Numerical analyses of tunnel-induced settlement damage to a masonry wall

Settlements due to underground construction represent a risk for the architectural heritage, especially in The Netherlands, because of the combination of soft soil, fragile pile foundation and brittle, un-reinforced masonry façade. Modelling of soil-structure interaction is fundamental to assess the risk of building damage due to tunnelling. This paper presents results of finite element analyses carried out with different models for a simple masonry wall. Focus is paid on the comparison between coupled, uncoupled and semi-coupled analyses, in which the soil-structure interaction is represented in different ways. In particular, the implementation of a soil-structure interface model in the numerical analyses is analysed, in order to asses its validity. The aim of the research project is the development of a damage classification system for different building typologies.

Guided self-organization in a dynamic embodied system based on attractor selection mechanism

Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics. © 2014 by the authors; licensee MDPI, Basel, Switzerland.