Une signature du polymorphisme structural d’acides ribonucléiques non-codants permettant de comparer leurs niveaux d’activités biochimiques

Des évidences expérimentales récentes indiquent que les ARN changent de structures au fil du temps, parfois très rapidement, et que ces changements sont nécessaires à leurs activités biochimiques. La structure de ces ARN est donc dynamique. Ces mêmes évidences notent également que les structures clés impliquées sont prédites par le logiciel de prédiction de structure secondaire MC-Fold. En comparant les prédictions de structures du logiciel MC-Fold, nous avons constaté un lien clair entre les structures presque optimales (en termes de stabilité prédites par ce logiciel) et les variations d’activités biochimiques conséquentes à des changements ponctuels dans la séquence. Nous avons comparé les séquences d’ARN du point de vue de leurs structures dynamiques afin d’investiguer la similarité de leurs fonctions biologiques. Ceci a nécessité une accélération notable du logiciel MC-Fold. L’approche algorithmique est décrite au chapitre 1. Au chapitre 2 nous classons les impacts de légères variations de séquences des microARN sur la fonction naturelle de ceux-ci. Au chapitre 3 nous identifions des fenêtres dans de longs ARN dont les structures dynamiques occupent possiblement des rôles dans les désordres du spectre autistique et dans la polarisation des œufs de certains batraciens (Xenopus spp.).

Parameter identification of structural dynamic models by inverse statistical analysis

Auf dem Gebiet der Strukturdynamik sind computergestützte Modellvalidierungstechniken inzwischen weit verbreitet. Dabei werden experimentelle Modaldaten, um ein numerisches Modell für weitere Analysen zu korrigieren. Gleichwohl repräsentiert das validierte Modell nur das dynamische Verhalten der getesteten Struktur. In der Realität gibt es wiederum viele Faktoren, die zwangsläufig zu variierenden Ergebnissen von Modaltests führen werden: Sich verändernde Umgebungsbedingungen während eines Tests, leicht unterschiedliche Testaufbauten, ein Test an einer nominell gleichen aber anderen Struktur (z.B. aus der Serienfertigung), etc. Damit eine stochastische Simulation durchgeführt werden kann, muss eine Reihe von Annahmen für die verwendeten Zufallsvariablengetroffen werden. Folglich bedarf es einer inversen Methode, die es ermöglicht ein stochastisches Modell aus experimentellen Modaldaten zu identifizieren. Die Arbeit beschreibt die Entwicklung eines parameter-basierten Ansatzes, um stochastische Simulationsmodelle auf dem Gebiet der Strukturdynamik zu identifizieren. Die entwickelte Methode beruht auf Sensitivitäten erster Ordnung, mit denen Parametermittelwerte und Kovarianzen des numerischen Modells aus stochastischen experimentellen Modaldaten bestimmt werden können.

Structural integrity identification based on smart materials and neural networks

This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based structural health monitoring technique, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations (typically>30 kHz), this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors. In order to quantitatively assess the state of structures, two sets of artificial neural networks, which utilize measured electrical impedance signals for input patterns, were developed. By employing high frequency ranges and by incorporating neural network features, this technique is able to detect the damage in its early stage and to estimate the nature of damage without prior knowledge of the model of structures. The paper concludes with an experimental example, an investigation on a massive quarter scale model of a steel bridge section, in order to verify the performance of this proposed methodology.

Structural FRF acquisition via electric impedance measurement applied to damage location

Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

Non-destructive evaluation tool for monitoring and detection of structural damage by using neural network.

This work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.

Structural health evaluation by optimization techinique and artificial neural network

This paper presents two different approaches to detect, locate, and characterize structural damage. Both techniques utilize electrical impedance in a first stage to locate the damaged area. In the second stage, to quantify the damage severity, one can use neural network, or optimization technique. The electrical impedance-based, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations, this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors, and therefore, it is able to detect the damage in its early stage. Optimization approaches must be used for the case where a good condensed model is known, while neural network can be also used to estimate the nature of damage without prior knowledge of the model of the structure. The paper concludes with an experimental example in a welded cubic aluminum structure, in order to verify the performance of these two proposed methodologies.

