The accurate measurement of total temperature in engine diagnostics is a challenging task which is subject to several sources of error. Conduction error is predominant among these sources since total temperature sensors are embedded into a cooled strut for measurement. This study seeks to understand the effect of conduction error on total temperature probe performance from an analytical and experimental standpoint and to provide an effective calibration procedure. The review of historical low-order models, as well as results from a developed thermal resistance model, indicates that conduction error is driven by dimensionless parameters, including the Biot, Nusselt, and Reynolds Numbers, as well as a non-dimensional temperature characterizing the flow/strut temperature difference. A conduction error calibration procedure for total temperature probes is experimentally tested in this study. Data were acquired for nominal flow total temperatures ranging from 550 °F to 850 °F with the probe Reynolds number varying from 2,000 to 12,000 for varying conduction conditions with axial temperature gradients up to 1150 °F per inch. A physics-based statistical model successfully expressed total temperature probe performance as a function of dimensionless conduction driver and probe Reynolds number. This statistical model serves as a “calibration surface” for a particular total temperature probe. Due to the scaling of the problem, this calibration is experimentally obtained in moderate temperature regimes, then implemented in higher temperature regimes. The calibration yields an overall uncertainty in total temperature measurement to be ±4% of the total temperature for flow conditions typical in engine diagnostics, with extreme uncertainties in input conditions. Conduction error is successfully shown to be independent of any temperature regime and driven by dimensionless parameters. / Master of Science

<p>The present work relates to a new procedure, to perform temperature measurements with unprecedented accuracy. The new approach relies on a correction based on a two-wire probe thermocouple that enables a precise estimation of the conduction error. The difference between measured temperature by a thermocouple and total gas temperature for steady conditions can be decomposed into three main contributions: velocity error, conduction error and radiation error. Radiation error can be considered negligible for temperatures lower than 800K. The velocity error can be corrected using dedicated experimental calibrations to measure the recovery factor. However, the conduction error, remains an unresolved challenge in the aerospace and power-energy community. The proposed method includes a comprehensive correction with different options for the postprocessing. The method has been demonstrated using high-fidelity aero-structural computational simulations.</p>

Human body temperature is an important indicator of physical performance and condition in terms of comfort, heat or cold stress. The aim of this research was to develop Temperature Sensing Fabric (TSF) for continuous temperature measurement in healthcare applications. The study covers the development and manufacture of TSF by embedding fine metallic wire into the structure of textile material using a commercial computerised knitting machine. The operational principle of TSF is based on the inherent propensity of a metal wire to respond to changes in temperature with variation in its electrical resistance. Over 60 TSF samples were developed with combinations of different sensing elements, two inlay densities and highly textured polyester yarn as the base material. TSF samples were created using either bare or insulated wires with a range of diameters from 50 to 150 μm and metal wires of nickel, copper, tungsten, and nickel coated copper. In order to investigate the Temperature-Resistance (T-R) relationship of TSF samples for calibration purposes, a customised test rig was developed and monitoring software was created in the LabVIEW environment, to record the temperature and resistance signals simultaneously. TSF samples were tested in various thermal environments, under laboratory conditions and in practical wear trials, to analyse the relationship between the temperature and resistance of the sensing fabric and to develop base line specifications such as sensitivity, resistance ratio, precision, nominal resistance, and response time; the influence of external parameters such as humidity and strain were also monitored. The regression uncertainty was found to be less than in ±0.1°C; the repeatability uncertainty was found to be less than ±0.5°C; the manufacturing uncertainty in terms of nominal resistance was found to be ± 2% from its mean. The experimental T-R relationship of TSF was validated by modelling in the thermo-electrical domain in both steady and transient states. A maximum error of 0.2°C was found between the experimental and modelled T-R relationships. TSF samples made with bare wire sensing elements showed slight variations in their resistance during strain tests, however, samples made with insulated sensing elements did not demonstrate any detectable strain-dependent-resistance error. The overall thermal response of TSF was found to be affected by basal fabric thickness and mass; the effect of RH was not found to be significant. TSF samples with higher-resistance sensing elements performed better than lower-resistance types. Furthermore, TSF samples made using insulated wire were more straightforward to manufacture because of their increased tensile strength and exhibited better sensing performance than samples made with bare wire. In all the human body wear trials, under steady-state and dynamic conditions both sensors followed the same trends and exhibited similar movement artifacts. When layers of clothing were worn over the sensors, the difference between the response of the TSF and a high-precision reference temperature were reduced by the improved isothermal conditions near the measurement site.