979 resultados para Automotive 3D modeling


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The objective of this research is to synthesize structural composites designed with particular areas defined with custom modulus, strength and toughness values in order to improve the overall mechanical behavior of the composite. Such composites are defined and referred to as 3D-designer composites. These composites will be formed from liquid crystalline polymers and carbon nanotubes. The fabrication process is a variation of rapid prototyping process, which is a layered, additive-manufacturing approach. Composites formed using this process can be custom designed by apt modeling methods for superior performance in advanced applications. The focus of this research is on enhancement of Young's modulus in order to make the final composite stiffer. Strength and toughness of the final composite with respect to various applications is also discussed. We have taken into consideration the mechanical properties of final composite at different fiber volume content as well as at different orientations and lengths of the fibers. The orientation of the LC monomers is supposed to be carried out using electric or magnetic fields. A computer program is modeled incorporating the Mori-Tanaka modeling scheme to generate the stiffness matrix of the final composite. The final properties are then deduced from the stiffness matrix using composite micromechanics. Eshelby's tensor, required to calculate the stiffness tensor using Mori-Tanaka method, is calculated using a numerical scheme that determines the components of the Eshelby's tensor (Gavazzi and Lagoudas 1990). The numerical integration is solved using Gaussian Quadrature scheme and is worked out using MATLAB as well. . MATLAB provides a good deal of commands and algorithms that can be used efficiently to elaborate the continuum of the formula to its extents. Graphs are plotted using different combinations of results and parameters involved in finding these results

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The Pleistocene carbonate rock Biscayne Aquifer of south Florida contains laterally-extensive bioturbated ooltic zones characterized by interconnected touching-vug megapores that channelize most flow and make the aquifer extremely permeable. Standard petrophysical laboratory techniques may not be capable of accurately measuring such high permeabilities. Instead, innovative procedures that can measure high permeabilities were applied. These fragile rocks cannot easily be cored or cut to shapes convenient for conducting permeability measurements. For the laboratory measurement, a 3D epoxy-resin printed rock core was produced from computed tomography data obtained from an outcrop sample. Permeability measurements were conducted using a viscous fluid to permit easily observable head gradients (~2 cm over 1 m) simultaneously with low Reynolds number flow. For a second permeability measurement, Lattice Boltzmann Method flow simulations were computed on the 3D core renderings. Agreement between the two estimates indicates an accurate permeability was obtained that can be applied to future studies.

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The research activities involved the application of the Geomatic techniques in the Cultural Heritage field, following the development of two themes: Firstly, the application of high precision surveying techniques for the restoration and interpretation of relevant monuments and archaeological finds. The main case regards the activities for the generation of a high-fidelity 3D model of the Fountain of Neptune in Bologna. In this work, aimed to the restoration of the manufacture, both the geometrical and radiometrical aspects were crucial. The final product was the base of a 3D information system representing a shared tool where the different figures involved in the restoration activities shared their contribution in a multidisciplinary approach. Secondly, the arrangement of 3D databases for a Building Information Modeling (BIM) approach, in a process which involves the generation and management of digital representations of physical and functional characteristics of historical buildings, towards a so-called Historical Building Information Model (HBIM). A first application was conducted for the San Michele in Acerboli’s church in Santarcangelo di Romagna. The survey was performed by the integration of the classical and modern Geomatic techniques and the point cloud representing the church was used for the development of a HBIM model, where the relevant information connected to the building could be stored and georeferenced. A second application regards the domus of Obellio Firmo in Pompeii, surveyed by the integration of the classical and modern Geomatic techniques. An historical analysis permitted the definitions of phases and the organization of a database of materials and constructive elements. The goal is the obtaining of a federate model able to manage the different aspects: documental, analytic and reconstructive ones.

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Today, the contribution of the transportation sector on greenhouse gases is evident. The fast consumption of fossil fuels and its impact on the environment has given a strong impetus to the development of vehicles with better fuel economy. Hybrid electric vehicles fit into this context with different targets, starting from the reduction of emissions and fuel consumption, but also for performance and comfort enhancement. Vehicles exist with various missions; super sport cars usually aim to reach peak performance and to guarantee a great driving experience to the driver, but great attention must also be paid to fuel consumption. According to the vehicle mission, hybrid vehicles can differ in the powertrain configuration and the choice of the energy storage system. Lamborghini has recently invested in the development of hybrid super sport cars, due to performance and comfort reasons, with the possibility to reduce fuel consumption. This research activity has been conducted as a joint collaboration between the University of Bologna and the sportscar manufacturer, to analyze the impact of innovative energy storage solutions on the hybrid vehicle performance. Capacitors have been studied and modeled to analyze the pros and cons of such solution with respect to batteries. To this aim, a full simulation environment has been developed and validated to provide a concept design tool capable of precise results and able to foresee the longitudinal performance on regulated emission cycles and real driving conditions, with a focus on fuel consumption. In addition, the target of the research activity is to deepen the study of hybrid electric super sports cars in the concept development phase, focusing on defining the control strategies and the energy storage system’s technology that best suits the needs of the vehicles. This dissertation covers the key steps that have been carried out in the research project.

