Dissertations / Theses on the topic 'Dynamic CBR'

This master thesis was performed in collaboration with Öhlins Racing AB. The company provides suspension systems to the automotive industry and to motorsport teams globally. Many of Öhlins’ customers compete in rallycross, a style of competition that generally involves highly modified production cars racing on closed, elevated and mixed surfaced circuits. Rallycross cars generally have an inherent problem and tend to over rotate mid-air after taking off from a jump. The vehicle often lands with a large pitch angle, damaging suspension components or losing valuable time when the driver waits for the vehicle to settle. The request from Öhlins was to analyse this phenomenon. The scope of the master thesis was to; investigate four different simulation software and choose the most appropriate software to simulate a rallycross car, perform a parameter study to analyse which parameters affect the jumping behaviour of the vehicle and study the force build up in the suspension during the landing phase. The four simulation software investigated were LMS Amesim, CarSim, Adams/Car and a 2D MATLAB model. The models were parameterised with vehicle data acquired from a rallycross car and validated against measured data obtained from tests with the same car. The MATLAB model was considered to be the best performing model given the criteria which were set up. A parameter study was conducted with the chosen simulation model where different vehicle parameters, driver behaviour and road profiles were analysed to investigate what impact they had on the jumping performance of the rallycross car. It could be concluded that the rear damper stiffness is critical for the jumping behaviour of the vehicle and that a stiffer rear damper generally gives the best performance. The longitudinal position of the centre of gravity also has a significant impact on vehicle jumping where a position in the middle between front and rear axle is preferred. The force build-up in the vehicle suspension was also analysed. Vehicle jumping and landing behaviour was compared to measurements from a human jumping in order to investigate if a human jumping utilised other force build-up strategies. It was found that the car force build-up during landing was similar to a human beings. Other force build-up strategies for the dampers were tested and it was found that dampers reacting to stroke position or hub acceleration can improve jumping performance of a rallycross car.

Les récepteurs cannabinoide type 1 (CB1R) médient la plasticité synaptique rétrograde dans les synapses excitatrices et inhibitrices et participent à de multiples fonctions physiologiques. Les mouvements de surface des récepteurs présynaptiques, tels que les CB1R, restent inconnus. Nous avons analysé la mobilité latérale des CB1R natifs sur les neurones corticaux, par imagerie du suivi de quantum dot unique. Nous avons trouvé que les CB1R sont mobiles et diffusent rapidement dans les présynapses. La désensibilisation, induite par un agoniste, diminue le nombre des CB1R de surface et réduit considérablement la dynamique membranaire des CB1R restant sur la surface présynaptique. La désensibilisation éliminerait les CB1R des synapses et augmenterait le nombre des récepteurs immobiles dans le compartiment extrasynaptique. Nos résultats suggèrent que la réduction de la mobilité pourrait être un des principaux mécanismes de la désensibilisation des CB1Rs, le plus abondant récepteur couplé aux protéines G dans le cerveau<br>Presynaptic cannabinoid type 1 receptors (CB1R) are major mediators of retrograde synaptic plasticity at both excitatory and inhibitory synapses and participate to a plethora of physiological functions. Whether presynaptic receptors, such as CB1R, display functionally relevant movements at the surface of neuronal membrane is not known. We analyzed the lateral mobility of native CB1R in cortical neurons, using single quantum dot imaging. We found that CB1R are highly mobile and rapidly diffuse in and out of presynapses. Agonist-induced desensitization reduced the number of surface CB1R and drastically decreased the membrane dynamic of the CB1R that remained at the presynaptic surface. Desensitization specifically excluded CB1R from synapses and increased the number of immobile receptors in the extrasynaptic compartment. The results suggest that decrease of mobility may be one of the core mechanisms underlying the desensitization of CB1R, the most abundant G-protein coupled receptor in the brain

Car-Parronello molecular dynamics simulations of twelve nanosized graphene sheets with a dozen to a hundred carbon atoms are performed using a mixed Gaussian and planewave approach within the frame-work of the density-functional theory. Two different origins for the rippled structure of graphene are found: the thermodynamic vibration of atoms and the local lattice defect. We suggest that the lattice defect, which changes the local atomic bonding state, should be responsible for the intrinsic ripples in graphene sheet. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/35242

Thesis (Ph. D.)--University of California, San Diego, 2008.<br>Title from first page of PDF file (viewed December 16, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 259-271).

