Advanced physics-based and data-driven strategies

Simulation Based Engineering Science (SBES) has brought major improvements in optimization, control and inverse analysis, all leading to a deeper understanding in many processes occuring in the real world. These noticeable breakthroughts are present in a vast variety of sectors such as aeronautic or automotive industries, mobile telecommunications or healthcare among many other fields. Nevertheless, SBES is currently confronting several difficulties to provide accurate results in complex industrial problems. Apart from the high computational costs associated with industrial applications, the errors introduced by constitutive modeling become more and more important when dealing with new materials. Concurrently, an unceasingly growing interest in concepts such as Big-Data, Machine Learning or Data-Analytics has been experienced. Indeed, this interest is intrinsically motivated by an exhaustive development in both data-acquisition and data-storage systems. For instance, an aircraft may produce over 500 GB of data during a single flight. This panorama brings a perfect opportunity to the so-called Dynamic Data Driven Application Systems (DDDAS), whose main objective is to merge classical simulation algorithms with data coming from experimental measures in a dynamic way. Within this scenario, data and simulations would no longer be uncoupled but rather a symbiosis that is to be exploited would achieve milestones which were inconceivable until these days. Indeed, data will no longer be understood as a static calibration of a given constitutive model but rather the model will be corrected dynamicly as soon as experimental data and simulations tend to diverge. Several numerical algorithms will be presented throughout this manuscript whose main objective is to strengthen the link between data and computational mechanics. The first part of the thesis is mainly focused on parameter identification, data-driven and data completion techniques. The second part is focused on Model Order Reduction (MOR) techniques, since they constitute a fundamental ally to achieve real time constraints arising from DDDAS framework.La Ciencia de la Ingeniería Basada en la Simulación (SBES) ha aportado importantes mejoras en la optimización, el control y el análisis inverso, todo lo cual ha llevado a una comprensión más profunda de muchos de los procesos que ocurren en el mundo real. Estos notables avances están presentes en una gran variedad de sectores como la industria aeronáutica o automotriz, las telecomunicaciones móviles o la salud, entre muchos otros campos. Sin embargo, SBES se enfrenta actualmente a varias dificultades para proporcionar resultados precisos en problemas industriales complejos. Aparte de los altos costes computacionales asociados a las aplicaciones industriales, los errores introducidos por el modelado constitutivo son cada vez más importantes a la hora de tratar con nuevos materiales. Al mismo tiempo, se ha experimentado un interés cada vez mayor en conceptos como Big-Data, Machine Learning o Data-Analytics. Ciertamente, este interés está intrínsecamente motivado por un desarrollo exhaustivo de los sistemas de adquisición y almacenamiento de datos. Por ejemplo, una aeronave puede producir más de 500 GB de datos durante un solo vuelo. Este panorama brinda una oportunidad perfecta a los denominados Sistemas de Aplicación Dinámicos Impulsados por Datos (DDDAS), cuyo objetivo principal es fusionar de forma dinámica los algoritmos clásicos de simulación con los datos procedentes de medidas experimentales. En este escenario, los datos y las simulaciones ya no se desacoplarían, sino que aprovechando una simbiosis se alcanzaría hitos que hasta ahora eran inconcebibles. Mas en detalle, los datos ya no se entenderán como una calibración estática de un modelo constitutivo dado, sino que el modelo se corregirá dinámicamente tan pronto como los datos experimentales y las simulaciones tiendan a diverger. A lo largo de este manuscrito se presentarán varios algoritmos numéricos cuyo objetivo principal es fortalecer el vínculo entre los datos y la mecánica computacional. La primera parte de la tesis se centra principalmente en técnicas de identificación de parámetros, basadas en datos y de compleción de datos. La segunda parte se centra en las técnicas de Reducción de Modelo (MOR), ya que constituyen un aliado fundamental para conseguir las restricciones de tiempo real derivadas del marco DDDAS.Les sciences de l'ingénieur basées sur la simulation (Simulation Based Engineering Science, SBES) ont apporté des améliorations majeures dans l'optimisation, le contrôle et l'analyse inverse, menant toutes à une meilleure compréhension de nombreux processus se produisant dans le monde réel. Ces percées notables sont présentes dans une grande variété de secteurs tels que l'aéronautique ou l'automobile, les télécommunications mobiles ou la santé, entre autres. Néanmoins, les SBES sont actuellement confrontées à plusieurs dificultés pour fournir des résultats précis dans des problèmes industriels complexes. Outre les coûts de calcul élevés associés aux applications industrielles, les erreurs introduites par la modélisation constitutive deviennent de plus en plus importantes lorsqu'il s'agit de nouveaux matériaux. Parallèlement, un intérêt sans cesse croissant pour des concepts tels que les données massives (big data), l'apprentissage machine ou l'analyse de données a été constaté. En effet, cet intérêt est intrinsèquement motivé par un développement exhaustif des systèmes d'acquisition et de stockage de données. Par exemple, un avion peut produire plus de 500 Go de données au cours d'un seul vol. Ce panorama apporte une opportunité parfaite aux systèmes d'application dynamiques pilotés par les données (Dynamic Data Driven Application Systems, DDDAS), dont l'objectif principal est de fusionner de manière dynamique des algorithmes de simulation classiques avec des données provenant de mesures expérimentales. Dans ce scénario, les données et les simulations ne seraient plus découplées, mais une symbiose à exploiter permettrait d'envisager des situations jusqu'alors inconcevables. En effet, les données ne seront plus comprises comme un étalonnage statique d'un modèle constitutif donné mais plutôt comme une correction dynamique du modèle dès que les données expérimentales et les simulations auront tendance à diverger. Plusieurs algorithmes numériques seront présentés tout au long de ce manuscrit dont l'objectif principal est de renforcer le lien entre les données et la mécanique computationnelle. La première partie de la thèse est principalement axée sur l'identification des paramètres, les techniques d'analyse des données et les techniques de complétion de données. La deuxième partie est axée sur les techniques de réduction de modèle (MOR), car elles constituent un allié fondamental pour satisfaire les contraintes temps réel découlant du cadre DDDAS

