Research Data Leeds Repository

Dataset for the Independent Experimental Calibration and Validation of Finite Element Models of Osteochondral Grafts in Tibiofemoral Joints

Day, Gavin A. and Jones, Alison C. and Mengoni, Marlène and Wicox, Ruth K. (2024) Dataset for the Independent Experimental Calibration and Validation of Finite Element Models of Osteochondral Grafts in Tibiofemoral Joints. University of Leeds. [Dataset] https://doi.org/10.5518/1387

This item is part of the The Institute of Medical and Biological Engineering Knee Dataset collection.

Dataset description

This dataset includes experimental data, three dimensional uCT image data, computational models and results from an associated study entitled: A Finite Element Model to Investigate the Stability of Osteochondral Grafts within a Human Tibiofemoral Joint. Specifically, the dataset includes packages of work from three parallel, experimental and computational pieces of work: a material property calibration study, a frictional force/ osteochondral graft push-in study and a tibiofemoral knee joint study. Each of these three include uCT scan data for the human knee specimens used, specimen specific finite element model input files for Abaqus and experimental and computational results.

Additional information: This dataset is not publicly available. Click the link under ‘Related resources’ to request access via the RADAR Restricted Access Data Repository. You will be asked to complete a request form explaining why you need access to the data. You will receive an initial response to your request within 5 working days.
Keywords: knee joint, tibiofemoral joint, micro computed tomography, pressure measurements, finite element analysis, osteochondral graft
Divisions: Faculty of Engineering and Physical Sciences > School of Mechanical Engineering
Related resources:
LocationType
https://doi.org/10.1007/s10439-024-03464-6Publication
https://radar.researchdata.leeds.ac.uk/48/Dataset
License: Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited: 08 Mar 2024 13:20
URI: https://archive.researchdata.leeds.ac.uk/id/eprint/1248

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