Efficient Computation of Electromagnetic Waves in Hydrocarbon Exploration Using the Improved Numerical Mode Matching (NMM) Method

In this study, we developed and improved the numerical mode matching (NMM) method which has previously been shown to be a fast and robust semi-analytical solver to investigate the propagation of electromagnetic (EM) waves in an isotropic layered medium. The applicable models, such as cylindrical waveguide, optical fiber, and borehole with earth geological formation, are generally modeled as an axisymmetric structure which is an orthogonal-plano-cylindrically layered (OPCL) medium consisting of materials stratified planarly and layered concentrically in the orthogonal directions.

In this report, several important improvements have been made to extend applications of this efficient solver to the anisotropic OCPL medium. The formulas for anisotropic media with three different diagonal elements in the cylindrical coordinate system are deduced to expand its application to more general materials. The perfectly matched layer (PML) is incorporated along the radial direction as an absorbing boundary condition (ABC) to make the NMM method more accurate and efficient for wave diffusion problems in unbounded media and applicable to scattering problems with lossless media. We manipulate the weak form of Maxwell's equations and impose the correct boundary conditions at the cylindrical axis to solve the singularity problem which is ignored by all previous researchers. The spectral element method (SEM) is introduced to more efficiently compute the eigenmodes of higher accuracy with less unknowns, achieving a faster mode matching procedure between different horizontal layers. We also prove the relationship of the field between opposite mode indices for different types of excitations, which can reduce the computational time by half. The formulas for computing EM fields excited by an electric or magnetic dipole located at any position with an arbitrary orientation are deduced. And the excitation are generalized to line and surface current sources which can extend the application of NMM to the simulations of controlled source electromagnetic techniques. Numerical simulations have demonstrated the efficiency and accuracy of this method.

Finally, the improved numerical mode matching (NMM) method is introduced to efficiently compute the electromagnetic response of the induction tool from orthogonal transverse hydraulic fractures in open or cased boreholes in hydrocarbon exploration. The hydraulic fracture is modeled as a slim circular disk which is symmetric with respect to the borehole axis and filled with electrically conductive or magnetic proppant. The NMM solver is first validated by comparing the normalized secondary field with experimental measurements and a commercial software. Then we analyze quantitatively the induction response sensitivity of the fracture with different parameters, such as length, conductivity and permeability of the filled proppant, to evaluate the effectiveness of the induction logging tool for fracture detection and mapping. Casings with different thicknesses, conductivities and permeabilities are modeled together with the fractures in boreholes to investigate their effects for fracture detection. It reveals that the normalized secondary field will not be weakened at low frequencies, ensuring the induction tool is still applicable for fracture detection, though the attenuation of electromagnetic field through the casing is significant. A hybrid approach combining the NMM method and BCGS-FFT solver based integral equation has been proposed to efficiently simulate the open or cased borehole with tilted fractures which is a non-axisymmetric model.

Dynamic-Data Driven Real-Time Identification for Electric Power Systems

Power system engineers face a double challenge: to operate electric power systems within narrow stability and security margins, and to maintain high reliability. There is an acute need to better understand the dynamic nature of power systems in order to be prepared for critical situations as they arise. Innovative measurement tools, such as phasor measurement units, can capture not only the slow variation of the voltages and currents but also the underlying oscillations in a power system. Such dynamic data accessibility provides us a strong motivation and a useful tool to explore dynamic-data driven applications in power systems. To fulfill this goal, this dissertation focuses on the following three areas: Developing accurate dynamic load models and updating variable parameters based on the measurement data, applying advanced nonlinear filtering concepts and technologies to real-time identification of power system models, and addressing computational issues by implementing the balanced truncation method. By obtaining more realistic system models, together with timely updated parameters and stochastic influence consideration, we can have an accurate portrait of the ongoing phenomena in an electrical power system. Hence we can further improve state estimation, stability analysis and real-time operation.

Uncertainties in projecting climate-change impacts in marine ecosystems

Projections of the impacts of climate change on marine ecosystems are a key prerequisite for the planning of adaptation strategies, yet they are inevitably associated with uncertainty. Identifying, quantifying, and communicating this uncertainty is key to both evaluating the risk associated with a projection and building confidence in its robustness. We review how uncertainties in such projections are handled in marine science. We employ an approach developed in climate modelling by breaking uncertainty down into (i) structural (model) uncertainty, (ii) initialization and internal variability uncertainty, (iii) parametric uncertainty, and (iv) scenario uncertainty. For each uncertainty type, we then examine the current state-of-the-art in assessing and quantifying its relative importance. We consider whether the marine scientific community has addressed these types of uncertainty sufficiently and highlight the opportunities and challenges associated with doing a better job. We find that even within a relatively small field such as marine science, there are substantial differences between subdisciplines in the degree of attention given to each type of uncertainty. We find that initialization uncertainty is rarely treated explicitly and reducing this type of uncertainty may deliver gains on the seasonal-to-decadal time-scale. We conclude that all parts of marine science could benefit from a greater exchange of ideas, particularly concerning such a universal problem such as the treatment of uncertainty. Finally, marine science should strive to reach the point where scenario uncertainty is the dominant uncertainty in our projections.