Pneumatic fracture propagation and particulate transport in geologic formations

Pneumatic fracturing is an in situ remediation enhancement technology developed to increase the permeability of contaminated geologic formations. This technology can also be used to deliver atomized liquid and particulate supplements to geologic formations, thereby enhancing in situ processes such as bioremediation and reactive dechlorination. The main objective of this study was the development of a mathematical model that simulates the propagation of pneumatic fractures in soil and rock formations. Pneumatic fracture propagation differs from other fluid fracturing phenomena in the propagation velocity (1-3 m/sec) and the viscosity of the fracturing fluid (1.9E-05 Pa•sec). For the purposes of model development, the geologic formation was assumed to be homogenous with regard to composition, anisotropic with respect to pneumatic conductivity, and overconsolidated with respect to geostatic stress. The propagation model was formulated by coupling equations describing the three physical processes controlling propagation: (i) pressure loss due to frictional effects; (ii) leak-off into the surrounding formation; and (iii) deflection of the overburden. Pressure dissipation was modeled based on Poiseuille\u27s law, and leak-off was modeled using two-dimensional Darcian flow. The deflection of the overlying formation was modeled as a circular plate clamped at its edges and subjected to logarithmically varying load. The model was solved numerically and the solution was expressed as an algorithm. The algorithm seeks an equilibrium fracture radius and aperture that simultaneously satisfies flow continuity and stress equilibrium criteria at the fracture tip. Different methods of solution convergence were examined and the Bisection Method was found to be the most efficient. Sensitivity analyses showed that model behavior was dominated by the pneumatic conductivity of the geologic formation since this parameter largely determines leak-off rate. The algorithm was calibrated with field data from six different pneumatic fracturing projects and regressed values of pneumatic conductivity and elastic modulus showed reasonable agreement with field measured values. The most important result of the calibration process was the coincidence between the regressed conductivity (1.1E-03 to 1.8E-05) and the post-fracture conductivities measured in the field (3.1E-03 to 1.7E-05). This result supported the fundamental thesis that final fracture radius is determined with the geologic formation in a disturbed state. A separate pneumatic fracture propagation model was developed and solved based solely on the continuity criterion. The solution demonstrated reasonable correlation with field measured radii, although it tended to overestimate fracture radius in soil formations at shallow depths of injection (on an average 15 % more than field measured radius). As a secondary objective of this study, a methodology to model the mechanism of particulate transport in a fluidized soil formation was proposed. The methodology was tested with field data from a recent case study

