Differentiable simulation for material thermal response design in additive manufacturing processes

The flexibility of modern manufacturing processes such as additive manufacturing creates an opportunity to build parts with customized material properties and geometries. However, converting this flexibility into func-tionality requires computational tools that can handle high-dimensional design spaces. In this work, we present a differentiable simulation method for AM processes that is capable of designing time-series laser power that optimizes thermal behaviors of materials, including the overall thermal history and heat treatment time for each material point. We analyze the feasibility of computing gradients using automatic differentiation and their usefulness in AM design tasks. Additionally, our methodology is validated by experimentally testing our designed parts. Our code is made available for the research community at https://github.com/mojtabamozaffar/differ-entiable-simulation-am.

Automated summary

This paper presents a differentiable simulation method for optimizing the thermal behavior of materials in additive manufacturing processes. By using automatic differentiation to compute gradients, high-dimensional design spaces can be handled. The methodology is validated through experimental testing.