Measurement Of Temperature Distribution Research Articles

State of health estimation of lithium-ion battery cell based on optical thermometry with physics-informed machine learning

Effective thermal management and accurate state of health (SOH) estimation of lithium-ion batteries is crucial for ensuring their safety, reliability, and longevity. This study presents three innovative physics-informed machine learning-based SOH estimation techniques trained and demonstrated using experimental temperature data. Temperature distribution measurements were obtained using optical frequency domain reflectometry with optical fibers embedded in a cylindrical lithium-ion battery cell under various SOH. One of the trained model accurately predicted the SOH of a cell within 2% with only a 10-minute measurement. This technique also enables the estimation of SOH for individual cells connected in series or parallel within a battery module or pack simultaneously, thereby reducing the overall SOH estimation uncertainty without the need for disassembly. Furthermore, this not only highlights the necessity of precise thermal management in maintaining battery health but also offers a practical and efficient solution for real-time SOH monitoring in battery systems.

An Elemental Abundance Diagnostic for Coordinated Solar Orbiter/SPICE and Hinode/EIS Observations

Plasma composition measurements are a vital tool for the success of current and future solar missions, but density- and temperature-insensitive spectroscopic diagnostic ratios are sparse, and their underlying accuracy in determining the magnitude of the first ionization potential (FIP) effect in the solar atmosphere remains an open question. Here we assess the Fe viii 185.213 Å/Ne viii 770.428 Å intensity ratio that can be observed as a multispacecraft combination between Solar Orbiter/SPICE and Hinode/EUV Imaging Spectrometer (EIS). We find that it is fairly insensitive to temperature and density in the range of log (T/K) = 5.65–6.05 and is therefore useful, in principle, for analyzing on-orbit EUV spectra. We also perform an empirical experiment, using Hinode/EIS measurements of coronal fan loop temperature distributions weighted by randomly generated FIP bias values, to show that our diagnostic method can provide accurate results as it recovers the input FIP bias to within 10%–14%. This is encouraging since it is smaller than the magnitude of variations seen throughout the solar corona. We apply the diagnostic to coordinated observations from 2023 March and show that the combination of SPICE and EIS allows measurements of the Fe/Ne FIP bias in the regions where the footpoints of the magnetic field connected to Solar Orbiter are predicted to be located. The results show an increase in FIP bias between the main leading polarity and the trailing decayed polarity that broadly agrees with Fe/O in situ measurements from Solar Orbiter/Solar Wind Analyser. Multispacecraft coordinated observations are complex, but this diagnostic also falls within the planned wavebands for Solar-C/Extreme UltraViolet high-throughput Spectroscopic Telescope.

Flame temperature and emissivity distribution measurement of solid propellant based on clustering analysis of multispectral radiation images.

To measure the combustion parameters of a solid propellant, this Letter researches the fitting method for flame temperature and emissivity based on multispectral images and proposes the particle swarm optimization-K-means (PSO-K-means) clustering optimization algorithm of a flame multispectral image. Considering the difference in flame radiation characteristics in different regions, the flame multispectral image is clustered, and spectra in different regions are analyzed and selected in different fitting bands to inverse temperature and emissivity. On this basis, the method is applied to measure solid propellant combustion parameters with different formulations. The measurement shows that the flame temperature is between 1700 and 2100 K, and the emissivity is concentrated in 0.1-0.5. Compared with temperature measurements obtained from tungsten-rhenium thermocouples, the relative deviation of multispectral imaging thermometry is less than 5%. The distribution characteristics of solid propellant combustion parameters with different formulations were analyzed, which provided important data support for evaluating combustion conditions and optimizing solid propellant formulations.

Upconverting thermal history paint for investigations of short thermal events

The main goal of the work was to develop phosphorescent coating for investigations of surface temperature distribution resulted from short duration and high energy thermal events such as small rocket engine testing. For that purpose, we developed thermal history paint with upconverting Gd2O3: Er3+, Yb3+, Mg2+ nanopowder. The developed paint was heated by Joule effect with precise control over temperature and heating time. Photoluminescence signal of cooled samples was excited with 980 nm laser and collected in automatic manner with use of an optical fibre probe connected to photospectrometer. The results show that irreversible changes of paint emission are temperature and heating time specific for calcination temperatures from 700 °C to 1150 °C. Calibration curves were prepared for heating times of 10, 60 and 180 seconds. Finally, 2D surface temperature samples were determined with use of upconverting thermal history paint and compared to IR camera and pyrometric measurements. The results indicate that uncertainty of temperature measurement below 10 °C was achieved for temperatures above 1000 °C. It has been demonstrated that developed thermal history paint allows for measurements of 2D surface temperature distribution with high spatial resolution and good agreement to standard measurements techniques like thermal camera and pyrometer.

