Academic literature on the topic 'Modelling and theoretical studies'

Based on analyses by a variety of investigators, it has become understood that gas phase reactions can account for much of the chemistry observed in dense interstellar clouds. However, quantitative calculations of molecular abundances utilizing gas phase reactions are beset with difficulties. These difficulties include uncertainties in needed rate coefficients at the low temperatures of interstellar clouds, uncertainties in the dynamics of physical processes such as cloud collapse and clumping, and uncertainties in our understanding of gasgrain interactions. New work in some of these areas and its impact on modelling is emphasized.

W Virginis variables are the population II counterparts of the classical cepheids, although they do not show quite the same trends as are seen in the latter. Theoretical studies of the population II cepheids have not been very extensive until recent studies of the shorter period variables (BL Herculis variables, with periods between 1 and 10 days). The variables with periods above 10 days (up to about 50 days) have only been studied by a few authors, modelling the prototype star (W Vir) (.g. Christy 1966; Davis 1974). Although these models qualitatively reproduced the observations they were not very successful, and were based on a stellar mass (0.88 Mʘ) that now seems likely to be too high.

AbstractThe construction of viable and physically-realistic interstellar dust models is only possible if the constraints imposed by laboratory data on interstellar dust analogue materials are respected and used within a meaningful theoretical framework. These “physical” dust models can then be directly compared to observations without the need for any tuning to fit the observations. Such models will generally fail to achieve the excellent fits to observations that “empirical” models are able to achieve. However, the physically-realistic approach will necessarily lead to a deeper insight and a fuller understanding of the nature and evolution of interstellar dust. The THEMIS modelling approach, based on (hydrogenated) amorphous carbons and amorphous silicates with metallic Fe and/or FeS nano-inclusions appears to be a promising move in this direction.

In this paper, we discuss how the adoption of a particular theoretical framework affects task design in the research field of modelling and applications. With this purpose, we start by referring to the existence of different reference epistemological models about mathematical modelling to analyse better the consequences they have for decision making concerning designing modelling tasks and their implementation. In particular, we present the analysis of three case studies, which have been selected as representatives of different theoretical perspectives to modelling. We discuss the impact of the chosen reference epistemological model on the task design process of mathematical modelling and the local ecologies suited for their implementation.

The present work is part of research project titled 'Modeling, Simulation, Theoretical and Experimental Thermal Studies of Ghardaia Local Climate. Effect of Thermal Insulation'. The main objective of the current work was to determine the temperatures of the building in question with or without thermal insulation. This paper presents experimental and theoretical studies of two rooms thermal behavior. These rooms are two parts of an apartment building located in semi arid area (Gharda?a). A mathematical model describing the thermal behavior of these rooms in question was developed and elaborated. These studies allowed also room internal temperature evolution profile to be determined. Through numerical simulation it has been found that the applied insulation layer reduced the losses of winter and maintained an appropriate temperature. It was found that the theoretically found results were consistent to an acceptable level with those found experimentally.

Understanding the interactions between dye molecules and their constituent moieties will lead to an improvement in the design of new molecules with the appropriate properties. Here, we use computational methods to investigate the relative stability of the three tautomers of hydroxy-triazine, and how they interact with themselves in the gas phase, in aqueous solution and in the solid state. Ab initio and density functional theory (DFT) methods were used to establish the relative gas phase stability of the tautomers, showing two of the tautomers to be significantly more stable than the third. Thermodynamic cycles were calculated using ab initio free energies of salvation and gas phase energies. The crystal phase investigation involved data mining of the Cambridge Structural Database and generating hypothetical crystal structures which were subjected to lattice energy minimisations. The interactions were investigated in the gas phase by minimising small clusters of the tautomers, treated as rigid molecules, from a number of random starting conformations. Molecule dynamics simulations looked at the behaviour in solution, while the lattice energy minimisations and the CSD were again used to look at solid phase interactions. The above methods were also incorporated into further investigations of the interactions between these tautomers and another important dye-related molecule, morpholine, both as an additive and as a covalently bonded fraction. Whole dye molecules containing these substructures, were then studied using the above methods, as well as UV-Vis spectroscopic analysis to calculate dimerisation equilibrium constants. Finally the computational methods were applied to look at the effects of substituents on the interactions of zinc phthalocyanine.

With respect to nitrides being considered as potential fast reactor fuels, research is conducted on the out-of-pile thermophysical properties, sintering and fabrication processes, gas migration mechanisms, self-diffusion and point defect behaviour of actinide nitrides, their surrogate materials, and the inert matrix material ZrN . The experimental research, carried out in the framework of qualifying fuel for the European Lead Cooled Training Reactor (ELECTRA), shows that sintered ZrN and (Dy,Zr)N pellet densities are influenced by the oxygen concentration in the material. The effect is confirmed in sintered (Pu,Zr)N pellets. Oxygen concentration also plays a role in the thermophysical properties of inert matrix nitride fuels, but does not have an impact on the electrical properties of these materials. With the fuel fabrication methods applied here, clean nitride powders can be synthesized. However, the subsequent fabrication phases, including milling and solid solution formation, increases the impurity levels significantly. Research of equal importance is performed on materials free of fabrication-induced impurities, whose properties are studied by employing first-principles methods. ZrN, UN and (U,Zr)N are studied, whereas the results from ZrN are expected to be applicable for actinide nitrides as a first approximation. The migration of noble gases in ZrN, on the atomic scale, confirms the experimentally observed tendency for noble gases with higher atomic number to be retained in the fuel matrix, while the majority of He is released to the fuel pin. Materials modelling implies that self-diffusion of nitrogen and metal atoms in inert matrix nitride fuels is accelerated under irradiation, since noble gas retention reduces migration barriers which govern self-diffusion. Unlike Kr and Xe, He has the capacity to be released into the fuel matrix, after having been trapped in a vacancy. The results are expected to aid in providing an explanation to the macroscopic diffusion phenomena in nitride fuels, as the diffusion behaviour of noble gases is sparsely studied. In addition, a study on the miscibility of ZrN and UN in a narrow composition range suggests solubility, based on the negative mixing energies. The results obtained from research on inert matrix nitride fuel underline several beneficial properties which are desirable in a fast reactor fuel. The relevance of these results is analyzed and contextualized in the thesis, from the perspective of current research and development in the field.

