32 resultados para Realistic threat


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Joints play a major role in the structural behaviour of old timber frames [1]. Current standards mainly focus on modern dowel-type joints and usually provide little guidance (with the exception of German and Swiss NAs) to designers regarding traditional joints. With few exceptions, see e.g. [2], [3], [4], most of the research undertaken today is mainly focused on the reinforcement of dowel-type connections. When considering old carpentry joints, it is neither realistic nor useful to try to describe the behaviour of each and every type of joint. The discussion here is not an extra attempt to classify or compare joint configurations [5], [6], [7]. Despite the existence of some classification rules which define different types of carpentry joints, their applicability becomes difficult. This is due to the differences in the way joints are fashioned depending, on the geographical location and their age. In view of this, it is mandatory to check the relevance of the calculations as a first step. This first step, to, is mandatory. A limited number of carpentry joints, along with some calculation rules and possible strengthening techniques are presented here.

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The present work describes a model for the determination of the moment–rotation relationship of a cross section of fiber reinforced concrete (FRC) elements that also include longitudinal bars for the flexural reinforcement (R/FRC). Since a stress–crack width relationship (σ–w)(σ–w) is used to model the post-cracking behavior of a FRC, the σ–w directly obtained from tensile tests, or derived from inverse analysis applied to the results obtained in three-point notched beam bending tests, can be adopted in this approach. For a more realistic assessment of the crack opening, a bond stress versus slip relationship is assumed to simulate the bond between longitudinal bars and surrounding FRC. To simulate the compression behavior of the FRC, a shear friction model is adopted based on the physical interpretation of the post-peak compression softening behavior registered in experimental tests. By allowing the formation of a compressive FRC wedge delimited by shear band zones, the concept of concrete crushing failure mode in beams failing in bending is reinterpreted. By using the moment–rotation relationship, an algorithm was developed to determine the force–deflection response of statically determinate R/FRC elements. The model is described in detail and its good predictive performance is demonstrated by using available experimental data. Parametric studies were executed to evidence the influence of relevant parameters of the model on the serviceability and ultimate design conditions of R/FRC elements failing in bending.

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Customer lifetime value (LTV) enables using client characteristics, such as recency, frequency and monetary (RFM) value, to describe the value of a client through time in terms of profitability. We present the concept of LTV applied to telemarketing for improving the return-on-investment, using a recent (from 2008 to 2013) and real case study of bank campaigns to sell long- term deposits. The goal was to benefit from past contacts history to extract additional knowledge. A total of twelve LTV input variables were tested, un- der a forward selection method and using a realistic rolling windows scheme, highlighting the validity of five new LTV features. The results achieved by our LTV data-driven approach using neural networks allowed an improvement up to 4 pp in the Lift cumulative curve for targeting the deposit subscribers when compared with a baseline model (with no history data). Explanatory knowledge was also extracted from the proposed model, revealing two highly relevant LTV features, the last result of the previous campaign to sell the same product and the frequency of past client successes. The obtained results are particularly valuable for contact center companies, which can improve pre- dictive performance without even having to ask for more information to the companies they serve.

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Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

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Dissertação de mestrado integrado em Engenharia e Gestão Industrial

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The monitoring data collected during tunnel excavation can be used in inverse analysis procedures in order to identify more realistic geomechanical parameters that can increase the knowledge about the interested formations. These more realistic parameters can be used in real time to adapt the project to the real structure in situ behaviour. However, monitoring plans are normally designed for safety assessment and not especially for the purpose of inverse analysis. In fact, there is a lack of knowledge about what types and quantity of measurements are needed to succeed in identifying the parameters of interest. Also, the optimisation algorithm chosen for the identification procedure may be important for this matter. In this work, this problem is addressed using a theoretical case with which a thorough parametric study was carried out using two optimisation algorithms based on different calculation paradigms, namely a conventional gradient-based algorithm and an evolution strategy algorithm. Calculations were carried for different sets of parameters to identify several combinations of types and amount of monitoring data. The results clearly show the high importance of the available monitoring data and the chosen algorithm for the success rate of the inverse analysis process.

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Tese de Doutoramento em Ciências da Educação (Área de Conhecimento: Educação ambiental e para a Sustentabilidade)

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The management of solid waste is a growing concern in many countries. Municipal solid waste is a major component of the total solid waste generated by society, and the composting of municipal solid waste has gained some attention even though a composting treatment for it is not yet widespread. It may not be realistic to replace large portions of these plastics with biodegradable materials, and it may be more important to separate plastics unsuitable for the composting process at the generating spots. However, for food packaging, there is still a great deal of interest in using biodegradable plastics that are difficult to sort at the generation spots. Under these circumstances, nanocomposites of biodegradable polymers as matrix and nanoparticles, that can be degraded along with organic wastes during composting could be a solution. Therefore, this chapter aims to give an overview on the biodegradability studies of bio-nanocomposites. It will focus on different polymers, nanocomposites containing different clay types and inorganic particles exposed under different environments.

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Dissertação de mestrado integrado em Psicologia

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Bacteria are central to human health and disease, but existing tools to edit microbial consortia are limited. For example, broad-spectrum antibiotics are unable to precisely manipulate bacterial communities. Bacteriophages can provide highly specific targeting of bacteria, but assembling well-defined phage cocktails solely with natural phages can be a time-, labor- and cost-intensive process. Here, we present a synthetic biology strategy to modulate phage host ranges by engineering phage genomes in Saccharomyces cerevisiae. We used this technology to redirect Escherichia coli phage scaffolds to target pathogenic Yersinia and Klebsiella bacteria, and conversely, Klebsiella phage scaffolds to target E. coli by modular swapping of phage tail components. The synthetic phages achieved efficient killing of their new target bacteria and were used to selectively remove bacteria from multi-species bacterial communities with cocktails based on common viral scaffolds. We envision this approach accelerating phage biology studies and enabling new technologies for bacterial population editing.

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Previously we have presented a model for generating human-like arm and hand movements on an unimanual anthropomorphic robot involved in human-robot collaboration tasks. The present paper aims to extend our model in order to address the generation of human-like bimanual movement sequences which are challenged by scenarios cluttered with obstacles. Movement planning involves large scale nonlinear constrained optimization problems which are solved using the IPOPT solver. Simulation studies show that the model generates feasible and realistic hand trajectories for action sequences involving the two hands. The computational costs involved in the planning allow for real-time human robot-interaction. A qualitative analysis reveals that the movements of the robot exhibit basic characteristics of human movements.

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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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This paper proposes a methodology for improvement of energy efficiency in buildings through the innovative simultaneous incorporation of three distinct phase change materials (here termed as hybrid PCM) in plastering mortars for façade walls. The thermal performance of a hybrid PCM mortar was experimentally evaluated by comparing the behaviour of a prototype test cell (including hybrid PCM plastering mortar) subjected to realistic daily temperature profiles, with the behaviour of a similar prototype test cell, in which no PCM was added. A numerical simulation model was employed (using ANSYS-FLUENT) to validate the capacity of simulating temperature evolution within the prototype containing hybrid PCM, as well as to understand the contribution of hybrid PCM to energy efficiency. Incorporation of hybrid PCM into plastering mortars was found to have the potential to significantly reduce heating/cooling temperature demands for maintaining the interior temperature within comfort levels when compared to normal mortars (without PCM), or even mortars comprising a single type of PCM.

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Dissertação de mestrado em Engenharia Industrial

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Tese de Doutoramento em Biologia de Plantas