Measurement and prediction of vertical temperature distribution above urban building roofs at an ultra-microenvironment scale

Microenvironment is critical for building thermal performance. Heat transfer through building envelope (such as roof and window) and mass transfer through building mechanical systems that are adjacent to building surfaces (such as roof-top unit) are influenced directly by the air conditions near the surfaces (e.g., within 1.5 m). These air environments are within the sublayer of the air thermal boundary layer around the buildings – here defined as ultra-microenvironments, to be distinct from the conventional microenvironment scale of 2–5 m from building surfaces. This study particularly investigates the vertical temperature profiles within the ultra-microenvironments above urban building roofs. Field tests were conducted on two roof tops in Wuhan, China and Boulder, US, respectively. Consistent vertical air temperature profiles above the roofs were observed for both days and nights. The study further identifies one recent above-roof air temperature model and validates it with the field test data, which can effectively predict the vertical air temperature at various heights within the ultra-microenvironment above the roof. Applications of this model using different local and climate data including weather station data are analyzed and discussed, along with their performance on prediction accuracy.

Evaluation of aerial thermography for measuring the thermal transmittance (U-value) of a building façade

In efforts to mitigate greenhouse gas emissions in the construction sector, policies promoting energy efficiency improvements in existing buildings are being implemented. Accurately assessing the impact of energy retrofit strategies requires precise determination of thermal envelope performance through energy audits. Aerial thermography, employing unmanned aerial vehicles (UAVs) equipped with infrared thermal cameras (IRT), is an underused method overcoming limitations in energy audits of large buildings or complexes. This approach offers an elevated perspective, providing an overview of the building’s thermal patterns, aiding in the identification of thermal envelope defects. By measuring temperature distribution, even in inaccessible envelope areas, the severity of identified defects can be estimated. Beyond detecting thermal bridges, air leaks, and moisture, aerial thermography is valid for estimating thermal transmittance (U-value) of enclosures. The aim of this research is to evaluate this method to calculate the U-value of the façade of an university building located in a Subtropical Mediterranean climate, during a typical full day in different seasons of the year. Concurrently with aerial thermography, the thermometric method (THM) was applied to compare results and refine the operational conditions during U-value measurement using different statistical indices and uncertainty analysis. The results demonstrated the validation of airborne thermography as a method for U-value calculation under specific meteorological and operational conditions, overcoming the common physical limitations of traditional building audit methods.

Toroidal mean flow and complex temperature distribution in a thermoacoustic core

Increasing the capacity of thermoacoustic machines (engines or refrigerators) requires increasing the diameter of the regenerator, which may result in non-uniform temperature distributions inside the regenerator. In the current study, the temperature is measured at different radial and axial locations inside the regenerator of a thermoacoustic refrigerator with a diameter of 148 mm. The working gas is a mixture of helium and Argon at a static pressure of 40 bar. Non-uniform radial temperature distributions are observed at different axial positions. Also, the predicted axial temperature distributions by a 1-D linear model (DeltaEC) do not agree with the measured temperature distributions. We suspect that the non-uniform radial temperature distribution generates a steady flow through the regenerator which increases the radial temperature non-uniformity and results in non-linear axial temperature distribution. Given the measured temperature distribution, the presence of a toroidal steady flow inside the regenerator is suspected. To confirm this hypothesis, the regenerator is divided into three segments connected in parallel in the DeltaEC model. Mean flows are added in each segment of the regenerator to simulate the presence of toroidal flow in the regenerator. The predicted temperature distributions from this modified DeltaEC model agree with the measured temperature distributions.