QC 20130611

This thesis focused on the review and background theory of previous studies on fatigue failure criteria, experimental work and results’ analysis. Several techniques are used for testing fatigue performance for both hot mix asphalt (HMA) and fine aggregate matrix (FAM), such as two-, three- and four-point bending, indirect tension and uniaxial tests. In recent years, a new technique has been introduced using the Dynamic Shear Rheometer (DSR). This technique is based on applying a sinusoidal deformation or loading onto small cylindrical samples, 12 mm diameter and 50 mm height, and the response is analysed to obtain phase angle and deformation data under any given circumstances, such as temperature, frequency, etc. The DSR is limited to test bitumen and fine aggregates matrix FAM samples only; nevertheless, no research efforts have been found that use a DSR to study the performance of full HMA samples. In this work, a successful trial was proposed using a DSR for fatigue testing of HMA under controlled strain and stress modes. Two types of aggregates, limestone and granite with two binder grades, 40/60 and 160/220, were employed to prepare four different mixes of hot rolled asphalt (HRA) and dense bitumen macadam (DBM). A technical procedure was adopted to prepare the DSR samples (12 mm in diameter and 50 mm in height) and a statistical procedure based on histograms and modes for the bulk density of the DSR samples was used to select the samples to be tested for fatigue. An approach was developed based on sweep strain/stress amplitude to arrive at a suitable strain and stress amplitude at the damage region to be used in the fatigue test. A new fatigue index (FIR) parameter was derived from the dissipated pseudo-strain energy for the stress-pseudo-strain relationship to be used for evaluating fatigue performance. Results showed that there is a plateau value for FIR which can be used to evaluate fatigue performance, and this value increases when the normalised shear modulus decreases to less than 0.35 and 0.20 for strain and stress test modes respectively. In addition, the FIR results were in agreement with the results from other reliable approaches that have been used for evaluating fatigue performance, such as the energy ratio (ER) and the traditional approach (TA). A two-point bending (2PB) test for trapezoidal samples was used to verify the DSR technique using FIR, TA and ER approaches; the analysis of results revealed the same conclusions as the DSR technique. The variance in the results of the tested samples was studied using error bars in terms of standard of error for all approaches in both techniques: DSR and 2PB. This variance analysis revealed that FIR has low variation in comparison with the TA and ER approaches in both test techniques. A computational model based on artificial neural networks (ANNs) was used in this work for developing models to predict the fatigue performance of hot mix asphalt (HMA). The fatigue performance was defined according to the criteria of the TA, ER and FIR approaches. The results revealed an excellent correlation between the predicted and experimental data. Bias analysis for ANN models involving average error, intercept and slope showed that the strain test mode was more accurate than the stress test mode. A fracture mechanistic approach was also used to evaluate the fracture performance of HMA tested in DSR. A simple fracture model was developed based on a modified Paris’ law and fatigue test parameters represented by relaxation test coefficient (m) and the dissipated pseudo-strain energy to calculate an internal damage parameter, namely the fracture damage index (FIc). The analysis of the results for FIc was in agreement with the FIR, ER and TA approaches; also, it showed better performance analysis in terms of variation than the TA and ER approaches. The fracture model, FIc, was used as a base for developing a model for predicting fatigue life of HMA in terms of number of cycles for strain and stress test modes. The bias analysis revealed that the strain model’s prediction accuracy was better than that of the stress model. Hysteretic behaviour represents the nonlinear relationship of the stress–strain response for HMA under cyclic loading during fatigue testing. In this regard, a successful trial introduced for modelling the hysteresis loops using Bouc-Wen model for HMA samples tested for fatigue under controlled strain mode using DSR. The nonlinear least squares algorithm was used to estimate the seven parameters for the Bouc-Wen model using experimental results for hysteresis loops of the HMA samples tested in DSR; these parameters control the shape and slope of the degraded hysteresis loops. The outcome of this work confirmed that there is a good agreement between the modelled and experimental hysteresis loops. Due to the variation in the fatigue performance of HMA samples as a result of their properties, the Bouc-Wen model was not able to fully simulate the degradation for different samples when there were changes in the parameters. To improve the Bouc-Wen model’s simulation performance, an ANN technique was used to develop models to predict its parameters; this technique improved the Bouc-Wen model’s performance in Phase I, while its performance in Phase II-III was still poor, despite the degradation simulation being clear. This work revealed the feasibility of using the DSR technique in evaluating the fatigue performance of full HMA according to the developed approaches for preparing and selecting DSR samples and performing fatigue tests. In addition, the work confirmed that limestone has a better fatigue performance for both HRA and DBM mixes than granite. On the other hand, the theoretical part included developing several models based on an ANN and constitutive equations showed the efficiency of these models in predicting the fatigue life of HMA samples tested in the DSR.

