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  • 1
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    A Computationally-Efficient Probabilistic Approach to Model-Based Damage Diagnosis (2017)
    In:  CASI
    Details
    Publication Date: 2019-06-14
    Description: This work presents a computationally-efficient, probabilistic approach to model-based damage diagnosis. Given measurement data, probability distributions of unknown damage parameters are estimated using Bayesian inference and Markov chain Monte Carlo (MCMC) sampling. Substantial computational speedup is obtained by replacing a three-dimensional finite element (FE) model with an efficient surrogate model. While the formulation is general for arbitrary component geometry, damage type, and sensor data, it is applied to the problem of strain-based crack characterization and experimentally validated using full-field strain data from digital image correlation (DIC). Access to full-field DIC data facilitates the study of the effectiveness of strain-based diagnosis as the distance between the location of damage and strain measurements is varied. The ability of the framework to accurately estimate the crack parameters and effectively capture the uncertainty due to measurement proximity and experimental error is demonstrated. Furthermore, surrogate modeling is shown to enable diagnoses on the order of seconds and minutes rather than several days required with the FE model.
    Keywords: Structural Mechanics
    Type: NF1676L-28090 , International Journal of Prognostics and Health Management (ISSN 2153-2648); 8; 2; 026
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  • 2
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    Damage Characterization Method for Structural Health Management Using Reduced Number of Sensor Inputs (2012)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: The development of validated multidisciplinary Integrated Vehicle Health Management (IVHM) tools, technologies, and techniques to enable detection, diagnosis, prognosis, and mitigation in the presence of adverse conditions during flight will provide effective solutions to deal with safety related challenges facing next generation aircraft. The adverse conditions include loss of control caused by environmental factors, actuator and sensor faults or failures, and damage conditions. A major concern in these structures is the growth of undetected damage (cracks) due to fatigue and low velocity foreign impacts that can reach a critical size during flight, resulting in loss of control of the aircraft. Hence, development of efficient methodologies to determine the presence, location, and severity of damage in critical structural components is highly important in developing efficient structural health management systems.
    Keywords: Structural Mechanics
    Type: AIAA Paper 2012-1361 , NF1676L-13373 , 13th AIAA Gossamer Systems Forum; Apr 23, 2012 - Apr 16, 2012; Honolulu, HI; United States|14th AIAA Non-Deterministic Approaches Conference; Apr 23, 2012 - Apr 16, 2012; Honolulu, HI; United States|53rd Structures, Structural Dynamics, and Materials Conference (SDM); Apr 23, 2012 - Apr 16, 2012; Honolulu, HI; United States|20th AIAA/ASME/AHS Adaptive Structures Conference; Apr 23, 2012 - Apr 16, 2012; Honolulu, HI; United States
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  • 3
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    Multiscale Modeling of Structurally-Graded Materials Using Discrete Dislocation Plasticity Models and Continuum Crystal Plasticity Models (2012)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: A multiscale modeling methodology that combines the predictive capability of discrete dislocation plasticity and the computational efficiency of continuum crystal plasticity is developed. Single crystal configurations of different grain sizes modeled with periodic boundary conditions are analyzed using discrete dislocation plasticity (DD) to obtain grain size-dependent stress-strain predictions. These relationships are mapped into crystal plasticity parameters to develop a multiscale DD/CP model for continuum level simulations. A polycrystal model of a structurally-graded microstructure is developed, analyzed and used as a benchmark for comparison between the multiscale DD/CP model and the DD predictions. The multiscale DD/CP model follows the DD predictions closely up to an initial peak stress and then follows a strain hardening path that is parallel but somewhat offset from the DD predictions. The difference is believed to be from a combination of the strain rate in the DD simulation and the inability of the DD/CP model to represent non-monotonic material response.
    Keywords: Structural Mechanics
    Type: AIAA Paper 2012-1726 , NF1676L-13294 , 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference - Special Sessions on Nanostructured Materials; Apr 23, 2012 - Apr 26, 2012; Honolulu, HI; United States
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  • 4
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    Multiscale Analysis of Structurally-Graded Microstructures Using Molecular Dynamics, Discrete Dislocation Dynamics and Continuum Crystal Plasticity (2014)
    In:  CASI
    Details
    Publication Date: 2019-07-12
    Description: A multiscale modeling methodology is developed for structurally-graded material microstructures. Molecular dynamic (MD) simulations are performed at the nanoscale to determine fundamental failure mechanisms and quantify material constitutive parameters. These parameters are used to calibrate material processes at the mesoscale using discrete dislocation dynamics (DD). Different grain boundary interactions with dislocations are analyzed using DD to predict grain-size dependent stress-strain behavior. These relationships are mapped into crystal plasticity (CP) parameters to develop a computationally efficient finite element-based DD/CP model for continuum-level simulations and complete the multiscale analysis by predicting the behavior of macroscopic physical specimens. The present analysis is focused on simulating the behavior of a graded microstructure in which grain sizes are on the order of nanometers in the exterior region and transition to larger, multi-micron size in the interior domain. This microstructural configuration has been shown to offer improved mechanical properties over homogeneous coarse-grained materials by increasing yield stress while maintaining ductility. Various mesoscopic polycrystal models of structurally-graded microstructures are generated, analyzed and used as a benchmark for comparison between multiscale DD/CP model and DD predictions. A final series of simulations utilize the DD/CP analysis method exclusively to study macroscopic models that cannot be analyzed by MD or DD methods alone due to the model size.
    Keywords: Structural Mechanics
    Type: NASA/TM-2014-218265 , L-20410 , NF1676L-18832
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  • 5
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    Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions (2011)
    In:  CASI
    Details
    Publication Date: 2019-07-12
    Description: A surrogate model methodology is described for predicting in real time the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. A residual strength test of a metallic, integrally-stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data would, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.
    Keywords: Structural Mechanics
    Type: NF1676L-11863
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  • 6
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    Probabilistic Fatigue Damage Prognosis Using a Surrogate Model Trained Via 3D Finite Element Analysis (2015)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: Utilizing inverse uncertainty quantification techniques, structural health monitoring can be integrated with damage progression models to form probabilistic predictions of a structure's remaining useful life. However, damage evolution in realistic structures is physically complex. Accurately representing this behavior requires high-fidelity models which are typically computationally prohibitive. In the present work, a high-fidelity finite element model is represented by a surrogate model, reducing computation times. The new approach is used with damage diagnosis data to form a probabilistic prediction of remaining useful life for a test specimen under mixed-mode conditions.
    Keywords: Structural Mechanics
    Type: NF1676L-20700 , International Workshop on Structural Health Monitoring; Sep 01, 2015 - Sep 03, 2015; Stanford, CA; United States
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