Banca de DEFESA: Jalusa Maria da Silva Ferrari

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : Jalusa Maria da Silva Ferrari
DATE: 10/11/2023
TIME: 13:30
LOCAL: Videoconferência Plataforma Teams
TITLE:

Inverse Problem of Damage Identification in Aeronautic Structure and its Connection using Dynamic Modeling with Uncertainty

KEY WORDS:

inverse problem, structural dynamics, damage identification, uncertainties

PAGES: 101
BIG AREA: Engenharias
AREA: Engenharia Mecânica
SUMMARY:

In aeronautics, the need to identify and monitor damage to complex and difficult-to-access structures still presents a major challenge for existing non-destructive monitoring techniques. Methods based on Structural Health Monitoring (SHM) demonstrate the potential to identify and monitor damage to aircraft through an on-board system for immediate comparison with an existing database. In this sense, the present work proposes a numerical study using the SHM damage prediction method with the solution of the inverse problem. The study structure was a fixed beam with elastic boundary conditions modeled using a low-order fidelity model. Using finite elements, a bolted joint with 4 NAS6208-16 bolts was modeled in Ansys APDL using the combin14 element from 6 stiffnesses, where 3 stiffnesses are torsional and 3 are flexural. A convergence analysis was performed, resulting in the evaluation of the modeling of the problem with elastic conditions and a discretization of 20 elements using quadratic interpolation functions between the elements. Beam damage was defined as a loss of tightening torque on the bolts ranging from 5% to 50%, resulting in a loss of stiffness in the beam connection. Using an R-index, results were evaluated based on acceleration in the vertical direction and normalized to the collected maximum acceleration signal. Transient simulations using modal superposition were performed to evaluate the robustness of the R-index. As a first result, it was observed that the selected R-index is robust in relation to changes in the force application position and also in the number and distribution of nodes for data reading. It was possible to approximate the results through a single quadratic curve, based on the averages obtained from the R-index. 95% confidence limit curves were plotted on the average values, enabling an attempt to solve the inverse problem. With the addition of noise of 1% to 5% in the vertical acceleration data obtained, the detection of torque loss at low levels was impaired. Despite this, through the analysis of the confidence interval, the method was still capable of satisfactorily identifying torque losses above 25%, especially when the use of the average of the values obtained from the sensors was considered to calculate the R-index

COMMITTEE MEMBERS:
Externo à Instituição - LIÉRCIO ANDRÉ ISOLDI - FURG
Presidente - 1693584 - JHON NERO VAZ GOULART
Interna - 1734228 - MARIA ALZIRA DE ARAUJO NUNES
Interna - 2213675 - SUZANA MOREIRA AVILA