Thermal Mapping Research Articles

Nugget and corona bond size measurement through active thermography and transfer learning model

Resistance spot welding (RSW) is considered a preferred technique for joining metal parts in various industries, mainly for its efficiency and cost-effectiveness. The mechanical properties of spot welds are pivotal in ensuring structural integrity and overall assembly performance. In this work, the quality attributes of resistance spot welding, such as both nugget and corona bond sizes, are assessed by analyzing the thermal behavior of the joint using a physical information neural network (PINN). Starting from the thermal signal phase gradient and amplitude gradient maps, a convolutional neural network (CNN) estimates the size of nuggets and corona bonds. The CNN architecture is based on the Inception V3 architecture, a state-of-the-art neural network that excels in image recognition tasks. This study suggests adopting a new methodology for automatic RSW quality control based on thermal signal analysis.

Deformation behavior and microstructure evolution of graphene/copper laminated composites

The strength and electrical conductivity of copper-based conductors are always contradictory, while graphene/copper (Gr-Cu) composites are expected to meet the strict requirements of high strength, high conductivity, and even high thermal stability conductors’ materials. In this work, hot compression and cold rolling behaviors of Gr-Cu composites were investigated. The results indicate that graphene at the Gr-Cu interface in the composites can inhibit dislocations movement and grain boundary migration thus affecting dynamic recovery and recrystallization during hot compression. The pinning effects of dispersed graphene on grain boundaries were gradually weakened, leading to the coarsening of grains at 850 °C. Moreover, the thermal processing maps were plotted and the optional thermal processing parameters of 650–850 °C and 0.03–0.35 s−1 were determined. In addition, laminated Cu grains were refined to nanoscale after 98 % rolling reduction owing to inhibiting restoration by the dispersed graphene. The Gr-Cu interface in the composites assisted deformation and induced nanotwins resulting in pronounced Brass type texture after 50 % rolling reduction. Furthermore, the dispersed graphene enhanced the thermal stability and nanotwins were remained stable at 1073 K for 1h.

Surface deformation monitoring of Raniganj coalfield, India, using advanced InSAR and DGPS

The Raniganj coalfield, which is the oldest coal mine in India, is susceptible to ground subsidence. For the purpose of detecting surface deformation, this work makes use of field surveys, interferometric synthetic aperture radar (InSAR), and Differential GPS (DGPS). The study utilised Sentinel-1 InSAR data spanning from 2017 to 2023. PS-InSAR was used for both ascending and descending datasets, while SBAS-InSAR was used for descending datasets alone. Records show a maximum subsidence rate of −21.18 mm/year. Three surface deformation maps were generated from time-series assessments of individual locations, revealing regions undergoing significant changes. Known mining collapse locations and continuing deformation zones were designated with four differential GPS stations. By analysing the DGPS data with the GAMIT/GLOBK software, we were able to measure surfaces that were undergoing rapid deformation. Using Google Earth Engine (GEE), we generated thermal maps to delve deeper into the coal fire activity. We found coal bed methane (CBM) mining causing substantial subsidence in Kataberia and the surrounding areas. Shyamsundarpur and New Kenda are impacted by mining voids and coal fire-induced subsidence, respectively. The results of this study give the Raniganj region’s decision-making procedures more credibility in terms of minimising and controlling geological dangers.

Numerical and experimental study of thermography parameters for inspection of composites repaired by CFRP patches

ABSTRACT Considering the ever-increasing importance of composite patches applied to repair or reinforce composite structures, radical health monitoring of these patches seems inescapable. Thermography method is one of the most influential non-destructive methods applied to inspect the repaired structures. Since there are many parameters influencing defects detection in repaired composite structures, extracting the most influential method to determine these parameters is significantly important. In the present study, a repaired carbon fiber reinforced plastic (CFRP) composite structure having defects of different dimensions, types and features located in different depths, is investigated by experiment and finite element simulations to assess the influence of the experimental parameters, like the thermal excitation pulse duration and the best image frame. In thermal simulation, two criteria, maximum thermal variations versus time and path length, are developed to derive the most optimum heating duration and the best thermal frames. The obtained results are validated through defining direct and diagonal paths passing through defects demonstrated on thermography images and thermal map images. The average error of thermal variations on different paths displayed on thermography and simulation images is less than 4.5 percent which confirms the correspondence of obtained results of both mentioned methods.