Abstract Magnetic Resonance Imaging (MRI) is a medical imaging technique used in radiology to visualize the anatomical structures and the functions of the body. Thanks to its fine spatial resolution and to the great contrast between the different soft tissues, MRI has become the most used method for the anatomical image generation. During the last two decades, MRI was widely studied and developed, so high performance devices and new analysis protocols are now available. As an outcome, MR can now be used also to perform functional analysis. Currently, the Positron Emission Tomography (PET) is the gold standard technique in functional imaging. However, MRI is becoming a valid alternative to PET in functional analysis because of its greater spatial resolution, its wide diffusion and the absence of ionizing radiations. Currently, perfusion magnetic resonance using an exogenous tracer, such as gadolinium, is the most interesting technique for the quantitative study of the hemodynamic. The Dynamic Susceptibility Contrast - Magnetic Resonance Imaging (DSC-MRI) allows to quantify important hemodynamic parameters that play an important role in the study of several pathologies, such as cerebral neoplasia, ischemia or infarction, epilepsy, dementia and schizophrenia. The commonly used model for describing the DSC-MRI signal is based on the non diffusible tracer theory, also called dilution theory. It assumes that the tracer remains intravascular, the blood-brain-barrier (BBB) is intact and there is no tracer recirculation. Under these assumptions, the model allows to estimate the Cerebral Blood Volume (CBV), the Cerebral Blood Flow (CBF) and the Mean Transit Time (MTT). The most crucial step in the DSC-MRI image quantification is the residue function estimate that presents some limitations. The most important ones, that are considered in this work, are: • the necessity to know the Arterial Input Function (AIF), which is the concentration time curve in the vessels feeding the tissue; • the assessment of the residue function requiring to perform a deconvolution operation, which is a well-known difficult mathematical problem. Currently, AIF is measured directly on the MR images, by selecting a small number of pixels containing one of the principal arterial vessels. The pixel selection can be made either manually, by a physician, or by means of automatic algorithms. During the past years, several automatic and semiautomatic methods for the AIF extraction have been proposed, but a standard has not been achieved, yet. In this work, the AIF selection and deconvolution problems are discussed in depth. A new selection method, combining anatomical information with MR-signal analysis in presented. It is compared to the other AIF selection algorithms proposed in literature on a simulated data set. Then, a comparison with the manual selection method on a clinical data set is performed and the AIF selection impact on CBF, CBV and MTT estimate is investigated. The proposed method has been shown to reliably reconstruct the true AIF, providing accurate estimates and very narrow confidence bands. Moreover, it is robust against the different noise levels, thus increasing the reproducibility level in DSC-MRI image quantification. Furthermore, AIFs obtained with the new method have been shown to lead to a more accurate diagnosis than the manual ones. Another critical step in DSC-MRI data analysis is the deconvolution operation, that allows to estimate the residue function. Problems in this step are due to the deconvolution intrinsic problems (e.g. the ill-posedness and the ill-conditioning) and to the physiological system specific problems (e.g. non negative constrains). Moreover, another important source of error in the residue function estimate is the possible presence of delay and/or dispersion in AIF. Currently, the most used deconvolution methods are the Singular Value Decomposition (SVD) and the block-Circulant Singular Value Decomposition (cSVD). SVD is historically the first and the most important deconvolution method proposed in the DSC-MRI context and it is currently the reference method. The cSVD method is the natural evolution of SVD and it has been proposed to overcome the problem of delay in the AIF. Several other deconvolution methods have been proposed in literature. Among them all, we focus on a recently proposed method, the Nonlinear Stochastic Regularization (NSR), that accounts for both the smoothness and the non-negativity constraint of the residue function. In this work, a new deconvolution method is presented. The Population Deconvolution (PD) method exploits a population approach to analyse a large set of similar voxels at the same time, thus improving the data quality in the deconvolution operation. PD has been validated on simulated data and compared to SVD and cSVD. PD can reconstruct reliable and physiological residue functions. The residue functions obtained using PD present very small and damped oscillations compared to SVD and cSVD ones. Furthermore, PD has been shown to accurately estimate the CBF both in presence and in absence of dispersion, providing better results than SVD and cSVD. SVD, cSVD and PD have been compared also to NSR on clinical data. CBF and MTT maps provided by PD present a greater contrast level than SVD and cSVD ones, as they emphasize the flow and transit time differences. Also NSR maps are extremely contrasted, but they appear noisier than the PD ones. A new physiological indicator, the Laterality Index, has also been introduced. It provides a graphical representation of the CBF and MTT map information, integrating all the information provided by the different parameters. NSR provides very large laterality indices, thus emphasizing the disease affected regions. Nevertheless, the detection of the pathological areas is not easy because of the large LI variability also in the healthy regions. On the contrary, SVD and cSVD laterality indices make the disease detection difficult because they do not emphasize the pathological areas. PD meets the need to underline the pathologic areas without showing false positive results, providing larger LIs than the SVD and cSVD ones, but smaller than the NSR ones. Therefore, PD has been shown to lead to a more accurate diagnosis than the other methods. Finally, another promising deconvolution method, called DNP, is presented. Differently from PD, that has to be applied to large data sets because of its population approach, DNP is a voxel based method, thus it can be applied also to a small number of voxels. The most interesting DNP feature is that it accounts for both the residue function continuity and the system BIBO-stability. Moreover, it can estimate the AIF delay, thus improving the accuracy in the R(t) estimation. Since it is still under development, only the DNP preliminary results are presented in this work. DNP has been shown to provide more accurate CBF estimates than SVD and cSVD, both in presence and absence of delay and dispersion. Furthermore, the DNP reconstructed residue functions show neither the negative values nor the spurious oscillations usually present in the SVD and cSVD ones. However, DNP bears some limitations too. Currently, the most important DNP limitation is the delay estimation. DNP usually overestimates the delay, above all in presence of dispersion, thus providing a non accurate characterization of the residue function. Another DNP problem is that the hyper-parameter quantification requires a non-linear step, which increases the computation time of the algorithm. In conclusion, although they present some limitations in the post-processing analysis, DSC-MRI techniques are becoming an important tool in medical research and in clinical practice. The development of a fully automatic algorithm for the AIF selection and of a deconvolution method based on a population approach would improve the clinical and scientific information provided by DSC-MRI analysis.