A design optimization framework for process parameters of additive manufacturing based on finite element simulation is proposed. The finite element method uses a coupled thermomechanical model developed for fused deposition modeling from the authors' previous work. Both gradient-based and gradient-free optimization methods are proposed. The gradient-based approach, which solves a PDE-constrained optimization problem, requires sensitivities computed from the fully discretized finite element model. We show the derivation of the sensitivities and apply them in a projected gradient descent algorithm. For the gradient-free approach, we propose two distinct algorithms: a local search algorithm called the method of local variations and a Bayesian optimization algorithm using Gaussian processes. To illustrate the effectiveness and differences of the methods, we provide two-dimensional design optimization examples using all three proposed algorithms.

翻译：本文提出了一种基于有限元仿真的增材制造工艺参数优化设计框架。该有限元方法采用作者前期工作中为熔融沉积建模开发的耦合热力学模型。本研究提出了基于梯度和无梯度两类优化方法。基于梯度的方法通过求解偏微分方程约束优化问题，需要利用全离散有限元模型计算灵敏度。我们推导了灵敏度的数学表达式，并将其应用于投影梯度下降算法。对于无梯度方法，我们提出了两种不同的算法：一种名为局部变分法的局部搜索算法，以及一种基于高斯过程的贝叶斯优化算法。为展示这些方法的有效性与差异性，我们使用所有三种算法提供了二维设计优化算例。