Validity of the quasi-2D optimal variable density lattice for effective liquid cooling based on Darcy–Forchheimer theory

In this study, we investigate the validity of variable-lattice-density optimization based on the Darcy–Forchheimer theory for an effective liquid-cooling quasi-2D structure including experimental verification. The unit lattice features a simple cylinder shape, and its size distribution is optimized. Considering its anisotropy, we regard Darcy’s permeability, Forchheimer’s drag coefficient, and the effective thermal conductivity as tensors and calculate these effective properties using the representative-volume-element method. Two types of optimizations are performed, i.e., minimizing the surface temperature and maximizing the flow rate, using the gradient method. We examine the results using three methods: an approximate simulation based on the Brinkman–Forchheimer equation, a detailed simulation based on the Navier–Stokes equation, and an experiment. We focus primarily on the exact measurement of planar temperature distribution using thermocouples. The proposed methodology exhibits high accuracy in regions with a certain flow level, although the error can be significant in low-flow regions.

Temperature distribution inversion in infrared multispectral imaging based on ensemble network.

Temperature distribution can be acquired through non-contact temperature measurement using multispectral imaging. However, the challenge lies in radiometric temperature inversion owing to the unknown emissivity. Despite the promising results demonstrated by traditional algorithms and neural networks, enhancing the precision and reliability of temperature inversion remains a challenge. To tackle these challenges, in this work, we propose the use of ensemble learning for temperature distribution inversion in infrared multispectral imaging. The network comprises a base-learner and a meta-learner, trained to establish the nonlinear relationship between temperature and multispectral distribution measurements. Moreover, the network architecture exhibits high robustness against noise arising in the testing environment. Simulations and real experiments on multispectral imaging measurements illustrate that ensemble learning can be a potent tool for multispectral imaging radiation temperature distribution measurement, achieving superior inversion performance compared to other neural networks. The reproducible code will be available at https://github.com/shuowenyang/Temperature-Inversion.

Thermal mixing and structure of the jet in swirling crossflow

The dilution zone in modern aero-engine combustors is characterized by a strong swirling mainstream with weak transverse jets. This characteristic brings new challenges in homogenizing the temperature distribution at the combustor exit. Therefore, it is imperative to understand the temperature penetration and mixing process of the jet in swirling crossflow (JISCF). This investigation provides new insight in the temperature mixing process for a JISCF in nozzle exit diameter (D) at 7.4, 10.7, and 14 mm and jet to mainstream velocity ratio (VR) from 2.0 to 6.6. The temperature mixing process was measured in a specially designed optical assessable three-dome model gas turbine combustor by planar 1-methylnaphthalene (1-MN) tracer laser-induced fluorescence thermometry. A detailed quantitative measurement of temperature distribution is achieved through the spectral red shift in the fluorescence of 1-MN as the temperature increase. This diagnostic was employed to provide the first two-dimensional temperature distribution for the JISCF. The results showed that the swirling crossflows induce strong spanwise thermal advection, forming secondary low-temperature regions downstream. Generally, the flow structure and mixing process are governed by the interaction of jet and swirling flow. The jet flow parameters, including velocity ratio and diameter, changed the flow structures by changing the interaction between jet and swirling flow. Statistical results and proper orthogonal decomposition (POD) analyses showed a strong anisotropic mixing process in the downstream of the jet.

Measurement of engine exhaust plume temperature and concentration distributions with tomographic absorption spectroscopy and learning-based absorbance recovery

Measuring the spatial distribution of temperature and species concentration is important to the thermodynamic analysis and validation of modern combustion systems. In this work, we developed a measurement method based on tomographic absorption spectroscopy (TAS) for the quantitative measurement of two-dimensional distributions of gas temperature and concentration. A learning-based absorbance recovery method was proposed and incorporated into TAS to address the baseline error induced distortion of absorbance and improve the accuracy of single path measurement. The developed TAS system, consisting of 12 laser beams, was demonstrated on a diesel fueled small turbojet engine. Temperature and H2O concentration distributions of the exhaust plume were measured with laser wavelength scan rates of 20 kHz. Temperature variations in microsecond-scale were captured and the time-averaged center temperature agreed well with thermocouple measurements. The developed TAS method demonstrates the feasibility of real-time and accurate tomographic imaging for practical combustion flows, which could be effectively applied for widespread combustion diagnostics.