<br>Abstract La Risonanza Magnetica (RM) è una tecnica di imaging medico che viene utilizzata in radiologia sia per le strutture anatomiche sia per le funzionalità del corpo umano. Grazie all’elevata risoluzione spaziale di cui dispone e al notevole livello di contrasto tra le differenti tipologie di tessuto, la RM è diventata lo strumento per la generazione di immagini anatomiche più diffuso. Negli ultimi decenni, la RM è stata oggetto di studi approfonditi e notevoli sviluppi, tanto che oggi sono disponibili macchinari ad elevate prestazioni e un ampio numero di protocolli d’acquisizione differenti. Di conseguenza, la RM ha cominciato a essere utilizzata anche per studi funzionali. Attualmente, la Tomografia ad Emissione di Positroni (PET) è la tecnica di riferimento per gli studi funzionali, ma la RM sta diventando una valida alternativa grazie alla sua maggiore risoluzione spaziale, alla sua maggiore diffusione e al fatto che non utilizza radiazioni ionizzanti nocive. Attualmente, la risonanza magnetica di perfusione che ricorre all’uso di un agente di contrasto esogeno, come il gadolinio, è la tecnica più interessante per lo studio quantitativo dell’emodinamica. La Dynamic Susceptibility Contrast - Magnetic Resonance Imaging (DSC-MRI) permette di ricavare importanti parametri emodinamici che ricoprono un ruolo chiave nello studio di svariate patologie, quali la neoplasia cerebrale, l’ischemia, l’infarto, l’epilessia, la demenza e la schizofrenia. Per caratterizzare il segnale ottenuto con la DSC-MRI viene generalmente utilizzato un modello basato sulla teoria dei traccianti non diffusibili (la teoria della diluizione). Basandosi sulle ipotesi che il tracciante sia intravascolare, che la barriera emato-encefalica sia intatta e che non ci sia ricircolo di tracciante, il modello permette di ricavare il Volume Ematico Cerebrale (CBV), il Flusso Ematico Cerebrale (CBF) e il Tempo Medio di Transito (MTT). I passaggio chiave per la stima di tali parametri è la quantificazione della funzione residuo, che presenta tuttavia alcuni problemi. In questa tesi saranno trattati i più importanti tra essi: • la necessità di ricavare la Funzione d’Ingresso Arteriale (AIF), che rappresenta l’andamento nel tempo della concentrazione di tracciante nei vasi che irrorano il tessuto; • la necessità di ricorrere ad un’operazione di deconvoluzione per ricavare la funzione residuo. La AIF è solitamente ricavata selezionando alcuni pixel che rappresentano i vasi arteriali principali direttamente sulle immagini di RM. La selezione dei pixel può essere fatta sia manualmente da un radiologo sia tramite un algoritmo di selezione automatica. Recentemente sono stati proposti numerosi algoritmi per svolgere tale compito, ma non si è ancora raggiunto uno standard. In questo lavoro il problema relativo all’estrazione della AIF viene discusso approfonditamente. Si propone un nuovo metodo per la selezione dei pixel arteriali che combina le informazioni anatomiche con l’analisi del segnale DSC-MRI. L’algoritmo è testato su dati simulati e confrontato con i più interessanti algoritmi proposti in letteratura. Successivamente viene applicato anche su dati reali e confrontato con la AIF ottenuta tramite selezione manuale al fine di valutare l’impatto che la scelta della AIF ha sulla stima dei parametri CBF, CBV e MTT. Il metodo proposto ha dimostrato di essere in grado di ricostruire la AIF originale, fornendo sia stime accurate che intervalli di confidenza molto stretti. Inoltre ha dimostrato di essere robusto nei confronti di diversi livelli di rumorosità nei dati, contribuendo quindi all’aumento della riproducibilità nello studio dell’emodinamica cerebrale. Infine, le AIF ottenute tramite il nuovo algoritmo hanno permesso di effettuare diagnosi più accurate rispetto a quelle ottenute tramite selezione manuale. Un altro passaggio critico per l’analisi dei dati DSC-MRI è rappresentato dall’operazione di deconvoluzione necessaria per la stima della funzione residuo. I problemi in quest’ambito sono legati sia ai problemi intrinseci della deconvoluzione (ad esempio il fatto che è un problema matematico mal condizionato e mal posto), sia ad aspetti dovuti al fatto che si tratta di un sistema fisiologico (ad esempio vincoli di non negatività). Inoltre, la possibile presenza di dispersione e ritardo nella AIF costituisce un’altra importante fonte di errore per la stima della funzione residuo. Ad oggi, i metodi di deconvoluzione più diffusi sono la Singular Value Decomposition (SVD) e la block-Circulant Singular Value Decomposition (cSVD). La SVD è storicamente il primo metodo proposto per lo studio dei dati DSC-MRI e rappresenta ancora il metodo di riferimento in quest’ambito. La cSVD è invece la naturale evoluzione della SVD, proposta per eliminare i problemi dovuti al ritardo nella AIF che caratterizzano la SVD. Numerosi metodi sono stati proposti negli anni in letteratura. Tra i vari, citiamo la Nonlinear Stochastic Regularization (NSR), che permette di tener conto sia dei vincoli di non negatività sia della regolarità della funzione residuo. In questo lavoro si presenta un nuovo metodo di deconvoluzione. La Population Deconvolution (PD) che analizza contemporaneamente un ampio numero di voxel simili sfruttando un approccio di popolazione, quindi migliorando la qualità dei dati utilizzati per l’operazione di deconvoluzione. Il metodo PD è stato validato su dati simulati e confrontato sia con la SVD che con la cSVD. PD riesce a ricostruire funzioni residuo che risultato credibili e fisiologiche in quanto presentano oscillazioni poco ampie e più smorzate rispetto a quelle presenti nelle funzioni residuo ottenuto con la SVD e la cSVD. PD permette inoltre di ricavare stime accurate di CBF, sia in presenza che in assenza di dispersione nella AIF, fornendo risultati migliori rispetto alla SVD e alla cSVD. PD, SVD e cSVD sono stati inoltre utilizzati per l’analisi di dati reali e sono stati confrontati anche con NSR. Le mappe di CBF e MTT ottenute tramite PD presentano un livello di contrasto migliore rispetto a quelle ottenute con SVD e cSVD, enfatizzando maggiormente le aree caratterizzate da un diverso flusso ematico. Anche le mappe ottenute tramite NSR presentano un alto livello di contrasto, risultando però più rumorose rispetto a quelle ottenute tramite PD. Si è inoltre introdotto un nuovo indicatore fisiologico, l’indice di lateralità, che permette di fornire una rappresentazione grafica e di integrare le informazioni contenute nelle mappe di CBF e MTT. NSR fornisce valori di lateralità molto ampi, evidenziando notevolmente le zone caratterizzate da diversi flussi ematici. Tuttavia, l’individuazione delle aree colpite dalla patologia è resa difficoltosa dal fatto che anche le aree sane sono caratterizzate da ampi indici di lateralità. L’opposto si verifica considerando gli indici di lateralità ottenuti tramite SVD o cSVD; in questo caso l’individuazione delle aree malate è resa difficile dal fatto che gli indici forniti sono molto piccoli. PD invece permette di ottenere degli indici di lateralità che evidenziano le aree malate più di quanto non facciano SVD o cSVD, ma con valori meno ampi rispetto a NSR, soprattutto nelle regioni sane. In questo modo, PD permette di ottenere diagnosi più accurate. Infine, in questo lavoro viene presentato un ulteriore promettente metodo di deconvoluzione, chiamato DNP. A differenza di PD, che deve essere utilizzato per l’analisi di un elevato numero di voxel a causa dell’approccio di popolazione, DNP è un metodo di deconvoluzione di singoli voxel, quindi può essere applicato anche all’analisi di regioni contenenti pochi voxel. L’aspetto più interessante del metodo DNP è che permette di tenere conto sia del fatto che la funzione residuo deve essere continua, sia del fatto che un sistema fisiologico è, naturalmente, BIBO stabile. Inoltre, tale metodo permette di stimare anche il ritardo normalmente presente nella AIF, migliorando la precisione nella stima della funzione residuo. Dato che il metodo è ancora in fase di sviluppo, nella tesi sono riportati solo dei risultati preliminari. Tali risultati mostrano che DNP è in grado di fornire stime di CBF più accurate rispetto a SVD e cSVD, sia in presenza che in assenza di dispersione e ritardo. Inoltre, le funzioni residuo ottenute tramite DNP non presentano valori negativi e le oscillazioni non fisiologiche generalmente presenti nei risultati forniti da SVD e cSVD. D’altro canto, DNP presenta ancora dei problemi, il più importante dei quali è il calcolo del ritardo nella AIF, poco preciso e generalmente sovrastimato, soprattutto in presenza di dispersione. Inoltre, DNP non riesce ancora a caratterizzare bene l’andamento della funzione residuo. Un altro problema non ancora risolto è legato alla stima degli iper-parametri. Infatti questo aspetto richiede alcuni passaggi non lineari che incrementano notevolmente i tempi di calcolo necessari all’algoritmo. In conclusione, anche se presenta ancora numerosi limiti nella fase di analisi del segnale, la DSC-MRI sta diventando uno strumento molto importante sia nella pratica clinica che nella fase di ricerca medica. Gli algoritmi di selezione della AIF e di deconvoluzione che sono stati proposti in questa tesi permettono di migliorare l’informazione clinica e scientifica che si può ottenere dall’analisi dei dati ottenuti tramite DSC-MRI.

