Design and Pre-Test Evaluation of a Low-Pressure Compressor Test Facility for Cryogenic Hydrogen Fuel Integration

Isak Jonsson, C. Xisto, M. Lejon, Anders Dahl, T. Grönstedt
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Abstract

The use of hydrogen as aviation fuel is again resurfacing with unprecedented vigor. It is well known that hydrogen is a formidable heat sink and the use of heat sinks in the compression system of an aero engine may enable not only preheating of the fuel but also improve the gas turbine cycle itself. One such opportunity arises from extracting heat to the fuel as part of the compression process. This work presents the design process and pre-test evaluation of a low-speed compressor test facility dedicated to aerothermal measurements. The design has been derived from a high-speed transonic compressor developed for a large sized geared turbofan engine. The proposed pre-test evaluation methodology provides a comprehensive and affordable way to estimate facility accuracy by virtually addressing all the experimental procedures, from data acquisition to a final performance map. The evaluation of gathering compressor performance parameters via a gas-path investigation process was achieved while relying on results from numerical simulations. The pre-test evaluation details uncertainties introduced throughout this process with transducers, flow and probe specific errors, traverse discretization, and data normalization. A suitable instrumentation configuration is presented which shows that the performance parameters pressure ratio (Π) and isentropic efficiency (ηc) can be determined with uncertainties below 1% for most operating conditions and below 0.5% at design conditions.
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低温氢燃料集成低压压缩机试验装置的设计与预试评估
氢作为航空燃料的使用再次以前所未有的活力重新浮出水面。众所周知,氢是一种强大的散热器,在航空发动机的压缩系统中使用散热器不仅可以使燃料预热,而且可以改善燃气轮机循环本身。其中一个机会是在压缩过程中向燃料中提取热量。本文介绍了一个专用于气动热测量的低速压缩机测试设备的设计过程和测试前评估。该设计源自为大型齿轮传动涡扇发动机开发的高速跨音速压气机。所提出的测试前评估方法提供了一种全面和负担得起的方法,通过解决从数据采集到最终性能图的所有实验程序来估计设施准确性。基于数值模拟结果,通过气路研究过程对聚气压缩机性能参数进行了评估。测试前评估详细说明了整个过程中引入的不确定性,包括传感器、流量和探头特定误差、导线离散化和数据归一化。提出了一种合适的仪器配置,表明在大多数工作条件下,压力比(Π)和等熵效率(ηc)的不确定度在1%以下,在设计条件下,不确定度在0.5%以下。
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