Advanced physics-based and data-driven strategies

Cotutela: Universitat Politècnica de Catalunya i École Centrale de Nantes.Premi Extraordinari de Doctorat, promoció 2018-2019. Àmbit d’Enginyeria Civil i AmbientalSimulation Based Engineering Science (SBES) has brought major improvements in optimization, control and inverse analysis, all leading to a deeper understanding in many processes occuring in the real world. These noticeable breakthroughts are present in a vast variety of sectors such as aeronautic or automotive industries, mobile telecommunications or healthcare among many other fields. Nevertheless, SBES is currently confronting several difficulties to provide accurate results in complex industrial problems. Apart from the high computational costs associated with industrial applications, the errors introduced by constitutive modeling become more and more important when dealing with new materials. Concurrently, an unceasingly growing interest in concepts such as Big-Data, Machine Learning or Data-Analytics has been experienced. Indeed, this interest is intrinsically motivated by an exhaustive development in both data-acquisition and data-storage systems. For instance, an aircraft may produce over 500 GB of data during a single flight. This panorama brings a perfect opportunity to the so-called Dynamic Data Driven Application Systems (DDDAS), whose main objective is to merge classical simulation algorithms with data coming from experimental measures in a dynamic way. Within this scenario, data and simulations would no longer be uncoupled but rather a symbiosis that is to be exploited would achieve milestones which were inconceivable until these days. Indeed, data will no longer be understood as a static calibration of a given constitutive model but rather the model will be corrected dynamicly as soon as experimental data and simulations tend to diverge. Several numerical algorithms will be presented throughout this manuscript whose main objective is to strengthen the link between data and computational mechanics. The first part of the thesis is mainly focused on parameter identification, data-driven and data completion techniques. The second part is focused on Model Order Reduction (MOR) techniques, since they constitute a fundamental ally to achieve real time constraints arising from DDDAS framework.La Ciencia de la Ingeniería Basada en la Simulación (SBES) ha aportado importantes mejoras en la optimización, el control y el análisis inverso, todo lo cual ha llevado a una comprensión más profunda de muchos de los procesos que ocurren en el mundo real. Estos notables avances están presentes en una gran variedad de sectores como la industria aeronáutica o automotriz, las telecomunicaciones móviles o la salud, entre muchos otros campos. Sin embargo, SBES se enfrenta actualmente a varias dificultades para proporcionar resultados precisos en problemas industriales complejos. Aparte de los altos costes computacionales asociados a las aplicaciones industriales, los errores introducidos por el modelado constitutivo son cada vez más importantes a la hora de tratar con nuevos materiales. Al mismo tiempo, se ha experimentado un interés cada vez mayor en conceptos como Big-Data, Machine Learning o Data-Analytics. Ciertamente, este interés está intrínsecamente motivado por un desarrollo exhaustivo de los sistemas de adquisición y almacenamiento de datos. Por ejemplo, una aeronave puede producir más de 500 GB de datos durante un solo vuelo. Este panorama brinda una oportunidad perfecta a los denominados Sistemas de Aplicación Dinámicos Impulsados por Datos (DDDAS), cuyo objetivo principal es fusionar de forma dinámica los algoritmos clásicos de simulación con los datos procedentes de medidas experimentales. En este escenario, los datos y las simulaciones ya no se desacoplarían, sino que aprovechando una simbiosis se alcanzaría hitos que hasta ahora eran inconcebibles. Mas en detalle, los datos ya no se entenderán como una calibración estática de un modelo constitutivo dado, sino que el modelo se corregirá dinámicamente tan pronto como los datos experimentales y las simulaciones tiendan a diverger. A lo largo de este manuscrito se presentarán varios algoritmos numéricos cuyo objetivo principal es fortalecer el vínculo entre los datos y la mecánica computacional. La primera parte de la tesis se centra principalmente en técnicas de identificación de parámetros, basadas en datos y de compleción de datos. La segunda parte se centra en las técnicas de Reducción de Modelo (MOR), ya que constituyen un aliado fundamental para conseguir las restricciones de tiempo real derivadas del marco DDDAS.Les sciences de l'ingénieur basées sur la simulation (Simulation Based Engineering Science, SBES) ont apporté des améliorations majeures dans l'optimisation, le contrôle et l'analyse inverse, menant toutes à une meilleure compréhension de nombreux processus se produisant dans le monde réel. Ces percées notables sont présentes dans une grande variété de secteurs tels que l'aéronautique ou l'automobile, les télécommunications mobiles ou la santé, entre autres. Néanmoins, les SBES sont actuellement confrontées à plusieurs dificultés pour fournir des résultats précis dans des problèmes industriels complexes. Outre les coûts de calcul élevés associés aux applications industrielles, les erreurs introduites par la modélisation constitutive deviennent de plus en plus importantes lorsqu'il s'agit de nouveaux matériaux. Parallèlement, un intérêt sans cesse croissant pour des concepts tels que les données massives (big data), l'apprentissage machine ou l'analyse de données a été constaté. En effet, cet intérêt est intrinsèquement motivé par un développement exhaustif des systèmes d'acquisition et de stockage de données. Par exemple, un avion peut produire plus de 500 Go de données au cours d'un seul vol. Ce panorama apporte une opportunité parfaite aux systèmes d'application dynamiques pilotés par les données (Dynamic Data Driven Application Systems, DDDAS), dont l'objectif principal est de fusionner de manière dynamique des algorithmes de simulation classiques avec des données provenant de mesures expérimentales. Dans ce scénario, les données et les simulations ne seraient plus découplées, mais une symbiose à exploiter permettrait d'envisager des situations jusqu'alors inconcevables. En effet, les données ne seront plus comprises comme un étalonnage statique d'un modèle constitutif donné mais plutôt comme une correction dynamique du modèle dès que les données expérimentales et les simulations auront tendance à diverger. Plusieurs algorithmes numériques seront présentés tout au long de ce manuscrit dont l'objectif principal est de renforcer le lien entre les données et la mécanique computationnelle. La première partie de la thèse est principalement axée sur l'identification des paramètres, les techniques d'analyse des données et les techniques de complétion de données. La deuxième partie est axée sur les techniques de réduction de modèle (MOR), car elles constituent un allié fondamental pour satisfaire les contraintes temps réel découlant du cadre DDDAS.Award-winningPostprint (published version