The continuously variable transmission (CVT), which has been in use in some of the vehicles in the market today, presents the possibility of decoupling the engine speed and the vehicle speed. By this way, it is now possible to operate the engine at its maximum efficient or performance point and fix it at that operating point without losing from the vehicle speed. Instead of using gears, which are the main transmission elements of conventional transmission, CVT uses two pulleys and a belt. By changing the pulley diameters, a continuously variable transmission ratio is obtained. Besides all its advantages, it has some big drawbacks like low efficiency, torque transmission ability and limited speed range. With developing technology, however, new solutions are developed to eliminate these drawbacks. In this study simulation models for the performance and fuel consumption of different types and arrangements of continuously variable transmission (CVT) systems are developed. Vehicles, which are equipped with two different arrangements of CVT and an automatic transmission, are modelled by using Matlab&amp<br>#8217<br>s simulation toolbox Simulink. By defining the required operating points for better acceleration performance and fuel consumption, and operating the engine at these points, performance optimization is satisfied. These transmissions are compared with each other according to their &amp<br>#8216<br>0-100 kph&amp<br>#8217<br>acceleration performances, maximum speeds, required time to travel 1000 m. and fuel consumptions for European driving cycles ECE and EUDC. These comparisons show that CVT systems are superior to automatic transmission, according to their acceleration and fuel consumption performances. CVTs also provide smoother driving, while they can eliminate jerks at gear shifting points.

