Non linear response of planar asymmetric systems

The seismic behaviour of one-storey asymmetric structures has been studied since 1970s by a number of researches studies which identified the coupled nature of the translational-to-torsional response of those class of systems leading to severe displacement magnifications at the perimeter frames and therefore to significant increase of local peak seismic demand to the structural elements with respect to those of equivalent not-eccentric systems (Kan and Chopra 1987). These studies identified the fundamental parameters (such as the fundamental period TL normalized eccentricity e and the torsional-to-lateral frequency ratio Ωϑ) governing the torsional behavior of in-plan asymmetric structures and trends of behavior. It has been clearly recognized that asymmetric structures characterized by Ωϑ >1, referred to as torsionally-stiff systems, behave quite different form structures with Ωϑ <1, referred to as torsionally-flexible systems. Previous research works by some of the authors proposed a simple closed-form estimation of the maximum torsional response of one-storey elastic systems (Trombetti et al. 2005 and Palermo et al. 2010) leading to the so called “Alpha-method” for the evaluation of the displacement magnification factors at the corner sides. The present paper provides an upgrade of the “Alpha Method” removing the assumption of linear elastic response of the system. The main objective is to evaluate how the excursion of the structural elements in the inelastic field (due to the reaching of yield strength) affects the displacement demand of one-storey in-plan asymmetric structures. The system proposed by Chopra and Goel in 2007, which is claimed to be able to capture the main features of the non-linear response of in-plan asymmetric system, is used to perform a large parametric analysis varying all the fundamental parameters of the system, including the inelastic demand by varying the force reduction factor from 2 to 5. Magnification factors for different force reduction factor are proposed and comparisons with the results obtained from linear analysis are provided.

Non linear application of an in-house finite elements software

Questa tesi si pone come obiettivo l'analisi delle componenti di sollecitazione statica di un serbatoio, in acciaio API 5L X52, sottoposto a carichi di flessione e pressione interna attraverso il programma agli elementi finiti PLCd4, sviluppato presso l'International Center for Numerical Methods in Engineering (CIMNE - Barcelona). Questo tipo di analisi rientra nel progetto europeo ULCF, il cui traguardo è lo studio della fatica a bassissimo numero di cicli per strutture in acciaio. Prima di osservare la struttura completa del serbatoio è stato studiato il comportamento del materiale per implementare all'interno del programma una nuova tipologia di curva che rappresentasse al meglio l'andamento delle tensioni interne. Attraverso il lavoro di preparazione alla tesi è stato inserito all'interno del programma un algoritmo per la distribuzione delle pressioni superficiali sui corpi 3D, successivamente utilizzato per l'analisi della pressione interna nel serbatoio. Sono state effettuate analisi FEM del serbatoio in diverse configurazioni di carico ove si è cercato di modellare al meglio la struttura portante relativa al caso reale di "full scale test". Dal punto di vista analitico i risultati ottenuti sono soddisfacenti in quanto rispecchiano un corretto comportamento del serbatoio in condizioni di pressioni molto elevate e confermano la bontà del programma nell'analisi computazionale.

Shear behaviour of reinforced cconcrete slab under concentrated load: an investigation through non-linear and sequentially linear analysis

English: The assessment of safety in existing bridges and viaducts led the Ministry of Public Works of the Netherlands to finance a specific campaing aimed at the study of the response of the elements of these infrastructures. Therefore, this activity is focused on the investigation of the behaviour of reinforced concrete slabs under concentrated loads, adopting finite element modeling and comparison with experimental results. These elements are characterized by shear behaviour and crisi, whose modeling is, from a computational point of view, a hard challeng, due to the brittle behavior combined with three-dimensional effects. The numerical modeling of the failure is studied through Sequentially Linear Analysis (SLA), an alternative Finite Element method, with respect to traditional incremental and iterative approaches. The comparison between the two different numerical techniques represents one of the first works and comparisons in a three-dimensional environment. It's carried out adopting one of the experimental test executed on reinforced concrete slabs as well. The advantage of the SLA is to avoid the well known problems of convergence of typical non-linear analysis, by directly specifying a damage increment, in terms of reduction of stiffness and resistance in particular finite element, instead of load or displacement increasing on the whole structure . For the first time, particular attention has been paid to specific aspects of the slabs, like an accurate constraints modeling and sensitivity of the solution with respect to the mesh density. This detailed analysis with respect to the main parameters proofed a strong influence of the tensile fracture energy, mesh density and chosen model on the solution in terms of force-displacement diagram, distribution of the crack patterns and shear failure mode. The SLA showed a great potential, but it requires a further developments for what regards two aspects of modeling: load conditions (constant and proportional loads) and softening behaviour of brittle materials (like concrete) in the three-dimensional field, in order to widen its horizons in these new contexts of study.