Identification of structural damage in flexible structures using system norm and neural networks

Nowadays there is great interest in damage identification using non destructive tests. Predictive maintenance is one of the most important techniques that are based on analysis of vibrations and it consists basically of monitoring the condition of structures or machines. A complete procedure should be able to detect the damage, to foresee the probable time of occurrence and to diagnosis the type of fault in order to plan the maintenance operation in a convenient form and occasion. In practical problems, it is frequent the necessity of getting the solution of non linear equations. These processes have been studied for a long time due to its great utility. Among the methods, there are different approaches, as for instance numerical methods (classic), intelligent methods (artificial neural networks), evolutions methods (genetic algorithms), and others. The characterization of damages, for better agreement, can be classified by levels. A new one uses seven levels of classification: detect the existence of the damage; detect and locate the damage; detect, locate and quantify the damages; predict the equipment's working life; auto-diagnoses; control for auto structural repair; and system of simultaneous control and monitoring. The neural networks are computational models or systems for information processing that, in a general way, can be thought as a device black box that accepts an input and produces an output. Artificial neural nets (ANN) are based on the biological neural nets and possess habilities for identification of functions and classification of standards. In this paper a methodology for structural damages location is presented. This procedure can be divided on two phases. The first one uses norms of systems to localize the damage positions. The second one uses ANN to quantify the severity of the damage. The paper concludes with a numerical application in a beam like structure with five cases of structural damages with different levels of severities. The results show the applicability of the presented methodology. A great advantage is the possibility of to apply this approach for identification of simultaneous damages.

Structural real time control using fluid magnetorheologic damper

In the last decades there was a great development in the study of control systems to attenuate the harmful effect of natural events in great structures, as buildings and bridges. Magnetorheological fluid (MR), that is an intelligent material, has been considered in many proposals of project for these controllers. This work presents the controller design using feedback of states through LMI (Linear Matrix Inequalities) approach. The experimental test were carried out in a structure with two degrees of freedom with a connected shock absorber MR. Experimental tests were realized in order to specify the features of this semi-active controller. In this case, there exist states that are not measurable, so the feedback of the states involves the project of an estimator. The coupling of the MR damper causes a variation in dynamics properties, so an identification methods, based on experimental input/output signal was used to compare with the numerical application. The identification method of Prediction Error Methods - (PEM) was used to find the physical characteristics of the system through realization in modal space of states. This proposal allows the project of a semi-active control, where the main characteristic is the possibility of the variation of the damping coefficient.

Adaptive filter feature identification for structural health monitoring in aeronautical panel

This paper presents an approach for structural health monitoring (SHM) by using adaptive filters. The experimental signals from different structural conditions provided by piezoelectric actuators/sensors bonded in the test structure are modeled by a discrete-time recursive least square (RLS) filter. The biggest advantage to use a RLS filter is the clear possibility to perform an online SHM procedure since that the identification is also valid for non-stationary linear systems. An online damage-sensitive index feature is computed based on autoregressive (AR) portion of coefficients normalized by the square root of the sum of the square of them. The proposed method is then utilized in a laboratory test involving an aeronautical panel coupled with piezoelectric sensors/actuators (PZTs) in different positions. A hypothesis test employing the t-test is used to obtain the damage decision. The proposed algorithm was able to identify and localize the damages simulated in the structure. The results have shown the applicability and drawbacks the method and the paper concludes with suggestions to improve it. ©2010 Society for Experimental Mechanics Inc.

