Name: Mauro Francisco Arcidiacono
University: University of Strathclyde, PhD
Research Title: Digital Twin for Manufacturing to Improve Mechanical Performance
Area of Research: Construction and experimental validation of physical based models to establish causal relationships between material microstructure, manufacturing routes and properties.
This post is the first of a series of posts showcasing some of the amazing research projects from our community of Lateral pioneers.
I conduct research in computational mechanics in the Design, Manufacturing & Engineering department and I am based at the Advanced Forming Research Centre (AFRC).
Computational mechanics is interdisciplinary and it combines applied mechanics, materials science, computer science, software engineering and applied mathematics. Currently, I am researching crystal plasticity finite element models and constitutive equations to create a digital twin to quantify the residual stresses after manufacturing at a micro and meso scale of Ti64. I am developing synthetic biphasic microstructures with Voronoi tessellations and using UMATs to model in ABAQUS.
In particular, the simulations will represent the flow forming and forging manufacturing processes. The digital twin will allow optimizing manufacturing routes to fabricate microstructures that will maximize fatigue life and crack resistance.
Additionally, the quantification of residual stresses will be fundamental information for design engineers in order to refine safety factors and minimize economic loss.
Invest time in defining a clear and realistic set of research objectives and in planning the steps towards those goals, and then, write this information in a research plan. This will provide you with a long-term vision and it will allow you to allocate time in the most efficient way.
Literature review implies reading a big amount of documents from different authors and then filter and carefully analyse the information. Lateral helps me by keeping my files organized in one place where I can create concepts that are transversal to several articles. By filtering per concept I can easily contrast models, materials, assumptions and more, which is something really helpful when extracting information from a big number of documents.
Additionally, I use the Document Viewer to highlight important information while I am reading and I make notes at the same time.
This post is the fifth of a series of posts showcasing some of the amazing research projects from our community of Lateral pioneers.
This post is the fourth of a series of posts showcasing some of the amazing research projects from our community of Lateral pioneers.