Astronomy with gravitational-wave observations is now a reality. Much of the theoretical research in this field falls under three broad themes: the mathematical description and physical understanding of gravitational radiation and its effects; the construction of accurate and computationally efficient waveform models for astrophysical sources; and the improved statistical analysis of noisy data from interferometric detectors, so as to extract and characterise source signals. The doctoral thesis presented in this dissertation is an investigation of various topics across these themes. Under the first theme, we examine the direct interaction between gravitational waves and electromagnetic fields in a self-contained theoretical study; this is done with a view to understanding the observational implications for highly energetic astrophysical events that radiate in both the gravitational and electromagnetic sectors. We then delve into the second theme of source modelling by developing and implementing an improved waveform model for the extreme-mass-ratio inspirals of stellar-mass compact objects into supermassive black holes, which are an important class of source for future space-based detectors such as the Laser Interferometer Space Antenna. Two separate topics are explored under the third theme of data analysis. We begin with the procedure of searching for gravitational-wave signals in detector data, and propose several combinatorial compression schemes for the large banks of waveform templates that are matched against putative signals, before studying the usefulness of these schemes for accelerating searches. After a gravitational-wave source is detected, the follow-up process is to measure its parameters in detail from the data; this is addressed as we apply the machine-learning technique of Gaussian process regression to gravitational-wave data analysis, and in particular to the formidable problem of parameter estimation for extreme-mass-ratio inspirals.

Dans cette thèse, nous nous proposons d'étudier et de traiter conjointement plusieurs problèmes phares en traitement d'images incluant le recalage d'images qui vise à apparier deux images via une transformation, la segmentation d'images dont le but est de délimiter les contours des objets présents au sein d'une image, et la décomposition d'images intimement liée au débruitage, partitionnant une image en une version plus régulière de celle-ci et sa partie complémentaire oscillante appelée texture, par des approches variationnelles locales et non locales. Les relations étroites existant entre ces différents problèmes motivent l'introduction de modèles conjoints dans lesquels chaque tâche aide les autres, surmontant ainsi certaines difficultés inhérentes au problème isolé. Le premier modèle proposé aborde la problématique de recalage d'images guidé par des résultats intermédiaires de segmentation préservant la topologie, dans un cadre variationnel. Un second modèle de segmentation et de recalage conjoint est introduit, étudié théoriquement et numériquement puis mis à l'épreuve à travers plusieurs simulations numériques. Le dernier modèle présenté tente de répondre à un besoin précis du CEREMA (Centre d'Études et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement) à savoir la détection automatique de fissures sur des images d'enrobés bitumineux. De part la complexité des images à traiter, une méthode conjointe de décomposition et de segmentation de structures fines est mise en place, puis justifiée théoriquement et numériquement, et enfin validée sur les images fournies
In this thesis, we study and jointly address several important image processing problems including registration that aims at aligning images through a deformation, image segmentation whose goal consists in finding the edges delineating the objects inside an image, and image decomposition closely related to image denoising, and attempting to partition an image into a smoother version of it named cartoon and its complementary oscillatory part called texture, with both local and nonlocal variational approaches. The first proposed model addresses the topology-preserving segmentation-guided registration problem in a variational framework. A second joint segmentation and registration model is introduced, theoretically and numerically studied, then tested on various numerical simulations. The last model presented in this work tries to answer a more specific need expressed by the CEREMA (Centre of analysis and expertise on risks, environment, mobility and planning), namely automatic crack recovery detection on bituminous surface images. Due to the image complexity, a joint fine structure decomposition and segmentation model is proposed to deal with this problem. It is then theoretically and numerically justified and validated on the provided images

