881 resultados para large course design


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The establishment of support platforms for the development of a new culture in design education, in order to achieve both research exploitation and its results, as an approach to the industrial community, challenges higher education institutions to rethink their functioning, divided between investigation on their own initiative or on demand, and its usefulness / practical application. At the same time, through design education, how can they be the engine that aggregates all these frequently antagonistic interests? Polytechnic institutes are predisposed to collaboration and interdisciplinarity. In our course of Technology and Design of Furniture, the availability of a production unit, testing laboratories, and expertise in engineering, design and marketing, encourage the development of a holistic project. In order to develop such knowledge, we adapt three important ways of thinking in designing interactions influenced by the traditional approach, namely, 1) identifying and understanding a design problem, i.e. a market need, 2) defining the design process and knowing what can be used for design education, i.e. opportunities for design education, and 3) sustainability of this framework and design projects' alignment with education in the same field. We explain our approach by arguing from the academicenterprise experiences perspective. This concept is proposed as a way to achieve those three ways of thinking in design education. Then, a set of interaction attributes is defined to explain how engineering and product design education can enhance meaningful relations with manufacturers, stakeholders and society in general. A final discussion is presented with the implications and benefits of this approach. The results suggest that through academic-enterprise partnerships in design, several goals such as students' motivation, product design innovation and potential for knowledge transfer to industries can be achieved.

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Metal oxide protection layers for photoanodes may enable the development of large-scale solar fuel and solar chemical synthesis, but the poor photovoltages often reported so far will severely limit their performance. Here we report a novel observation of photovoltage loss associated with a charge extraction barrier imposed by the protection layer, and, by eliminating it, achieve photovoltages as high as 630mV, the maximum reported so far for water-splitting silicon photoanodes. The loss mechanism is systematically probed in metal-insulator-semiconductor Schottky junction cells compared to buried junction p(+) n cells, revealing the need to maintain a characteristic hole density at the semiconductor/insulator interface. A leaky-capacitor model related to the dielectric properties of the protective oxide explains this loss, achieving excellent agreement with the data. From these findings, we formulate design principles for simultaneous optimization of built-in field, interface quality, and hole extraction to maximize the photovoltage of oxide-protected water-splitting anodes.

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This essay addresses the hitches and glitches in the hybrid instruction system of teaching and learning for large-enrollment courses. This new instructional methodology asks facilitators to redesign their entire traditional teaching and learning practices. The nature of subject to be taught via the hybrid mode further affects the success rate of the modules from the time of inception to launch to actual delivery and completion of the course. The entire process involves undoing the old habits and methodologies and instructors picking up new skills, along with the right motivation to take up the task. The course planning and delivery require a substantial commitment in terms of hours from the instructors catering to large-enrollment courses, along with pursuing their routine roles at the campuses. From the pupil’s perspective, the response varies, as hybrid learning seeks self-discipline and time management skills from the learner. After the initial roadblocks, students enjoy hybrid learning if the course structure and instructions are simple and the course content flexible and varied. We will study the problems and possible solutions to the success of the hybrid teaching–learning system at each stage where large number of students enrolled for a specific course.

