Mechanical Engineering MS Thesis Defense by Ms. Stephanie DeCarvalho
When: Friday,
May 10, 2024
1:00 PM
-
3:00 PM
Where: > See description for location
Description: Mechanical Engineering MS Thesis Defense by
Ms. Stephanie DeCarvalho
DATE:
May 10, 2024
TIME:
1:00 P.M. - 3:00 P.M.
LOCATION:
ZOOM link:
https://umassd.zoom.us/j/91399406281?pwd=aUNpWS8ybFQ5eFNIWlVmRGNjbmlaZz09
(Contact scunha@umassd.edu for Meeting ID and PassCode)
TOPIC:
Computational Modeling of Materials and Structures for Biomedical Applications: from 3D Printed Implants to Tissue Growth
ABSTRACT:
Computational modeling has been increasingly used to aid and improve engineering design, fabrication, and manufacturing. In the biomedical field, scientists and clinicians could use computational models to better understand biological phenomena and develop more precise treatment strategies. This thesis employs computational modeling of materials and structures to study two examples in biomedical applications: the development of a patient-specific additively manufactured knee implant and the prediction of an embryonic chick in its first stages of growth. Additive manufacturing (AM) has emerged as an innovative way of manufacturing products of complicated and customized geometries. Bioengineering has a special interest in AM as the possibility of creating patient specific implants that can help increase satisfaction and comfort with procedures. This study explores the use of patient data in combination with finite element modeling and analysis to evaluate the performance of an AM knee implant. The approach is demonstrated on a distal femur replacement for a 50-year-old male patient from the open-access Natural Knee Data. The performance of the implant is influenced by the printing process parameters that are used to print the part. The results show that build orientations have a significant impact on both shape distortions and residual stresses. Understanding the developmental growth from a single cell into a more complex multicellular structure contributes to topics such as tissue engineering and growth defects as well as developing individual treatments. In combination with experimental results, computational analysis can increase the understanding of the behavior of organisms. Morphomechanics are used to create a computational model to simulate the tissue growth in the embryonic chick during the early stages of its development. As the chick embryo develops, the behavior and positioning of the embryo is affected by the membrane in which it develops. The effects of the growth and its surroundings result in a series of coupled bending and twisting of the embryonic body. Using computational modeling in personalized medical implants and developmental biology, this study contributes to the goals of advancing precision health initiatives. Patient-specific implants that are created to be a perfect fit would increase the probability of more patients recovering with diminished pain, increased mobility, and an improvement in their quality of life. The deformation and behavior of biological development supports the research of quantifying health conditions that may result from environmental, developmental, or genetic influences. Understanding these factors supports the advancement of preventative medical research to preserve the health of patients.
ADVISOR:
- Dr. Jun Li, Assistant Professor of Mechanical Engineering, College of Engineering, UMass Dartmouth
COMMITTEE MEMBERS:
- Dr. Wenzhen Huang, Professor of Mechanical Engineering, College of Engineering, UMass Dartmouth
- Dr. Alfa Heryudono, Associate Professor of Department of Mathematics, UMass Dartmouth
Open to the public.
All MNE students are encouraged to attend.
For more information, please contact Dr. Jun Li (jun.li@umassd.edu).
Ms. Stephanie DeCarvalho
DATE:
May 10, 2024
TIME:
1:00 P.M. - 3:00 P.M.
LOCATION:
ZOOM link:
https://umassd.zoom.us/j/91399406281?pwd=aUNpWS8ybFQ5eFNIWlVmRGNjbmlaZz09
(Contact scunha@umassd.edu for Meeting ID and PassCode)
TOPIC:
Computational Modeling of Materials and Structures for Biomedical Applications: from 3D Printed Implants to Tissue Growth
ABSTRACT:
Computational modeling has been increasingly used to aid and improve engineering design, fabrication, and manufacturing. In the biomedical field, scientists and clinicians could use computational models to better understand biological phenomena and develop more precise treatment strategies. This thesis employs computational modeling of materials and structures to study two examples in biomedical applications: the development of a patient-specific additively manufactured knee implant and the prediction of an embryonic chick in its first stages of growth. Additive manufacturing (AM) has emerged as an innovative way of manufacturing products of complicated and customized geometries. Bioengineering has a special interest in AM as the possibility of creating patient specific implants that can help increase satisfaction and comfort with procedures. This study explores the use of patient data in combination with finite element modeling and analysis to evaluate the performance of an AM knee implant. The approach is demonstrated on a distal femur replacement for a 50-year-old male patient from the open-access Natural Knee Data. The performance of the implant is influenced by the printing process parameters that are used to print the part. The results show that build orientations have a significant impact on both shape distortions and residual stresses. Understanding the developmental growth from a single cell into a more complex multicellular structure contributes to topics such as tissue engineering and growth defects as well as developing individual treatments. In combination with experimental results, computational analysis can increase the understanding of the behavior of organisms. Morphomechanics are used to create a computational model to simulate the tissue growth in the embryonic chick during the early stages of its development. As the chick embryo develops, the behavior and positioning of the embryo is affected by the membrane in which it develops. The effects of the growth and its surroundings result in a series of coupled bending and twisting of the embryonic body. Using computational modeling in personalized medical implants and developmental biology, this study contributes to the goals of advancing precision health initiatives. Patient-specific implants that are created to be a perfect fit would increase the probability of more patients recovering with diminished pain, increased mobility, and an improvement in their quality of life. The deformation and behavior of biological development supports the research of quantifying health conditions that may result from environmental, developmental, or genetic influences. Understanding these factors supports the advancement of preventative medical research to preserve the health of patients.
ADVISOR:
- Dr. Jun Li, Assistant Professor of Mechanical Engineering, College of Engineering, UMass Dartmouth
COMMITTEE MEMBERS:
- Dr. Wenzhen Huang, Professor of Mechanical Engineering, College of Engineering, UMass Dartmouth
- Dr. Alfa Heryudono, Associate Professor of Department of Mathematics, UMass Dartmouth
Open to the public.
All MNE students are encouraged to attend.
For more information, please contact Dr. Jun Li (jun.li@umassd.edu).
Topical Areas: Faculty, General Public, Staff and Administrators, Students, Students, Graduate, Students, Undergraduate, University Community, College of Engineering, Mechanical Engineering, Lectures and Seminars