1. The Force Field Accuracy Problem. The utility and applicability of MD simulations to model biomolecular systems goes only as far as its ability to sufficiently sample the conformational space and the correct description of the potential in terms of the force field functional form and parameter set. Clearly, the force field defines the shape of the conformational space for a given set of atomic positions and also the accessibility of energy minima. When simulating systems at equilibrium, especially quite stable systems such as DNA, the force fields strive to generate ensembles that reproduce well real systems and this does not have to come as a big trade-off with sampling power. In recent years it has become the business of computer engineers and software developers to address the issue of achieving long and biologically relevant time scales. Convergence and reproducibility of atomistic DNA simulations with state-of-the-art force fields such as our parmbsc1 has been convincingly demonstrated. It also seems that until a significant revolution, where milliseconds of simulation become routine, current sampling ranges completely cover the internal structures and dynamics of B-DNAs at this time scale. The growing confidence has allowed many researchers to use MD for very detailed studies on the sequence-dependent nature of DNA oligomers and on the complex arsenal of mechanisms that govern its behavior. In any such studies careful validation of results is necessary since it is not yet entirely clear how well and to what degree are sequence effects reproduced in MD. The fact that the latest-generation of force fields agree very well between themselves and that they fit with the sparse experimental data is surely very encouraging, but it will be some time until small differences in sequence geometries can be validated. Our own extensive validation of the parmbsc1 force field, as well as a large number of other works that have, since its publication, either specifically set out to assess its performance, or have just applied it with success, speak of a very stable parametrization able to deal with a wide range of DNAs. It is worth to mention that in special conditions small improvements might be necessary, which could be achieved with the inclusion of polarization terms. However, up to date, no force field has been able to model polarization without eventually destabilizing the system and this at a huge cost (a factor of 10) to calculation speed. To sum up, based on the remarkable performance of parmbsc1, we and other groups can employ it with confidence in the detailed study of DNA dynamics and we expect that the number of supporting results will only increase. 2. 2. Sequence-dependence and polymorphisms of B-DNA. So what is it that we actually learn from analyzing the conformation variability of DNA over its sequence space at the tetramer level? It is well established that different bps have different preferences regarding their internal geometries, and to some extent, Calladine’s set of heuristic rules is able to make sense of these differences. At the bps level, some sequences are extremely stable, such as ApT, and some sequences, such as CpG, have a bi-stable equilibrium and they convert between different arrangements of their internal geometries. There are cases where this frustration can be explained by their charge distribution, bulkiness or the strength of their stacking and h-bonding interactions, but in many cases in requires a more holistic view, taking higher-level sequence effects into account. In multi-microsecond MD simulations, intra-base-pair parameters are always unimodal since alternative states that might be accessed through base opening are not sampled in at this time scale. However, their ensemble averages show sizeable differences according to the change in sequence. Inter- base-pair parameters can be bimodal, but only in certain tetranulceotide combinations that make up about 5% of cases. This can be explained considering that the central bps of a particular combination of four nucleotides has a structural preference that is in conflict with those of its neighboring steps. In order to minimize the energy cost and satisfy as best as possible all conformational requirements, a more flexible bps will populate several states, usually a maximum of two. Optimization of geometries between several bps generally involve backbone rearrangements, with the sugar-phosphate acting as a hinge that allows consecutive bps to coordinate in a complex choreography often involving other factors, such as subtle changes in the solvent environment environment. In B-DNA the most important backbone transition is the BI/BII, which can be related to the base chemistry through the sequence-dependent relative strength of unconventional h-bonds that stabilize BII conformations. In a tetramer model of B-DNA, the backbone transitions of different tetramers are translated into motions along different internal degrees of freedom, depending on the sequence. Therefore, we are able now to build a picture of the interconnected conformational space of DNA as an overlap of tetranucleotide sequences with transferable structural descriptors. It is still a matter of speculation how these properties might be exploited by proteins and other binders for biological function. 3. Information transfer through the DNA. There are however a few special cases where the tetramer model does not seem to be sufficient. The CTAG is one such case that demonstrates that for a highly flexible and polymorphic tetramer, long-range sequence composition can have a notable effect on the structural properties of the central bps. Analyzing the mechanism behind this long-range communication through the DNA has meant more than anything else an opportunity to understand rare events of sequence modulation that might be a lot more general in cases of larger, induced distortions on the helix. In CTAG we could observe sequence influence not only from the hexamer level, but even from beyond, and the data points to a complex mechanism of information transfer across DNA through coordinated backbone movements. In performing biological function, DNA is often mistakenly viewed as an inert lattice onto which proteins assemble to replicate or transcribe genes. However, experiments demonstrate that information transfer in the DNA can happen even over long distances and can produce allosteric effects upon ligand binding. Without question, the binding of proteins or small molecules to the DNA can produce coupled conformational changes that may affect a neighboring binding site and increase its affinity for the secondary binding protein. Such changes need not alter ensemble averages and only potentiate modifications in the shape of the energy well at the secondary binding site. As seen from the dynamic information provided by an MD trajectory, maybe in more than one case of protein couples, DNA acts as a wire transmitting pulses of information originated at the primary binding site that travel to distant regions. We show that MD methods can provide reasonable explanations for cooperative binding phenomena on the DNA and open for the first time the possibility of the “allostery without conformational change” in the recruitment of proteins of the DNA scaffold. From a thermodynamic point of view, this type of cooperative binding seems to be entropy-driven. Thus, the first binding event freezes some of the degrees of freedom around it’s own binding region, but also reduces the entropy cost associated to the second binding.
1. Problema de exactitud del campo de fuerza La utilidad y aplicabilidad de las simulaciones de DM para modelar sistemas biomoleculares depende de su capacidad para muestrear suficientemente el espacio conformacional y la descripción correcta del potencial en términos de la forma funcional del campo de fuerza y el conjunto de parámetros. Claramente, el campo de fuerza define la forma del espacio conformacional para un conjunto dado de posiciones atómicas y también el acceso a los mínimos energéticos. Al simular sistemas en equilibrio, especialmente en sistemas bastante estables como el ADN, los campos de fuerza se esfuerzan por generar conjuntos que reproducen sistemas reales y no tiene por qué ser una gran desventaja con el poder de muestreo. En los últimos años, se ha convertido en tarea de los ingenieros informáticos y los desarrolladores de software abordar el problema de lograr escalas de tiempo largas y biológicamente relevantes. La convergencia y reproducibilidad de simulaciones de ADN atomístico con campos de fuerza de última generación, como nuestro parmbsc1, se ha demostrado de forma convincente. También parece que hasta llegar a una revolución significativa, donde los milisegundos de simulación se vuelven rutinarios, los rangos de muestreo actuales cubren por completo las estructuras internas y la dinámica de los ADN-B en esta escala de tiempo. La creciente confianza ha permitido a muchos investigadores utilizar DM para estudios muy detallados sobre la naturaleza dependiente de la secuencia de oligómeros de ADN y sobre el complejo arsenal de mecanismos que rigen su comportamiento. En cualquiera de estos estudios es necesaria una validación cuidadosa de los resultados ya que aún no está del todo claro qué tan bien y en qué grado se reproducen los efectos de secuencia en DM. El hecho de que la última generación de campos de fuerza coincida muy bien entre sí y que se ajusten a los escasos datos experimentales es seguramente muy alentador, pero pasará algún tiempo hasta que se puedan validar pequeñas diferencias en las geometrías de las secuencias. Nuestra propia validación extensiva del campo de fuerza parmbsc1, así como una gran cantidad de otros trabajos que, desde su publicación, se han establecido específicamente para evaluar su rendimiento, o simplemente lo han aplicado con éxito, hablan de una parametrización muy estable capaz de tratar con una amplia gama de ADN. Vale la pena mencionar que en condiciones especiales podrían ser necesarias pequeñas mejoras, lo que podría lograrse con la inclusión de términos de polarización. Sin embargo, hasta la fecha, ningún campo de fuerza ha sido capaz de modelar la polarización sin desestabilizar finalmente el sistema y esto a un costo enorme (un factor de 10) a la velocidad de cálculo. En resumen, con base en el notable desempeño de parmbsc1, nosotros y otros grupos podemos emplearlo con confianza en el estudio detallado de la dinámica del ADN y esperamos que el número de resultados de soporte solo aumente. 2. Dependencia de la secuencia y polimorfismos del ADN-B. Entonces, ¿qué es lo que realmente aprendemos al analizar la variabilidad de conformación del ADN sobre su espacio de secuencia a nivel de los tetrámeros? Está bien establecido que diferentes bps tienen diferentes preferencias con respecto a sus geometrías internas, y hasta cierto punto, el conjunto de reglas heurísticas de Calladine es capaz de dar sentido a estas diferencias. A nivel de bps, algunas secuencias son extremadamente estables, como ApT, y algunas secuencias, como CpG, tienen un equilibrio biestable y convierten entre diferentes disposiciones de sus geometrías internas. Hay casos en que esta frustración puede explicarse por la distribución de cargas, el volumen o la fuerza de sus interacciones de apilamiento y los puentes de hidrógeno, pero en muchos casos requiere una visión más integral, teniendo en cuenta los efectos de secuencia de más alto nivel. En simulaciones de DM de multi-microsegundos, los parámetros de pares intra-base son siempre unimodales ya que los estados alternativos a los que se puede acceder a través de la apertura de la base no se muestrean en esta escala de tiempo. Sin embargo, sus promedios de conjunto muestran diferencias considerables de acuerdo con el cambio en la secuencia. Los parámetros de pares de bases pueden ser bimodales, pero solo en ciertas combinaciones de tetranulceótidos que constituyen aproximadamente el 5% de los casos. Esto puede explicarse teniendo en cuenta que el bps central de una combinación particular de cuatro nucleótidos tiene una preferencia estructural que está en conflicto con la de sus pasos vecinos. Con el fin de minimizar el costo de energía y satisfacer de la mejor manera posible todos los requisitos conformacionales, un bps más flexible poblará varios estados, generalmente un máximo de dos. La optimización de las geometrías entre varios bps generalmente implica reorganizaciones de la red troncal, con el azúcar fosfato actuando como una bisagra que permite la coordinación consecutiva de bps en una coreografía compleja que a menudo involucra otros factores, tales como cambios sutiles en el entorno del solvente. En los ADN-B, la transición principal más importante es BI/BII, que se puede relacionar con la química a través de la fuerza relativa dependiente de la secuencia de puentes de hidrógeno no convencionales que estabilizan las conformaciones BII. En un modelo de tetrámero de ADN-B, las transiciones de la cadena principal de diferentes tetrámeros se traducen en movimientos a lo largo de diferentes grados internos de libertad, dependiendo de la secuencia. Por lo tanto, ahora podemos construir una imagen del espacio conformacional interconectado del ADN como una superposición de secuencias de tetranucleótidos con descriptores estructurales transferibles. Todavía es una cuestión de especulación cómo estas propiedades podrían ser explotadas por proteínas y otras moléculas que se unen al ADN para diferentes funciones biológicas. 3. Transferencia de información a través del ADN. Sin embargo, hay algunos casos especiales en los que el modelo de tetrámero no parece ser suficiente. El CTAG es uno de esos casos que demuestra que, para un tetrámero altamente flexible y polimórfico, la composición de la secuencia de largo alcance puede tener un efecto notable sobre las propiedades estructurales del bps central. Analizar el mecanismo detrás de esta comunicación de largo alcance a través del ADN ha significado más que nada una oportunidad para comprender los raros eventos de modulación de secuencia que podrían ser mucho más generales en casos de distorsiones mayores e inducidas en la hélice. En CTAG pudimos observar la influencia de la secuencia no solo desde el nivel del hexámero, sino incluso más allá, y los datos apuntan a un complejo mecanismo de transferencia de información a través del ADN mediante movimientos coordinados de la cadena principal. En la realización de la función biológica, el ADN a menudo se considera erróneamente como un retículo inerte sobre el cual las proteínas se ensamblan para replicar o transcribir genes. Sin embargo, los experimentos demuestran que la transferencia de información en el ADN puede ocurrir incluso a largas distancias y puede producir efectos alostéricos sobre la unión al ligando. Sin lugar a duda, la unión de proteínas o moléculas pequeñas al ADN puede producir cambios conformacionales acoplados que pueden afectar a un sitio de unión vecino y aumentar su afinidad por la proteína de unión secundaria. Tales cambios no necesitan alterar los promedios del conjunto y solo potencian modificaciones en la forma del pozo de energía en el sitio de unión secundario. Como se ve a partir de la información dinámica proporcionada por una trayectoria de DM, tal vez en más de un caso de parejas de proteínas, el ADN actúa como un cable que transmite pulsos de información originados en el sitio primario de unión que viajan a regiones distantes. Mostramos que los métodos de DM pueden proporcionar explicaciones razonables para los fenómenos de unión cooperativa en el ADN y abren por primera vez la posibilidad de la "alostería sin cambio conformacional" en el reclutamiento de proteínas al ADN. Desde un punto de vista termodinámico, este tipo de enlace cooperativo parece estar impulsado por la entropía. Por lo tanto, el primer evento vinculante congela algunos de los grados de libertad alrededor de su propia región de unión, pero también reduce el costo de entropía asociado al segundo enlace.

