Alloy modelling has a history of machine-learning-like approaches, preceding the tide of
data-science-inspired work. The dawn of computational databases has made the integration …

From the past few years, developments of β-Ti alloys have been the subject of active
research in the medical domain. The current paper highlights significant findings in the area …

In this review, some of the latest applicable methods of machine learning (ML) in additive
manufacturing (AM) have been presented and the classification of the most common ML …

The mean stress effect plays an important role in the fatigue life predictions, its influence
significantly changes high-cycle fatigue behaviour, directly decreasing the fatigue limit with …

A neural-network machine called “βLow” enables a high-throughput recommendation for
new β titanium alloys with Young's moduli lower than 50 GPa. The machine was trained by …

The increasing demand for orthopedic implants has driven the search for materials that
combine strength, biocompatibility, and long lifetime. Compared to stainless steel and Co-Cr …

Herein, an extensive review of the design of titanium alloys with low elastic modulus as
implant materials is provided. Due to the high specific strength, low elastic modulus, fatigue …

Recently, the hybrid method has been developed in which wire and arc additive
manufacturing (WAAM) use to produce the near net shape preform for the single-step hot …

This study has successfully formulated artificial neural network models to predict thermal
comfort evaluation in outdoor urban parks in Hong Kong, a sub-tropical city, for both summer …

Artificial neural networks (ANN) models are becoming more popular than mathematical and
transport-based models due to their high performance and accuracy. Previous literature …