Development and characterization of a nano-scale temperature sensor (T-NSTAP) for turbulent temperature measurements

Gilad Arwatz, Yuyang Fan, Carla Bahri, Marcus Hultmark

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

A new nano-scale temperature sensor (T-NSTAP) is presented. The T-NSTAP is a sub-miniature, free-standing, platinum wire suspended between silicon supports, designed for temperature measurements at high frequencies. The new sensor is designed to have a bandwidth far superior to that of conventional cold-wires, which in combination with its small size, minimizes the effect of temporal and spatial filtering on the data. Unfiltered data allows for unique investigations of the scalar turbulence, including the dissipation range. Temperature measurements were conducted with the T-NSTAP in a heated grid-turbulence setup, with constant mean temperature gradient, and compared to data acquired with a conventional cold-wire. It is shown that the cold-wire signal is significantly attenuated over a broad range of frequencies, including lower frequencies. The attenuation has a direct and substantial effect on the measured variances and the estimated scalar rate of dissipation. The observed differences between the conventional cold-wire and the T-NSTAP are compared to what is predicted by a cold-wire model with convincing agreement over the entire spectrum. A close to perfect agreement between the two sensors is shown when the cold-wire data is corrected for end-conduction effects using the cold-wire model. In addition, a frequency content analysis of the probability density function of the temperature and its derivative is performed with direct comparison between the cold-wire and the T-NSTAP.

Original languageEnglish (US)
Article number035103
JournalMeasurement Science and Technology
Volume26
Issue number3
DOIs
StatePublished - Mar 1 2015

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Applied Mathematics

Keywords

  • NSTAP
  • cold-wire
  • grid turbulence
  • temperature
  • temporal filtering

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