Considerable research is being carried out into the parameters that affect catalyst performance in order to meet the latest emission regulations. The conversion efficiency and the durability of automotive catalytic converters are significantly dependent on catalyst flow performance. Related investigations are commonly conducted using CFD techniques which represent an inexpensive and fast alternative to experimental methods. This thesis focuses on the flow performance of automotive catalytic converters using both experimental and computational techniques. The work describes the effects of inlet flow conditions on catalyst performance, the application of radial vanes to catalyst systems and the refinement of the CFD flow model which increases the accuracy of the predicted catalyst flow performance. the effects of inlet flow conditions on the flow maldistribution across the catalyst face and the total pressure loss through the system were assessed using a steady air flow rig. Tests were conducted over a range of Reynolds numbers typically encountered in automotive catalytic converters using a uniform and a fully-developed inlet flow condition. The results showed that the flow maldistribution significantly increases with Reynolds number notably in wide-angled diffusers. The catalyst flow performance is considerably improved when the inlet flow is uniform rather than fully-developed, the non-dimensional total pressure loss is reduced by 8% at Re=60000 and the flow maldistribution across the catalyst face is decreased by 12.5% and 15% respective Reynolds numbers of 30000 and 60000 when using a 60 degree diffuser. The total pressure loss through the system was found to be mostly associated with the monolith brick resistance. When the flow maldistribution is approximately 2, the pressure loss across the monolith brick represents 80% of the system pressure loss. The flow maldistribution across the catalyst face was improved by locating a system of radial splitters in the diffuser. The optimum flow performance was found to be a complex function of the vane design. A maximum improvement in the flow maldistrution indices M and Mi of 25% and 50% respectively was achieved at the expense of an increase in total pressure loss of 13.5% at Re = 60000. Both CFD and flow visualisation techniques were used as an aid to interpreting the flow field in the diffuser. Although a qualitative agreement was obtained using CFD, the flow maldistribution across the catalyst face was underpredected by up to 20%. The accuracy of the flow predictions was significantly improved by investigating the flow field in the monolith channels. Flow recirculation occurs in the channel entry length when the flow approaches the monolith channels at an angle which induces an additional implemented into four models of the flow through axisymmetric catalyst assemblies using various diffuser geometries and inlet flow conditions. By including the flow entrance effects in the porous media approach, the flow maldistribution was predicted within 8% instead of 15% when these effects are neglected. Further investigation of the flow in the monolith channels will be required to accurately model three-dimentional flows (racetrack catalysts) and to include various channel geometries and system flow rates.