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This thesis deals with optimization techniques and modeling of vehicular networks. Thanks to the models realized with the integer linear programming (ILP) and the heuristic ones, it was possible to study the performances in 5G networks for the vehicular. Thanks to Software-defined networking (SDN) and Network functions virtualization (NFV) paradigms it was possible to study the performances of different classes of service, such as the Ultra Reliable Low Latency Communications (URLLC) class and enhanced Mobile BroadBand (eMBB) class, and how the functional split can have positive effects on network resource management. Two different protection techniques have been studied: Shared Path Protection (SPP) and Dedicated Path Protection (DPP). Thanks to these different protections, it is possible to achieve different network reliability requirements, according to the needs of the end user. Finally, thanks to a simulator developed in Python, it was possible to study the dynamic allocation of resources in a 5G metro network. Through different provisioning algorithms and different dynamic resource management techniques, useful results have been obtained for understanding the needs in the vehicular networks that will exploit 5G. Finally, two models are shown for reconfiguring backup resources when using shared resource protection.

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This thesis focuses on finding the optimum block cutting dimensions in terms of the environmental and economic factors by using a 3D algorithm for a limestone quarry in Foggia, Italy. The environmental concerns of quarrying operations are mainly: energy consumption, material waste, and pollution. The main economic concerns are the block recovery, the selling prices, and the production costs. Fractures adversely affect the block recovery ratio. With a fracture model, block production can be optimized. In this research, the waste volume produced by quarrying was minimised to increase the recovery ratio and ensure economic benefits. SlabCutOpt is a software developed at DICAM–University of Bologna for block cutting optimization which tests different cutting angles on the x-y-z planes to offer up alternative cutting methods. The program tests several block sizes and outputs the optimal result for each entry. By using SlabCutOpt, ten different block dimensions were analysed, the results indicated the maximum number of non-intersecting blocks for each dimension. After analysing the outputs, the block named number 1 with the dimensions ‘1mx1mx1m’ had the highest recovery ratio as 43% and the total Relative Money Value (RMV) with a value of 22829. Dimension number 1, also had the lowest waste volume, with a value of 3953.25 m3, for the total bench. For cutting the total bench volume of 6932.25m3, the diamond wire cutter had the lowest dust emission values for the block with the dimension ‘2mx2mx2m’, with a value of 24m3. When compared with the Eco-Label standards, block dimensions having surface area values lower than 15m2, were found to fit the natural resource waste criteria of the label, as the threshold required 25% of minimum recovery [1]. Due to the relativity of production costs, together with the Eco-Label threshold, the research recommends the selection of the blocks with a surface area value between 6m2 and 14m2.

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Building Information Modelling is changing the design and construction field ever since it entered the market. It took just some time to show its capabilities, it takes some time to be mastered before it could be used expressing all its best features. Since it was conceived to be adopted from the earliest stage of design to get the maximum from the decisional project, it still struggles to adapt to existing buildings. In fact, there is a branch of this methodology that is dedicated to what has been already made that is called Historic BIM or HBIM. This study aims to make clear what are BIM and HBIM, both from a theoretical point of view and in practice, applying from scratch the state of the art to a case study. It had been chosen the fortress of San Felice sul Panaro, a marvellous building with a thousand years of history in its bricks, that suffered violent earthquakes, but it is still standing. By means of this example, it will be shown which are the limits that could be encountered when applying BIM methodology to existing heritage, moreover will be pointed out all the new features that a simple 2D design could not achieve.

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A fianco ai metodi più tradizionali, fin ora utilizzati, le tecnologie additive hanno subito negli ultimi anni una notevole evoluzione nella produzione di componenti. Esse permettono un ampio di range di applicazioni utilizzando materiali differenti in base al settore di applicazione. In particolare, la stampa 3D FDM (Fused Deposition Modeling) rappresenta uno dei processi tecnologici additivi più diffusi ed economicamente più competitivi. Gli attuali metodi di analisi agli elementi finiti (FEM) e le tecnologie CAE (Computer-Aided Engineering) non sono in grado di studiare modelli 3D di componenti stampati, dal momento che il risultato finale dipende dai parametri di processo e ambientali. Per questo motivo, è necessario uno studio approfondito della meso struttura del componente stampato per estendere l’analisi FEM anche a questa tipologia di componenti. Lo scopo del lavoro proposto è di creare un elemento omogeneo che rappresenti accuratamente il comportamento di un componente realizzato in stampa 3D FDM, questo avviene attraverso la definizione e l’analisi di un volume rappresentativo (RVE). Attraverso la tecnica dell’omogeneizzazione, il volume definito riassume le principali caratteristiche meccaniche della struttura stampata, permettendo nuove analisi e ottimizzazioni. Questo approccio permette di realizzare delle analisi FEM sui componenti da stampare e di predire le proprietà meccaniche dei componenti a partire da determinati parametri di stampa, permettendo così alla tecnologia FDM di diventare sempre di più uno dei principali processi industriali a basso costo.

