The development and use of a digital twin model for tire touchdown health monitoring
Document Type
Conference Proceeding
Publication Date
1-5-2017
Abstract
Under performing aircraft tires can drive high program costs in addition to increasing the logistical and environmental footprint of that aircraft. Aircraft tire wear mechanisms are very complex and depend on a multitude of interdependent variables. Recent work has been completed showing that non-ideal touchdown (spin-up) landings can lead to potential tire flat spots and even mishaps. To enhance this tire touchdown wear prediction, a Digital Twin (DTw) model of a specific aircraft tire at touchdown was developed and utilized. This paper details the derivation of a physics based tire wear equation, Slip Wear Rate, for use in a nonlinear touchdown wear response model built from the high fidelity testing data. The response model was derived to be a function of variables that are easily visible in a field setting. A Monte Carlo analysis was used in conjunction with a Cotter sensitivity analysis to determine the uncertainty associated with the touchdown wear prediction. The DTw model was then used to determine Probability of Failure (POF) for varying distributions of sink rates, yaw angles, tire conditions (new to worn), and touchdown speeds. The DTw touchdown model results show future potential benefit for aircraft mission decisions that can assist in cost savings and health monitoring of tire’s at touchdown. The initial DTw touchdown model is reviewed and future work is recommended to enhance the DTw touchdown model POF predictions. This initial DTw foundation is then extrapolated to show the future benefit of a DTw model for predicting the tire’s full fielded life.
Source Publication
58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
Recommended Citation
Zakrajsek, A. J., & Mall, S. (2017, January). The development and use of a digital twin model for tire touchdown health monitoring. 58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. https://doi.org/10.2514/6.2017-0863
Comments
This conference paper is available through subscription or purchase from the publisher, AIAA, using the DOI link below.
Author note: Andrew Zakrajsek was an AFIT PhD student at the time of this conference. (March 2018). He was co-affiliated with the 96 TG/OL-ACL Landing Gear Test Facility.
Conference Session: Structural Health Monitoring and Prognosis, Model Uncertainty