Heterogeneous electrocatalysis is the usage of solid materials to decrease the amount of energy needed to produce chemicals using electricity. It is of core importance for modern life, as it enables production of chemicals, such as chlorine gas and sodium chlorate, needed for e.g. materials and pharmaceuticals production. Furthermore, as the need to make a transition to usage of renewable energy sources is growing, the importance for electrocatalysis used for electrolytic production of clean fuels, such as hydrogen, is rising. In this thesis, work aimed at understanding and improving electrocatalysts used for these purposes is presented. A main part of the work has been focused on the selectivity between chlorine gas, or sodium chlorate formation, and parasitic oxygen evolution. An activation of anode surface Ti cations by nearby Ru cations is suggested as a reason for the high chlorine selectivity of the “dimensionally stable anode” (DSA), the standard anode used in industrial chlorine and sodium chlorate production. Furthermore, theoretical methods have been used to screen for dopants that can be used to improve the activity and selectivity of DSA, and several promising candidates have been found. Moreover, the connection between the rate of chlorate formation and the rate of parasitic oxygen evolution, as well as the possible catalytic effects of electrolyte contaminants on parasitic oxygen evolution in the chlorate process, have been studied experimentally. Additionally, the properties of a Co-doped DSA have been studied, and it is found that the doping makes the electrode more active for hydrogen evolution. Finally, the hydrogen evolution reaction on both RuO2 and the noble-metal-free electrocatalyst material MoS2 has been studied using a combination of experimental and theoretically calculated X-ray photoelectron chemical shifts. In this way, insight into structural changes accompanying hydrogen evolution on these materials is obtained.
Heterogen elektrokatalys innebär användningen av fasta material för att minska energimängden som krävs för produktion av kemikalier med hjälp av elektricitet. Heterogen elektrokatalys har en central roll i det moderna samhället, eftersom det möjliggör produktionen av kemikalier såsom klorgas och natriumklorat, som i sin tur används för produktion av t ex konstruktionsmaterial och läkemedel. Vikten av användning av elektrokatalys för produktion av förnybara bränslen, såsom vätgas, växer dessutom i takt med att en övergång till användning av förnybar energi blir allt nödvändigare. I denna avhandling presenteras arbete som utförts för att förstå och förbättra sådana elektrokatalysatorer. En stor del av arbetet har varit fokuserat på selektiviteten mellan klorgas och biprodukten syrgas i klor-alkali och kloratprocesserna. Inom ramen för detta arbete har teoretisk modellering av det dominerande anodmaterialet i dessa industriella processer, den så kallade “dimensionsstabila anoden” (DSA), använts för att föreslå en fundamental anledning till att detta material är speciellt klorselektivt. Vi föreslår att klorselektiviteten kan förklaras av en laddningsöverföring från ruteniumkatjoner i materialet till titankatjonerna i anodytan, vilket aktiverar titankatjonerna. Baserat på en bred studie av ett stort antal andra dopämnen föreslår vi dessutom vilka dopämnen som är bäst lämpade för produktion av aktiva och klorselektiva anoder. Med hjälp av experimentella studier föreslår vi dessutom en koppling mellan kloratbildning och oönskad syrgasbildning i kloratprocessen, och vidare har en bred studie av tänkbara elektrolytföroreningar utförts för att öka förståelsen för syrgasbildningen i denna process. Två studier relaterade till elektrokemisk vätgasproduktion har också gjorts. En experimentell studie av Co-dopad DSA har utförts, och detta elektrodmaterial visade sig vara mer aktivt för vätgasutveckling än en standard-DSA. Vidare har en kombination av experimentell och teoretisk röntgenfotoelektronspektroskopi använts för att öka förståelsen för strukturella förändringar som sker i RuO2 och i det ädelmetallfria elektrodmaterialet MoS2 under vätgasutveckling.

