No description available.

This project has examined the effects of plasma delay time (PDT) and pulse height defect (PHD) for protons, tritons and alpha particles. The goal was to determine PDT and PHD for alpha particles relative to protons, by using data from a subset of measurements taken with a silicon detector of type PIPS at the LOHENGRIN spectrometer. The PIPS detectors were used in combination with an MCP to measure the time of flight (ToF) of the particles, in addition to their energies. The project involved calibrating energy and time measurements with linear calibration. As a first step, peaks were identified for each particle event in the data set. A Gaussian fit was used to determine the mean value and spread of the peak. Under the assumption that protons have zero PDT and PHD, the proton peaks were used to calibrate all the data with a linear fit. In order to determine the PDT and PHD the real values of ToF and energy for the particles had to be estimated and compared with the measurements. The LOHENGRIN spectrometer gives the real energy of the ions reaching the MCP chamber. The energy losses that occur when using the MCP were estimated with the program SRIM, used to calculate stopping-power and ranges of ions. The real ToF was derived from energy and flight path of the particles. For the flight path measurements of the experimental equipment had to be conducted, partly by the writers of this project and partly by a research team with access to the LOHENGRIN. The result presents the relative PDT and PHD of protons, alpha particles and a triton. The relationship of PDT and PHD to mass and energy is discussed. Notably the PDT was found to depend inversely on the energy of the particle. No definite trend in PHD of alpha particles relative to protons was found, thought to be due to the effect being to small to observe in this study. Empirical formulae from earlier papers were tested to compare with the result of this project. The trend of the results are supported by these formulae.

No description available.

No description available.

No description available.

The Future Circular electron-positron Collider (FCC-ee) is a high luminosity frontier particle accelerator for high precision measurements of the heaviest fundamental particles and possible evidence of new physics. Heavy Neutral Leptons (HNLs) are examples of new particles with discovery potential at the FCC-ee that could answer some of the most substantial questions in particle physics, such as how neutrinos oscillate between flavour eigenstates. Their estimated discovery region at the FCC-ee includes masses and mixing angles that allow the HNLs to attain long-lived properties. Therefore, long-lived signatures such as displaced vertices can be considered in this search for these particles. This thesis presents the first sensitivity analysis of these long-lived HNLs in the FCC-ee framework for the experimental run at the Z pole. The signal simulation used the Type I Seesaw mechanism with one benchmark HNL mixing with electron flavours and leptonic final states with electrons and electron neutrinos. An analysis of the signal and background is given, which results in a proposed event selection to reduce the background and increase the signal sensitivity. The final results include a sensitivity plot as a function of mass and mixing angle. This first successful implementation of a HNL analysis in future colliders can be used as a foundation for future explorations of long-lived HNLs at FCC-ee.

The Stockholm Educational Air Shower Array (SEASA) project is deploying an array of plastic scintillator detector stations on school roofs in the Stockholm area. Signals from GPS satellites are used to time synchronise signals from the widely separated detector stations, allowing cosmic ray air showers to be identified and studied. A low-cost and highly scalable data acquisition system has been produced using embedded Linux processors which communicate station data to a central server. Air shower data can be visualised in real-time using a Java-applet client. The design and performance of the first three detector stations located at the AlbaNova University Centre are presented. The detectors have been running since the beginning of October 2005 and the data from this period is analysed to assess the stability and performance of the detector array. A total of 503 showers with a primary particle energy above 1016 eV, hitting all three detector stations simultaneously, have been detected during this period. The read out and data-base system used to collect the data are described together with a quicklook tool for ensuring the integrity of the data. A preliminary study of the acceptance of the detector array as a function of weather conditions, to be used in future studies of cosmic ray anisotropy, is presented. The acceptance of the single detector stations is found to decrease with increasing atmospheric pressure and to stay constant over a large range of temperatures. The acceptance of the entire array of detector stations is found to have a stronger continuous dependence on temperature than single stations. The dependence of the array acceptance on pressure is inconclusive. The ability of the array to reconstruct the primary cosmic ray direction is assessed with simulations. A critical feature for the reconstruction is the time resolution of the system. The performance of the GPS system is therefore tested, and the time resolution is found to be better than 15 ns for all tested GPS units. The angular resolution of the array for this time resolution is found to be (7.0\pm0.3)^{\circ}. As the time resolution is expected to decrease for a larger array of detectors, the dependency of the time resolution on the angular resolution is derived. The measured distribution of the primary cosmic ray arrival direction is derived and compared to the expected distribution to check the performance of the system. The agreement between the distributions is good and the GPS timing system can therefore be concluded to work well. The simulations also show that the energy threshold of the array is slightly above 1016 eV. A preliminary study of the cosmic ray anisotropy is presented. The hypothesis of an isotropic flux of cosmic rays was tested using a two point correlation function. The probability that the observed flux is a random sampling from an isotropic flux was checked with a Kolmogorov test and it was found to be 82%. The hypothesis of an isotropic flux is therefore supported. / QC 20101116

QC 20101123

One of the most important affairs in the nuclear industry is the fuel cycle situation prediction. It affects the energy company’s profit, environment and even the safety of reactor operation. For these reasons, a series of computer codes have been generated to simulate the fuel cycle scenario including NFCSim, ORION and so on. At the Department of Reactor Physics, a new fuel cycle simulation code is under development and this code will be used in the present thesis.In order to simulate the nuclides transmutation chains, MCNP was first used to calculate the neutron spectrum and cross section data for the reactor cores, using JEF 3.0 and EAF 99 data libraries.The main task of this project is to simulate the present and future status of all the facilities in Chinese reactor park. Three consecutive scenarios (present, near-term and long-term) are defined for this comparison, simulation time scale is set to be 208 years (1992~2200) and four groups of nuclides (major actinides, minor actinides, major fission products and safety related nuclides) are defined and presented.Power balance scenario, plutonium self-sustained scenario and CIAE proposals are discussed individually as choices of reactor parks’ future development. The result is that at least 70 years (cooling storage time is not included) are needed to transmute the minor actinides inventory after the large-scale FBR (Fast Breeder Reactor) technology is mature enough for large scale commissioning in plutonium-sustained scenario.

In the recent decade, neural networks have become one of the leading tools in the search for the elusive nature of dark matter and its interactions through the analysis of numerically simulated data. This project introduces a minimal dark sector consisting of three additional fields and studies it through two mono-X signatures,mono-jet and mono-Z. A convolutional neural network is then implemented to identify and characterise thedark matter components of the generated signals. Using the data from the mono-jet signature, the networkclassifies the signals by number of dark matter components and then determines their masses; for the mono-Z, the network is also able to identify the spin of single component dark matter signals.The classification task is performed with perfect accuracy for both mono-X signatures. The regression task isnotoriously more complex. However, by increasing the size of the layers, the network is able to characterisethe masses of the dark matter components present in the signal with errors below 5% of the considered massranges. For both single and two-component dark matter signals, the network performs this task with betteraccuracy when using data from the mono-Z signature.