Abstract
This paper introduces the use of a Rayleigh backscatter-based distributed fiber optic sensor to map the temperature field in air flow for a thermal fatigue application. The experiment involves a pair of air jets at 22 and 70 °C discharging from 136 mm hexagonal channels into a 1 × 1 × 1.7 m tank at atmospheric pressure. A 40 m-long, ϕ155 µm fiber optic sensor was wound back and forth across the tank midplane to form 16 horizontal measurement sections with a vertical spacing of 51 mm. This configuration generated a 2D temperature map with 2800 data points over a 0.76 × 1.7 m plane. Fiber optic sensor readings were combined with PIV and infrared measurements to relate flow field characteristics to the thermal signature of the tank lid. The paper includes sensor stability data and notes issues encountered using the distributed temperature sensor in a flow field. Sensors are sensitive to strain and humidity, and so accuracy relies upon strict control of both.
Highlights
A typical electric power station uses high-temperature fluids to turn turbines that generate electricity
Velocity data can be obtained with particle image velocimetry (PIV), a familiar optical technique that is well-suited for computational fluid dynamics (CFD) validation since it can generate high-resolution data without disturbing the flow
A later model interrogator, the ODiSI B, has a spatial resolution of 5 mm with a bandwidth of 250 Hz at a maximum sensor length of 2 m or 50 Hz for sensors up to 20 m long. Such data rates are more suitable for the turbulence spectrum expected of the jet-mixing tests, but far less flow field can be covered with these shorter sensors, and so the ODiSi B will be used in future studies for complementary measurements at higher temporal resolution
Summary
A typical electric power station uses high-temperature fluids to turn turbines that generate electricity. Computational fluid dynamics (CFD) tools are being used to simulate fluid/structure interactions to improve understanding and management of thermal cycling in nuclear power system components (Galpin and Simoneau 2011; Hannink and Blom 2011). Broader acceptance of these tools for plant design and licensing will require additional validation against experimental data, especially for cases involving complex interactions between interdependent physical phenomena. A large region of the flow field is mapped at high resolution to capture both local turbulence quantities and large-scale flow structures The former supports physics modeling while the latter reveals flow phenomena at scales that concern
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