TECHNICAL DATA ANALYSIS, INC. STTR Phase I Award, August 2018

TDA focuses on developing a state of the art time-frequency-based fatigue spectrum editing (TF-based FSE) framework to reduce the time of fatigue computational analysis and tests. The proposed framework will address (a) through understanding of fatigue loading histories including stationary, nonstationary, linear, and non-linear spectrums, (b) developing a multi-approach TF framework for both uniaxial and multiaxial FSE, (c) implementing innovative damage models to account for loading sequence effect, (d) developing a multi-objective optimization framework to enhance the performance of edited spectrums, and (e) the validation of proposed methods and algorithms through conduction of critical uniaxial and multiaxial fatigue tests. The key elements of research proposal are the multi-approach TF-based FSE algorithms and methods development. The TF-based FSE algorithms include advanced signal processing methods, rigorous damage analysis techniques, and innovative heuristic optimization algorithms that will be applied to the uniaxial and multiaxial test data for performance evaluation and validation purposes. We will validate the proposed methods through conduction of uniaxial and multiaxial fatigue tests for different loading histories i.e. high cycle and high and low cycle with nonstationary linear and nonlinear conditions.