Non-linear modelling of microwave devices embedding nano-ferroelectric materials for real-time reconfigurable transmitarray

In this thesis work a nonlinear model for Interdigitated Capacitors (IDCs) based on ferroelectric materials, is proposed. Through the properties of materials such as Hafnium-Zirconium Oxide (HfZrO2), it is possible to realize tunable radiofrequency (RF) circuits. In particular, the model proposed in this thesis describes the use of an IDC, realized on a High-Resistivity silicon substrate, as a phase shifter for beam-steering applications. The model is obtained starting from already present experimental measurements, through which it is possible to identify a circuit model. The model is tested for both low power values and other power values using Harmonic Balance simulations, which show an excellent convergence of the model up to 40 dBm of input power. Furthermore, an array composed by two patches operating both at 2.55 GHz, which exploits the tunable properties of the HfZrO-based IDC is proposed. At 0dBm the model shows a 47° phase shift with polarization -1 V and 1 V which leads to a 11° steering of the main lobe of the array.

Synthetic generation of amyloid PET images by non-linear dimensionality reduction inversion

Privacy issues and data scarcity in PET field call for efficient methods to expand datasets via synthetic generation of new data that cannot be traced back to real patients and that are also realistic. In this thesis, machine learning techniques were applied to 1001 amyloid-beta PET images, which had undergone a diagnosis of Alzheimer’s disease: the evaluations were 540 positive, 457 negative and 4 unknown. Isomap algorithm was used as a manifold learning method to reduce the dimensions of the PET dataset; a numerical scale-free interpolation method was applied to invert the dimensionality reduction map. The interpolant was tested on the PET images via LOOCV, where the removed images were compared with the reconstructed ones with the mean SSIM index (MSSIM = 0.76 ± 0.06). The effectiveness of this measure is questioned, since it indicated slightly higher performance for a method of comparison using PCA (MSSIM = 0.79 ± 0.06), which gave clearly poor quality reconstructed images with respect to those recovered by the numerical inverse mapping. Ten synthetic PET images were generated and, after having been mixed with ten originals, were sent to a team of clinicians for the visual assessment of their realism; no significant agreements were found either between clinicians and the true image labels or among the clinicians, meaning that original and synthetic images were indistinguishable. The future perspective of this thesis points to the improvement of the amyloid-beta PET research field by increasing available data, overcoming the constraints of data acquisition and privacy issues. Potential improvements can be achieved via refinements of the manifold learning and the inverse mapping stages during the PET image analysis, by exploring different combinations in the choice of algorithm parameters and by applying other non-linear dimensionality reduction algorithms. A final prospect of this work is the search for new methods to assess image reconstruction quality.

Shear behavior of reinforced concrete slabs under concentrated load: an investigation through Sequentially Linear Analysis

ABSTRACT (italiano) Con crescente attenzione riguardo al problema della sicurezza di ponti e viadotti esistenti nei Paesi Bassi, lo scopo della presente tesi è quello di studiare, mediante la modellazione con Elementi Finiti ed il continuo confronto con risultati sperimentali, la risposta in esercizio di elementi che compongono infrastrutture del genere, ovvero lastre in calcestruzzo armato sollecitate da carichi concentrati. Tali elementi sono caratterizzati da un comportamento ed una crisi per taglio, la cui modellazione è, da un punto di vista computazionale, una sfida piuttosto ardua, a causa del loro comportamento fragile combinato a vari effetti tridimensionali. La tesi è incentrata sull'utilizzo della Sequentially Linear Analysis (SLA), un metodo di soluzione agli Elementi Finiti alternativo rispetto ai classici approcci incrementali e iterativi. Il vantaggio della SLA è quello di evitare i ben noti problemi di convergenza tipici delle analisi non lineari, specificando direttamente l'incremento di danno sull'elemento finito, attraverso la riduzione di rigidezze e resistenze nel particolare elemento finito, invece dell'incremento di carico o di spostamento. Il confronto tra i risultati di due prove di laboratorio su lastre in calcestruzzo armato e quelli della SLA ha dimostrato in entrambi i casi la robustezza del metodo, in termini di accuratezza dei diagrammi carico-spostamento, di distribuzione di tensioni e deformazioni e di rappresentazione del quadro fessurativo e dei meccanismi di crisi per taglio. Diverse variazioni dei più importanti parametri del modello sono state eseguite, evidenziando la forte incidenza sulle soluzioni dell'energia di frattura e del modello scelto per la riduzione del modulo elastico trasversale. Infine è stato effettuato un paragone tra la SLA ed il metodo non lineare di Newton-Raphson, il quale mostra la maggiore affidabilità della SLA nella valutazione di carichi e spostamenti ultimi insieme ad una significativa riduzione dei tempi computazionali. ABSTRACT (english) With increasing attention to the assessment of safety in existing dutch bridges and viaducts, the aim of the present thesis is to study, through the Finite Element modeling method and the continuous comparison with experimental results, the real response of elements that compose these infrastructures, i.e. reinforced concrete slabs subjected to concentrated loads. These elements are characterized by shear behavior and crisis, whose modeling is, from a computational point of view, a hard challenge, due to their brittle behavior combined with various 3D effects. The thesis is focused on the use of Sequentially Linear Analysis (SLA), an alternative solution technique to classical non linear Finite Element analyses that are based on incremental and iterative approaches. The advantage of SLA is to avoid the well-known convergence problems of non linear analyses by directly specifying a damage increment, in terms of a reduction of stiffness and strength in the particular finite element, instead of a load or displacement increment. The comparison between the results of two laboratory tests on reinforced concrete slabs and those obtained by SLA has shown in both the cases the robustness of the method, in terms of accuracy of load-displacements diagrams, of the distribution of stress and strain and of the representation of the cracking pattern and of the shear failure mechanisms. Different variations of the most important parameters have been performed, pointing out the strong incidence on the solutions of the fracture energy and of the chosen shear retention model. At last a confrontation between SLA and the non linear Newton-Raphson method has been executed, showing the better reliability of the SLA in the evaluation of the ultimate loads and displacements, together with a significant reduction of computational times.

