20 resultados para Driver-Vehicle System Modeling.
Resumo:
I applied the SBAS-DInSAR method to the Mattinata Fault (MF) (Southern Italy) and to the Doruneh Fault System (DFS) (Central Iran). In the first case, I observed limited internal deformation and determined the right lateral kinematic pattern with a compressional pattern in the northern sector of the fault. Using the Okada model I inverted the observed velocities defining a right lateral strike slip solution for the MF. Even if it fits the data within the uncertainties, the modeled slip rate of 13-15 mm yr-1 seems too high with respect to the geological record. Concerning the Western termination of DFS, SAR data confirms the main left lateral transcurrent kinematics of this fault segment, but reveal a compressional component. My analytical model fits successfully the observed data and quantifies the slip in ~4 mm yr-1 and ~2.5 mm yr-1 of pure horizontal and vertical displacement respectively. The horizontal velocity is compatible with geological record. I applied classic SAR interferometry to the October–December 2008 Balochistan (Central Pakistan) seismic swarm; I discerned the different contributions of the three Mw > 5.7 earthquakes determining fault positions, lengths, widths, depths and slip distributions, constraining the other source parameters using different Global CMT solutions. A well constrained solution has been obtained for the 09/12/2008 aftershock, whereas I tested two possible fault solutions for the 28-29/10/08 mainshocks. It is not possible to favor one of the solutions without independent constraints derived from geological data. Finally I approached the study of the earthquake-cycle in transcurrent tectonic domains using analog modeling, with alimentary gelatins like crust analog material. I successfully joined the study of finite deformation with the earthquake cycle study and sudden dislocation. A lot of seismic cycles were reproduced in which a characteristic earthquake is recognizable in terms of displacement, coseismic velocity and recurrence time.
Resumo:
The cardiomyocyte is a complex biological system where many mechanisms interact non-linearly to regulate the coupling between electrical excitation and mechanical contraction. For this reason, the development of mathematical models is fundamental in the field of cardiac electrophysiology, where the use of computational tools has become complementary to the classical experimentation. My doctoral research has been focusing on the development of such models for investigating the regulation of ventricular excitation-contraction coupling at the single cell level. In particular, the following researches are presented in this thesis: 1) Study of the unexpected deleterious effect of a Na channel blocker on a long QT syndrome type 3 patient. Experimental results were used to tune a Na current model that recapitulates the effect of the mutation and the treatment, in order to investigate how these influence the human action potential. Our research suggested that the analysis of the clinical phenotype is not sufficient for recommending drugs to patients carrying mutations with undefined electrophysiological properties. 2) Development of a model of L-type Ca channel inactivation in rabbit myocytes to faithfully reproduce the relative roles of voltage- and Ca-dependent inactivation. The model was applied to the analysis of Ca current inactivation kinetics during normal and abnormal repolarization, and predicts arrhythmogenic activity when inhibiting Ca-dependent inactivation, which is the predominant mechanism in physiological conditions. 3) Analysis of the arrhythmogenic consequences of the crosstalk between β-adrenergic and Ca-calmodulin dependent protein kinase signaling pathways. The descriptions of the two regulatory mechanisms, both enhanced in heart failure, were integrated into a novel murine action potential model to investigate how they concur to the development of cardiac arrhythmias. These studies show how mathematical modeling is suitable to provide new insights into the mechanisms underlying cardiac excitation-contraction coupling and arrhythmogenesis.
