For the predictions and simulations of energy pile behavior under a combination of thermal and mechanical loads, with a complexity of parameters describing the energy pile, the surrounding soil and their interaction, modelers may be faced with the decision of whether it is better to spend more resource on determining the appropriate value of certain model parameters with high precision or on running more simulations to account for various uncertain input factors. In this study global sensitivity analysis is applied to explore the relative importance of the parameters of interest as model inputs and their contributions to the final results of the energy pile numerical model for different outputs. The interaction of uncertainties between different parameters is also analyzed with second order and total indices. Findings of this study indicate that the sensitivity of numerical energy pile predictions is more complex than previously thought. With a varying external forcing like the mechanical load or temperature change, the influence of input factor (e.g. model parameters) for the predictions of different spatially lumped model outputs is found to change but not always monotonically despite a monotonic variation of the output value. Spatial variability in the influence of the input factors which may be hidden by the spatially lumped analysis is also examined and inhomogeneous distribution of the input factor importance can be revealed along the whole length of the energy pile. The input factors that modelers should prioritize will not only differ depending on the assessed model output, but also on the location of the output and the surrounding circumstances which provide external loads and thermal effects.

对于热负荷和机械负荷共同作用下的能量堆行为的预测和模拟，具有描述能量堆，周围土壤及其相互作用的参数的复杂性，建模者可能会面临以下决定：花更多的钱是否更好资源，以高精度确定某些模型参数的适当值，或运行更多模拟以解决各种不确定的输入因素。在这项研究中，采用全局敏感性分析来探索目标参数作为模型输入的相对重要性，以及它们对不同输出的能量堆数值模型最终结果的贡献。还使用二阶和总指数分析了不同参数之间不确定性的相互作用。这项研究的结果表明，数值能桩预测的敏感性比以前认为的要复杂。随着机械力或温度变化等外部力的变化，尽管输出值具有单调变化，但输入因子（例如模型参数）对不同空间集总模型输出的预测的影响却发生了变化，但并不总是单调变化。还检查了可能被空间集总分析隐藏的输入因子影响的空间变异性，并且可以显示出沿能量堆的整个长度输入因子重要性的不均匀分布。建模人员应优先考虑的输入因素不仅会因评估的模型输出而有所不同，