Construção de modelos de interação in silico e in vitro do inibidor do tipo Kunitz de Adenanthera pavonina L. para as enzimas cisteínicas e serínicas

Serines proteinases inhibitors (PIs) are widely distributed in nature and are able to inhibit both in vitro and in vivo enzymatic activites. Seed PIs in than leguminous are classified in seven families, Bowman-Birk and Kunitz type families that most studied representing an important role in the first line of defense toward insects pests. Some Kunitz type inhibitors possess activities serine and cysteine for proteinases named bifunctional inhibitor, as ApTKI the inhibitor isolate from seed of Adenanthera pavonina. The A. pavonina inhibitor presenting the uncommon property and was used for interaction studies between proteinases serine (trypsin) and cysteine (papain). In order to determinate the in vitro interaction of ApTKI against enzymes inhibitor purification was carried cut by using chromatographic techniques and inhibition assays. The 3D model of the bifunctional inhibitor ApTKI was constructed SWISS-MODEL program by homology modeling using soybean trypsin inhibitor (STI, pdb:1ba7), as template which presented 40% of identity to A. pavonina inhibitor. Model quality was evaluated by PROCHECK program. Moreover in silico analyzes of formed complex between the enzymes and ApTKI was evaluated by HEX 4.5 program. In vitro results confirmed the inhibitory assays, where the inhibitor presented the ability to simultaneously inhibit trypsin and papain. The residues encountered in the inhibitor model of folder structural three-dimensional that make contact to enzymes target coud explain the specificity pattern against serine and cysteine proteinases

A contribution towards the performance and structural understanding of copper and nickel salts as ammonia stores

The ongoing depletion of fossil fuels and the severe consequences of the greenhouse effect make the development of alternative energy systems crucially important. While hydrogen is, in principle, a promising alternative, releasing nothing but energy and pure water. Hydrogen storage is complicated and no completely viable technique has been proposed so far. This work is concerned with the study of one potential alternative to pure hydrogen: ammonia, and more specifically its storage in solids. Ammonia, NH3, can be regarded as a chemical hydrogen carrier with the advantages of strongly reduced flammability and explosiveness as compared to hydrogen. Furthermore, ammine metal salts presented here as promising ammonia stores easily store up to 50 wt.-% ammonia, giving them a volumetric energy density comparable to natural gas. The model system NiX2–NH3 ( X = Cl, Br, I) is studied thoroughly with respect to ammine salt formation, thermal decomposition, air stability and structural effects. The system CuX2–NH3 ( X = Cl, Br) has an adverse thermal decomposition behaviour, making it impractical for use as an ammonia store. This system is, however, most interesting from a structural point of view and some work concerning the study of the structural behaviour of this system is presented. Finally, close chemical relatives to the metal ammine halides, the metal ammine nitrates are studied. They exhibit interesting anion arrangements, which is an impressive showcase for the combination of diffraction and spectroscopic information. The characterisation techniques in this thesis range from powder diffraction over single crystal diffraction, spectroscopy, computational modelling, thermal analyses to gravimetric uptake experiments. Further highlights are the structure solutions and refinements from powder data of (NH4)2[NiCl4(H2O)(NH3)] and Ni(NH3)2(NO3)2, the combination of crystallographic and chemical information for the elucidation of the (NH4)2[NiCl4(H2O)(NH3)] formation reaction and the growth of single crystals under ammonia flow, a technique allowing the first documented successful growth and single crystal diffraction measurement for [Cu(NH3)6]Cl2.