Resumo:
Traditionally, the study of internal combustion engines operation has focused on the steady-state performance. However, the daily driving schedule of automotive engines is inherently related to unsteady conditions. There are various operating conditions experienced by (diesel) engines that can be classified as transient. Besides the variation of the engine operating point, in terms of engine speed and torque, also the warm up phase can be considered as a transient condition. Chapter 2 has to do with this thermal transient condition; more precisely the main issue is the performance of a Selective Catalytic Reduction (SCR) system during cold start and warm up phases of the engine. The proposal of the underlying work is to investigate and identify optimal exhaust line heating strategies, to provide a fast activation of the catalytic reactions on SCR. Chapters 3 and 4 focus the attention on the dynamic behavior of the engine, when considering typical driving conditions. The common approach to dynamic optimization involves the solution of a single optimal-control problem. However, this approach requires the availability of models that are valid throughout the whole engine operating range and actuator ranges. In addition, the result of the optimization is meaningful only if the model is very accurate. Chapter 3 proposes a methodology to circumvent those demanding requirements: an iteration between transient measurements to refine a purpose-built model and a dynamic optimization which is constrained to the model validity region. Moreover all numerical methods required to implement this procedure are presented. Chapter 4 proposes an approach to derive a transient feedforward control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient.
Resumo:
The aim of this work is to investigate, using extensive Monte Carlo computer simulations, composite materials consisting of liquid crystals doped with nanoparticles. These systems are currently of great interest as they offer the possibility of tuning the properties of liquid crystals used in displays and other devices as well as providing a way of obtaining regularly organized systems of nanoparticles exploiting the molecular organization of the liquid crystal medium. Surprisingly enough, there is however a lack of fundamental knowledge on the properties and phase behavior of these hybrid materials, making the route to their application an essentially empirical one. Here we wish to contribute to the much needed rationalization of these systems studying some basic effects induced by different nanoparticles on a liquid crystal host. We investigate in particular the effects of nanoparticle shape, size and polarity as well as of their affinity to the liquid crystal solvent on the stability of the system, monitoring phase transitions, order and molecular organizations. To do this we have proposed a coarse grained approach where nanoparticles are modelled as a suitably shaped (spherical, rod and disk like) collection of spherical Lennard-Jones beads, while the mesogens are represented with Gay-Berne particles. We find that the addition of apolar nanoparticles of different shape typically lowers the nematic–isotropic transition of a non-polar nematic, with the destabilization being greater for spherical nanoparticles. For polar mesogens we have studied the effect of solvent affinity of the nanoparticles showing that aggregation takes places for low solvation values. Interestingly, if the nanoparticles are polar the aggregates contribute to stabilizing the system, compensating the shape effect. We thus find the overall effects on stability to be a delicate balance of often contrasting contributions pointing to the relevance of simulations studies for understanding these complex systems.
Resumo:
Aberrant expression of ETS transcription factors, including FLI1 and ERG, due to chromosomal translocations has been described as a driver event in initiation and progression of different tumors. In this study, the impact of prostate cancer (PCa) fusion gene TMPRSS2-ERG was evaluated on components of the insulin-like growth factor (IGF) system and the CD99 molecule, two well documented targets of EWS-FLI1, the hallmark of Ewing sarcoma (ES). The aim of this study was to identify common or distinctive ETS-related mechanisms which could be exploited at biological and clinical level. The results demonstrate that IGF-1R represents a common target of ETS rearrangements as ERG and FLI1 bind IGF-1R gene promoter and their modulation causes alteration in IGF-1R protein levels. At clinical level, this mechanism provides basis for a more rationale use of anti-IGF-1R inhibitors as PCa cells expressing the fusion gene better respond to anti-IGF-1R agents. EWS-FLI1/IGF-1R axis provides rationale for combination of anti-IGF-1R agents with trabectedin, an alkylator agent causing enhanced EWS-FLI1 occupancy on the IGF-1R promoter. TMPRSS2-ERG also influences prognosis relevance of IGF system as high IGF-1R correlates with a better biochemical progression free survival (BPFS) in PCa patients negative for the fusion gene while marginal or no association was found in the total cases or TMPRSS2-ERG-positive cases, respectively. This study indicates CD99 is differentially regulated between ETS-related tumors as CD99 is not a target of ERG. In PCa, CD99 did not show differential expression between TMPRSS2-ERG-positive and –negative cells. A direct correlation was anyway found between ERG and CD99 proteins both in vitro and in patients putatively suggesting that ERG target genes comprehend regulators of CD99. Despite a little trend suggesting a correlation between CD99 expression and a better BPFS, no clinical relevance for CD99 was found in the field of prognostic biomarkers.