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Shearing is the process where sheet metal is mechanically cut between two tools. Various shearing technologies are commonly used in the sheet metal industry, for example, in cut to length lines, slitting lines, end cropping etc. Shearing has speed and cost advantages over competing cutting methods like laser and plasma cutting, but involves large forces on the equipment and large strains in the sheet material. The constant development of sheet metals toward higher strength and formability leads to increased forces on the shearing equipment and tools. Shearing of new sheet materials imply new suitable shearing parameters. Investigations of the shearing parameters through live tests in the production are expensive and separate experiments are time consuming and requires specialized equipment. Studies involving a large number of parameters and coupled effects are therefore preferably performed by finite element based simulations. Accurate experimental data is still a prerequisite to validate such simulations. There is, however, a shortage of accurate experimental data to validate such simulations. In industrial shearing processes, measured forces are always larger than the actual forces acting on the sheet, due to friction losses. Shearing also generates a force that attempts to separate the two tools with changed shearing conditions through increased clearance between the tools as result. Tool clearance is also the most common shearing parameter to adjust, depending on material grade and sheet thickness, to moderate the required force and to control the final sheared edge geometry. In this work, an experimental procedure that provides a stable tool clearance together with accurate measurements of tool forces and tool displacements, was designed, built and evaluated. Important shearing parameters and demands on the experimental set-up were identified in a sensitivity analysis performed with finite element simulations under the assumption of plane strain. With respect to large tool clearance stability and accurate force measurements, a symmetric experiment with two simultaneous shears and internal balancing of forces attempting to separate the tools was constructed. Steel sheets of different strength levels were sheared using the above mentioned experimental set-up, with various tool clearances, sheet clamping and rake angles. Results showed that tool penetration before fracture decreased with increased material strength. When one side of the sheet was left unclamped and free to move, the required shearing force decreased but instead the force attempting to separate the two tools increased. Further, the maximum shearing force decreased and the rollover increased with increased tool clearance. Digital image correlation was applied to measure strains on the sheet surface. The obtained strain fields, together with a material model, were used to compute the stress state in the sheet. A comparison, up to crack initiation, of these experimental results with corresponding results from finite element simulations in three dimensions and at a plane strain approximation showed that effective strains on the surface are representative also for the bulk material. A simple model was successfully applied to calculate the tool forces in shearing with angled tools from forces measured with parallel tools. These results suggest that, with respect to tool forces, a plane strain approximation is valid also at angled tools, at least for small rake angles. In general terms, this study provide a stable symmetric experimental set-up with internal balancing of lateral forces, for accurate measurements of tool forces, tool displacements, and sheet deformations, to study the effects of important shearing parameters. The results give further insight to the strain and stress conditions at crack initiation during shearing, and can also be used to validate models of the shearing process.

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The aim of this study was to identify how pitch area-restrictions affects the tactical behavior, physical and physiological performances of players during soccer large-sided games. A 10 vs. 9 large-sided game was performed under three experimental conditions: (i) restricted-spacing, the pitch was divided into specific areas where players were assigned and they should not leave it; (ii) contiguous-spacing, the pitch was divided into specific areas where the players were only allowed to move to a neighboring one; (iii) free-spacing, the players had no restrictions in space occupation. The positional data were used to compute players’ spatial exploration index and also the distance, coefficient of variation, approximate entropy and frequency of near-in-phase displacements synchronization of players’ dyads formed by the outfield teammates. Players’ physical and physiological performances were assessed by the distance covered at different speed categories, game pace and heart rate. Most likely higher values were found in players’ spatial exploration index under free-spacing conditions. The synchronization between dyads’ displacements showed higher values for contiguous-spacing and free-spacing conditions. In contrast, for the jogging and running intensity zones, restricted-spacing demanded a moderate effect and most likely decrease compared to other scenarios (~20-50% to jogging and ~60-90% to running). Overall, the effects of limiting players’ spatial exploration greatly impaired the co-adaptation between teammates’ positioning while decreasing the physical and physiological performances. These results allow for a better understanding of players’ decision-making process according to specific task rules and can be relevant to enrich practice task design, such that coaches acknowledge the differential effect by using specific pitch-position areas restrictions.

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The application of Computational Fluid Dynamics based on the Reynolds-Averaged Navier-Stokes equations to the simulation of bluff body aerodynamics has been thoroughly investigated in the past. Although a satisfactory accuracy can be obtained for some urban physics problems their predictive capability is limited to the mean flow properties, while the ability to accurately predict turbulent fluctuations is recognized to be of fundamental importance when dealing with wind loading and pollution dispersion problems. The need to correctly take into account the flow dynamics when such problems are faced has led researchers to move towards scale-resolving turbulence models such as Large Eddy Simulations (LES). The development and assessment of LES as a tool for the analysis of these problems is nowadays an active research field and represents a demanding engineering challenge. This research work has two objectives. The first one is focused on wind loads assessment and aims to study the capabilities of LES in reproducing wind load effects in terms of internal forces on structural members. This differs from the majority of the existing research, where performance of LES is evaluated only in terms of surface pressures, and is done with a view of adopting LES as a complementary design tools alongside wind tunnel tests. The second objective is the study of LES capabilities in calculating pollutant dispersion in the built environment. The validation of LES in this field is considered to be of the utmost importance in order to conceive healthier and more sustainable cities. In order to validate the numerical setup adopted, a systematic comparison between numerical and experimental data is performed. The obtained results are intended to be used in the drafting of best practice guidelines for the application of LES in the urban physics field with a particular attention to wind load assessment and pollution dispersion problems.