Thesis (Ph. D.)--University of Oregon, 2003.<br>Typescript. Includes vita and abstract. Includes bibliographical references (leaves 68-69). Also available for download via the World Wide Web; free to University of Oregon users.

Virtual prototyping is becoming more and more important and reliable in the automotive field as new tools and software are being developed. This has created the need of virtual drivers and controllers to test virtual vehicles. In this thesis, we propose a maneuver regulation controller able to steer a vehicle to a desired trajectory. In order to design the controller and subsequently validate it, we study at first two vehicle models, a single track and a double track. Transverse coordinates are then introduced to perform the maneuver regulation in a geometric domain. The equilibrium states and the behaviour of the proposed models is then explored with an iterative algorithm. This knowledge is used by the controller to perform the dynamic inversion of the system. The controller is then developed and tested in Python, and its performances are commented.

Les pathogènes neurotropiques représentent une banque d’outils biologique afin de cibler spécifiquement le système nerveux central (SNC), pour son étude mais aussi dans l’optique d’une thérapie. Parmi eux, l’adénovirus canin de type 2 (CAV-2) est un vecteur prometteur pour cibler le SNC. CAR a été principalement étudié en tant que récepteur viral. Cependant, plusieurs études montrent que CAR est essentiel dans le développement du cœur ainsi que du système lymphatique. De manière intéressante, CAR est fortement exprimé pendant le développement du SNC, suggérant un rôle dans l’établissement des réseaux neuronaux. Dans ce travail, nous avons confirmé que CAR est lié aux mécanismes d’endocytoses et au trafic intracellulaire. L’endocytose de CAR est ligand dépendant. La partie intracellulaire de CAR régule son endocytose. Nos données suggèrent que CAR est l’unique récepteur pour CAV-2. Le présent travail de recherche montre aussi que CAR ne semble pas participer à la formation du SNC. En revanche, au niveau du SNC mature, CAR est impliqué dans la plasticité synaptique, dans la neurogénèse adulte et participe à l’homéostasie des synapses, mécanismes impliqués dans les processus mnésiques<br>The coxsackievirus and adenovirus receptor (CAR) is a single-pass transmembrane protein belonging to the CTX subfamily of the immunoglobulin superfamily. CAR has been extensively studied as a viral receptor for coxsackie B viruses and some adenoviruses (AdVs). CAR is essential for the development of the cardiovascular and lymphatic system. Interestingly, CAR is highly expressed in the developing brain and has been hypothesized to regulate the establishment of the neuronal networks. In my PhD work, I showed that CAR can be link to the endocytic pathways and intracellular trafficking. CAR endocytosis is ligand-dependent and is regulated by CAR intracellular domain (ICD), suggesting strongly that CAR is most likely the unique receptor for canine adenovirus type 2 (CAV-2). Moreover, we demonstrated that CAR depletion in the developing brain did not significantly perturb brain development. In the healthy adult brain, CAR is relatively abundant and we demonstrated that CAR loss of function affected hippocampal plasticity, adult neurogenesis and synapse homeostasis, which affect cognition

This research aims to investigate the nature of high β-angle cornering as seen in rallying and in particular the World Rally Championship. This is achieved through a combination of sensor development, on-car measurement and vehicle dynamic simulation. Through the development of novel β-angle measurement technology it has become possible to measure and study vehicle attitude dynamics on loose gravel surfaces. Using this sensor, an understanding of how a rally driver uses the dynamics of the vehicle and surface to maximise performance has been obtained. By combining the new data stream with accepted vehicle dynamic theory, the tyres have been considered and general trends in gravel tyre performance unveiled. Through feedback, these trends have been implemented as a means of tuning a dynamic model to improve realism and permit an analysis of cornering trends in rally cars. Active control systems have been considered that could implement more sophisticated algorithms based on this understanding and potentially use the new sensor information as an input signal. A case study which explores such a possibility is included.

