ORCID

https://orcid.org/0009-0007-6840-5695

Degree

Bachelor of Science (B.S.)

Major(s)

Mechanical Engineering

Document Type

Temporary Embargo for Patent/Proprietary Reasons then Open Access

Abstract

Bioreactors are widely used in tissue engineering to support cell and tissue growth under controlled conditions. Perfusion-compression bioreactors, like the one developed in our lab, can be used to replicate the physiological loading of bone on 3D-printed scaffolds. When seeded with osteogenic cells and subjected to mechanical loading, these scaffolds serve as a model to study osteogenesis. To simulate physiological conditions, the bioreactor must apply 1000 compression cycles at forces up to 200 N, three times daily over 14 days. Upon implementation, validation testing and experimental studies exposed several limitations in the bioreactor’s control code. The system was initially programmed in LabVIEW, which is expensive, closed source, and not readily adaptable to changing research needs. During testing, the LabVIEW code frequently overloaded bone explant samples. To resolve these issues, the objective of this project was to transition the control code to Python, an open-source, non-graphical programming language that offers greater flexibility and customization. Transitioning to Python also allows for a more user-friendly, customizable graphical user interface (GUI) to improve accessibility for future researchers. The transition has been implemented step by step. First, timers were enabled to control the retraction and extension of the NEMA 17 linear actuator, which applies compressive forces. Load cells were verified to ensure the force readings were accurate. The actuator and load cell functions have been integrated so the actuator’s behavior adjusts in real time based on the load cell readings. Next, the Linear Variable Differential Transducer (LVDT) displacement sensor will be incorporated to measure small displacements and calculate the stiffness of the scaffold. Beyond optimizing data handling and visualization, this transition from LabVIEW to Python will ensure the bioreactor remains adaptable to new technologies and applications, improving system performance and sustainability.

DOI

https://doi.org/10.54718/IEVW6579

Date Defended

4-22-2025

Funding Source

Shackouls Honors College Provost Scholarship Program, Bagley College of Engineering Undergraduate Student Research Award, ORED #ACR2022-022

Thesis Director

Lauren B. Priddy

Second Committee Member

Matthew W. Priddy

Third Committee Member

Brian Pugh

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Available for download on Friday, May 15, 2026

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