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Integrins are α/β-heterodimeric transmembrane adhesion receptors that mediate cell-cell and cell-ECM interactions. Integrins are bidirectional signalling receptors that respond to external signals (“outside-in” signalling) and in parallel, transduce internal signals to the matrix (“inside-out” signalling), to regulate vital cellular functions including migration, survival, growth and differentiation. Therefore, dysregulation of these tightly regulated processes often results in uncontrolled integrin activation and abnormal tissue expression that is responsible for many diseases. Because of their important roles in physiological and pathological events, they represent a validated target for therapeutic and diagnostic purposes. The aim of the present Thesis was focused on the development of peptidic ligands for α4β1 and αvβ3 integrin subtypes, involved in inflammatory responses (leukocytes recruitment and extravasation) and cancer progression (angiogenesis, tumor growth, metastasis), respectively. Following the peptidomimetic strategy, we designed and synthesized a small library of linear and cyclic hybrid α/β-peptidomimetics based on the phenylureido-LDV scaffolds for the treatment of chronic inflammatory autoimmune diseases. In order to implement a fast and non-invasive diagnostic method for monitoring the course of the inflammatory processes, a flat glass-surface of dye-loaded Zeolite L-crystal nanoparticles was coated with bioactive α4β1-peptidomimetics to detect specific integrin-expressing cells as biomarkers of inflammatory diseases. Targeted drug delivery has been considered a promising alternative to overcome the pharmacokinetic limitations of conventional anticancer drugs. Thus, a novel Small-Molecule Drug Conjugate was synthesized by connecting the highly cytotoxic Cryptophycin to the tumor-targeting RGDfK-peptide through a protease-cleavable linker. Finally, in view to making the peptide synthesis more sustainable and greener, we developed an alternative method for peptide bonds formation employing solvent-free mechanochemistry and ultra-mild minimal solvent-grinding conditions in common, inexpensive laboratory equipment. To this purpose, standard amino acids, coupling agents and organic-green solvents were used in the presence of nanocrystalline hydroxyapatite as a reusable, bio-compatible inorganic basic catalyst.

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Several decision and control tasks in cyber-physical networks can be formulated as large- scale optimization problems with coupling constraints. In these "constraint-coupled" problems, each agent is associated to a local decision variable, subject to individual constraints. This thesis explores the use of primal decomposition techniques to develop tailored distributed algorithms for this challenging set-up over graphs. We first develop a distributed scheme for convex problems over random time-varying graphs with non-uniform edge probabilities. The approach is then extended to unknown cost functions estimated online. Subsequently, we consider Mixed-Integer Linear Programs (MILPs), which are of great interest in smart grid control and cooperative robotics. We propose a distributed methodological framework to compute a feasible solution to the original MILP, with guaranteed suboptimality bounds, and extend it to general nonconvex problems. Monte Carlo simulations highlight that the approach represents a substantial breakthrough with respect to the state of the art, thus representing a valuable solution for new toolboxes addressing large-scale MILPs. We then propose a distributed Benders decomposition algorithm for asynchronous unreliable networks. The framework has been then used as starting point to develop distributed methodologies for a microgrid optimal control scenario. We develop an ad-hoc distributed strategy for a stochastic set-up with renewable energy sources, and show a case study with samples generated using Generative Adversarial Networks (GANs). We then introduce a software toolbox named ChoiRbot, based on the novel Robot Operating System 2, and show how it facilitates simulations and experiments in distributed multi-robot scenarios. Finally, we consider a Pickup-and-Delivery Vehicle Routing Problem for which we design a distributed method inspired to the approach of general MILPs, and show the efficacy through simulations and experiments in ChoiRbot with ground and aerial robots.

