Performance improvements in Stirling cycle machines by a modified appendix gap geometry,International Journal of Energy Research

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Performance improvements in Stirling cycle machines by a modified appendix gap geometry
International Journal of Energy Research ( IF 4.3 ) Pub Date : 2021-09-20 , DOI: 10.1002/er.7237
Jan Sauer ₁ , Hans‐Detlev Kühl ₁

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In this contribution, the optimization potential of the seal geometry in Stirling machines is explored both numerically and analytically, leading to a significant reduction of the related losses which are often referred to as appendix gap losses. These are induced by the narrow gap between the displacer and the cylinder and have mostly been underestimated so far. A recent experimental investigation revealed large optimization potentials by reduction of the seal and cylinder wall diameter near the seal, resulting in reduced appendix gap losses and further indirect positive effects. In this work, these experimental findings could be reproduced by a one-dimensional differential simulation model at a fully satisfyingaccuracy. Furthermore, these investigations reveal that the optimum geometry is largely machine-dependent. To provide an easily applicable design rule for this optimum geometry, a refined analytical model for the mass flow at the top of the gap is derived, which is based on a phasor analysis and a linearized mass balance that also accounts for changes in the spatial mean gas temperature in the gap. The optimum design predicted by this model is very close to numerical optimization results and sufficiently accurate under practical aspects. Furthermore, this model contributes to a better theoretical understanding of the loss mechanisms in the gap.

中文翻译：

通过改进的附件间隙几何形状提高斯特林循环机器的性能

在此贡献中，从数值和分析角度探讨了斯特林机器中密封几何形状的优化潜力，从而显着减少了通常被称为附件间隙损失的相关损失。这些是由置换器和气缸之间的狭窄间隙引起的，迄今为止大多被低估了。最近的一项实验研究表明，通过减小密封件和密封件附近的气缸壁直径，可以实现很大的优化潜力，从而减少附件间隙损失和进一步的间接积极影响。在这项工作中，这些实验结果可以通过一维微分模拟模型以完全令人满意的精度再现。此外，这些调查表明，最佳几何形状很大程度上取决于机器。为了为这种最佳几何形状提供易于应用的设计规则，导出了间隙顶部质量流量的精细分析模型，该模型基于相量分析和线性化质量平衡，也考虑了空间平均值的变化间隙中的气体温度。该模型预测的优化设计与数值优化结果非常接近，并且在实际方面足够准确。此外，该模型有助于更好地理解差距中的损失机制。该模型预测的优化设计与数值优化结果非常接近，并且在实际方面足够准确。此外，该模型有助于更好地理解差距中的损失机制。该模型预测的优化设计与数值优化结果非常接近，并且在实际方面足够准确。此外，该模型有助于更好地理解差距中的损失机制。

更新日期：2021-09-20

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