Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE. / Includes bibliographical references. / by Jocelyn Irene Petit. / M.S.

Thermally cycling a thin plate of nickel-based superalloy with an intense in-plane thermal gradient, or hot spot, produces thermally induced crack growth not represented by classic thermo-mechanical fatigue (TMF). With the max hot spot temperature at 1093 C (2000 F) of a 1.5 mm thick, 82.55 mm diameter circular plate of B-1900+Hf, annular buckling and bending stresses result during each thermal cycle which drive the crack initiation and propagation. A finite element analysis (FEA) model, using ANSYS 7.1, has been developed which models the buckling and as well as represents the stress intensity at simulated crack lengths upon cool down of each thermal cycle. The model approximates the out-of-plane response at heat-up within 5% error and a difference in the final displacement of 0.185 mm after twelve thermal cycles. Using published da/dN vs. Keff data, the number of cycles needed to grow the crack to the experimental arrest distance is modeled within 1 mm. The number of cycles to this point is within 5 out of 462 in comparison to the experimental test.

Engineers constantly seek advancements in the performance of aircraft and power generation engines, including, lower costs and emissions, and improved fuel efficiency. Nickel-base superalloys are the material of choice for turbine discs, which experience some of the highest temperatures and stresses in the engine. Engine performance is proportional to operating temperatures. Consequently, the high-temperature capabilities of disc materials limit the performance of gas-turbine engines. Therefore, any improvements to engine performance necessitate improved alloy performance. In order to take advantage of improvements in high-temperature capabilities through tailoring of alloy microstructure, the overall objectives of this work were to establish relationships between alloy processing and microstructure, and between microstructure and mechanical properties. In addition, the project aimed to demonstrate the applicability of neural network modeling to the field of Ni-base disc alloy development and behavior. A full program of heat-treatment, microstructural quantification, mechanical testing, and neural network modeling was successfully applied to next generation Ni-base disc alloys. Mechanical testing included hot tensile, hot hardness, creep deformation, creep crack growth, and fatigue crack growth. From this work the mechanisms of processing-structure and structure-property relationships were studied. Further, testing results were used to demonstrate the applicability of machine-learning techniques to the development and optimization of this family of superalloys.

Ni-base superalloys are widely used in hot sections of gas turbine engines due to the high resistance to fatigue and creep at elevated temperatures. Due to the demands for improved performance and efficiency in applications of the superalloys, new and improved higher temperature alloy systems are being developed. Constitutive relations for these materials need to be formulated accordingly to predict behavior of cracks at notches in components under cyclic loading with peak dwell periods representative of gas turbine engine disk materials. Since properties are affected by microstructure at various length scales ranging from 10 nm tertiary γ' precipitates to 5-30 μm grains, hierarchical multiscale modeling is essential to address behavior at the component level. The goal of this work is to develop a framework for hierarchical multiscale modeling network that features linkage of several fine scale models to incorporate relevant microstructure attributes into the framework to improve the predictability of the constitutive model. This hierarchy of models is being developed in a collaborative research program with the Ohio State University. The fine scale models include the phase field model which addresses dislocation dissociation in the γ matrix and γ' precipitate phases, and the critical stresses from the model are used as inputs to a grain scale crystal plasticity model in a bottom-up fashion. The crystal plasticity model incorporates microstructure attributes by homogenization. A major task of the present work is to link the crystal plasticity model, informed by the phase field model, to the macroscale model and calibrate models in a top-down fashion to experimental data for a range of microstructures of the improved alloy system by implementing a hierarchical optimization scheme with a parameter clustering strategy. Another key part of the strategy to be developed in this thesis is the incorporation of polycrystal plasticity simulations to model a large range of virtual microstructures that have not been experimentally realized (processed), which append the experimentally available microstructures. Simulations of cyclic responses with dwell periods for this range of virtual (and limited experimental) polycrystalline microstructures will be used to (i) provide additional data to optimize parameter fitting for a microstructure-insensitive macroscopic internal state variable (ISV) model with thermal recovery and rate dependence relevant to the temperatures of interest, and (ii) provide input to train an artificial neural network that will associate the macroscopic ISV model parameters with microstructure attributes for this material. Such microstructure sensitive macroscopic models can then be employed in component level finite element studies to model cyclic behavior with dwell times at smooth and cracked notched specimens.

Nickel-base superalloys obtain high temperature mechanical properties through formation of precipitate phases formed via heat treatment. The precipitate microstructure evolves with heat treatment or thermal exposure, which can lead to degrading mechanical properties. This project focuses on the use of electrical resistivity as a non-destructive testing method to monitor the precipitate phase in Waspaloy (a polycrystalline nickel-base superalloy). The evolution of the precipitate microstructure is characterized throughout the volume of the specimens using both small angle neutron scattering (SANS) and ultra small angle X-ray scattering (USAXS) measurements. These measurements are also aided by microscopy and X-ray diffraction measurements.

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Thesis (M. App. Sc.)--Carleton University, 2004. / Includes bibliographical references (p. 99-114). Also available in electronic format on the Internet.

Thesis (M.App.Sc.) - Carleton University, 2005. / Includes bibliographical references (p. 57-63). Also available in electronic format on the Internet.

Thesis (M.App.Sc.) - Carleton University, 2006. / Includes bibliographical references (p. 110-113). Also available in electronic format on the Internet.

No description available.