The Texas A&M University Formula SAE program currently has no rigorous method for analyzing or predicting the overall dynamic behavior of the student-designed racecars. The objective of this study is to fulfill this need by creating a full vehicle ADAMS/Car model incorporating an empirical tire-road force model and validating the longitudinal performance of the model by using vehicle responses recorded at the track. Creating the model requires measuring mass and inertia properties for each part, measuring the locations of all the kinematic joints, testing the Risse Racing Jupiter-5 shocks to characterize damping and stiffness, measuring engine torque, and modeling the tire behavior. Measuring the vehicle performance requires installation of the Pi Research DataBuddy data acquisition system and appropriate sensors. The 2002 Texas A&M University Formula SAE racecar, the subject vehicle, was selected because it already included some accommodations for sensors and is almost identical in layout to the available ADAMS/Car model Formula SAE templates. The tire-road interface is described by the Pacejka ??94 handling force model within ADAMS/Car that is based on a set of Goodyear coefficients. The majority of the error in the model originated from the Goodyear tire model and the 2004 engine torque map. The testing used Hoosier tires and the 2002 engine intake and exhaust configuration. The deliverable is a full vehicle model of the 2002 racecar with a 2004 engine torque map and a tire model correlated to longitudinal performance recorded at the track using the installed data acquisition system. The results of the correlation process, confirmed by driver impressions and performance of the 2004 racecar, show that the 2004 engine torque map predicts higher performance than the measured response with the 2002 engine. The Hoosier tire on the Texas A&M University Riverside Campus track surface produces 75??3% of peak longitudinal tire performance predicted by the Goodyear tire model combined with a road surface friction coefficient of 1.0. The ADAMS/Car model can now support the design process as an analysis tool for full vehicle dynamics and with continued refinement, will be able to accurately predict behavior throughout a complete autocross course.

This theasis deals with modeling dynamics and visualization of experimental vehicle CAR4 in software V-REP. The first part shows introduction with V-REP and its possibilities for usage in simulations. The second part presents modelling of CAR4 vehicle and its control by using software V-REP and Matlab. In last part are models of vehicle tested in simulation

The aim of the diploma thesis is the design of mechanical parts of the rear axle driveline suitable for rebuilding of a given sports car into an electric car. The introductory part briefly explains the physical principles of the drive and contains a brief summary of the current concepts of electric vehicle propulsion. Afterwards, there is a comparison and selection of a suitable concept for a given electric vehicle, determination of the basic vehicle parameters based on the calculation of the longitudinal vehicle dynamics and the gearbox calculation on the basis of which the design is solved. The next part is dedicated to the computational inspection of parts using the finite element method. The final part deals with the placement of the assembly inside the vehicle and the evaluation of the drive mechanism.

Thesis (Ph. D.)--University of California, San Diego, 2006.<br>Title from first page of PDF file (viewed July 10, 2006). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 159-171).

The subject of the present licentiate thesis is density functional theorybased electronic structure calculations of organic thermoelectric materials and novel organic molecules. We used the Car-Parrinello molecular dynamics method in order to investigate the electronic structure of “green energy” and “greenchemistry” compounds. First, we have investigated the electronic structure of the poly(3,4-ethylene-dioxythiophene) (PEDOT) and its derivatives - the best studied and successfully implemented by industry organic thermoelectric material. Its transparency, low toxicity and high stability in the oxidized state are combined withan ability to produce electrical current when applying a temperature gradient. This makes PEDOT a perfect “organic metal” and a first candidate for organic thermoelectrogenerators - devices that can produce “green energy” from a temperature difference. The average structures found in these quantum dynamical simulations agree well with earlier static electronic structure studies. The energy gap of two, four and six unit oligomers of PEDOT was calculated and was found to lie in the range of previous theoretical studies. We have also calculatedthe point-charge distributions along the polymer backbone in order to investigate the polaron formed by doping agents of PEDOT. Our analysis allowed us to predict possible localization of the charge in the center of the polymer chain. However, further calculations of the twelve unit PEDOT and its selenium and tellurium derivatives will provide more information. First-principles calculations for the tellurium derivative of PEDOT are here presented for the first time. The second part of our investigation concerns theoretical calculations of novel piperidine-containing acetylene glycols. These molecules were newly synthesized by our experimental collaborators and are expected to provideplant growth stimulation properties, the same as its diacetylene analogs. We performed quantum mechanical calculations of four compounds, presented ananalysis of the highest occupied and lowest unoccupied molecular orbitals and collected detailed information on point-charges for further parametrization of novel molecules for future computational studies. According to these results, the low production yield found in the experiments cannot be attributed to chemical instability in these novel compounds.<br><p>QC 20150629</p><br>ScalTEG SSF

