A dilogarithmic integral arising in quantum field theory

Recently, an interesting dilogarithmic integral arising in quantum field theory has been closed-form evaluated in terms of the Clausen function $\text{Cl}_2(\theta)$ by Coffey [J. Math. Phys.} 49 (2008), 093508]. It represents the volume of an ideal tetrahedron in hyperbolic space and is involved in two intriguing equivalent conjectures of Borwein and Broadhurst. It is shown here, by simple and direct arguments, that this integral can be expressed by the triplet of the Clausen function values which are involved in one of the two above-mentioned conjectures.Comment: 6 page

Use of Machine Learning for Partial Discharge Discrimination

Partial discharge (PD) measurements are an important tool for assessing the condition of power equipment. Different sources of PD have different effects on the insulation performance of power apparatus. Therefore, discrimination between PD sources is of great interest to both system utilities and equipment manufacturers. This paper investigates the use of a wide bandwidth PD on-line measurement system to facilitate automatic PD source identification. Three artificial PD models were used to simulate typical PD sources which may exist within power systems. Wavelet analysis was applied to pre-process the obtained measurement data. This data was then processed using correlation analysis to cluster the discharges into different groups. A machine learning technique, namely the support vector machine (SVM) was then used to identify between the different PD sources. The SVM is trained to differentiate between the inherent features of each discharge source signal. Laboratory experiments indicate that this approach is applicable for use with field measurement data

Effect of Cross-Linking on the Electrical Properties of LDPE and its Lightning Impulse Ageing Characteristics

Cross-linked polyethylene (XLPE) is commonly used within high voltage cable insulation. It has improved thermal and mechanical resistance compared to normal low density polyethylene (LDPE). However, the cross-linking process may also vary the electrical characteristics of the material. This paper investigates changes in electrical properties of one type of LDPE before and after cross-linking. The effective lightning resistance is also considered, as the application of repetitive lightning impulse overvoltages can be a factor in insulation material ageing of high voltage cables. The material was cross-linked using trigonox-145 peroxide with controlled concentration. Samples were moulded to have a Rogowski profile and gold coated to make sure that they are evenly electrically stressed. Obtained results show that there are reductions in both space charge injection and the permittivity of the material after it is cross-linked. The breakdown strength of the material was also improved. However, the samples studied are more susceptible to ageing due to lightning impulses

Prochloron research

The purpose was to prepare Prochloron photosynthetic membranes for the isolation of the two major chlorophyll-proteins, the P700-chlorophyll a-protein and the light-harvesting chlorophyll a/b-protein, using SDS-polyacrylamide gel electrophoresis. The prepared proteins (purified) were examined for their cross-reactivity to polyclonal antibodies prepared from higher plant proteins. In addition, material was prepared for electron microscopy, and isolation of the DNA for determination of its general complexity (COT analysis) and similarity to barley chloroplast DNA and Anabaena DNA by using restriction-endonuclease analysis. Kleinschmidt spreads of the DNA were in the electron microscope to identify and measure the extent and size of the circlar DNA

Location of Partial Discharges within a Transformer Winding Using Principal Component Analysis

Partial discharge (PD) may occur in a transformer winding due to ageing processes or defects introduced during manufacture. A partial discharge is defined as a localised electric discharge that only partially bridges the dielectric insulator between conductors when the electric field exceeds a critical value. The presence of PD does not necessarily indicate imminent failure of the transformer but it is a serious degradation and ageing mechanism which can be considered as a precursor of transformer failure. PD might occur anywhere along the transformer winding and the discharge signal can propagate along the winding to the bushing and neutral to earth connections. As far as maintenance and replacement processes are concerned, it is important to identify the location of PD activity so any repair or replace decision is assured to be cost effective. Therefore, identification of a PD source as well as its location along the transformer winding is of great interest to both manufacturers and system operators. The wavelet transform is a mathematical function that can be used to decompose a PD signal into detail levels and an approximation. Wavelet filtering is often used to improve signal to noise ratio (SNR) of measured signals, but in this case it is used to identify the distribution of signal energies in both the time and frequency domains. This method produces a feature vector for each captured discharge signal. The use of principle component analysis (PCA) can compress this data into three dimensions, to aid visualisation. Data captured by sensors over hundreds of cycles of applied voltage can be analysed using this approach. An experiment (Figure 1) has been developed that can be used to create PD data in order to investigate the feasibility of using PCA analysis to identify PD source location

Scalar Field Theory at Finite Temperature in D=2+1

We discuss the $\phi^6$ theory defined in $D=2+1$-dimensional space-time and assume that the system is in equilibrium with a thermal bath at temperature $\beta^{-1}$. We use the $1/N$ expansion and the method of the composite operator (CJT) for summing a large set of Feynman graphs.We demonstrate explicitly the Coleman-Mermin-Wagner theorem at finite temperature.Comment: 12 pages, 1 figure. To be published in Journal Mathematical Physics, typos adde

Modelling the Non-equilibrium Electric Double Layer at Oil-pressboard Interface of High Voltage Transformers

In large oil-filled power transformers, cellulose-based pressboard and paper are used throughout for electrical insulation. Microscopic views have shown that pressboard insulation is a fibrous and porous structure with non-homogeneous surface. It has been recognised that the pressboard structure is more porous towards the edge [1]. The pores within the pressboard allow oil absorption during impregnation process and provide paths for oil to penetrate until saturation is reached. The ratio of fibre and oil changes as the material structure changes from a medium of bulk oil-pressboard composite toward the bulk oil medium. The porosity of pressboard can also result in impurities within the oil being drawn into the pressboard. It has also been recognised that physicochemical process of a liquid in contact with solid wall leads to the formation of electric double layer (EDL) in the liquid region [2, 3]. The material properties and geometry of pressboard thus lead to a complex oil-pressboard interface. A 2-D model of oil-pressboard interface has been constructed using Comsol Multiphysics Finite Element Analysis software and this is shown in Figure 1. The mathematical model considers the dissociation of a generic impurity in the oil into positive and negative ions and considers the role of the porous and non-homogeneous wall of pressboard in the formation of the EDL. The pressboard, which is represented by different arrays of fibre, promotes preferential adsorption and desorption processes between ions in the oil and unoccupied fibre surfaces of oil impregnated pressboard. The model studies the non-equilibrium charge density profile in the EDL at the oil-pressboard interface when the oil is in the stationary condition

A New Method to Improve the Sensitivity of Leak Detection in Self-Contained Fluid-filled Cables

A method of real-time detection of leaks for self-contained fluid-filled cables without taking them out of service has been assessed and a novel machine learning technique, i.e. support vector regression (SVR) analysis has been investigated to improve the detection sensitivity of the self-contained fluid-filled (FF) cable leaks. The condition of a 400 kV underground FF cable route within the National Grid transmission network has been monitored by Drallim pressure, temperature and load current measurement system. These three measured variables are used as parameters to describe the condition of the cable system. In the regression analysis the temperature and load current of the cable circuit are used as independent variables and the pressure within cables is the dependent variable to be predicted. As a supervised learning algorithm, the SVR requires data with known attributes as training samples in the learning process and can be used to identify unknown data or predict future trends. The load current is an independent variable to the fluid-filled system itself. The temperature, namely the tank temperature is determined by both the load current and the weather condition i.e. ambient temperature. The pressure is directly relevant to the temperature and therefore also correlated to the load current. The Gaussian-RBF kernel has been used in this investigation as it has a good performance in general application. The SVR algorithm was trained using 4 days data, as shown in Figure 1, and the optimized SVR is used to predict the pressure using the given load current and temperature information