Experimental Study on Friction between Saline Ice and Steel

Understanding the interaction of sea ice with offshore structures is of primary importance for the development of technology in cold climate regions. The rheological properties of sea ice (strength, creep, viscosity) as well as the roughness of the contact surface are the main factors influencing the type of interaction with a structure. A device was developed and designed and small scale laboratory experiments were carried out to study sea ice frictional interaction with steel material by means of a uniaxial compression rig. Sea-ice was artificially grown between a stainless steel piston (of circular cross section) and a hollow cylinder of the same material, coaxial to the former and of the same surface roughness. Three different values for the roughness were tested: 1.2, 10 and 30 μm Ry (maximum asperities height), chosen as representative values for typical surface conditions, from smooth to normally corroded steel. Creep tests (0.2, 0.3, 0.4 and 0.6 kN) were conducted at T = -10 ºC. By pushing the piston head towards the cylinder base, three different types of relative movement were observed: 1) the piston slid through the ice, 2) the piston slid through the ice and the ice slid on the surface of the outer cylinder, 3) the ice slid only on the cylinder surface. A cyclic stick-slip motion of the piston was detected with a representative frequency of 0.1 Hz. The ratio of the mean rate of axial displacement to the frequency of the stick-slip oscillations was found to be comparable to the roughness length (Sm). The roughness is the most influential parameter affecting the amplitude of the oscillations, while the load has a relevant influence on the their frequency. Guidelines for further investigations were recommended. Marco Nanetti - seloselo@virgilio.it

A numerical program for Railway vehicle-track-structure dynamic interaction using a modal substructuring approach

This work presents a program for simulations of vehicle-track and vehicle-trackstructure dynamic interaction . The method used is computationally efficient in the sense that a reduced number of coordinates is sufficient and doesn’t require high efficiency computers. The method proposes a modal substructuring approach of the system by modelling rails , sleepers and underlying structure with modal coordinates, the vehicle with physical lumped elements coordinates and by introducing interconnection elements between these structures (wheel-rail contact, railpads and ballast) by means of their interaction forces. The Frequency response function (FRF) is also calculated for both cases of track over a structure (a bridge, a viaduct ...) and for the simple vehicle-track program; for each case the vehicle effect on the FRF is then analyzed through the comparison of the FRFs obtained introducing or not a simplified vehicle on the system.

Structure learning of graphical models for task-oriented robot grasping

In the collective imaginaries a robot is a human like machine as any androids in science fiction. However the type of robots that you will encounter most frequently are machinery that do work that is too dangerous, boring or onerous. Most of the robots in the world are of this type. They can be found in auto, medical, manufacturing and space industries. Therefore a robot is a system that contains sensors, control systems, manipulators, power supplies and software all working together to perform a task. The development and use of such a system is an active area of research and one of the main problems is the development of interaction skills with the surrounding environment, which include the ability to grasp objects. To perform this task the robot needs to sense the environment and acquire the object informations, physical attributes that may influence a grasp. Humans can solve this grasping problem easily due to their past experiences, that is why many researchers are approaching it from a machine learning perspective finding grasp of an object using information of already known objects. But humans can select the best grasp amongst a vast repertoire not only considering the physical attributes of the object to grasp but even to obtain a certain effect. This is why in our case the study in the area of robot manipulation is focused on grasping and integrating symbolic tasks with data gained through sensors. The learning model is based on Bayesian Network to encode the statistical dependencies between the data collected by the sensors and the symbolic task. This data representation has several advantages. It allows to take into account the uncertainty of the real world, allowing to deal with sensor noise, encodes notion of causality and provides an unified network for learning. Since the network is actually implemented and based on the human expert knowledge, it is very interesting to implement an automated method to learn the structure as in the future more tasks and object features can be introduced and a complex network design based only on human expert knowledge can become unreliable. Since structure learning algorithms presents some weaknesses, the goal of this thesis is to analyze real data used in the network modeled by the human expert, implement a feasible structure learning approach and compare the results with the network designed by the expert in order to possibly enhance it.

"Offshore tower or platform foundations: numerical analysis of a laterally loaded single pile or pile group in soft clay and analysis of actions on a jacket structure"

Laterally loaded piles are a typical situation for a large number of cases in which deep foundations are used. Dissertation herein reported, is a focus upon the numerical simulation of laterally loaded piles. In the first chapter the best model settings are largely discussed, so a clear idea about the effects of interface adoption, model dimension, refinement cluster and mesh coarseness is reached. At a second stage, there are three distinct parametric analyses, in which the model response sensibility is studied for variation of interface reduction factor, Eps50 and tensile cut-off. In addition, the adoption of an advanced soil model is analysed (NGI-ADP). This was done in order to use the complex behaviour (different undrained shear strengths are involved) that governs the resisting process of clay under short time static loads. Once set a definitive model, a series of analyses has been carried out with the objective of defining the resistance-deflection (P-y) curves for Plaxis3D (2013) data. Major results of a large number of comparisons made with curves from API (America Petroleum Institute) recommendation are that the empirical curves have almost the same ultimate resistance but a bigger initial stiffness. In the second part of the thesis a simplified structural preliminary design of a jacket structure has been carried out to evaluate the environmental forces that act on it and on its piles foundation. Finally, pile lateral response is studied using the empirical curves.

Dynamical Casimir effect and the structure of vacuum in quantum field theory

Some of the most interesting phenomena that arise from the developments of the modern physics are surely vacuum fluctuations. They appear in different branches of physics, such as Quantum Field Theory, Cosmology, Condensed Matter Physics, Atomic and Molecular Physics, and also in Mathematical Physics. One of the most important of these vacuum fluctuations, sometimes called "zero-point energy", as well as one of the easiest quantum effect to detect, is the so-called Casimir effect. The purposes of this thesis are: - To propose a simple retarded approach for dynamical Casimir effect, thus a description of this vacuum effect when we have moving boundaries. - To describe the behaviour of the force acting on a boundary, due to its self-interaction with the vacuum.