972 resultados para simulation training


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Due to the increasing acceptance of BPM, nowadays BPM tools are extensively used in organizations. Core to BPM are the process modeling languages, of which BPMN is the one that has been receiving most attention these days. Once a business process is described using BPMN, one can use a process simulation approach in order to find its optimized form. In this context, the simulation of business processes, such as those defined in BPMN, appears as an obvious way of improving processes. This paper analyzes the business process modeling and simulation areas, identifying the elements that must be present in the BPMN language in order to allow processes described in BPMN to be simulated. During this analysis a set of existing BPM tools, which support BPMN, are compared regarding their limitations in terms of simulation support.

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This work intends to present a newly developed test setup for dynamic out-of-plane loading using underWater Blast Wave Generators (WBWG) as loading source. Underwater blasting operations have been, during the last decades, subject of research and development of maritime blasting operations (including torpedo studies), aquarium tests for the measurement of blasting energy of industrial explosives and confined underwater blast wave generators. WBWG allow a wide range for the produced blast impulse and surface area distribution. It also avoids the generation of high velocity fragments and reduces atmospheric sound wave. A first objective of this work is to study the behavior of masonry infill walls subjected to blast loading. Three different masonry walls are to be studied, namely unreinforced masonry infill walls and two different reinforcement solutions. These solutions have been studied previously for seismic action mitigation. Subsequently, the walls will be simulated using an explicit finite element code for validation and parametric studies. Finally, a tool to help designers to make informed decisions on the use of infills under blast loading will be presented.

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The present paper focuses on a damage identification method based on the use of the second order spectral properties of the nodal response processes. The explicit dependence on the frequency content of the outputs power spectral densities makes them suitable for damage detection and localization. The well-known case study of the Z24 Bridge in Switzerland is chosen to apply and further investigate this technique with the aim of validating its reliability. Numerical simulations of the dynamic response of the structure subjected to different types of excitation are carried out to assess the variability of the spectrum-driven method with respect to both type and position of the excitation sources. The simulated data obtained from random vibrations, impulse, ramp and shaking forces, allowed to build the power spectrum matrix from which the main eigenparameters of reference and damage scenarios are extracted. Afterwards, complex eigenvectors and real eigenvalues are properly weighed and combined and a damage index based on the difference between spectral modes is computed to pinpoint the damage. Finally, a group of vibration-based damage identification methods are selected from the literature to compare the results obtained and to evaluate the performance of the spectral index.

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A new very high-order finite volume method to solve problems with harmonic and biharmonic operators for one- dimensional geometries is proposed. The main ingredient is polynomial reconstruction based on local interpolations of mean values providing accurate approximations of the solution up to the sixth-order accuracy. First developed with the harmonic operator, an extension for the biharmonic operator is obtained, which allows designing a very high-order finite volume scheme where the solution is obtained by solving a matrix-free problem. An application in elasticity coupling the two operators is presented. We consider a beam subject to a combination of tensile and bending loads, where the main goal is the stress critical point determination for an intramedullary nail.

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There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

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This paper deals with a computing simulation for an offshore wind energy system taking into account the influence of the marine waves action throughout the floating platform. The wind energy system has a variable-speed turbine equipped with a permanent magnet synchronous generator and a full-power five level converter, injecting energy into the electric grid through a high voltage alternate current link. A reduction on the unbalance of the voltage in the DC-link capacitors of the five-level converter is proposed by a strategic selection of the output voltage vectors. The model for the drive train of the wind energy system is a two mass model, including the dynamics of the floating platform. A case study is presented and the assessment of the quality of the energy injected into the electric grid is discussed.

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A new integrated mathematical model for the simulation of an offshore wind system having a rectifier input voltage malfunction at one phase is presented in this paper. The mathematical model considers an offshore variable-speed wind turbine on a floating platform, equipped with a permanent magnet synchronous generator using full-power three-level converter to inject energy into the electric network, through a high voltage direct current transmission submarine cable. The model for the drive train is a discrete three mass, incorporating the dynamic of the moving surface. A case study is presented to access conclusion about the malfunction.

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Recent studies have demonstrated the positive effects of musical training on the perception of vocally expressed emotion. This study investigated the effects of musical training on event-related potential (ERP) correlates of emotional prosody processing. Fourteen musicians and fourteen control subjects listened to 228 sentences with neutral semantic content, differing in prosody (one third with neutral, one third with happy and one third with angry intonation), with intelligible semantic content (semantic content condition--SCC) and unintelligible semantic content (pure prosody condition--PPC). Reduced P50 amplitude was found in musicians. A difference between SCC and PPC conditions was found in P50 and N100 amplitude in non-musicians only, and in P200 amplitude in musicians only. Furthermore, musicians were more accurate in recognizing angry prosody in PPC sentences. These findings suggest that auditory expertise characterizing extensive musical training may impact different stages of vocal emotional processing.

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Dissertação de mestrado integrado em Mechanical Engineering

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FOSTER aims to support different stakeholders, especially young researchers, in adopting open access in the context of the European Research Area (ERA) and in complying with the open access policies and rules of participation set out for Horizon 2020 (H2020). FOSTER establish a European-wide training programme on open access and open data, consolidating training activities at downstream level and reaching diverse disciplinary communities and countries in the ERA. The training programme includes different approaches and delivery options: elearning, blearning, self-learning, dissemination of training materials/contents, helpdesk, face-to-face training, especially training-the-trainers, summer schools, seminars, etc.

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In this work, we present a 3D web-based interactive tool for numerical modeling and simulation approach to breast reduction surgery simulation, to assist surgeons in planning all aspects related to breast reduction surgery before the actual procedure takes place, thereby avoiding unnecessary risks. In particular, it allows the modeling of the initial breast geometry, the definition of all aspects related to the surgery and the visualization of the post-surgery breast shape in a realistic environment.

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A survey of European Microbial Biological Resource Centers and their users provided an overview on Microbiology education and training. The results identified future increases in demand despite several shortcomings and gaps in the current offer. Urgent adjustments are needed to match users' needs, integrate innovative programs, and adopt new technologies.

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Dissertação de mestrado integrado em Civil Engineering