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In this study, structural vibration analyses for a 5MW offshore wind wind-turbine model have been performed for different substructure models. The efficient equivalent modeling method based on computational multi-body dynamics are applied to the finite element models of the present offshore wind turbines. Monopile and tri-pod substructure types of the typical offshore windturbine are considered herein. Detailed finite element modeling concepts and boundary conditions are described and the comparison results for previous analyses are presented in order to show the verification of the present numerical approach. Campbell diagrams are also present to investigate the rotational resonance characteristics of the offshore wind-turbines with different substructures.
This paper examines how the conceptual blending theory deals with meaning construction of computer humors. The conceptual blending theory, developed by Fauconnier & Turner (1994, 1998, 2002) and Fauconnier (1997), posits the four-space network consisting of two input spaces, the generic space, and the blended space. For humors to be effective, there should be some conflict or incongruity between the two events consisting of the humorous situation. One of the two events structures the input space1, and the other the input space2. I choose computer humors for the elaboration of my argument. The humor "It's the latest innovation in office safety. When your computer crashes, an air bag is activated so you won't bang your head in frustration" is a typical example of computer humors. Two events are involved in this humor. One is the fact that computers sometimes stop working because of some technical problems of computers. The other is the fact that the air bag is activated because of the car collision. These two events structure two input spaces. And then partial mapping between two input spaces and the selective projection from the input spaces to the blended space operate. The blended space motivates the meaning construction of this humor.
This paper aims to show how the conceptual blending theory deals with meaning construction in language. The conceptual blending theory, developed by Fauconnier & Turner(1994, 1998) and Fauconnier(l997), posits the four-space network consisting of two input spaces, the generic space, and the blended space. Conceptual integration network consists of four mental spaces which are local constructions in our short-term memory. Meaning is constructed by the operation of conceptual blending. I suggest that conceptual blending is the sum of three cognitive processes. Those are the establishment of input spaces, the partial cross-space mapping, and the selective projection. Then three aspects of meaning construction occur as a result of the different operations of each sub-cognitive process. The first aspect of meaning construction is resulted from different establishments of input spaces, the second aspect of meaning construction from the different operations of the cross-space mapping, and the third aspect of meaning construction from the different operations of the selective projection.
The aim of this paper is to study the types of conceptual integration networks constructed by the operation of conceptual blending on the base of the conceptual blending theory. The conceptual blending theory, developed by Fauconnier & Turner (1994, 1998, 2002) and Fauconnier (1997), posits the four-space network consisting of two input spaces, the generic space, and the blended space. Conceptual blending is a cognitive process which is the combination of input space construction, cross-space mapping, and selective projection. The meaning of language is constructed by the operation of conceptual blending. In chapter 2, I deal with the difference between conceptual blending theory and conceptual metaphor theory, specifying the nature and structural characteristics of conceptual blending. In chapter 3, I present the four types of conceptual integration networks with specific examples and investigate the way the networks are constructed. These integration networks are divided based on two dimensions; (ⅰ) whether all mental spaces in the network share a common frame, (ⅱ) whether two input spaces are involved in the construction of emergent structures in the blended space.