Erik
Haapa
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Areas of expertise
Biography
B.A.Sc.; Energy and environmental engineering (energy generation and distribution systems)
M.Sc.; Materials engineering (materials in energy technology)
Erik Haapa works and has worked in projects dealing with industrualisation of AM and academia-industry cooperation in Finland. His role also involves teaching annually in the M.Sc. level AM courses KTEK0012 and KTEK0063, especially on topics of the characteristics of and design strategies for different AM technologies, process modeling, industry outlook and economics, and supervision of student projects.
He is a metal AM technology enthusiast and frequenter of Formnext AM trade fairs, especially interested in practical industrial AM application; optimisation of the process and its integration into manufacturing chains.
Research in his doctoral studies is focused on simulation-based process optimisation and application to novel/challenging materials such as refractories/tungsten, multi-materials, and shape memory alloys. The simulation tools used are computational fluid dynamics (CFD) of the melt pool during laser material interaction, and discrete element method (DEM) simulation of powder particle behavior.
Current project of employment: EU funded project "Metallituotteen uusi elämä" (industrialisation and life cycle analysis of repair of metal products using DED processes)
Teaching
Lecturing/lab supervision in courses "3D printing and additive manufacturing" and "Advanced additive manufacturing", "Teolliset valmistusmenetelmät".
Research
Researching simulation of PBF-LB/M and other AM processes; from powder particle behavior and the powder bed layering to the laser-material interaction.
The work includes development and application of validation methods, workflows for single track, or multi-layer, or multi-material modeling, microstructure prediction, melt pool stability assessment, and parameter optimisation. Work is especially focused on enabling the application of AM to challenging or novel materials in industrially relevant processing conditions.
Simulation is also applied to understanding AM processes and linking data from real life process monitoring to certain thermo-fluid or kinetic behaviour of the melt pool or powder particles.