Efecto determinante de la motivación de viaje sobre la imagen de destino en turistas de ocio a un destino urbano: El caso de Monterrey, México. Una aproximación por medio de mínimos cuadrados parciales (PLS) = Determinant effect of travel motivation on the destination image of leisure tourist in an urban destination: the case of Monterrey, México. An approach through partial least squares (PLS)

Los turistas urbanos se caracterizan por ser uno de los segmentos de mayor crecimiento en los mercados turísticos actuales. Monterrey (México), uno de los principales destinos urbanos del país, ha apostado en la actualidad por mejorar su competitividad. Esta investigación se propuso encontrar evidencia acerca de la relación causal de la motivación de viaje sobre la imagen percibida del destino, dos variables importantes por su influencia en la satisfacción de los visitantes. Una revisión de la literatura permitió proponer constructos teóricos integrados en un instrumento para la recogida de datos vía encuesta a una muestra representativa. Por medio del método de regresión y ecuaciones estructurales por mínimos cuadrados parciales (PLS), se identificaron los componentes principales de ambas variables y se obtuvo un modelo explicativo de la imagen percibida del destino en función de la motivación de viaje. Finalmente, se emiten recomendaciones para la gestión del destino urbano en función de los resultados obtenidos. ABSTRACT: Abstract Urban tourists are recognized as one of the fastest growing segments in today’s tourism markets. Monterrey, Mexico, one of the main urban destinations in the country aims at improving its competitiveness. This research work had the purpose of finding evidence on the causal relationship between travel motivation and destination image, two important variables because of their influence on visitors’ satisfaction. A literature review enabled the proposal of a research instrument with theoretically based constructs to gather data through survey from a representative sample. Using regression and structural equations modelling by partial least squares (pls) a set of main components of both variables were identified thus enabling the obtention of a explanatory model of destination image in terms of travel motivations. Finally based on the results some recommendations of tourism management are given.

A THEORETICAL STUDY OF INTERACTION OF NANOPARTICLES WITH BIOMOLECULE

Many types of materials at nanoscale are currently being used in everyday life. The production and use of such products based on engineered nanomaterials have raised concerns of the possible risks and hazards associated with these nanomaterials. In order to evaluate and gain a better understanding of their effects on living organisms, we have performed first-principles quantum mechanical calculations and molecular dynamics simulations. Specifically, we will investigate the interaction of nanomaterials including semiconducting quantum dots and metallic nanoparticles with various biological molecules, such as dopamine, DNA nucleobases and lipid membranes. Firstly, interactions of semiconducting CdSe/CdS quantum dots (QDs) with the dopamine and the DNA nucleobase molecules are investigated using similar quantum mechanical approach to the one used for the metallic nanoparticles. A variety of interaction sites are explored. Our results show that small-sized Cd4Se4 and Cd4S4 QDs interact strongly with the DNA nucleobase if a DNA nucleobase has the amide or hydroxyl chemical group. These results indicate that these QDs are suitable for detecting subcellular structures, as also reported by experiments. The next two chapters describe a preparation required for the simulation of nanoparticles interacting with membranes leading to accurate structure models for the membranes. We develop a method for the molecular crystalline structure prediction of 1,2-Dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC), 1,2-Dimyristoyl-sn-glycero-3-phosphorylethanolamine (DMPE) and cyclic di-amino acid peptide using first-principles methods. Since an accurate determination of the structure of an organic crystal is usually an extremely difficult task due to availability of the large number of its conformers, we propose a new computational scheme by applying knowledge of symmetry, structural chemistry and chemical bonding to reduce the sampling size of the conformation space. The interaction of metal nanoparticles with cell membranes is finally carried out by molecular dynamics simulations, and the results are reported in the last chapter. A new force field is developed which accurately describes the interaction forces between the clusters representing small-sized metal nanoparticles and the lipid bilayer molecules. The permeation of nanoparticles into the cell membrane is analyzed together with the RMSD values of the membrane modeled by a lipid bilayer. The simulation results suggest that the AgNPs could cause the same amount of deformation as the AuNPs for the dysfunction of the membrane.

MODELLING AND CONTROL OF ERSW PROCESSES BY NEURONAL NETWORK

A study on the use of artificial intelligence (AI) techniques for the modelling and subsequent control of an electric resistance spot welding process (ERSW) is presented. The ERSW process is characterized by the coupling of thermal, electrical, mechanical, and metallurgical phenomena. For this reason, early attempts to model it using computational methods established as the methods of finite differences, finite element, and finite volumes, ask for simplifications that lead the model obtained far from reality or very costly in terms of computational costs, to be used in a real-time control system. In this sense, the authors have developed an ERSW controller that uses fuzzy logic to adjust the energy transferred to the weld nugget. The proposed control strategies differ in the speed with which it reaches convergence. Moreover, their application for a quality control of spot weld through artificial neural networks (ANN) is discussed.