The Integrated Vehicle Dynamics Control (IVDC) concept can influence the vehicle behaviour both longitudinally and laterally with just one upper level control concept and further lower level controllers. This demands for state estimation of the vehicle which also includes estimating parameters of interest for the vehicle dynamicist. The approach to this research is firstly in developing a robust unscented Kalman filter (UKF) estimator for the vehicle side slip tracking and also for cornering stiffness estimation which is then fed to the existing model predictive control allocation (MPCA) controller to enhance the lateral stability of the vehicle for the different manoeuvres studied. Based on these developments, two types of filters are created. One with adaption of distance between center of gravity (COG) and roll center height and another without adaption. The key factor in the estimator development is the time adaptive process covariance matrix for the cornering stiffnesses, with which only the initial values have to be parameterised. Combining this research encompasses effective and adaptive method for a better quality of estimation with a kinematic vehicle model which behaves like a real world vehicle, at least virtually.This study is carried out with the understanding of various optimal estimators, parametric sensitivity analysis and statistical inferences, facilitating a base for robust estimation. Keywords: kalametric, state estimation, design matrix, aliasing, kalman filter, projection algorithm, resolution<br>Konceptet Integrated Vehicle Dynamics Control (IVDC) kan påverka fordonets beteende både longitudinellt och lateralt med bara ett regler koncept iett övre lager och ytterligare regulatorer på lägre nivåer. Detta kräver tillståndsuppskattning av fordonet som också inkluderar uppskattning av parametrar av intresse för en fordonsdynamiker. Tillvägagångssättet för denna studie är för det första att utveckla en robust tillståndsestimering med hjälp av ett Unscented Kalman Filter (UKF) för att uppskatta ett fordons avdriftsvinkel och även för uppskattning av ett däcks sidkraftskoefficient, vilket sedan används i den befintliga modell-prediktiva regleralgoritmen (MPCA) för att förbättra lateralstabiliteten hos fordonet för de olika studerade manövrarna. Baserat på denna utveckling skapades två typer av filter, ett med anpassning av avståndet mellan tyngdpunkten (COG) och krängcentrumhöjden och ett annat utan anpassning. Nyckelfaktorn i estimeringsutvecklingen är den tidsberoende adaptiva inställningenav processkovariansmatrisen för sidkraftskoefficienterna, med vilken endast de initiala värdena behöver parametriseras. Efter filterutvecklingen identifieras parametrar baserade på en förväntad kundanvändning och en statistisk variansanalys (ANOVA) utförs för att bestämma de mest inflytelserika faktorerna i gruppen. En parameteroptimering utförs för att förbättra uppskattningskvaliteten. Kombinationen av detta arbete omfattar en effektiv och anpassningsbar metod för en bättre uppskattningskvalitet med en kinematisk fordonsmodell som har en fordonsrespons som ett verkligt fordon, åtminstone praktiskt taget. Denna studie har genomförts med förståelse för olika optimala estimatorer, parametrisk känslighetsanalys och statistiska slutsatser, vilket underlättaren bas för robust uppskattning. Nyckelord: kalametric, tillståndsestimering, designmatris, vikningsdistorsion, kalmanfilter,projection algorithm, upplösning

With the growing complexity of vehicle control systems it is becoming increasingly important to understand the interaction between drivers and vehicles. Existing driver models do not adequately characterise limitations resulting from drivers’ physical systems. In particular, sensory dynamics limit the ability of drivers to perceive the states of real or simulated vehicles. Therefore, the aim of this thesis is to understand the impact of sensory dynamics on the control performance of a human driver in real and virtual environments. A new model of driver steering control is developed based on optimal control and state estimation theory, incorporating models of sensory dynamics, delays and noise. Some results are taken from published literature, however recent studies have shown that sensory delays and noise amplitudes may increase during an active control task such as driving. Therefore, a parameter identification procedure is used to fit the model predictions to measured steering responses of real drivers in a simulator. The model is found to fit measured results well under a variety of conditions. An initial experiment is designed with the physical motion of the simulator matching the motion of the virtual vehicle at full scale. However, during more realistic manoeuvres the physical motion must be scaled or filtered, introducing conflicts between measurements from different sensory systems. Drivers are found to adapt to simple conflicts such as scaled motion, but they have difficulty adapting to more complicated motion filters. The driver model is initially derived for linear vehicles with stochastic target and disturbance signals. In later chapters it is extended to account for transient targets and disturbances and vehicles with nonlinear tyres, and validated once again with experimental results. A series of simulations is used to demonstrate novel insights into how drivers use sensory information, and the resulting impact on control performance. The new model is also shown to predict difficulties real drivers have controlling unstable vehicles more reliably than existing driver models.

For controller design, design of experiments, and other dynamic simulation purposes there is a need to be able to predict the dynamic response and joint reaction forces of a quarter-car suspension. This need is addressed by this study through development and system identification of both a linear and a non-linear multibody dynamics McPherson strut quarter-car suspension model. Both models are developed using a method customary to multibody dynamics so that the same numerical integrator can be used to compare their respective performances. This method involves using the Lagrange multiplier form of the constrained equations of motion to assemble a set of differential algebraic equations that characterize each modelâ s dynamic response. The response of these models to a band-limited random tire displacement time array is then simulated using a Hilber-Hughes-Taylor integrator. The models are constructed to match the dynamic response of a state-of-the-art quarter-car test rig that was designed, constructed, and installed at the Institute for Advanced Learning and Research (IALR) for the Performance Engineering Research Lab (PERL). Attached to the experimental quarter-car rig was the front left McPherson strut suspension from a 2004 Porsche 996 Grand American Cup GS Class race car. This quarter-car rig facilitated acquisition of the experimental reference data to which the simulated data is compared. After developing these models their optimal parameters are obtained by performing system identification. The performance of both models using their respective optimal parameters is presented and discussed in the context of the basic linearity of the experimental suspension. Additionally, a method for estimating the loads applied to the experimental quarter-car rig bearings is developed. Finally, conclusions and recommendations for future research and applications are presented.<br>Master of Science

Thesis (Ph. D.)--University of California, San Diego, 2010.<br>Title from first page of PDF file (viewed June 23, 2010). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (leaves 177-192).

