implemented in the CFD codes. The thermodynamic properties of vapour and liquid phases were evaluated with real gas models. In this thesis, various topics, namely the influence of real gas properties, turbulence mod- elling, unsteadiness and the blade trailing edge shape on wet-steam flows, are studied with different convergent-divergent nozzles, turbine stator cascade and 3D turbine stator-rotor stage. The simulated results of this study were evaluated and discussed together with the available experimental data in the literature. The grid independence study revealed that an adequate grid size is required to capture correct trends of condensation phenomena in LP turbine flows. The study shows that accurate real gas properties are important for the precise modelling of non-equilibrium condensing steam flows. The turbulence modelling revealed that the flow expansion and subsequently the rate of formation of liquid droplet nuclei and its growth process were affected by the turbulence modelling. The losses were rather sensitive to turbulence modelling as well. Based on the presented results, it could be observed that the correct computational prediction of wet-steam flows in the LP turbine requires the turbulence to be modelled accurately. The trailing edge shape of the LP turbine blades influenced the liquid droplet formulation, distribution and sizes, and loss generation. The study shows that the semicircular trailing edge shape predicted the smallest droplet sizes. The square trailing edge shape estimated greater losses. The analysis of steady and unsteady calculations of wet-steam flow exhibited that in unsteady simulations, the interaction of wakes in the rotor blade row affected the flow field. The flow unsteadiness influenced the nucleation and droplet growth processes due to the fluctuation in the Wilson point.