Call us  Contact Us: (937) 431-5100

3040 Presidential Dr. Suite 100 Fairborn, Ohio 45324


AMP2 Simulation Process

AMP² (Additive Manufacturing Parameter Predictor) is an ICME (Integrated Computational Materials Engineering) software suite developed by Applied Optimization (AO) to predict optimized key deposition parameters for the reduction of defects during the powder bed or blown powder additive manufacturing processes. This suite incorporates a number of AO’s software programs to perform a multi-scale analysis of the build across three levels: the macroscale, mesoscale, and microscale. The macro- and mesoscale models are transient simulations that solve for the temperature rise in the built-up material due to the additive process. This temperature profile is then utilized by a steady-state, thermal-CFD microscale simulation to calculate the characteristics and dimensions of the melt pool.

The Simulations Steps in the AMP² Process

Macroscale Model

Macroscale (Part Scale) Model

The macroscale model uses AO’s PowderBedSimulator software to simulate the gradual heat-up of a part as layers are added. It incorporates AbaqusTM (a finite element analysis software) as a solver.


Mesoscale Model

Mesoscale (Layer Scale)

The mesoscale model employs the PowderBedSimulator software. This model simulates the layer-scale temperature rise which accounts for the scan strategy and build heat up due to the deposition of preceding layers. The PowderBedSimulator and a Face Partition plug-in that comes with the PowderBedSimulator are used to set up the layer scale simulation. AbaqusTM also acts as a solver for this model.


Microscale Model

Microscale (Melt Pool Scale)

The microscale model employs AO’s ParaGen (Parameter Generation) software to predict the microscale thermal-fluid interactions of the heat source and melt pool in the formation of an individual track in the interior or adjacent to the boundary of a layer. ParaGen accounts for the local thermal conditions arising from up-skin or down-skin geometry, scan strategy, and the residual heat up due to the deposition of preceding layers. Users can optimize the deposition parameters for a given part to target the mitigation of defects such as lack-of-fusion, key-holing, and surface roughness at specific locations.