An experimental study of the jet of a boat propeller

An experimental study of the velocity and concentration (scalar) fields of a propeller is presented. Field and laboratory measurements were undertaken. The former were up to 50 diameters downstream. Important findings were that the mean velocity and scalar fields quickly become Gaussian while further downstream they both become irregular sometimes approaching approximately linear profiles. Propeller turbulence causes rapid mixing giving an initial concentration dilution factor of 1/20,000 after fifty propeller diameters. Some preliminary comparisons with field measurements of an actual boat in a natural waterway are made. Considerably more work is needed to gain a full understanding of the complex problem of propeller mixing.

CFD analyses of fibre transport and fibre deposition at plunging jet conditions

The investigation of insulation debris generation, transport and sedimentation becomes important with regard to reactor safety research for PWR and BWR, when considering the long-term behaviour of emergency core cooling systems during all types of loss of coolant accidents. A joint research project on such questions is being performed in cooperation between the University of Applied Sciences Zittau/Görlitz (HSZG) and the Helmholtz-Zentrum Dresden-Rossendorf (HZDR). The project deals with the experimental investigation of particle transport phenomena in coolant flow and the development of CFD models for its description (see [10-12]). While the experiments are performed at the University at Zittau/Görlitz, the theoretical modelling efforts are concentrated in Rossendorf. In the current paper, the basic concepts for CFD modelling are described and feasibility studies are presented. The model capabilities are demonstrated via complex flow situations, where a plunging jet agitates insulation debris. © Carl Hanser Verlag, München.

Disruption prediction at JET [Joint European Torus]

The sudden loss of the plasma magnetic confinement, known as disruption, is one of the major issue in a nuclear fusion machine as JET (Joint European Torus), Disruptions pose very serious problems to the safety of the machine. The energy stored in the plasma is released to the machine structure in few milliseconds resulting in forces that at JET reach several Mega Newtons. The problem is even more severe in the nuclear fusion power station where the forces are in the order of one hundred Mega Newtons. The events that occur during a disruption are still not well understood even if some mechanisms that can lead to a disruption have been identified and can be used to predict them. Unfortunately it is always a combination of these events that generates a disruption and therefore it is not possible to use simple algorithms to predict it. This thesis analyses the possibility of using neural network algorithms to predict plasma disruptions in real time. This involves the determination of plasma parameters every few milliseconds. A plasma boundary reconstruction algorithm, XLOC, has been developed in collaboration with Dr. D. Ollrien and Dr. J. Ellis capable of determining the plasma wall/distance every 2 milliseconds. The XLOC output has been used to develop a multilayer perceptron network to determine plasma parameters as ?i and q? with which a machine operational space has been experimentally defined. If the limits of this operational space are breached the disruption probability increases considerably. Another approach for prediction disruptions is to use neural network classification methods to define the JET operational space. Two methods have been studied. The first method uses a multilayer perceptron network with softmax activation function for the output layer. This method can be used for classifying the input patterns in various classes. In this case the plasma input patterns have been divided between disrupting and safe patterns, giving the possibility of assigning a disruption probability to every plasma input pattern. The second method determines the novelty of an input pattern by calculating the probability density distribution of successful plasma patterns that have been run at JET. The density distribution is represented as a mixture distribution, and its parameters arc determined using the Expectation-Maximisation method. If the dataset, used to determine the distribution parameters, covers sufficiently well the machine operational space. Then, the patterns flagged as novel can be regarded as patterns belonging to a disrupting plasma. Together with these methods, a network has been designed to predict the vertical forces, that a disruption can cause, in order to avoid that too dangerous plasma configurations are run. This network can be run before the pulse using the pre-programmed plasma configuration or on line becoming a tool that allows to stop dangerous plasma configuration. All these methods have been implemented in real time on a dual Pentium Pro based machine. The Disruption Prediction and Prevention System has shown that internal plasma parameters can be determined on-line with a good accuracy. Also the disruption detection algorithms showed promising results considering the fact that JET is an experimental machine where always new plasma configurations are tested trying to improve its performances.