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Advancements in technology have enabled increasingly sophisticated automation to be introduced into the flight decks of modern aircraft. Generally, this automation was added to accomplish worthy objectives such as reducing flight crew workload, adding additional capability, or increasing fuel economy. Automation is necessary due to the fact that not all of the functions required for mission accomplishment in today’s complex aircraft are within the capabilities of the unaided human operator, who lacks the sensory capacity to detect much of the information required for flight. To a large extent, these objectives have been achieved. Nevertheless, despite all the benefits from the increasing amounts of highly reliable automation, vulnerabilities do exist in flight crew management of automation and Situation Awareness (SA). Issues associated with flight crew management of automation include: • Pilot understanding of automation’s capabilities, limitations, modes, and operating principles and techniques. • Differing pilot decisions about the appropriate automation level to use or whether to turn automation on or off when they get into unusual or emergency situations. • Human-Machine Interfaces (HMIs) are not always easy to use, and this aspect could be problematic when pilots experience high workload situations. • Complex automation interfaces, large differences in automation philosophy and implementation among different aircraft types, and inadequate training also contribute to deficiencies in flight crew understanding of automation.

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This guide is a comprehensive summary of how we went about creating Citizen Maths, an open online maths course and service. The guide shares our design principles and the techniques we used to put them into practice. Our aim is to provide – with the appropriate ‘translation’ – a resource that will be useful to to other teams who are developing online education initiatives.

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Power-to-Gas storage systems have the potential to address grid-stability issues that arise when an increasing share of power is generated from sources that have a highly variable output. Although the proof-of-concept of these has been promising, the behaviour of the processes in off-design conditions is not easily predictable. The primary aim of this PhD project was to evaluate the performance of an original Power-to-Gas system, made up of innovative components. To achieve this, a numerical model has been developed to simulate the characteristics and the behaviour of the several components when the whole system is coupled with a renewable source. The developed model has been applied to a large variety of scenarios, evaluating the performance of the considered process and exploiting a limited amount of experimental data. The model has been then used to compare different Power-to-Gas concepts, in a real scenario of functioning. Several goals have been achieved. In the concept phase, the possibility to thermally integrate the high temperature components has been demonstrated. Then, the parameters that affect the energy performance of a Power-to-Gas system coupled with a renewable source have been identified, providing general recommendations on the design of hybrid systems; these parameters are: 1) the ratio between the storage system size and the renewable generator size; 2) the type of coupled renewable source; 3) the related production profile. Finally, from the results of the comparative analysis, it is highlighted that configurations with a highly oversized renewable source with respect to the storage system show the maximum achievable profit.

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High Energy efficiency and high performance are the key regiments for Internet of Things (IoT) end-nodes. Exploiting cluster of multiple programmable processors has recently emerged as a suitable solution to address this challenge. However, one of the main bottlenecks for multi-core architectures is the instruction cache. While private caches fall into data replication and wasting area, fully shared caches lack scalability and form a bottleneck for the operating frequency. Hence we propose a hybrid solution where a larger shared cache (L1.5) is shared by multiple cores connected through a low-latency interconnect to small private caches (L1). However, it is still limited by large capacity miss with a small L1. Thus, we propose a sequential prefetch from L1 to L1.5 to improve the performance with little area overhead. Moreover, to cut the critical path for better timing, we optimized the core instruction fetch stage with non-blocking transfer by adopting a 4 x 32-bit ring buffer FIFO and adding a pipeline for the conditional branch. We present a detailed comparison of different instruction cache architectures' performance and energy efficiency recently proposed for Parallel Ultra-Low-Power clusters. On average, when executing a set of real-life IoT applications, our two-level cache improves the performance by up to 20% and loses 7% energy efficiency with respect to the private cache. Compared to a shared cache system, it improves performance by up to 17% and keeps the same energy efficiency. In the end, up to 20% timing (maximum frequency) improvement and software control enable the two-level instruction cache with prefetch adapt to various battery-powered usage cases to balance high performance and energy efficiency.

