2 resultados para embedding capacity

em Universidade do Minho


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Timber connections represent the crucial part of a timber structure and a great variability exists in terms of types of connections and mechanisms. Taking as case study the widespread traditional timber frame structures, in particular the Portuguese Pombalino buildings, one of the most common timber connection is the half-lap joint. Connections play a major role in the overall behaviour of a structure, particularly when assessing their seismic response, since damage is concentrated at the connections. For this reason, an experimental campaign was designed and distinct types of tests were carried out on traditional half-lap joints to assess their in-plane response. In particular, pull-out and in-plane cyclic tests were carried out on real scale unreinforced connections. Subsequently, the connections were retrofitted, using strengthening techniques such as self-tapping screws, steel plates and GFRP sheets. The tests chosen were meant to capture the hysteretic behaviour and dissipative capacity of the connections and characterise their response and, therefore, their influence on the seismic response of timber frame walls, particularly concerning their uplifting and rotation capacity, that could lead to rocking in the walls. In this paper, the results of the experimental campaign are presented in terms of hysteretic curves, dissipated energy and equivalent viscous damping ratio. Moreover, recommendations are provided on the most appropriate retrofitting solutions.

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This paper proposes and validates a model-driven software engineering technique for spreadsheets. The technique that we envision builds on the embedding of spreadsheet models under a widely used spreadsheet system. This means that we enable the creation and evolution of spreadsheet models under a spreadsheet system. More precisely, we embed ClassSheets, a visual language with a syntax similar to the one offered by common spreadsheets, that was created with the aim of specifying spreadsheets. Our embedding allows models and their conforming instances to be developed under the same environment. In practice, this convenient environment enhances evolution steps at the model level while the corresponding instance is automatically co-evolved.Finally,wehave designed and conducted an empirical study with human users in order to assess our technique in production environments. The results of this study are promising and suggest that productivity gains are realizable under our model-driven spreadsheet development setting.