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IN AIRCRAFT TESTING, it has been difficult to accurately determine small differential temperatures in mediums such as engine oils and aircraft fuels which may vary in temperature over several hundred degrees. A method of measuring this temperature with an electronic circuit utilising platinum probes is presented which is capable of measuring temperature differentials as low as 2.5°C. This method utilises two platinum element probes connected in series driven by a constant current generator. An electronic circuit holds the mid‐point of the probes at virtual ground minimising common mode voltages across the probes. A differential amplifier provides an output proportional to the differential temperature. The mis‐matching and non‐linearity of the platinum sensors is compensated. Voltage sensed across one probe provides an output proportional to the temperature of the medium.

The purpose of this paper is to employ the Generalized Integral Transform Technique in the analysis of conjugated heat transfer in micro-heat exchangers, by combining this hybrid numerical-analytical approach with a reformulation strategy into a single domain that envelopes all of the physical and geometric sub-regions in the original problem. The solution methodology advanced is carefully validated against experimental results from non-intrusive techniques, namely, infrared thermography measurements of the substrate external surface temperatures, and fluid temperature measurements obtained through micro Laser Induced Fluorescence.

The methodology is applied in the hybrid numerical-analytical treatment of a multi-stream micro-heat exchanger application, involving a three-dimensional configuration with triangular cross-section micro-channels. Space variable coefficients and source terms with abrupt transitions among the various sub-regions interfaces are then defined and incorporated into this single domain representation for the governing convection-diffusion equations. The application here considered for analysis is a multi-stream micro-heat exchanger designed for waste heat recovery and built on a PMMA substrate to allow for flow visualization.

The methodology here advanced is carefully validated against experimental results from non-intrusive techniques, namely, infrared thermography measurements of the substrate external surface temperatures and fluid temperature measurements obtained through Laser Induced Fluorescence. A very good agreement among the proposed hybrid methodology predictions, a finite elements solution from the COMSOL code, and the experimental findings has been achieved. The proposed methodology has been demonstrated to be quite flexible, robust, and accurate.

The hybrid nature of the approach, providing analytical expressions in all but one independent variable, and requiring numerical treatment at most in one single independent variable, makes it particularly well suited for computationally intensive tasks such as in optimization, inverse problem analysis, and simulation under uncertainty.

This purpose of this paper is to report about the temperature distribution in metal and ceramic powder beds during 3D printing. The differing powders are thoroughly characterized in terms of thermal conductivity, thermal diffusivity, emissivity spectra and density.

The temperature distribution was measured in a 3D printing appliance (Prometal R1) with the help of thin thermocouples (0.25 mm diameter) and thermographic imaging. Temperatures at the powder bed surface as well as at differing powder bed depths were determined. The thermal conductivity, thermal diffusivity and emissivity spectra of the powders were measured as well. Numerical simulation was used to verify the measured temperatures.

The ceramic powder heated up and cooled down more quickly. This finding corresponds well with numerical simulations based on measured values for thermal conductivity and thermal diffusivity as well as emissivity spectra. An observed color change at the metal powder has only little effect on emissivity in the relevant wavelength region.

It was found that thermocouple‐based temperature measurements at the powder bed surface are difficult and these results should be considered with caution.

The results give practitioners valuable information about the transient temperature evolution for two widely used but differing powder systems (metal, ceramic). The paramount importance of powder bed porosity for thermal conductivity was verified. Already small differences in thermal conductivity, thermal diffusivity and hence volumetric heat capacity lead to marked differences in the transient temperature evolution.

The paper combines several techniques such as temperature measurements, spectral emissivity measurements, measurements of thermal conductivity and diffusivity and density measurements. The obtained results are put into a numerical model to check the obtained temperature data and the other measured values for consistency. This approach illustrates that determinations of surface temperatures of the powder beds are difficult.

In response to the common low sensitivity of fiber Bragg grating (FBG) temperature sensors in measurement, an FBG temperature sensor sensitized in a substrate-type package structure is proposed.

The sensitivity of sensors is analyzed theoretically; aluminum alloys with large coefficient of thermal expansion are used; the ANSYS software is used for simulation analysis and optimization design of sensors; real sensors are developed based on simulation results; in this study, a test system was built to test the performance of the proposed sensor.

The results suggested that the sensitivity of encapsulated FBG temperature sensor is 27.3 pm/°C in the range of −20 °C to 40 °C, which is 2.7 times that of bare FBG sensor, while the linearity is up to more than 0.99.

The sensitivity of FBG temperature sensor is greatly improved by the design of the structure.

This study innovatively proposes substrate-type sensitized FBG temperature sensor. The temperature sensitivity of fiber grating can be improved by single metal structure, and the effect of structural strain can be reduced by a tab structure. The study results provide a reference for the development of like sensors and the further improvement in the sensitivity of FBG temperature sensors.

This paper discusses an algorithm for phase change front identification in continuous casting. The problem is formulated as an inverse geometry problem, and the solution procedure utilizes temperature measurements inside the solid phase and sensitivity coefficients. The proposed algorithms make use of the boundary element method, with cubic boundary elements and Bezier splines employed for modelling the interface between the solid and liquid phases. A case study of continuous casting of copper is solved to demonstrate the main features of the proposed algorithms.

