This paper presents a hybrid snapshot simulation methodology to accelerate the generation of high-quality data for proper orthogonal decomposition (POD) and reduced-order model (ROM) development. The entire span of the snapshot simulation is divided into multiple intervals, each simulated by either high-fidelity full-order model (FOM) or fast local ROM. The simulation then alternates between FOM and local ROM to accelerate snapshot data generation while maintaining the data fidelity and representation. Model switch is determined on-the-fly by evaluating several criteria that monitor the dominance of leading POD modes and ROM trajectory. The incremental singular value decomposition (iSVD) is employed to continuously update ROMs for enhanced accuracy and utilization. A global ROM broadly applicable to various online simulation is immediately available at the end of the simulation. The hybrid snapshot simulation demonstrates excellent accuracy ([Formula: see text] error) and 2.09–2.6[Formula: see text]X speedup relative to its traditional counterpart. The constructed ROMs also preserve salient accuracy ([Formula: see text] error). The results prove feasibility of the proposed method for robust and efficient snapshot data generation and ROM development.

中文翻译：

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基于混合快照仿真的降阶建模

本文提出了一种混合快照模拟方法，以加速为正确的正交分解 (POD) 和降阶模型 (ROM) 开发生成高质量数据。快照模拟的整个跨度被划分为多个区间，每个区间通过高保真全阶模型 (FOM) 或快速本地 ROM 进行模拟。然后模拟在 FOM 和本地 ROM 之间交替，以加速快照数据的生成，同时保持数据的保真度和表示。通过评估监控领先 POD 模式和 ROM 轨迹的优势的几个标准，即时确定模型切换。增量奇异值分解 (iSVD) 用于不断更新 ROM，以提高准确性和利用率。广泛适用于各种在线模拟的全局 ROM 在模拟结束时立即可用。混合快照模拟展示了出色的准确性（[公式：参见文本]错误）和 2.09-2.6[公式：参见文本]相对于其传统对应物的 X 加速。构建的 ROM 还保留了显着的准确性（[公式：见文本]错误）。结果证明了所提出的鲁棒和高效快照数据生成和ROM开发方法的可行性。