Electroluminescence in epitaxial thin film zns and znse

The application of the metalorganic chemical vapour deposition technique to the production of II-VI compound semiconductor electroluminescent devices is discussed. Both low field MIS minority carrier injection devices and high field impact excitation structures are considered, and comparisons are drawn with more commiercially orientated electroluminescent displays. The epitaxial growth of ZnS and ZnSe onto (100) orientated GaAs substrates, using the reactions between dimethyl zinc and the hydrides HgS and H2Se, is described. Details are given of a novel epitaxial MISi device processing technology, in which a ZnS I-layer also acts as an etch-stop, thus enabling chemical removal of the GaAs substrate. Metal electrodes deposited directly onto the ZnS and ZnSe allow the electrical and electroluminescent characteristics of these epitaxial II-VI compound layers to be investigated in the absence of any influence from the substrate material. X-ray diffraction and reflection high energy electron dififraction confirm that the structures are epitaxial and of excellent crystallinity. It is demonstrated in an electron beam induced current study that conduction in the epitaxial MIS devices is highly uniform, and this is manifested in a uniform spatial distribution of electroluminescence. A description is given of high field impact excitation electroluminescent devices, in which the ZnS layer is doped with manganese during MOCVD growth. The spatial distribution of EL in these devices is shown to be non-uniform, and thus indicative of filamentary conduction in the ZnS:Mn, in accordance with a recently proposed dielectric breakdown model of instability. It is demonstrated that the transient characteristics of the epitaxial structures correlate with those of commercial polycrystalline devices, and are also consistent with the predictions of a dynamic model of instability. As a result of filamentary conduction, both epitaxial and polycrystalline devices are prone to degradation through localised dielectric breakdown. These breakdown events generally result in a gradual erosion of the active electrode area, although, under certain operating conditions, mobile filaments can cause rapid destruction of epitaxial structures. The columnar microstructure of sputtered devices appears to prevent such filament mobility, and it is concluded that, although filamentary conduction is a result of the carrier injection mechanism and is independent of the crystallinity, the associated damage is strongly influenced by the microstructure of the device

Helmholtz Equation Least Squares Based Near-Field Acoustic Holography With Laser

This dissertation presents the HELS based NAH with laser and use normal surface velocity as input in near-field acoustic holography. The conventional HELS based NAH uses acoustic pressure as input to reconstruct sound field quantities, while this modified HELS based NAH with laser utilizes the normal surface velocities measured by LDV to reconstruct the acoustic quantities at interested positions. Theoretical principles of the HELS based NAH with laser have been fully developed and the method has been verified in theoretical perspective. Two theoretical examples verify that HELS based NAH with laser can obtain exactly the same results as analytic solution. The error analysis shows that the magnitudes of errors are bounded and the HELS based NAH with laser is robust and reliable. Numerical simulations have been conducted on ideal sound sources. Another numerical study has been conducted on some special cases of a transverse vibration problem of thin plates. The reconstructed acoustic field is compared with the theoretical values, and it testifies that HELS based NAH with laser is also applicable to both ideal sound sources and complex sound sources. Experimental validation was finished by reconstructing acoustic pressure generated by a subwoofer. Through comparing the reconstructed sound pressure at 4 different positions with measured values from microphones, it demonstrates that the HELS based NAH with laser demonstrates succeed in reconstructing sound pressure based on normal surface velocity input