The purpose of this paper is to develop a transform method and a deep learning model to identify the inner surface shape based on the measurement temperature at the outer boundary of the pipe.

The training process is assisted by the finite element method (FEM) simulation which solves the direct problem for the data preparation. To avoid re-meshing the domain when the inner surface shape varies, a new transform method is proposed to transform the shape identification problem into the effective thermal conductivity identification problem. The deep learning model is established to set up the relationship between the measurement temperature and the effective thermal conductivity. Then the unknown geometry shape is acquired by the mapping between the inner shape and the effective thermal conductivity through the inverse transform method.

The new method is successfully applied to identify the internal boundary of a pipe with eccentric circle, ellipse and nephroid inner geometries. The results show that as the measurement points increased and the measurement error decreased, the results became more accurate. The position of the measurement point and mesh density of the FEM model have less effect on the results.

The deep learning model and the transform method are developed to identify the pipe inner surface shape. There is no need to re-mesh the domain during the computation progress. The results show that the proposed method is a fast and an accurate tool for identifying the pipe inner surface.

The purpose of this paper is to calibrate the surface emissivity of micro drill bit and to investigate the effect of different drilling parameters on the temperature of micro drill bit in printed circuit board (PCB) micro drilling process.

The surface emissivity of micro drill bit was obtained by experiments. Analysis of variance (ANOVA) was applied in this study to analysis the effect of different drilling parameters on the temperature of micro drill bit in PCB micro hole drilling. The most significant influencing factor on micro drill bit temperature was achieved by ANOVA.

First, the surface emissivity of cemented carbide rod decreased from 0.4 to 0.32 slowly with temperature in the range of 50-220°C. Second, the most significant influencing factor on the micro drill bit temperature was spindle speed among the drilling parameters including spindle speed, retract rate and infeed rate.

In this paper, the influence of roughness of black coating, carbide rod and micro drill bit on the surface emissivity calibration and the temperature measurement was not considered.

A new simple method has been presented to calibrate the surface emissivity of micro drill bit. Through calibrating the surface emissivity of micro drill bit, the temperature of micro drill bit can be measured accurately by infrared thermometry. Analyzing the influences of different drilling parameters on the temperature of micro drill bit, the mechanism of drilling parameters on drilling temperature is achieved. The basis for the selection of drilling parameters to improve the hole quality is enhanced.

This paper aims to examine the use of a commercial pyrometer to measure the surface temperature of workpieces as machining takes place. The pyrometer readings are to be compared with model predictions.

The pyrometer was mounted on an industrial milling machine and the temperature of the workpiece was measured behind the cutting tool as it traversed the workpiece. A mathematical spreadsheet model was used to predict the temperatures at the point measured by the pyrometer and at the point where cutting took place.

It was found by selecting the “partition ratio” of the power being transmitted to the workpiece that agreement could be found between measured and predicted results.

The work was mainly carried out on aluminium samples, which exhibited low cutting temperatures.

The paper describes a method of finding the partition ratio of heat going into the workpiece.

The purpose of this paper is to provide the method and system to conduct online measurement and the characterization of temperature during printed circuit board (PCB) routing process as well as the optimization of router design based on the investigation of routing temperature.

The background of this research is introduced first. Then the method to measure the routing temperature on-line by using an infrared camera is presented. The routing process is characterized by investigating the routing temperature. Tool design optimization is conducted based on the temperature in processing PCB with aluminum substrate. Finally the concluding remarks of this research are presented.

The routing temperature can be accurately measured by an infrared camera. Routing temperature is sensitive to properties of PCB, types of router and routing parameters. Very high temperature is experienced if non-appropriate routers are used to process board with aluminum substrate. It is demonstrated by the experiments that two fluted tool, three fluted tool and coated tool with three flutes are suitable for aluminum substrate processing by considering the low temperature and the nice surface finish.

The paper highlights the key points to measure the routing temperature on-line by an infrared camera and characterize the routing process and optimize the tool design by investigating the measured temperature as well.

The aim of the study is the question, that is, which evaluation method for the measured temperature profile is more suitable and feasible for quantitative thermometry (QT): A simple measurement setup based on 3-point temperature sensing by means of semiconductor sensors (NTCs) or thermographic methods which offer 2-dimensional (2D) temperature measurements of the sample with good spatial resolution but an inferior temperature sensitivity. What experimental effort is required to adjust the test setup to satisfy the boundary conditions of the underlying thermodynamic equations?

In this paper results of both methods are contrasted and the error of QT measurement is assessed by finite element analysis (FEA) in this follow-up.

The low-cost NTC method allows a straightforward determination of a lower estimate of the fatigue strength with only a very small measurement error. Even asymmetries in the thermal boundary conditions of the test setup are broadly tolerated, as well as a lack of thermal isolation.

The method is restricted to metallic materials without phase transitions during fatigue in the fatigue strength regime.

QT is not a new method. The assessment of the methods proposed in the literature regarding their practicability in terms of accuracy is innovative focus of this work. Nevertheless, highly accurate thermometric measurements can be performed by using simple commercial sensors in combination with a standard digital multimeter.