THE MICROSTRUCTURES OF ZR-EXCEL ALLOY: EFFECTS OF HEAVY ION IRRADIATION, PLASTIC DEFORMATION, THERMAL TREATMENT AND IN-SITU HEATING

Zr-Excel alloy (Zr-3.5Sn-0.8Nb-0.8Mo) is a dual phase (α + β) alloy in the as-received pressure tube condition. It has been proposed to be the pressure tube candidate material for the Generation-IV CANDU-Supercritical Water Reactor (CANDU-SCWR). In this dissertation, the effects of heavy ion irradiation, deformation and heat treatment on the microstructures of the alloy were investigated to enable us to have a better understanding of the potential in-reactor performance of this alloy. In-situ heavy ion (1 MeV) irradiation was performed to study the nucleation and evolution of dislocation loops in both α- and β-Zr. Small and dense type dislocation loops form under irradiation between 80 and 450 °C. The number density tends to saturate at ~ 0.1 dpa. Compared with the α-Zr, the defect yield is much lower in β-Zr. The stabilities of the metastable phases (β-Zr and ω-Zr) and the thermal-dynamically equilibrium phase, fcc Zr(Mo, Nb)2, under irradiation were also studied at different temperatures. Chemi-STEM elemental mapping was carried out to study the elemental redistribution caused by irradiation. The stability of these phases and the elemental redistribution are strongly dependent on irradiation temperature. In-situ time-of-flight neutron diffraction tensile and compressive tests were carried out at different temperatures to monitor lattice strain evolutions of individual grain families during these tests. The β-Zr is the strengthening phase in this alloy in the as-received plate material. Load is transferred to the β-Zr after yielding of the α-Zr grains. The temperature dependence of static strain aging and the yielding sequence of the individual grain families were discussed. Strong tensile/compressive asymmetry was observed in the {0002} grain family at room temperature. The microstructures of the sample deformed at 400 °C and the samples only subjected to heat treatment at the same temperature were characterized with TEM. Concentration of β phase stabilizers in the β grain and the morphology of β grain have significant effect on the stability of β- and ω-Zr under thermal treatment. Applied stress/strain enhances the decomposition of isothermal ω phase but suppresses α precipitation inside the β grains at high temperature. An α → ω/ZrO phase transformation was observed in the thin foils of Zr-Excel alloy and pure Zr during in-situ heating at 700 °C in TEM.

A cloud-based system for measuring radiation treatment plan similarity

PURPOSE: Radiation therapy is used to treat cancer using carefully designed plans that maximize the radiation dose delivered to the target and minimize damage to healthy tissue, with the dose administered over multiple occasions. Creating treatment plans is a laborious process and presents an obstacle to more frequent replanning, which remains an unsolved problem. However, in between new plans being created, the patient's anatomy can change due to multiple factors including reduction in tumor size and loss of weight, which results in poorer patient outcomes. Cloud computing is a newer technology that is slowly being used for medical applications with promising results. The objective of this work was to design and build a system that could analyze a database of previously created treatment plans, which are stored with their associated anatomical information in studies, to find the one with the most similar anatomy to a new patient. The analyses would be performed in parallel on the cloud to decrease the computation time of finding this plan. METHODS: The system used SlicerRT, a radiation therapy toolkit for the open-source platform 3D Slicer, for its tools to perform the similarity analysis algorithm. Amazon Web Services was used for the cloud instances on which the analyses were performed, as well as for storage of the radiation therapy studies and messaging between the instances and a master local computer. A module was built in SlicerRT to provide the user with an interface to direct the system on the cloud, as well as to perform other related tasks. RESULTS: The cloud-based system out-performed previous methods of conducting the similarity analyses in terms of time, as it analyzed 100 studies in approximately 13 minutes, and produced the same similarity values as those methods. It also scaled up to larger numbers of studies to analyze in the database with a small increase in computation time of just over 2 minutes. CONCLUSION: This system successfully analyzes a large database of radiation therapy studies and finds the one that is most similar to a new patient, which represents a potential step forward in achieving feasible adaptive radiation therapy replanning.