5 resultados para NOMINAL RESPONSE MODEL

em Universidad Politécnica de Madrid


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Reducing energy consumption and eliminating wastage are among the main goals of the European Union (EU) [2]. In order to satisfy all challenges arising from the Kyoto protocol, improving energy efficiency is a very important factor to take into account. There is significant potential for reducing consumption with cost-effective measures. Some studies show that 40% of our energy is consumed in buildings, and the EU has introduced legislation that aims to ensure that less energy is consumed in this way in the future.

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Este trabajo fin de Máster consiste en la realización de un modelo de respuesta ante procesos de concentración de proveedores, que permita a las empresas proveedoras de servicios profesionales adaptarse a las necesidades crecientes o decrecientes que puedan plantearse en los clientes, además de identificar las diferentes problemáticas que puedan aparecer, de cara a realizar una gestión adecuada de las mismas, garantizando la sostenibilidad económica del negocio. Este modelo de respuesta, estará formado por una serie de mecanismos, que mediante su activación posibilitarán que las empresas de servicios se encuentren preparadas y con garantías en las dos vertientes posibles que se derivan de un proceso de concentración, la más positiva, en la que el desarrollo de actividad requiera nuevas habilidades o nuevos dimensionamientos y la vertiente negativa, donde el nivel de actividad disminuirá. ---ABSTRACT---This Master final work is based on the creation of a response model for the concentration processes carried out by professional services clients, enabling companies that provides this kind of services the capabilities to be adapted for the increasing or decreasing needs that may arise, and identifying the problems that can appears, in order to make a proper management of them and ensuring the economic sustainability of the business. This pattern of response will consist on several mechanisms, which through its activation will enable the capabilities for professional services companies to be prepared and guaranteed the two possible angles derived from a concentration process, the more positive, where activity requires the development of new skills or new sizing and the negative one, where the level of activity decrease or disappears.

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Numerous damage models have been developed in order to analyze seismic behavior. Among the different possibilities existing in the literature, it is very clear that models developed along the lines of continuum damage mechanics are more consistent with the definition of damage as a phenomenon with mechanical consequences because they include explicitly the coupling between damage and mechanical behavior. On the other hand, for seismic processes, phenomena such as low cycle fatigue may have a pronounced effect on the overall behavior of the frames and, therefore, its consideration turns out to be very important. However, most of existing models evaluate the damage only as a function of the maximum amplitude of cyclic deformation without considering the number of cycles. In this paper, a generalization of the simplified model proposed by Cipollina et al. [Cipollina A, López-Hinojosa A, Flórez-López J. Comput Struct 1995;54:1113–26] is made in order to include the low cycle fatigue. Such a model employs in its formulation irreversible thermodynamics and internal state variable theory.

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Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties,instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.

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This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of baseline (1981 to 2010) daily weather, with CO2 concentration fixed at 360 ppm. The IRS approach offers an effective method of portraying model behaviour under changing climate as well as advantages for analysing, comparing and presenting results from multi-model ensemble simulations. Though individual model behaviour occasionally departed markedly from the average, ensemble median responses across sites and crop varieties indicated that yields decline with higher temperatures and decreased precipitation and increase with higher precipitation. Across the uncertainty ranges defined for the IRSs, yields were more sensitive to temperature than precipitation changes at the Finnish site while sensitivities were mixed at the German and Spanish sites. Precipitation effects diminished under higher temperature changes. While the bivariate and multi-model characteristics of the analysis impose some limits to interpretation, the IRS approach nonetheless provides additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development.