基于特征值标准的最优实验设计与Pyomo.DoE
Optimal Experimental Design using Eigenvalue-Based Criteria with Pyomo.DoE
AI总结：
本文提出基于特征值的最优实验设计方法，通过Pyomo.DoE扩展实现E-最优和ME-最优，提升数字孪生参数方向的建模效率与鲁棒性。
摘要：
数字孪生需要高质量数据以实现预测能力，但时间和资源限制使高效实验设计至关重要。基于模型的实验设计可通过方程导向优化和第一原理模型解决这一挑战。Pyomo.DoE是一个用于高保真方程导向模型最优实验设计的软件包；然而，将矩阵求逆和特征值计算等线性代数操作嵌入这些优化问题仍具挑战性。本文通过回调机制扩展Pyomo.DoE，实现了在方程导向优化框架内严格计算基于特征值的设计指标，包括最小特征值最优性（E-最优）和条件数最优性（ME-最优）。这些新增功能使实验设计可直接聚焦于信息不足或数值问题的参数方向。此外，本文还提出了一种新的实验创建建模抽象，用于Pyomo中的侵入性不确定性量化，通过统一模型和软件抽象降低用户建模工作量。同时，方法部分提供了关于实验设计指标的简要教程。总体而言，本文扩展了Pyomo.DoE中可用的最优设计准则范围，并改进了构建和优化高价值数字孪生的工作流程。
英文摘要：
Digital twins require high-quality data to achieve predictive capability, but time and resource limitations make efficient experiment design essential. Model-based design of experiments can address this challenge, especially when coupled with equation-oriented optimization and first-principles models. Pyomo.DoE is a software package for optimal experimental design of high-fidelity, equation-oriented models; however, embedding linear algebra operations such as matrix inversion and eigenvalue computation within these optimization problems remains difficult. This work extends Pyomo.DoE with callback-based capabilities that enable rigorous computation of eigenvalue-based design metrics, including minimum eigenvalue optimality (E-optimality) and condition number optimality (ME-optimality), within equation-oriented optimization frameworks. These additions allow experimental design to focus directly on poorly informed or numerically problematic parameter directions. We also present a new experiment-creation modeling abstraction for intrusive uncertainty quantification in Pyomo that reduces user modeling effort by aligning model and software abstractions across the digital twin workflow. In addition, a brief tutorial on experimental design metrics is provided in the methodology and supplementary information. Overall, this work expands the range of practical optimal design criteria available in Pyomo.DoE and improves the workflow for building and refining high-value digital twins.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
