Randomness in topological models

p. 914-925There are two aspects of randomness in topological models. In the first one, topological idealization of random patterns found in the Nature can be regarded as planar representations of three-dimensional lattices and thus reconstructed in the space. Another aspect of randomness is related to graphs in which some properties are determined in a random way. For example, combinatorial properties of graphs: number of vertices, number of edges, and connections between them can be regarded as events in the defined probability space. Random-graph theory deals with a question: at what connection probability a particular property reveals. Combination of probabilistic description of planar graphs and their spatial reconstruction creates new opportunities in structural form-finding, especially in the inceptive, the most creative, stage.Tarczewski, R.; Bober, W. (2010). Randomness in topological models. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/695

Kernel arquitecture for CAD/CAM in shipbuilding enviroments

The capabilities of complex software products such as CAD/CAM systems are strongly supported by basic information technologies related with data management, visualization, communication, geometry modeling and others related with the development process. These basic information technologies are involved in a continuous evolution process, but over recent years this evolution has been dramatic. The main reason for this has been that new hardware capabilities (including graphic cards) are available at very low cost, but also a contributing factor has been the evolution of the prices of basic software. To take advantage of these new features, the existing CAD/CAM systems must undergo a complete and drastic redesign. This process is complicated but strategic for the future evolution of a system. There are several examples in the market of how a bad decision has lead to a cul-de-sac (both technically and commercially). This paper describes what the authors consider are the basic architectural components of a kernel for a CAD/CAM system oriented to shipbuilding. The proposed solution is a combination of in-house developed frameworks together with commercial products that are accepted as standard components. The proportion of in-house frameworks within this combination of products is a key factor, especially when considering CAD/CAM systems oriented to shipbuilding. General-purpose CAD/CAM systems are mainly oriented to the mechanical CAD market. For this reason several basic products exist devoted to geometry modelling in this context. But these basic products are not well suited to deal with the very specific geometry modelling requirements of a CAD/CAM system oriented to shipbuilding. The complexity of the ship model, the different model requirements through its short and changing life cycle and the many different disciplines involved in the process are reasons for this inadequacy. Apart from these basic frameworks, specific shipbuilding frameworks are also required. This second layer is built over the basic technology components mentioned above. This paper describes in detail the technological frameworks which have been used to develop the latest FORAN version.Postprint (published version

A simple spatiotemporal evolution model of a transmission power grid

In this paper, we present a model for the spatial and temporal evolution of a particularly large human-made network: the 400-kV French transmission power grid. This is based on 1) an attachment procedure that diminishes the connection probability between two nodes as the network grows and 2) a coupled cost function characterizing the available budget at every time step. Two differentiated and consecutive processes can be distinguished: a first global space-filling process and a secondary local meshing process that increases connectivity at a local level. Results show that even without power system engineering design constraints (i.e., population and energy demand), the evolution of a transmission network can be remarkably explained by means of a simple attachment procedure. Given a distribution of resources and a time span, the model can also be used to generate the probability distribution of cable lengths at every time step, thus facilitating network planning. Implications for network's fragility are suggested as a starting point for new design perspectives in this kind of infrastructures.Peer ReviewedPostprint (author's final draft