Microstructural evolution of deep cryogenically treated steel

This study answered the microstructural changes that occur during deep cryogenic treatment of steels. The results pointed to a strong correlation between the amount of transformed retained austenite during DCT and the tribological behaviour of the stee

Generic low power reconfigurable distributed arithmetic processor

Higher performance, lower cost, increasingly minimizing integrated circuit components, and higher packaging density of chips are ongoing goals of the microelectronic and computer industry. As these goals are being achieved, however, power consumption and flexibility are increasingly becoming bottlenecks that need to be addressed with the new technology in Very Large-Scale Integrated (VLSI) design. For modern systems, more energy is required to support the powerful computational capability which accords with the increasing requirements, and these requirements cause the change of standards not only in audio and video broadcasting but also in communication such as wireless connection and network protocols. Powerful flexibility and low consumption are repellent, but their combination in one system is the ultimate goal of designers. A generic domain-specific low-power reconfigurable processor for the distributed arithmetic algorithm is presented in this dissertation. This domain reconfigurable processor features high efficiency in terms of area, power and delay, which approaches the performance of an ASIC design, while retaining the flexibility of programmable platforms. The architecture not only supports typical distributed arithmetic algorithms which can be found in most still picture compression standards and video conferencing standards, but also offers implementation ability for other distributed arithmetic algorithms found in digital signal processing, telecommunication protocols and automatic control. In this processor, a simple reconfigurable low power control unit is implemented with good performance in area, power and timing. The generic characteristic of the architecture makes it applicable for any small and medium size finite state machines which can be used as control units to implement complex system behaviour and can be found in almost all engineering disciplines. Furthermore, to map target applications efficiently onto the proposed architecture, a new algorithm is introduced for searching for the best common sharing terms set and it keeps the area and power consumption of the implementation at low level. The software implementation of this algorithm is presented, which can be used not only for the proposed architecture in this dissertation but also for all the implementations with adder-based distributed arithmetic algorithms. In addition, some low power design techniques are applied in the architecture, such as unsymmetrical design style including unsymmetrical interconnection arranging, unsymmetrical PTBs selection and unsymmetrical mapping basic computing units. All these design techniques achieve extraordinary power consumption saving. It is believed that they can be extended to more low power designs and architectures. The processor presented in this dissertation can be used to implement complex, high performance distributed arithmetic algorithms for communication and image processing applications with low cost in area and power compared with the traditional methods

Multi-physics for integrated analysis of flexible body dynamics with tribological conjunction in IC engines

Since the inception of internal combustion engine, there has been a continual strive to improve its efficiency and refinement. Until very recently, the developments in this regard have been largely based on an experiential basis, or backed by analytical investigations, confined to particular features of the engines. This has been due to lack of computational power, and analysis tools of an integrative nature. In recent years enhanced computing power has meant that complex models, chiefly based on multi-body dynamics could be developed, and further enhanced by the inclusion of component flexibility in the form of structural modes, obtained through finite element analysis. This approach has enabled study of dynamics/vibration response of engines in a more quantitative manner than hitherto possible. Structural integrity issues, as well as noise and vibration (refinement) can then be studied in an integrated manner. However, earlier models still lack sufficient detail to include, within the same analysis, issues related to efficiency, chiefly prediction of parasitic losses due to mechanical imbalance and friction. [Continues.

Engineering Education and Research Using MATLAB

MATLAB is a software package used primarily in the field of engineering for signal processing, numerical data analysis, modeling, programming, simulation, and computer graphic visualization. In the last few years, it has become widely accepted as an efficient tool, and, therefore, its use has significantly increased in scientific communities and academic institutions. This book consists of 20 chapters presenting research works using MATLAB tools. Chapters include techniques for programming and developing Graphical User Interfaces (GUIs), dynamic systems, electric machines, signal and image processing, power electronics, mixed signal circuits, genetic programming, digital watermarking, control systems, time-series regression modeling, and artificial neural networks

Thermal Barrier Coating Workshop, 1997

This document contains papers from the 1997 Thermal Barrier Coatings Workshop, sponsored by the TBC Interagency Coordination Committee. The Workshop was held in Fort Mitchell, Kentucky, May 19-21, 1997. The papers cover the topics of heat transfer and conductivity of thermal barrier coatings, failure mechanisms and characterization of the coatings as well as characterization of coating deposition methods. Speakers included research, development and user groups in academia, industry and government