Water detection in jet fuel using a polymer optical fibre Bragg grating

Water is a common impurity of jet fuel, and can exist in three forms: dissolved in the fuel, as a suspension and as a distinct layer at the bottom of the fuel tank. Water cannot practically be eliminated from fuel but must be kept to a minimum as large quantities can cause engine problems, particularly when frozen, and the interface between water and fuel acts as a breeding ground for biological contaminants. The quantities of dissolved or suspended water are quite small, ranging from about 10 ppm to 150 ppm. This makes the measurement task difficult and there is currently a lack of a convenient, electrically passive system for water-in-fuel monitoring; instead the airlines rely on colorimetric spot tests or simply draining liquid from the bottom of fuel tanks. For all these reason, people have explored different ways to detect water in fuel, however all these approaches have problems, e.g. they may not be electrically passive or they may be sensitive to the refractive index of the fuel. In this paper, we present a simple, direct and sensitive approach involving the use of a polymer optical fibre Bragg grating to detect water in fuel. The principle is that poly(methyl methacrylate) (PMMA) can absorb moisture from its surroundings (up to 2% at 23 °C), leading to both a swelling of the material and an increase in refractive index with a consequent increase in the Bragg wavelength of a grating inscribed in the material.

Water detection in jet fuel using a polymer optical fibre Bragg grating

Water is a common impurity of jet fuel, and can exist in three forms: dissolved in the fuel, as a suspension and as a distinct layer at the bottom of the fuel tank. Water cannot practically be eliminated from fuel but must be kept to a minimum as large quantities can cause engine problems, particularly when frozen, and the interface between water and fuel acts as a breeding ground for biological contaminants. The quantities of dissolved or suspended water are quite small, ranging from about 10 ppm to 150 ppm. This makes the measurement task difficult and there is currently a lack of a convenient, electrically passive system for water-in-fuel monitoring; instead the airlines rely on colorimetric spot tests or simply draining liquid from the bottom of fuel tanks. For all these reason, people have explored different ways to detect water in fuel, however all these approaches have problems, e.g. they may not be electrically passive or they may be sensitive to the refractive index of the fuel. In this paper, we present a simple, direct and sensitive approach involving the use of a polymer optical fibre Bragg grating to detect water in fuel. The principle is that poly(methyl methacrylate) (PMMA) can absorb moisture from its surroundings (up to 2% at 23 °C), leading to both a swelling of the material and an increase in refractive index with a consequent increase in the Bragg wavelength of a grating inscribed in the material.

Trade marks, registered designs and the monopolisation of functional shapes:a consideration of Lego and Dyson

Legislation: Regulation 6/2002 on Community designs art.3(3)(e) Directive 98/71 on the legal protection of designs art.7(1) Cases: Dyson Ltd v Vax Ltd [2010] EWHC 1923 (Pat); [2011] Bus. L.R. 232 (Ch D (Patents Ct)) Lego Juris A/S v Office for Harmonisation in the Internal Market (Trade Marks and Designs) (OHIM) (C-48/09 P) Unreported September 14, 2010 (ECJ) *E.I.P.R. 60 In Lego, the Court of Justice of the European Union denied registration for an exclusively functional shape mark despite the availability of other shapes capable of fulfilling the same function and in Dyson v Vax Mr Justice Arnold established that a design can not be registered for a purely functional shape even though another shape could fulfil the same required function.

The correlation of the indentation size effect measured with indenters of various shapes

Experimental results are presented which show that the indentation size effect for pyramidal and spherical indenters can be correlated. For a pyramidal indenter, the hardness measured in crystalline materials usually increases with decreasing depth of penetration, which is known as the indentation size effect. Spherical indentation also shows an indentation size effect. However, for a spherical indenter, hardness is not affected by depth, but increases with decreasing sphere radius. The correlation for pyramidal and spherical indenter shapes is based on geometrically necessary dislocations and work-hardening. The Nix and Gao indentation size effect model (J. Mech. Phys. Solids 46 (1998) 411) for conical indenters is extended to indenters of various shapes and compared to the experimental results. © 2002 Elsevier Science Ltd. All rights reserved.

The New Software Package for Dynamic Hierarchical Clustering for Circles Types of Shapes

In data mining, efforts have focused on finding methods for efficient and effective cluster analysis in large databases. Active themes of research focus on the scalability of clustering methods, the effectiveness of methods for clustering complex shapes and types of data, high-dimensional clustering techniques, and methods for clustering mixed numerical and categorical data in large databases. One of the most accuracy approach based on dynamic modeling of cluster similarity is called Chameleon. In this paper we present a modified hierarchical clustering algorithm that used the main idea of Chameleon and the effectiveness of suggested approach will be demonstrated by the experimental results.

Lower Bounds on the Directed Sweepwidth of Planar Shapes

We investigate a recently introduced width measure of planar shapes called sweepwidth and prove a lower bound theorem on the sweepwidth.