Abstract A quantitative understanding of thermal field evolution is vital for quality control in additive manufacturing (AM). Because of the unknown material parameters, high computational costs, and imperfect understanding of the underlying science, physically-based approaches alone are insufficient for component-scale thermal field prediction. Here, we present a new framework that integrates physically-based and data-driven approaches with quasi in situ thermal imaging to address this problem. The framework consists of (i) thermal modeling using 3D finite element analysis (FEA), (ii) surrogate modeling using functional Gaussian process, and (iii) Bayesian calibration based on the thermal imaging data. According to heat transfer laws, we first investigate the transient thermal behavior during AM using 3D FEA. A functional Gaussian process-based surrogate model is then constructed to reduce the computational costs from the high-fidelity, physically-based model. We finally employ a Bayesian calibration method, which compares the surrogate modeling results and thermal measurements, to enable layer-to-layer thermal field prediction across the whole component. A case study on fused deposition modeling is conducted for components with 7 to 16 layers. The cross-validation results show that the proposed framework allows for accurate and fast thermal field prediction for components with different process settings and geometric designs.

中文翻译：

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将基于物理和数据驱动的方法集成到增材制造中进行热场预测

摘要 对热场演化的定量理解对于增材制造 (AM) 的质量控制至关重要。由于未知的材料参数、高计算成本和对基础科学的不完全理解，仅基于物理的方法不足以进行组件规模的热场预测。在这里，我们提出了一个新的框架，它将基于物理和数据驱动的方法与准原位热成像相结合来解决这个问题。该框架包括 (i) 使用 3D 有限元分析 (FEA) 的热建模，(ii) 使用函数高斯过程的替代建模，以及 (iii) 基于热成像数据的贝叶斯校准。根据传热定律，我们首先使用 3D FEA 研究 AM 期间的瞬态热行为。然后构建基于函数高斯过程的代理模型，以降低高保真、基于物理的模型的计算成本。我们最终采用贝叶斯校准方法，该方法比较了替代建模结果和热测量值，以实现整个组件的层到层热场预测。对 7 到 16 层的组件进行了熔融沉积建模的案例研究。交叉验证结果表明，所提出的框架允许对具有不同工艺设置和几何设计的组件进行准确和快速的热场预测。它将替代建模结果和热测量结果进行比较，以实现整个组件的层到层热场预测。对 7 到 16 层的组件进行了熔融沉积建模的案例研究。交叉验证结果表明，所提出的框架允许对具有不同工艺设置和几何设计的组件进行准确和快速的热场预测。它将替代建模结果和热测量结果进行比较，以实现整个组件的层到层热场预测。对 7 到 16 层的组件进行了熔融沉积建模的案例研究。交叉验证结果表明，所提出的框架允许对具有不同工艺设置和几何设计的组件进行准确和快速的热场预测。