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The microstructure of 6XXX aluminum alloys deeply affects mechanical, crash, corrosion and aesthetic properties of extruded profiles. Unfortunately, grain structure evolution during manufacturing processes is a complex phenomenon because several process and material parameters such as alloy chemical composition, temperature, extrusion speed, tools geometries, quenching and thermal treatment parameters affect the grain evolution during the manufacturing process. The aim of the present PhD thesis was the analysis of the recrystallization kinetics during the hot extrusion of 6XXX aluminum alloys and the development of reliable recrystallization models to be used in FEM codes for the microstructure prediction at a die design stage. Experimental activities have been carried out in order to acquire data for the recrystallization models development, validation and also to investigate the effect of process parameters and die design on the microstructure of the final component. The experimental campaign reported in this thesis involved the extrusion of AA6063, AA6060 and AA6082 profiles with different process parameters in order to provide a reliable amount of data for the models validation. A particular focus was made to investigate the PCG defect evolution during the extrusion of medium-strength alloys such as AA6082. Several die designs and process conditions were analysed in order to understand the influence of each of them on the recrystallization behaviour of the investigated alloy. From the numerical point of view, innovative models for the microstructure prediction were developed and validated over the extrusion of industrial-scale profiles with complex geometries, showing a good matching in terms of the grain size and surface recrystallization prediction. The achieved results suggest the reliability of the developed models and their application in the industrial field for process and material properties optimization at a die-design stage.

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The field of bioelectronics involves the use of electrodes to exchange electrical signals with biological systems for diagnostic and therapeutic purposes in biomedical devices and healthcare applications. However, the mechanical compatibility of implantable devices with the human body has been a challenge, particularly with long-term implantation into target organs. Current rigid bioelectronics can trigger inflammatory responses and cause unstable device functions due to the mechanical mismatch with the surrounding soft tissue. Recent advances in flexible and stretchable electronics have shown promise in making bioelectronic interfaces more biocompatible. To fully achieve this goal, material science and engineering of soft electronic devices must be combined with quantitative characterization and modeling tools to understand the mechanical issues at the interface between electronic technology and biological tissue. Local mechanical characterization is crucial to understand the activation of failure mechanisms and optimizing the devices. Experimental techniques for testing mechanical properties at the nanoscale are emerging, and the Atomic Force Microscope (AFM) is a good candidate for in situ local mechanical characterization of soft bioelectronic interfaces. In this work, in situ experimental techniques with solely AFM supported by interpretive models for the characterization of planar and three-dimensional devices suitable for in vivo and in vitro biomedical experimentations are reported. The combination of the proposed models and experimental techniques provides access to the local mechanical properties of soft bioelectronic interfaces. The study investigates the nanomechanics of hard thin gold films on soft polymeric substrates (Poly(dimethylsiloxane) PDMS) and 3D inkjet-printed micropillars under different deformation states. The proposed characterization methods provide a rapid and precise determination of mechanical properties, thus giving the possibility to parametrize the microfabrication steps and investigate their impact on the final device.

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Gaze estimation has gained interest in recent years for being an important cue to obtain information about the internal cognitive state of humans. Regardless of whether it is the 3D gaze vector or the point of gaze (PoG), gaze estimation has been applied in various fields, such as: human robot interaction, augmented reality, medicine, aviation and automotive. In the latter field, as part of Advanced Driver-Assistance Systems (ADAS), it allows the development of cutting-edge systems capable of mitigating road accidents by monitoring driver distraction. Gaze estimation can be also used to enhance the driving experience, for instance, autonomous driving. It also can improve comfort with augmented reality components capable of being commanded by the driver's eyes. Although, several high-performance real-time inference works already exist, just a few are capable of working with only a RGB camera on computationally constrained devices, such as a microcontroller. This work aims to develop a low-cost, efficient and high-performance embedded system capable of estimating the driver's gaze using deep learning and a RGB camera. The proposed system has achieved near-SOTA performances with about 90% less memory footprint. The capabilities to generalize in unseen environments have been evaluated through a live demonstration, where high performance and near real-time inference were obtained using a webcam and a Raspberry Pi4.

