About this role
A large amount of high-fidelity experimental data is generated during the destructive mechanical testing of material characterization specimens and structural test articles in the Materials Research Laboratory at NASA Langley Research Center. The specimens tested range in size from simple material characterization coupons to structural details, such as hat-stiffened panels and low-velocity impact panels. The collected experimental data includes, but is not limited to, load; displacement and strain gage data; three-dimensional displacement and strain data recorded via digital image correlation; ultrasound scans of interlaminar delaminations taken during and after the tests; X-ray computed tomography of broken fiber tows, matrix cracks, and delaminations; and thermography data. Due to the large amount of data in terms of both the number of specimens tested and the amount of data collected per test, the development of automated or semi-automated data processing scripts or software is necessary to make full use of the rich datasets.
Much of this high-fidelity experimental data is generated for use in verification and validation programs for progressive damage analysis tools for fiber-reinforced composite material models. These material models are used in finite element analyses to predict the onset and growth of multiple damage modes under general loading conditions. State-of-the-art progressive damage analysis models can make predictions of damage on very small length scales. The sequence of data predictions and the rates of growth of multiple interacting damage mechanisms all need to be compared and validated with experimental data.
The purpose of this work is to help characterize the basic fracture behavior of composites and develop useful experimental data for use in making predictions, with an emphasis placed on using experimental data to understanding composite delamination and fracture The selected student(s) will test specimens and aid in processing and interpreting experimental data,. Students will operate servo-hydraulic test systems to perform tests. Automated methods for reducing test data will be developed in python for fracture testing. Digital Image Correlation (DIC) data will be processed and analyzed to aid in understanding of the failure process. Ultrasound and X-ray data will be interpreted to understand damage.
**Eligible Applicants:** Student
**Academic Level:** Undergraduate Senior, Graduate Master's, Graduate Doctoral, Post Doctoral
**Activity Type:** In-person
**Citizenship:** US Citizen Only
**Type:** Internships