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The metal laser powder bed fusion additive manufacturing process uses high power lasers to build parts layer upon layer by melting fine metal powders. Qualification of parts produced using this technology is broadly recognised as a significant challenge. Physics based process models have been identified as being foundational to qualification of additively manufactured metal parts. In the present article, a multiscale modelling strategy is described that will serve as the foundation upon which process control and part qualification can be built. This includes a model at the scale of the powder that simulates single track/single multilayer builds and provides powder bed and melt pool thermal data. A second model computationally builds a complete part and predicts manufactured properties (residual stress, dimensional accuracy) in three dimensions. Modelling is tied to experiment through data mining.

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SUMMARYAn explicit predictor-corrector algorithm is derived from the implicit a-method. This explicit algorithm is shown to have better stability and accuracy properties than its Newmark-based predecessor. This algorithm is then combined with the implicit a-method, resulting in an implicit-explicit a-method which can be effectively utilized for linear and non-linear structural dynamics calculations.

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