QC 20151119

A large amount of nuclear waste is stored in tailings ponds as a solid-liquid slurry, and liquid flows containing suspensions of solid particles are encountered in the treatment and disposal of this waste. In processing this waste, it is important to understand the behaviour of particles within the flow in terms of their settling characteristics, their propensity to form solid beds, and the re-suspension characteristics of particles from a bed. A clearer understanding of such behaviour would allow the refinement of current approaches to waste management, potentially leading to reduced uncertainties in radiological impact assessments, smaller waste volumes and lower costs, accelerated clean-up, reduced worker doses, enhanced public confidence and diminished grounds for objection to waste disposal. Mathematical models are of significant value in nuclear waste processing since the extent of characterisation of wastes is in general low. Additionally, waste processing involves a diverse range of flows, within vessels, ponds and pipes. To investigate experimentally all waste form characteristics and potential flows of interest would be prohibitively expensive, whereas the use of mathematical models can help to focus experimental studies through the more efficient use of existing data, the identification of data requirements, and a reduction in the need for process optimisation in full-scale experimental trials. Validated models can also be used to predict waste transport behaviour to enable cost effective process design and continued operation, to provide input to process selection, and to allow the prediction of operational boundaries that account for the different types and compositions of particulate wastes. In this paper two mathematical modelling techniques, namely Reynolds-averaged Navier-Stokes (RANS) and large eddy simulation (LES), have been used to investigate particle-laden flows in a straight square duct and a duct with a bend. The flow solutions provided by these methods have been coupled to a three-dimensional Lagrangian particle tracking routine to predict particle trajectories. Simulation results are shown to be good agreement with experimental data, where available. Based on the LES and RANS-Lagrangian methods, the mean value of the particle displacement in a straight square duct is found to generally decrease with time due to gravity effects, with the rate of deposition increasing with particle size. Using the RANS-Lagrangian method to study flows in a duct bend, there is good agreement between predicted profiles and data, with the method able to simulate particle dispersion, the phenomenon of particle roping and the increase of particle collisions with the bend-wall with particle size. With the LES-Lagrangian method, particle re-suspension from a bed is studied in a straight square duct flow and this process shown to be dominated by secondary flows within the duct, with smaller particles tending to re-suspend in preference to larger ones. Overall, the study demonstrates that modelling techniques can be used to provide insight in to processes that are of relevance to the processing of nuclear waste, and are capable of predicting their transport behaviour. In particular, they are able to provide reliable predictions of particle deposition within flows to form solid beds, the re-suspension of particles from a bed, and the influence of complex flow geometries on particle dispersion. In the latter case, they are also of value to studies of erosion due to particle impact. Such models are therefore of value as engineering tools for use in the prediction of waste behaviour and in cost effective process design.

Abstract Majority of gas-condensate reservoir discoveries in Dnieper-Donets Basin (Ukraine), is characterized by limited composition only up to C5+, phase behavior studied by non-equilibrium, so called differential condensation PVT experiment, combined with the uncertainty in condensate production allocation to individual wells, makes the direct application of the results in modern PVT modeling software not possible. The new method, based on the Engler distillation test (ASTM86) for definition of pseudo-components combined with synthetic creation of liquid saturation curve for CVD experiment, was proposed and successfully applied for different gas-condensate reservoirs in the area of study. The quality control (QC) of the PVT model is further performed by applying material-balance method on a single-cell simulation model for exported black-oil PVT formulation when needed. The method proved being useful for modeling of multiple gas-condensate reservoirs of Dnieper-Donets Basin with different potential condensate yields varying from 30 to 700 g/m3 and as an example presented for two reservoir fluids with 108 and 536 g/m3. Results of numerical simulation studies were within the engineering accuracy in comparison to historically observed values. The investigation showed that a representative fluid model can be create in the cases when no detailed fluid composition or required laboratory experiments are available. PVT model can be efficiently validated and QC-ed by performing material-balance type numeric simulation constructed with one cell. However, the proper fluid sampling and PVT cell laboratory experiments are still major requirements for precise reservoir fluid characterization and equation of state (EOS) modeling.

In this paper, a dynamic model of a rotor-ball bearing system is developed in Msc. ADAMS commercial software. Contacts between the balls and the rings are modelled according to Hertzian theory. The bearing model is capable of representing the effects of bearing defects and internal clearances. When they are coupled with the rotor structures, bearings without any defect can also cause excessive vibrations due to the resonance characteristics of the system. In order to demonstrate these characteristics the rotor itself is modelled as a flexible shaft and a disc positioned at the free end of the shaft. The rotor-ball bearing model developed here is capable of representing the gyroscopic effects and the behaviour of the system under different unbalance conditions. Various case studies are performed and Campbell diagrams are obtained by using short-time Fourier transform method. A test rig consisting of two ball bearings, a shaft and a disc is also designed and developed so as to validate the theoretical model using experimental data. The test rig is developed in such a way that all of the elements are easy to assemble/disassamble, allowing quick observation of the system’s dynamic behaviour for different parameters including imbalance, internal clearance and bearing defects. Modal analysis and order tracking analysis were carried out using the test rig. Both the modal results and Campbell diagrams obtained using experimental data are compared with their theoretical counterparts. In the light of the experimental data, the theoretical model is validated for the purpose of further analyses and research.

As the first of two companion papers, theoretical models are proposed to describe the motions of free falling wedges vertically entering the water surface at Froude numbers: 1 ≤ Fn < 9 (Here, the Froude number is defined as Fn=V0/gc0). The time evolutions of the penetration depth, the velocity and the acceleration are analyzed and expressed explicitly The maximum and average accelerations are predicted. The drag (slamming) coefficients are extensively studied. It is found that for the light wedge the transient drag coefficients have slow variation in the first half stage and rapid variation in the last half stage, and for the heavy wedge the transient drag coefficients vary slowly during the whole stage and can be treated as constant. The theoretical results are compared with numerical simulations by nonlinear BEM (Wang & Faltinsen (2010, 2013)), and good agreements are obtained.

