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Modelling Additive Manufacturing Processes

Additive manufacturing (AM) is a process whereby three dimensional objects are created layer-by-layer using 3D object scanners or computer aided design. Additive manufacturing offers cost reductions for high-value parts due to the lack of material wastage and can also reduce lead times. In addition, this manufacturing process can improve strength and durability as items can be created as one solid object rather than being assembled from multiple parts. This versatile manufacturing technique is widely used in industries including aerospace, automotive, and medical.

Numerical Modelling and Optimisation at TWI

The Numerical Modelling and Optimisation section at TWI is made up of Chartered Engineers, Chartered Mathematicians and NAFEMS-certified Professional Simulation Engineers. The section offers a variety of computational engineering capabilities including finite element analysis (FEA), computational fluid dynamics (CFD), and data analysis as well as bespoke mathematical modelling capabilities.    

CFD analysis of an AM heat exchanger
CFD analysis of an AM heat exchanger

Additive Manufacturing Simulations

Simulation technology is seen as a key enabling technology for additive manufacturing that allows for:

  • Process parameter and scan strategy optimisation
  • Topology optimisation for light-weighting and enhanced design
  • Residual stress and distortion prediction
  • Defect estimation and integrity assessments
  • Microstructure predictions and material performance

TWI has world-leading AM process simulation capabilities, having received First Prize in the International NIST AM Benchmark competition [1, 2]. TWI’s work on AM modelling has covered almost all metal AM processes (laser powder bed fusion, laser metal deposition, direct energy deposition, and wire-arc additive) along with most material systems (stainless steels, nickel, aluminium, and titanium alloys). Our work has resulted in several, highly-cited, peer-reviewed journal publications [3-5].

Some of the most significant barriers to the wider industrial adoption of AM processes are a lack of reliability and repeatability. To address these challenges, modelling can provide insight into the key influence variables. This helps minimise time-consuming and expensive trial-and-error experimentation.


To that end, TWI has recently delivered over £2M of public-funded R&D related to AM modelling as well as a large number of industrially-funded research and consultancy programmes to help companies leverage emerging modelling capabilities. This work has focused on high-performance AM heat exchangers; topology optimisation to design light-weight, highly efficient parts; and microstructure predictions to change process parameters to achieve better performing parts.


[2] Yang et al, 2019: ‘Residual Strain Predictions for a Powder Bed Fusion Inconel 625 Single Cantilever Part’, Integrating Materials and Manufacturing Innovation, Vol 8.

[3] Q Zhang et al, 2019: ‘Estimates of the mechanical properties of laser powder bed fusion Ti-6Al-4V parts using finite element models’, Materials & Design, Vol 169.

[4] Q Zhang et al 2019: ‘A metallurgical phase transformation framework applied to SLM additive manufacturing processes’, Materials & Design, Vol 166.

[5] M Zavala-Arrendondo et al, 2019: ‘Use of power factor […] as design parameters in laser powder bed fusion of AliSi10Mg’, Materials and Design, Vol 182.

Solidification microstructure prediction for direct energy deposition
Solidification microstructure prediction for direct energy deposition