Effective Noise Reduction Filters for Precise Temperature Measurement Using Brillouin Distributed Optical Fiber Sensors

This study explores the effectiveness of various noise reduction filters in accurately measuring temperature distributions over a 38.2 km single-mode fiber (SMF). Brillouin optical time-domain analysis (BOTDA) sensor is utilized to gather Brillouin gain spectra (BGSs), which are denoised using bilateral filter (BF), guided filter (GF), adaptive Wiener filter (AWF), non-local means filter (NLMF), average filter (AF) and disc filter (DF). The temperature distributions over the SMF are then determined by applying least-squares curve fitting (LSCF). The study assesses the efficacy of noise reduction filters considering signal-to-noise ratio (SNR), uncertainty in temperature measurement (UTM), experimental spatial resolution (ESR) and signal processing speed (SPS). Among six different filters, NLMF outperforms other filters which can provide SNR improvement of 10.22 dB for which the UTM can be improved by 58.93% without deteriorating the ESR of the sensor. The noise reduction using such filter can also provide 6.2% faster SPS. Therefore, NLMF can be considered as an effective noise reduction filter for the precise temperature measurement using BOTDA sensors. DUJASE Vol. 8 (1) 42-50, 2023 (January)

Assessment of CFD Predictions Using Experiments from a Heated Gas-Cooled Pebble Bed Facility

This paper presents computational fluid dynamics (CFD) simulations of the coolant gas flow in a pebble bed reactor core to assess the suitability of CFD models to accurately predict the temperature distribution and possible occurrence of local hot spots that may affect pebble integrity. This study assessed CFD predictions against temperature distribution measurements from the SANA test facility at the Research Center Jülich in Germany. A realistic pebble bed structure of randomly packed 1584 pebbles was produced using the discrete element method to model the pebble packing in detail. A total of 96 experimental temperature pebble points were used for the assessments, covering a broad range of heating powers (10 kW ≤ Poperation ≤ 35 kW). A good agreement between the CFD predictions and the SANA measurements was obtained for two coolants, nitrogen and helium, along the height of the pebble bed. It is anticipated that a better understanding of the suitability of the existing CFD models gained through this study will aid in the identification of gaps and areas of improvement for CFD to support the design and safety evaluations for pebble bed small modular reactors.

Transient experimental study on cooling performance of a radial turbine with impingement cooling in rotating state

Increasing the inflow temperature of a turbine is an effective approach for enhancing the thermal efficiency of devices operating in the Brayton cycle, such as micro-gas-turbines and waste heat recovery systems. However, elevated temperatures also pose a significant risk of thermal fatigue failure. This paper presents an experimental investigation of impingement cooling for radial turbines, aiming to achieve high cooling performance with a simple structure. High-frequency infrared thermal imaging technology was employed to measure temperature distribution in the turbine rotor under various operational conditions. The results indicate that jet-impingement cooling can substantially reduce the solid temperature of the radial turbine, with a maximum temperature reduction of approximately 44 K achieved by consuming the coolant with ṁre= 5%. Increasing the mass flow rate of the coolant consistently lowers the rotor temperature; however, an increase in rotational speed results in higher thermal inertia, thereby diminishing the cooling enhancement effect. The temperature distribution on the turbine surface exhibits significant periodic characteristics over time, leading to temperature fluctuations of 5 K to 30 K at the hub position. Furthermore, the cooling performance is further enhanced near the jet hole on the back-disc side of the inducer region, while the tip side closer to the exducer obtains better cooling effects.

Integration and evaluation of the high-precision MotionCam-3D into a 3D thermography system

Abstract. Infrared thermal imaging enables fast, accurate and non-contact measurement of temperature distributions. However, 2D representations of 3D objects often require several images to provide significant information. For such cases, 3D thermograms allow a quick temporal and spatial analysis. In this paper, the integration of an industrial high-precision 3D sensor into a 3D thermography system is presented. The performances of the existing and new systems are assessed and compared by analyzing 3D thermograms of an industry-related test object. The geometry of the obtained point cloud is evaluated by means of a non-referenced point cloud quality assessment approach. It is shown that, in the presence of the spatial resolution and the local curvature, the proposed system performs significantly better than the existing one.