Dynamic analysis for different finite element models of beams with viscoelastic damping layer

Many new viscoelastic materials have been developed recently to help improve noise and vibration levels in mechanical structures for applications in automobile and aeronautical industry. The viscoelastic layer treatment applied to solid metal structures modifies two main properties which are related to the mass distribution and the damping mechanism. The other property controlling the dynamics of a mechanical system is the stiffness that does not change much with the viscoelastic material. The model of such system is usually complex, because the viscoelastic material can exhibit nonlinear behavior, in contrast with the many available tools for linear dynamics. In this work, the dynamic behavior of sandwich beam is modeled by finite element method using different element types which are then compared with experimental results developed in the laboratory for various beams with different viscoelastic layer materials. The finite element model is them updated to help understand the effects in the damping for various natural frequencies and the trade-off between attenuation and the mass add to the structure.

Non-parametric identification of a non-linear buckled beam using discrete-time Volterra Series

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Numerical tests of an adaptive sectioned airfoil actuated by shape memory alloys

The main objective of this work is to illustrate an application of angular active control in a sectioned airfoil using shape memory alloys. In the proposed model, one wants to establish the shape of the airfoil profile based on the determination of an angle between its two sections. This angle is obtained by the effect of the shape memory of the alloy by passing an electric current that modifies the temperature of the wire through the Joule effect, changing the shape of the alloy. This material is capable of converting thermal energy into mechanical energy and once permanently deformed, the material can return to its original shape by heating. Due to the presence of nonlinear effects, especially in the mathematical model of the alloy, this work proposes the application of a control system based on fuzzy logic. Through numerical tests, the performance of the fuzzy controller is compared with an on-off controller applied in a sectioned airfoil model.

Characterization of grazing bifurcation in airfoils with control surface freeplay nonlinearity

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Pushover analysis of an existing reinforced concrete bridge:Jamboree Road Overcrossing in Irvine, California

The work for the present thesis started in California, during my semester as an exchange student overseas. California is known worldwide for its seismicity and its effort in the earthquake engineering research field. For this reason, I immediately found interesting the Structural Dynamics Professor, Maria Q. Feng's proposal, to work on a pushover analysis of the existing Jamboree Road Overcrossing bridge. Concrete is a popular building material in California, and for the most part, it serves its functions well. However, concrete is inherently brittle and performs poorly during earthquakes if not reinforced properly. The San Fernando Earthquake of 1971 dramatically demonstrated this characteristic. Shortly thereafter, code writers revised the design provisions for new concrete buildings so to provide adequate ductility to resist strong ground shaking. There remain, nonetheless, millions of square feet of non-ductile concrete buildings in California. The purpose of this work is to perform a Pushover Analysis and compare the results with those of a Nonlinear Time-History Analysis of an existing bridge, located in Southern California. The analyses have been executed through the software OpenSees, the Open System for Earthquake Engineering Simulation. The bridge Jamboree Road Overcrossing is classified as a Standard Ordinary Bridge. In fact, the JRO is a typical three-span continuous cast-in-place prestressed post-tension box-girder. The total length of the bridge is 366 ft., and the height of the two bents are respectively 26,41 ft. and 28,41 ft.. Both the Pushover Analysis and the Nonlinear Time-History Analysis require the use of a model that takes into account for the nonlinearities of the system. In fact, in order to execute nonlinear analyses of highway bridges it is essential to incorporate an accurate model of the material behavior. It has been observed that, after the occurrence of destructive earthquakes, one of the most damaged elements on highway bridges is a column. To evaluate the performance of bridge columns during seismic events an adequate model of the column must be incorporated. Part of the work of the present thesis is, in fact, dedicated to the modeling of bents. Different types of nonlinear element have been studied and modeled, with emphasis on the plasticity zone length determination and location. Furthermore, different models for concrete and steel materials have been considered, and the selection of the parameters that define the constitutive laws of the different materials have been accurate. The work is structured into four chapters, to follow a brief overview of the content. The first chapter introduces the concepts related to capacity design, as the actual philosophy of seismic design. Furthermore, nonlinear analyses both static, pushover, and dynamic, time-history, are presented. The final paragraph concludes with a short description on how to determine the seismic demand at a specific site, according to the latest design criteria in California. The second chapter deals with the formulation of force-based finite elements and the issues regarding the objectivity of the response in nonlinear field. Both concentrated and distributed plasticity elements are discussed into detail. The third chapter presents the existing structure, the software used OpenSees, and the modeling assumptions and issues. The creation of the nonlinear model represents a central part in this work. Nonlinear material constitutive laws, for concrete and reinforcing steel, are discussed into detail; as well as the different scenarios employed in the columns modeling. Finally, the results of the pushover analysis are presented in chapter four. Capacity curves are examined for the different model scenarios used, and failure modes of concrete and steel are discussed. Capacity curve is converted into capacity spectrum and intersected with the design spectrum. In the last paragraph, the results of nonlinear time-history analyses are compared to those of pushover analysis.