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A fianco ai metodi più tradizionali, fin ora utilizzati, le tecnologie additive hanno subito negli ultimi anni una notevole evoluzione nella produzione di componenti. Esse permettono un ampio di range di applicazioni utilizzando materiali differenti in base al settore di applicazione. In particolare, la stampa 3D FDM (Fused Deposition Modeling) rappresenta uno dei processi tecnologici additivi più diffusi ed economicamente più competitivi. Le tempistiche e le richieste industriali obbligano sempre di più i progettisti ad uno studio predittivo delle problematiche che si possono incontrare in fare produttiva. In ambito strutturale questo è già da diversi anni la norma per componenti realizzati con tecnologia tradizionale. In ambito termico, invece, si procede ancora troppo spesso per tentativi seguendo l’esperienza del singolo. Per questo motivo, è necessario uno studio approfondito e un metodo per caratterizzare i transitori termici. Per fare ciò è necessario introdurre un modello semplificativo attraverso l’uso su un provino cilindrico. Questa semplice geometria permette di mettere in relazione la soluzione analitica, la soluzione approssimata agli elementi finiti e la soluzione sperimentale. Una volta ottenuti questi risultati sarà poi possibile, mantenendo invariati il ciclo termico e le caratteristiche termo-strutturali del materiale, modificare a piacimento la geometria per analizzare un qualsiasi componente. Questo approccio permette quindi di realizzare delle analisi FEM sui componenti da stampare e di predirne i gradienti termici e le deformazioni a partire dalle caratteristiche del materiale, della geometria e del ciclo termico a cui sono sottoposti. Permettendo così di valutare in modo preventivo e predittivo problematiche di stabilità geometrica e strutturale.

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In this study, the transmission-line modeling (TLM) applied to bio-thermal problems was improved by incorporating several novel computational techniques, which include application of graded meshes which resulted in 9 times faster in computational time and uses only a fraction (16%) of the computational resources used by regular meshes in analyzing heat flow through heterogeneous media. Graded meshes, unlike regular meshes, allow heat sources to be modeled in all segments of the mesh. A new boundary condition that considers thermal properties and thus resulting in a more realistic modeling of complex problems is introduced. Also, a new way of calculating an error parameter is introduced. The calculated temperatures between nodes were compared against the results obtained from the literature and agreed within less than 1% difference. It is reasonable, therefore, to conclude that the improved TLM model described herein has great potential in heat transfer of biological systems.

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American tegumentary leishmaniasis (ATL) is a disease transmitted to humans by the female sandflies of the genus Lutzomyia. Several factors are involved in the disease transmission cycle. In this work only rainfall and deforestation were considered to assess the variability in the incidence of ATL. In order to reach this goal, monthly recorded data of the incidence of ATL in Orán, Salta, Argentina, were used, in the period 1985-2007. The square root of the relative incidence of ATL and the corresponding variance were formulated as time series, and these data were smoothed by moving averages of 12 and 24 months, respectively. The same procedure was applied to the rainfall data. Typical months, which are April, August, and December, were found and allowed us to describe the dynamical behavior of ATL outbreaks. These results were tested at 95% confidence level. We concluded that the variability of rainfall would not be enough to justify the epidemic outbreaks of ATL in the period 1997-2000, but it consistently explains the situation observed in the years 2002 and 2004. Deforestation activities occurred in this region could explain epidemic peaks observed in both years and also during the entire time of observation except in 2005-2007.

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In this work, all publicly-accessible published findings on Alicyclobacillus acidoterrestris heat resistance in fruit beverages as affected by temperature and pH were compiled. Then, study characteristics (protocols, fruit and variety, °Brix, pH, temperature, heating medium, culture medium, inactivation method, strains, etc.) were extracted from the primary studies, and some of them incorporated to a meta-analysis mixed-effects linear model based on the basic Bigelow equation describing the heat resistance parameters of this bacterium. The model estimated mean D* values (time needed for one log reduction at a temperature of 95 °C and a pH of 3.5) of Alicyclobacillus in beverages of different fruits, two different concentration types, with and without bacteriocins, and with and without clarification. The zT (temperature change needed to cause one log reduction in D-values) estimated by the meta-analysis model were compared to those ('observed' zT values) reported in the primary studies, and in all cases they were within the confidence intervals of the model. The model was capable of predicting the heat resistance parameters of Alicyclobacillus in fruit beverages beyond the types available in the meta-analytical data. It is expected that the compilation of the thermal resistance of Alicyclobacillus in fruit beverages, carried out in this study, will be of utility to food quality managers in the determination or validation of the lethality of their current heat treatment processes.