2 resultados para Fast heavy ion
em Coffee Science - Universidade Federal de Lavras
Resumo:
As nuclear energy systems become more advanced, the materials encompassing them need to perform at higher temperatures for longer periods of time. In this Master’s thesis we experiment with an oxide dispersion strengthened (ODS) austenitic steel that has been recently developed. ODS materials have a small concentration of nano oxide particles dispersed in their matrix, and typically have higher strength and better extreme temperature creep resistance characteristics than ordinary steels. However, no ODS materials have ever been installed in a commercial power reactor to date. Being a newer research material, there are many unanswered phenomena that need to be addressed regarding the performance under irradiation. Furthermore, due to the ODS material traditionally needing to follow a powder metallurgy fabrication route, there are many processing parameters that need to be optimized before achieving a nuclear grade material specification. In this Master’s thesis we explore the development of a novel ODS processing technology conducted in Beijing, China, to produce solutionized bulk ODS samples with ~97% theoretical density. This is done using relatively low temperatures and ultra high pressure (UHP) equipment, to compact the mechanically alloyed (MA) steel powder into bulk samples without any thermal phase change influence or oxide precipitation. By having solutionized bulk ODS samples, transmission electron microscopy (TEM) observation of nano oxide precipitation within the steel material can be studied by applying post heat treatments. These types of samples will be very useful to the science and engineering community, to answer questions regarding material powder compacting, oxide synthesis, and performance. Subsequent analysis performed at Queen’s University included X-ray diffraction (XRD) and inductively coupled plasma optical emission spectrometry (ICP-OES). Additional TEM in-situ 1MeV Kr2+ irradiation experiments coupled with energy dispersive X-ray (EDX) techniques, were also performed on large (200nm+) non-stoichiometric oxides embedded within the austenite steel grains, in an attempt to quantify the elemental compositional changes during high temperature (520oC) heavy ion irradiation.
Resumo:
Lithium Ion (Li-Ion) batteries have got attention in recent decades because of their undisputable advantages over other types of batteries. They are used in so many our devices which we need in our daily life such as cell phones, lap top computers, cameras, and so many electronic devices. They also are being used in smart grids technology, stand-alone wind and solar systems, Hybrid Electric Vehicles (HEV), and Plug in Hybrid Electric Vehicles (PHEV). Despite the rapid increase in the use of Lit-ion batteries, the existence of limited battery models also inadequate and very complex models developed by chemists is the lack of useful models a significant matter. A battery management system (BMS) aims to optimize the use of the battery, making the whole system more reliable, durable and cost effective. Perhaps the most important function of the BMS is to provide an estimate of the State of Charge (SOC). SOC is the ratio of available ampere-hour (Ah) in the battery to the total Ah of a fully charged battery. The Open Circuit Voltage (OCV) of a fully relaxed battery has an approximate one-to-one relationship with the SOC. Therefore, if this voltage is known, the SOC can be found. However, the relaxed OCV can only be measured when the battery is relaxed and the internal battery chemistry has reached equilibrium. This thesis focuses on Li-ion battery cell modelling and SOC estimation. In particular, the thesis, introduces a simple but comprehensive model for the battery and a novel on-line, accurate and fast SOC estimation algorithm for the primary purpose of use in electric and hybrid-electric vehicles, and microgrid systems. The thesis aims to (i) form a baseline characterization for dynamic modeling; (ii) provide a tool for use in state-of-charge estimation. The proposed modelling and SOC estimation schemes are validated through comprehensive simulation and experimental results.