Microwave breast imaging reconstruction

In this thesis I analyzed the microwave tomography method to recognize breast can- cer. I study how identify the dielectric permittivity, the Helmoltz equation parameter used to model the real physic problem. Through a non linear least squares method I solve a problem of parameters identification; I show the theoric approach and the devel- opment to reach the results. I use the Levenberg-Marquardt algorithm, applied on COMSOL software to multiphysic models; so I do numerical proofs on semplified test problems compared to the specific real problem to solve.

Effective procedure for the optimization of the linear controller in an industrial drive for a nonlinear mechanism

Il progetto di tesi è incentrato sull’ottimizzazione del procedimento di taratura dei regolatori lineari degli anelli di controllo di posizione e velocità presenti negli azionamenti usati industrialmente su macchine automatiche, specialmente quando il carico è ad inerzia variabile in dipendenza dalla posizione, dunque non lineare, come ad esempio un quadrilatero articolato. Il lavoro è stato svolto in collaborazione con l’azienda G.D S.p.A. ed il meccanismo di prova è realmente utilizzato nelle macchine automatiche per il packaging di sigarette. L’ottimizzazione si basa sulla simulazione in ambiente Matlab/Simulink dell’intero sistema di controllo, cioè comprensivo del modello Simulink degli anelli di controllo del drive, inclusa la dinamica elettrica del motore, e del modello Simscape del meccanismo, perciò una prima necessaria fase del lavoro è stata la validazione di tali modelli affinché fossero sufficientemente fedeli al comportamento reale. Il secondo passo è stato fornire una prima taratura di tentativo che fungesse da punto di partenza per l’algoritmo di ottimizzazione, abbiamo fatto ciò linearizzando il modello meccanico con l’inerzia minima e utilizzando il metodo delle formule di inversione per determinare i parametri di controllo. Già questa taratura, seppur conservativa, ha portato ad un miglioramento delle performance del sistema rispetto alla taratura empirica comunemente fatta in ambito industriale. Infine, abbiamo lanciato l’algoritmo di ottimizzazione definendo opportunamente la funzione di costo, ed il risultato è stato decisamente positivo, portando ad un miglioramento medio del massimo errore di inseguimento di circa il 25%, ma anche oltre il 30% in alcuni casi.

Experimental determination of burning velocity in metal dust explosions

The modeling of metal dust explosion phenomenon is important in order to safeguard industries from potential accidents. A key parameter of these models is the burning velocity, which represents the consumption rate of the reactants by the flame front, during the combustion process. This work is focused on the experimental determination of aluminium burning velocity, through an alternative method, called "Direct method". The study of the methods used and the results obtained is preceded by a general analysis on dust explosion phenomenon, flame propagation phenomenon, characteristics of the metals combustion process and standard methods for determining the burning velocity. The “Direct method” requires a flame propagating through a tube recorded by high-speed cameras. Thus, the flame propagation test is carried out inside a vertical prototype made of glass. The study considers two optical technique: the direct visualization of the light emitted by the flame and the Particle Image Velocimetry (PIV) technique. These techniques were used simultaneously and allow the determination of two velocities: the flame propagation velocity and the flow velocity of the unburnt mixture. Since the burning velocity is defined by these two quantities, its direct determination is done by substracting the flow velocity of the fresh mixture from the flame propagation velocity. The results obtained by this direct determination, are approximated by a linear curve and different non-linear curves, which show a fluctuating behaviour of burning velocity. Furthermore, the burning velocity is strongly affected by turbulence. Turbulence intensity can be evaluated from PIV technique data. A comparison between burning velocity and turbulence intensity highlighted that both have a similar trend.