Oscillating water column (OWC) wave energy converters (WECs) are a popular type of wave energy devices. Generally, the OWC WECs have a simple structure and working principle, but with a high conversion efficiency, and a high reliability in power take-off due to a small torque and a high rotation speed for a certain power extraction. The OWC devices convert wave energy into pneumatic energy primarily by producing the pressured and de-pressured air (pneumatic energy) in the air chamber through the motions of the interior water surface in the water column. Conventionally, the pneumatic energy is converted into mechanical energy through an air turbine (in small scaled model, an orifice or porous membrane material is used for non-linear or linear power take-off modelling). However, these processes are very limitedly understood due to the complexities of the hydrodynamics, aerodynamics, and thermodynamics and their coupling effects. Theoretical and numerical attempts are very limited, especially when the coupling effects are included. As a result of the difficulties, in the device development, the most popular and acceptable approach may be the model tests, with different scaling factors in their corresponding development stages, as recommended by the relevant wave energy development protocols. To reduce the dependencies on the physical modelling in the OWC device development, numerical methods are very desirable to accommodate the simulation and assessment of the hydrodynamic and aerodynamic/thermodynamic performances of the OWC WECs. This is the main target of this investigation. In this numerical simulation, the hydrodynamic performances (including the motions of the structure and the interior water surface in waves) are carried out by employing a conventional boundary element method (i.e., WAMIT in this case) in frequency domain. To include the effects of the airflow passing through an orifice, its aerodynamic performance is much simplified by assuming its effects on the hydrodynamic performance through some extra damping coefficients to the motions of the floating structure and to the motion of the interior water surface. In this way, the interior water surface response can be obtained for the coupling effects of the hydrodynamics and aerodynamics of the OWC WEC. In this regard, an important issue in the numerical simulation is to seek an appropriate representation of the damping levels.

Multilayer neural networks are considered universal<br>approximators applicable to a wide range of problems. There are quite detailed theoretical and applied studies for fully connected networks, while for convolutional networks the results are more scarce. In this paper, we tested the approximating capability of deep neural networks with typical architectures like ConvNet, ResNet, and UNet as applied to classical image processing algorithms. Canny edge detector and grayscale morphological dilation with the disk structuring element were selected as target algorithms. As we have seen, even relatively lightweight neural models are able to approximate a filter with fixed parameters. Since classical algorithms are parameterized, we considered different approaches to the parameterization of the neural networks and found out that even the simplest of them, adding parameters in the input images channels, works well for low parameter count. Also, we measured an inference time of a neural network approximation and a classical implementation of the grayscale dilation with the disk structuring element. Starting from a certain radius, a neural network works faster than an algorithm even on one core of the CPU without fine-tuning the architecture for performance, thus confirming the viability of ConvNets as a differentiable approximation technique for optimization of classical-based methods.

Understanding of the rewetting behavior of heated vertical fuels pins is an important part of establishing reliable cooling of a PWR core following a loss of coolant accident (LOCA). Ahead of the quench front, complex and chaotic processes occur over a very small axial range, where high temperature gradients exist. In particular, repeated cyclic wetting and explosive evaporation at frequencies in the range 0.1 to 1.0 kHz is observed experimentally [1]. Despite extensive experimental and theoretical studies, the heat transfer mechanism in this region is still not well understood. In this paper we propose a mechanism, based on these observations, to explain the cyclical behavior. This postulated mechanism is transient near-surface cooling, followed by temperature recovery, of the metal substrate, with explosive vaporization when the homogeneous nucleation temperature is restored at the metal-water interface. A one-dimensional model of this cyclical process is constructed. The model indicates that the mechanism is plausible, predicting the observed periodic behavior, with predicted frequencies consistent with those observed in experiments.

We present a modeling study of the effective thermal conductance of metal foams as a thermal interface focusing on the electronics cooling applications. Metal foam material as a porous media has been considered for several applications because of its significantly large surface area for a given volume. In the electronics cooling, aluminum porous heat sinks have been well studied. It is not only cost effective due to the unique production process, but also attractive for the theoretical modeling study to determine the performance. In the past studies, effective thermal conductivity for heat transfer through solid with the tetrahedral geometry, while the pores, assumed to have vacant volumes, has been modeled. Instead of allowing the refrigerant flow through the connected pores in the porous medium, we considered the vacant space filled with stationary air. The major transport of the heat is considered to flow through the solid bridges, which connect the onside to the other side directly. Thus, the porous density for our application shall be relatively lower than the best value for heat sink applications. It must, however, be in a specific range such that it is mechanically compliant to make proper contact to both, the cooling target surface and the heat sink surface. It is obvious that the smaller pore ratio makes the metal foam stiffer. We model the contact thermal performance with considering the mechanical stiffness as a function of pore ratio as well as an intrinsic thermal conductance across the metal foam. Due to the limited literature of the variation of the pore size, we present the first order analysis assuming a fixed and uniform pore size.

Pesticide leaching in heterogeneous field soils is relatively unstudied and is the focus of this project. A wide variety of heterogeneous soils exist, characterized by processes that result from the presence of structural cracks, worm holes, and other preferred pathways within which the majority of transport can occur (called physical non-equilibrium processes), along with the presence of sorption processes that are both equilibrium and kinetic (chemical non-equilibrium processes). Previous studies of pesticide leaching have focused primarily on relatively homogeneous soils, which are less widely distributed in nature, but more studied due to the relative ease with which quantitative theory can be applied to interpret experimental results. The objectives of the proposed project were: first, to gain greater insight into the basic physical and chemical processes that characterize non-equilibrium systems, second, to improve our ability to predict pesticide leaching in heterogeneous field soils, and third, to estimate the consequences of non-equilibrium processes at the field scale by conducting an analysis of the probability of pesticide leaching when non-equilibrium processes prevail. The laboratory, theoretical and modelling aspects of the project were successful; the field aspects less so. We gained greater insight into basic processes in heterogeneous field soils, and we improved and tested tools (simulation models) and the methodology of using such tools for assessing the probability of pesticide leaching as a contribution to broader risk analysis efforts.