Thesis (Ph. D.)--University of Oregon, 2001.<br>Typescript. Includes vita and abstract. Includes bibliographical references (leaves 119-130). Also available for download via the World Wide Web; free to University of Oregon users.

Thesis (Ph. D.)--University of Oregon, 2003.<br>Typescript. Includes vita and abstract. Includes bibliographical references (leaves 253-263). Also available for download via the World Wide Web; free to University of Oregon users.

Biomolecular systems, in particular those involving proteins and their constituents, have been the focus of much research in the last century. The relationship between experiment, development of models and simulation has enabled vast improvements in our knowledge of subjects such as protein folding and the processes by which key biomolecules affect the human body. In particular, vital information can be obtained from understanding the building blocks of polypeptides and proteins involved in these processes. This work focuses on simulating two such building blocks; glutamate, the salt of the proteinogenic amino acid, glutamic acid, and glycine-proline-glutamate, or GPE, a related tripeptide. Both are important in neurotransmission processes in the brain. Glutamate is the most abundant neurotransmitter in the central nervous system and GPE is an important neuroprotective agent. This work aims to elucidate the key structural properties of aqueous solutions of glutamate and GPE, focusing on the solute-solute as well as the solute-solvent interactions. Both systems were considered with classical empirical potentials using the CHARMM22 force-fi eld. The glutamate system has also been studied using Car-Parrinello Molecular Dynamics and classical parallel tempering. In both the aqueous glutamate and GPE systems the molecules formed a large proportion of bifurcated bonding motifs with both carboxyl groups, but not with the amin (N-terminal) of the molecules. Bifurcated bonds form between solute molecules as well as in the solute-solvent interactions. The structure of the glutamate solution was found to be dependent on the initial con figuration and thus the parallel tempering simulations enabled better sampling of the conformational landscape. In addition, in the glutamate system single water molecules form a stable structure by bonding to both the amine (N-terminal) and C -carboxyl within the same glutamate molecule.

Connected vehicles is a growing market. There are currently several such services available, but many of them are constrained in the sense that they are bound to recently produced cars and either expensive or strongly limited in the services that they provide. In this master thesis we investigate the possibility to implement a generic platform that is of low cost and simple to install in any vehicle, but that still has the ability to provide a wide range of services. It is proposed that a crucial step in such a system is to reconstruct the vehicle’s kinematics, as this enables the possibility to developed a wide range of services by feature extraction and interpret the result from a dynamics perspective. A mathematical model that describes how the kinematics can be reconstructed is proposed, and a filter that performs such reconstruction is implemented. Based on this reconstruction, two filters that interpret the output are implemented as a proof of concept for the proposed mathematical model. The complete implemented filter solution is tested on measurement data from actual driving scenarios and it is seen that we can identify when the vehicle makes a hard turn, and find where the surrounding road conditions are poor.<br>Uppkopplade fordon är en växande marknad. I dagsläget finns flera sådana tjänster, men ofta är dessa begränsade i den meningen att de antingen endast finns tillgängliga för nyproducerade fordon eller bara erbjuder ett smalt utbud av tjänster. I detta examensarbete undersöker vi möjligheten att utveckla en generisk plattform för uppkopplade fordon som är billig och enkel att installera, men som också kan erbjuda ett stort urval av tjänster. Det föreslås att ett viktigt steg i en sådan lösning är att rekonstruera fordonets kinematik, då detta möjliggör utvecklandet av ett brett urval av tjänster genom att identifiera karakteristiska egenskaper i kinematiken, samt göra tolkningar utifrån dynamikbetraktelser. En matematisk modell för att beskriva hur kinematiken kan rekonstrueras från givna indata presenteras, och ett filter som utför denna rekonstruktion implementeras. Ytterligare två filter implementeras för att påvisa att den rekonstruerade kinematiken samt den föreslagna matematiska modellen kan användas till att identifiera olika scenarion ur verkligheten. Den kompletta filterlösningen testas på mätdata från faktiska körningar och vi ser att vi kan identifiera när fordonet gör skarpa svängar, samt när vägförhållandena är dåliga.

ABSTRACT DESIGN OF A MECHANISM FOR OPENING HACTHBACK CAR BAGGAGE DOOR Duran, Yusuf M.S., Department of Mechanical Engineering Supervisor: Prof. Dr. Eres S&ouml<br>ylemez September 2009, 65 Pages In this thesis, a new mechanism design for opening hatchback-car baggage door is introduced. Unlike the classical hinged doors used, this new design will include a mechanism so that the door will be opened vertically and thus occupy less space behind the car during the opening. In this fashion even the hatchback doors of closely parked cars may be opened. First, considering type synthesis, different mechanism types are investigated. In dimensional synthesis, with the help of Burmester theory, motion generation is applied. Using the circle and center point curves, considering link dimensions, transmission angle characteristics, branching and some order issues possible solutions that satisfy the position requirements are found. To actuate the mechanism, an appropriate gas-spring is sought. As a case study a prototype is manufactured and mounted on a sample hatchback car to check the mechanism performance.