Computational cost of high-fidelity simulations limits the number of evaluations which may be performed in design exploration and optimization. Surrogates based on samples of multiple fidelities are used to decrease computational cost and lower error from single-fidelity surrogates. This paper develops a novel multi-fidelity surrogate model based on principal components which are shared between multiple fidelities of finite element model samples. This method does not require a common grid between the fidelities, further reducing computational cost. The new method was tested on various design spaces of the Transonic Purdue Research Compressor and compared to other common and novel multi-fidelity methods. The new method was more accurate and required less computational cost than the other tested methods. Little to no increase in computational cost was needed to reduce surrogate error to 50% of the single-fidelity error. For fixed error, the computational cost was reduced by more than 75%. These results were also validated by testing the method on a more complex turbomachinery blade, Parametric Blade Study Rotor 4. The decreased error and computational cost improve effectiveness of design exploration and optimization. Such improvements help meet the demand for cleaner and safer engines by allowing high-fidelity design exploration within reasonable time frames.

高保真仿真的计算成本限制了可以在设计探索和优化中执行的评估数量。基于多个保真度样本的代理人可用于降低计算成本，并降低来自单保真度代理人的误差。本文基于有限元模型样本的多个保真度之间共享的主成分，开发了一种新颖的多保真度替代模型。此方法不需要保真度之间的公共网格，从而进一步降低了计算成本。该新方法已在Transonic Purdue Research Compressor的各种设计空间上进行了测试，并与其他常见和新颖的多保真方法进行了比较。与其他经过测试的方法相比，该新方法更加准确，并且所需的计算成本更低。将代理误差降低到单保真度误差的50％时，几乎不需要增加计算成本。对于固定错误，计算成本降低了75％以上。这些结果也通过在更复杂的涡轮机叶片参数叶片研究转子4上测试该方法而得到验证。减少的误差和计算成本提高了设计探索和优化的效率。通过在合理的时间范围内进行高保真设计探索，此类改进有助于满足对更清洁，更安全的发动机的需求。减少的误差和计算成本提高了设计探索和优化的效率。通过在合理的时间范围内进行高保真设计探索，此类改进有助于满足对更清洁，更安全的发动机的需求。减少的误差和计算成本提高了设计探索和优化的效率。通过在合理的时间范围内进行高保真设计探索，此类改进有助于满足对更清洁，更安全的发动机的需求。