A computational analysis of substrate binding strength by phosphorylase kinase and protein kinase A

Protein kinases exhibit various degrees of substrate specificity. The large number of different protein kinases in the eukaryotic proteomes makes it impractical to determine the specificity of each enzyme experimentally. To test if it were possible to discriminate potential substrates from non-substrates by simple computational techniques, we analysed the binding enthalpies of modelled enzyme-substrate complexes and attempted to correlate it with experimental enzyme kinetics measurements. The crystal structures of phosphorylase kinase and cAMP-dependent protein kinase were used to generate models of the enzyme with a series of known peptide substrates and non-substrates, and the approximate enthalpy of binding assessed following energy minimization. We show that the computed enthalpies do not correlate closely with kinetic measurements, but the method can distinguish good substrates from weak substrates and non-substrates. Copyright (C) 2002 John Wiley Sons, Ltd.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

Modelling of species in hood fires by conditional moment closure

Carbon monoxide, the chief killer in fires, and other species are modelled for a series of enclosure fires. The conditions emulate building fires where CO is formed in the rich, turbulent, nonpremixed flame and is transported frozen to lean mixtures by the ceiling jet which is cooled by radiation and dilution. Conditional moment closure modelling is used and computational domain minimisation criteria are developed which reduce the computational cost of this method. The predictions give good agreement for CO and other species in the lean, quenched-gas stream, holding promise that this method may provide a practical means of modelling real, three-dimensional fire situations. (c) 2005 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.

Simplified computational routine to correct the modal decoupling in transmission lines and power systems modelling

Modal analysis is widely approached in the classic theory of power systems modelling. This technique is also applied to model multiconductor transmission lines and their self and mutual electrical parameters. However, this methodology has some particularities and inaccuracies for specific applications, which are not clearly described in the technical literature. This study provides a brief review on modal decoupling applied in transmission line digital models and thereafter a novel and simplified computational routine is proposed to overcome the possible errors embedded by the modal decoupling in the simulation/ modelling computational algorithm. © The Institution of Engineering and Technology 2013.

Dynamic analysis of the motorcycle chattering behaviour by means of symbolic multibody modelling

Aim of this research is the development and validation of a comprehensive multibody motorcycle model featuring rigid-ring tires, taking into account both slope and roughness of road surfaces. A novel parametrization for the general kinematics of the motorcycle is proposed, using a mixed reference-point and relative-coordinates approach. The resulting description, developed in terms of dependent coordinates, makes it possible to efficiently include rigid-ring kinematics as well as road elevation and slope. The equations of motion for the multibody system are derived symbolically and the constraint equations arising from the dependent-coordinate formulation are handled using a projection technique. Therefore the resulting system of equations can be integrated in time domain using a standard ODE algorithm. The model is validated with respect to maneuvers experimentally measured on the race track, showing consistent results and excellent computational efficiency. More in detail, it is also capable of reproducing the chatter vibration of racing motorcycles. The chatter phenomenon, appearing during high speed cornering maneuvers, consists of a self-excited vertical oscillation of both the front and rear unsprung masses in the range of frequency between 17 and 22 Hz. A critical maneuver is numerically simulated, and a self-excited vibration appears, consistent with the experimentally measured chatter vibration. Finally, the driving mechanism for the self-excitation is highlighted and a physical interpretation is proposed.

Closed-loop investigation of the dynamical properties of cardiomyocyte electrophysiology by means of Dynamic clamp and Mathematical modelling

The research field of my PhD concerns mathematical modeling and numerical simulation, applied to the cardiac electrophysiology analysis at a single cell level. This is possible thanks to the development of mathematical descriptions of single cellular components, ionic channels, pumps, exchangers and subcellular compartments. Due to the difficulties of vivo experiments on human cells, most of the measurements are acquired in vitro using animal models (e.g. guinea pig, dog, rabbit). Moreover, to study the cardiac action potential and all its features, it is necessary to acquire more specific knowledge about single ionic currents that contribute to the cardiac activity. Electrophysiological models of the heart have become very accurate in recent years giving rise to extremely complicated systems of differential equations. Although describing the behavior of cardiac cells quite well, the models are computationally demanding for numerical simulations and are very difficult to analyze from a mathematical (dynamical-systems) viewpoint. Simplified mathematical models that capture the underlying dynamics to a certain extent are therefore frequently used. The results presented in this thesis have confirmed that a close integration of computational modeling and experimental recordings in real myocytes, as performed by dynamic clamp, is a useful tool in enhancing our understanding of various components of normal cardiac electrophysiology, but also arrhythmogenic mechanisms in a pathological condition, especially when fully integrated with experimental data.