Multi-Objective Machine Learning Optimization of Cylindrical TPMS Lattices for Bone Implants

Multi-Objective Machine Learning Optimization of Cylindrical TPMS Lattices for Bone Implants

This study presents a multi-objective optimization framework for designing cylindrical triply periodic minimal surface (TPMS) lattices tailored for bone implant applications. Using an artificial neural network (ANN) as a surrogate model trained on simulated data, four key properties—ultimate stress...

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Bibliographic Details
Main Authors: Mansoureh Rezapourian, Ali Cheloee Darabi, Mohammadreza Khoshbin, Irina Hussainova
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Biomimetics
Subjects:
triply periodic minimal surfaces (TPMS)
bone implants
multi-objective optimization
machine learning
artificial neural network (ANN)
mechanical property prediction
Online Access:https://www.mdpi.com/2313-7673/10/7/475
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