P‐204: Simulation Study of Temperature Profile on AMOLED Panel Under High Brightness Mode

In this paper, we present a thermal simulation model designed to accurately predict the temperature distribution of AMOLED panel when operating in high brightness mode (HBM). The model incorporates panel geometric parameters, taking into account stacking configuration and material properties of actual OLED panel module. The simulation results demonstrate excellent agreement with the measured temperature distribution, with a maximum temperature difference of less than 1.5°. This thermal simulation model holds significant potential for evaluating OLED display performance and reliability risks associated with temperature increases. It can also serve as a valuable tool for guiding panel wiring design.

Influence of blowing ratio on double-wall cooling characteristics under the condition of high-temperature flue gas

Double-wall cooling has been extensively investigated due to its exceptional cooling performance. However, most previous studies on the cooling characteristics of double-wall geometry have been conducted under non-reacting conditions, neglecting the influence of high-temperature flue gas radiation. In this paper, an experiment investigation was carried out to evaluate the impact of blowing ratio <italic>M</italic> and coolant-to-gas temperature ratio on the cooling characteristics of effusion/impingement cooling at reacting flow conditions. The experiments were performed at atmospheric pressure with flame temperatures of 1,800 and 1,900 K respectively. Flue gas temperature was measured by S-type thermocouples, while an infrared camera and N-type thermocouples were employed for the gas-side wall surface temperature distribution measurements. The results demonstrate that the laterally averaged cooling effectiveness of the effusion/impingement cooling system increases with the increase of <italic>M</italic>. However, beyond a blowing ratio of 5.1, further increments in <italic>M</italic> do not significantly affect the cooling effectiveness. Moreover, it is observed that the laterally averaged cooling effectiveness gradually improves along the flow direction but at a reduced rate. Additionally, no significant changes in cooling effectiveness are observed after <italic>X</italic>/<italic>D</italic> > 50. Furthermore, when considering a blowing ratio of 4, higher coolant temperatures result in higher cooling effectiveness compared to lower coolant temperatures.

Event-triggered background-oriented schlieren: high-frequency visualization of a heated jet flow.

This Letter reports a novel, to our knowledge, event-triggered background-oriented schlieren (EBOS) technique using a combination of an event-triggered camera and pulsed laser speckle projection. The BOS images are reconstructed using the event data generated by the pulsed laser speckle projection and then processed to obtain the density and temperature distribution of the flow. This technique enables continuous visualization and recording of flows at kFPS frame rates with a very low cost, breaking through the short operating times of existing high-frame-rate BOSs. To examine the event-triggered BOS technique, tests are conducted on a hot air gun. The measured temperature distribution coincides with the thermocouple data with an error of no more than 10.8%. Measurements taken during the start-up of the hot air gun demonstrate that the presented technique can measure the evolution of the jet temperature for at least 150 s, as well as capture the localized unsteady turbulent structure in the heated jet flow.

Multi-point thermometry tool and in-situ measurement of temperature fields

In-situ real-time measurement of instantaneous milling temperature distribution is a key issue to realize efficient machining. For the foregoing reasons, the milling model of Inconel 718 was established, and the cloud diagram of tool temperature distribution during milling was obtained. A multi-point temperature measurement tool for milling temperature with an integrated thin-film temperature sensor was designed. The real-time temperature distribution of the tool during milling was obtained from 27 sets of milling tests. The impact of each milling parameter on the milling temperature was analyzed by ANOVA.

Thermal measurements of boiling granular films.

This study focused on two familiar items in our daily lives: grains and boiling water. Accurately measuring boiling dense granular beds requires specialized instruments and novel techniques. An annular vertical riser was used to boil granular films. The riser was filled with glass beads and then immersed in liquid water. The water is heated by inducing eddy currents at the base of the riser, which is composed of carbon steel. Beyond the critical electric current, Ic, the Lyapunov exponent of the time series of the measured temperature distributions within the granular films became positive. This indicates the chaotic behavior of the films. Slightly above Ic, patterned instabilities with affine fractal-like structures were observed in the boiling granular films. Chaotic boiling granular films manifested percolation and transition to turbulence. Computer simulations of the above system under the guidance of generative AI (GenAI) successfully reproduced many critical features of the experimental observations, which can be considered a significant breakthrough in the modeling and simulation of complex systems. With this success in utilizing GenAI, more accurate instruments can be developed, resulting in the world of tomorrow rapidly becoming today's world.