Deep Learning Architectures for time of arrival detection in Acoustic Emissions Monitoring

Acoustic Emission (AE) monitoring can be used to detect the presence of damage as well as determine its location in Structural Health Monitoring (SHM) applications. Information on the time difference of the signal generated by the damage event arriving at different sensors is essential in performing localization. This makes the time of arrival (ToA) an important piece of information to retrieve from the AE signal. Generally, this is determined using statistical methods such as the Akaike Information Criterion (AIC) which is particularly prone to errors in the presence of noise. And given that the structures of interest are surrounded with harsh environments, a way to accurately estimate the arrival time in such noisy scenarios is of particular interest. In this work, two new methods are presented to estimate the arrival times of AE signals which are based on Machine Learning. Inspired by great results in the field, two models are presented which are Deep Learning models - a subset of machine learning. They are based on Convolutional Neural Network (CNN) and Capsule Neural Network (CapsNet). The primary advantage of such models is that they do not require the user to pre-define selected features but only require raw data to be given and the models establish non-linear relationships between the inputs and outputs. The performance of the models is evaluated using AE signals generated by a custom ray-tracing algorithm by propagating them on an aluminium plate and compared to AIC. It was found that the relative error in estimation on the test set was < 5% for the models compared to around 45% of AIC. The testing process was further continued by preparing an experimental setup and acquiring real AE signals to test on. Similar performances were observed where the two models not only outperform AIC by more than a magnitude in their average errors but also they were shown to be a lot more robust as compared to AIC which fails in the presence of noise.

Variational Quantum Splines: Moving Beyond Linearity for Quantum Activation Functions

Activation functions within neural networks play a crucial role in Deep Learning since they allow to learn complex and non-trivial patterns in the data. However, the ability to approximate non-linear functions is a significant limitation when implementing neural networks in a quantum computer to solve typical machine learning tasks. The main burden lies in the unitarity constraint of quantum operators, which forbids non-linearity and poses a considerable obstacle to developing such non-linear functions in a quantum setting. Nevertheless, several attempts have been made to tackle the realization of the quantum activation function in the literature. Recently, the idea of the QSplines has been proposed to approximate a non-linear activation function by implementing the quantum version of the spline functions. Yet, QSplines suffers from various drawbacks. Firstly, the final function estimation requires a post-processing step; thus, the value of the activation function is not available directly as a quantum state. Secondly, QSplines need many error-corrected qubits and a very long quantum circuits to be executed. These constraints do not allow the adoption of the QSplines on near-term quantum devices and limit their generalization capabilities. This thesis aims to overcome these limitations by leveraging hybrid quantum-classical computation. In particular, a few different methods for Variational Quantum Splines are proposed and implemented, to pave the way for the development of complete quantum activation functions and unlock the full potential of quantum neural networks in the field of quantum machine learning.

Depth Estimation in Stereo Biomedical Images via Proxy-Supervised Deep Learning

In order to estimate depth through supervised deep learning-based stereo methods, it is necessary to have access to precise ground truth depth data. While the gathering of precise labels is commonly tackled by deploying depth sensors, this is not always a viable solution. For instance, in many applications in the biomedical domain, the choice of sensors capable of sensing depth at small distances with high precision on difficult surfaces (that present non-Lambertian properties) is very limited. It is therefore necessary to find alternative techniques to gather ground truth data without having to rely on external sensors. In this thesis, two different approaches have been tested to produce supervision data for biomedical images. The first aims to obtain input stereo image pairs and disparities through simulation in a virtual environment, while the second relies on a non-learned disparity estimation algorithm in order to produce noisy disparities, which are then filtered by means of hand-crafted confidence measures to create noisy labels for a subset of pixels. Among the two, the second approach, which is referred in literature as proxy-labeling, has shown the best results and has even outperformed the non-learned disparity estimation algorithm used for supervision.

Conditional entropy and predictability for non-reversible Markov systems

The purpose of this thesis is to clarify the role of non-equilibrium stationary currents of Markov processes in the context of the predictability of future states of the system. Once the connection between the predictability and the conditional entropy is established, we provide a comprehensive approach to the definition of a multi-particle Markov system. In particular, starting from the well-known theory of random walk on network, we derive the non-linear master equation for an interacting multi-particle system under the one-step process hypothesis, highlighting the limits of its tractability and the prop- erties of its stationary solution. Lastly, in order to study the impact of the NESS on the predictability at short times, we analyze the conditional entropy by modulating the intensity of the stationary currents, both for a single-particle and a multi-particle Markov system. The results obtained analytically are numerically tested on a 5-node cycle network and put in correspondence with the stationary entropy production. Furthermore, because of the low dimensionality of the single-particle system, an analysis of its spectral properties as a function of the modulated stationary currents is performed.