Structural analysis of the major lightharvesting complex II by electron paramagnetic resonance (EPR) : comparison between monomers and trimers

Der Haupt-Lichtsammenkomplex II (LHCII) höherer Pflanzen ist das häufigsternMembranprotein der Welt und in die chloroplastidäre Thylakoidmembran integriert. DerrnLHCII kann als Modellsystem genutzt werden, um die Funktionsweise vonrnMembranproteinen besser zu verstehen, da 96 % seiner Struktur kristallografisch aufgelöstrnist und er in rekombinanter Form in vitro rückgefaltet werden kann. Hierbei entsteht einrnvoll funktionaler Protein-Pigment.Komplex, der nahezu identisch mit der in vivo Varianternist.rnElektronenparamagnetischen Resonanz (EPR) Spektroskopie ist eine hoch sensitive undrnideal geeignete Methode, um die Strukturdynamik von Proteinen zu untersuchen. Hierzurnist eine ortsspezifische Markierung mit Spinsonden notwendig, die kovalent an Cysteinernbinden. Möglich wird dies, indem sorgfältig ausgewählte Aminosäuren gegen Cysteinerngetauscht werden, ohne dass die Funktionsweise des LHCII beeinträchtigt wird.rnIm Rahmen dieser Arbeit wurden die Stabilität des verwendeten Spinmarkers und diernProbenqualität verbessert, indem alle Schritte der Probenpräparation untersucht wurden.rnMithilfe dieser Erkenntnisse konnte sowohl die Gefahr einer Proteinaggregation als auchrnein Verlust des EPR Signals deutlich vermindert werden. In Kombination mit derrngleichzeitigen Etablierung des Q-Band EPR können nun deutlich geringer konzentrierternProben zuverlässig vermessen werden. Darüber hinaus wurde eine reproduzierbarernMethode entwickelt, um heterogene Trimere herzustellen. Diese bestehen aus einemrndoppelt markierten Monomer und zwei unmarkierten Monomeren und erlauben es, diernkristallografisch unvollständig aufgelöste N-terminale Domäne im monomeren undrntrimeren Assemblierungsgrad zu untersuchen. Die Ergebnisse konnten einerseits diernVermutung bestätigen, dass diese Domäne im Vergleich zum starren Proteinkern sehrrnflexibel ist und andererseits, dass sie in Monomeren noch mobiler ist als in Trimeren.rnZudem wurde die lumenale Schleifenregion bei unterschiedlichen pH Werten undrnvariierender Pigmentzusammensetzung untersucht, da dieser Bereich sehr kontroversrndiskutiert wird. Die Messergebnisse offenbarten, dass diese Region starre und flexiblerernSektionen aufweist. Während der pH Wert keinen Einfluss auf die Konformation hatte,rnzeigte sich, dass die Abwesenheit von Neoxanthin zu einer Änderung der Konformationrnführt. Weiterführende Analysen der strukturellen Dynamik des LHCII in einerrnLipidmembran konnten hingegen nicht durchgeführt werden, da dies eine gerichteternInsertion des rückgefalteten Proteins in Liposomen erfordert, was trotz intensiverrnVersuche nicht zum Erfolg führte.