Ph.D. Thesis Proposal

Niharika Akula

(Faculty Advisor: Professor Dimitri Mavris)

"Multidisciplinary and Multifidelity Analysis and Design Optimization Framework for Twin Web Turbine Disk Technologies"

Friday, May 15

9:30 a.m.

Weber, CoVE

Abstract:

The continued push for higher thermal efficiency and reduced fuel consumption in modern gas turbine engines has led to increasingly aggressive operating conditions, including higher turbine inlet temperatures, elevated blade loading, and increased rotational speeds. While advances in materials, aerodynamics, and cooling technologies have enabled these trends, their full potential remains constrained by the structural capability of rotating components. Among these, the turbine disk is a critical limiting element, as it must sustain severe centrifugal loads and thermal gradients while interacting with complex cooling flows. This has motivated the development of advanced disk architectures such as the twin-web turbine disk (TWD), originally explored under the U.S. Air Force’s Composite Ring Reinforced Turbine (CRRT) program. However, despite its promise, the existing body of research on TWDs remains limited and fragmented across structural, thermal, and manufacturing domains.

The design of TWDs is inherently multidisciplinary, requiring the coupled treatment of thermo-fluid-structural interactions alongside practical considerations such as manufacturability and cost. Current approaches often rely on partitioned, black-box workflows that require inter-solver data transfer, introducing additional sources of error and computational overhead. Furthermore, high-fidelity multiphysics simulations, particularly for cooling analysis, are computationally expensive, limiting their direct use in optimization. These challenges highlight the need for a unified framework that can consistently capture coupled physics while remaining computationally tractable.

Motivated by these gaps, this work proposes the development of a unified, multidisciplinary, and multifidelity framework for the analysis and design optimization of TWDs. The proposed approach will systematically progress from a baseline partitioned formulation to a fully coupled monolithic solver, with the aim of improving numerical stability and predictive accuracy. To address computational cost, targeted surrogate models, particularly for cooling-related analyses, will be developed and incorporated to enable rapid yet reliable evaluations within the design loop. Sensitivity analysis and design space exploration will be carried out to identify the dominant design drivers, and the resulting framework will be embedded within a multidisciplinary optimization environment to generate Pareto-optimal designs. Through these efforts, this research aims to help bridge the gap between conceptual design and practical implementation of improved turbine disk technologies by combining high-fidelity multiphysics modeling with effective optimization strategies in a coherent formulation.

Committee:
Dr. Dimitri Mavris (advisor), School of Aerospace Engineering
Dr. Jechiel Jagoda, School of Aerospace Engineering
Dr. Kai James, School of Aerospace Engineering
Dr. Jonathan C. Gladin, School of Aerospace Engineering