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This doctoral dissertation represents a cluster of research activities carried out at the DICAM Department of the University of Bologna during a three-year Ph.D. course. The goal of this research is to show how the development of an interconnected infrastructure network, aimed at promoting accessibility and sustainability of places, is fundamental in a framework of deep urban regeneration. Sustainable urban mobility plays an important role in improving the quality of life of citizens. From an environmental point of view, a sustainable mobility system means reducing fuel discharges and energy waste and, in general, aims to promote low carbon emissions. At the same time, a socially and economically sustainable mobility system should be accessible to everybody and create more job opportunities through better connectivity and mobility. Environmentally friendly means of transport such as non-motorized transport, electric vehicles, and hybrid vehicles play an important role in achieving sustainability but require a planned approach at the local policy level. The aim of this study is to demonstrate that, through a targeted reconnection of road and cycle-pedestrian routes, the quality of life of an urban area subject to degradation can be significantly improved just by increasing its accessibility and sustainability. Starting from a detailed study of the European policies and from the comparison with real similar cases, the case study of the Canal Port of Rimini (Italy) has been analysed within the European project FRAMESPORT. The analysis allowed the elaboration of a multicriterial methodology to get to the definition of a project proposal and of a priority scale of interventions. The applied methodology is a valuable tool that may be used in the future in similar urban contexts. Finally, the whole project was represented by using virtual reality to visually show the difference between the before and after the regeneration intervention.

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This PhD thesis summarize the work carried out during three years of PhD course. Several thematic concerning gold(I) chemistry are analysed by crossing data from different chemistry areas as: organic chemistry, organometallic chemistry, inorganic chemistry and computational chemistry. In particular, the thesis focuses its attention on the evaluation of secondary electronic interactions, subsisting between ligand and Au(I) metal centre in the catalyst, and their effects on catalytic activity. The interaction that has been taken in consideration is the Au…Ar π-interaction which is known to prevent the decomposition of catalyst, but exhaustive investigations of further effects has never been done so far. New libraries of carbene (ImPy) and biarylphosphine ligands have been designed and synthetized for the purpose and subsequently utilized for the synthesis of corresponding Au(I) complexes. Resulting catalysts are tested in various catalytic processes involving different intermediates and in combination with solid state information from SC-XRD revealed an unprecedented activation mode which is only explained by considering both electronic nature and strength of Au…Ar π-interaction. DFT calculation carried on catalysis intermediates are in agreement with experimental ones, giving robustness to the theory. Moreover, a new synthetic protocol for the lactonization of N-allenyl indole-2-carboxylic acids is presented. Reaction conditions are optimized with the newly synthetized ImPy-Au(I) catalysts and different substrates are also tested providing a quite broad reaction scope. Chiral ImPy ligands have also been developed for the asymmetric variant of the same reaction and encouraging enantiomeric excess are obtained.

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Cable-driven parallel robots offer significant advantages in terms of workspace dimensions and payload capability. They are attractive for many industrial tasks to be performed on a large scale, such as handling and manufacturing, without a substantial increase in costs and mechanical complexity with respect to a small-scale application. However, since cables can only sustain tensile stresses, cable tensions must be kept within positive limits during the end-effector motion. This problem can be managed by overconstraining the end-effector and controlling cable tensions. Tension control is typically achieved by mounting a load sensor on all cables, and using specific control algorithms to avoid cable slackness or breakage while the end-effector is controlled in a desired position. These algorithms require multiple cascade control loops and they can be complex and computationally demanding. To simplify the control of overconstrained cable-driven parallel robots, this Thesis proposes suitable mechanical design and hybrid control strategies. It is shown how a convenient design of the cable guidance system allows kinematic modeling to be simplified, without introducing geometric approximations. This guidance system employs swiveling pulleys equipped with position and tension sensors and provides a parallelogram arrangement of cables. Furthermore, a hybrid force/position control in the robot joint space is adopted. According to this strategy, a particular set of cables is chosen to be tension-controlled, whereas the other cables are length-controlled. The force-controlled cables are selected based on the computation of a novel index called force-distribution sensitivity to cable-tension errors. This index aims to evaluate the maximum expected cable-tension error in the length-controlled cables if a unit tension error is committed in the force-controlled cables. In practice, the computation of the force-distribution sensitivity allows determining which cables are best to be force-controlled, to ensure the lowest error in the overall force distribution when a hybrid force/position joint-space strategy is used.