Enhancing point cloud data fusion through 2D thermal infrared camera and 2D lidar scanning

Sensor data fusion from multiple sources plays a pivotal role in advancing our understanding of real-world phenomena. This paper focuses on the integration of a thermal imager and a lidar to simultaneously capture four-dimensional (XYZT) space coordinates and temperatures. The fusion of data relies on establishing correspondence between overlapping lines in the lidar’s 3D point cloud and the infrared (IR) camera’s 2D thermal map. The presented combination method offers several key advantages. Firstly, it simplifies the calibration process. Furthermore, it can achieve near real-time performance, enabling prompt data analysis. Moreover, the method demonstrates high accuracy in capturing spatial information and temperature measurements. The thermal IR camera used in the experiment features a 1280 × 1024 pixel cooled indium antimonide (InSb) detector, operating in the short wavelength infrared (MWIR) spectral range of 1.5 to 5.5 µm. It provides temperature readings with ± 1 K accuracy and sub-30 mK resolution. On the other hand, the lidar system delivers centimeter-level precision within a range of approximately 1 to 12 m, even in well-lit outdoor environments. The experimental results validate the effectiveness of our combined system, successfully generating high-quality four-dimensional (4D) point clouds. The integration of the thermal IR camera and profilometer presents an intriguing tool with significant potential in various industrial applications. For instance, it can be employed to accurately assess gas leaks, enhance metallurgical processes, and improve safety on construction sites.

Thermal mapping: Assessing the optimal sites for temperature measurement in the human body and emerging technologies.

Numerous body locations have been utilized to obtain an accurate body temperature. While some are commonly used, their accuracy, response time, invasiveness varies greatly, and determines their potential clinical and/or research use. This review discusses human body temperature locations, their accuracy, ease of use, advantages, and drawbacks. We explain the concept of core body temperature and which of the locations achieve the best correlation to this temperature. The body locations include axilla, oral cavity, rectum, digestive and urinary tracts, skin, tympanic, nasopharynx, esophagus, and pulmonary artery. The review also discusses the latest temperature technologies, heat-flux technology and telemetric ingestible temperature pills, and the body locations used to validate these devices. Rectal and esophageal measurements are the most frequently used.

Hot deformation behavior and processing workability of a powder forged Fe-2.1Cu-0.5C alloy

Hot deformation behavior of as-sintered Fe-2.1Cu-0.5C alloy was evaluated through the construction of constitutive equations and a hot processing map. The hot deformation behavior was investigated at different temperatures and strain rates and microstructure observations were subsequently conducted. Flow stress for the initiation of dynamic recrystallization mechanism was determined. Tensile and fatigue strength tests were conducted at room temperature. It was observed that the microstructure of the alloy forged at lower temperature exhibited smaller grain size and its grain size increased with higher forging temperatures. Mechanical testing results revealed that an increase in the forging temperature led to a lower tensile strength and a higher fatigue strength. This change can be attributed to the larger grain sizes and the reduction of microcracks. A forging temperature at 1050 °C was recommended to achieve optimal mechanical properties for powder forged Fe-2.1Cu-0.5C products. These results might give some hints for optimizing process conditions and improving mechanical properties of powder metallurgy alloys by the use of constitutive equations and thermal processing maps.

Solid-state diffusion bonding for INCONEl 617 superalloy using field-assisted sintering technology (FAST) guided by CALPHAD approach

This study investigates solid-state diffusion bonding between two INCONEL 617 alloy samples using field-assisted sintering technology (FAST). The study focuses on analyzing the faying surface validating the theoretical alloy design modeling done by the CALculation of PHAse Diagrams (CALPHAD) approach followed by experimental validation. Varying kinetics’ limitations enabled phase stability and phase control governed by the CALPHAD approach alloy design. The alloy design contains a pseudo-binary phase diagram assisted with thermal mapping of a property phase diagram to obtain the optimum temperature of solid-state diffusion bonding while understanding phase fields and their evolution through Molybdenum (Mo) increasing content and temperature increase. The FAST parameters recommended by CALPHAD were 800 °C under 10 MPa pressure with a holding time of 30 min. The investigation observations were promising in a way that the faying surface contains gamma (γ) only, while the further region on the alloy contains γ and gamma prime (γ′). It is worth mentioning that FAST joining resulted in fine faying surface thickness of around 10 μm and a controlled heat affected zone (HAZ) leading to relevant reduction in the recrystallization zone yielding an average grain size of 60–100 μm before and after diffusion bonding. Furthermore, two modes of metal carbide (MC) have been found; MC formed under the faying surface and micro-MC pools formed around the faying surface.

Electrochemical impedance spectroscopy analysis and thermal mapping of different cross-sectional cathode channels in open-cathode polymer electrolyte membrane fuel cell stack

The Electrochemical impedance spectroscopy (EIS) of three novel cathode channels designs square, boot, and triangular for open cathode polymer electrolyte cathode fuel cell stacks are analyzed. Fundamental mechanisms such as oxygen reduction reaction, proton conductivity, bulk resistance of stack, capacitance and structure features of the porous carbon electrode etc. are investigated with the help of Nyquist/Bode plots and Randles circuit. Operational parameters including airflow rate, current, H2 gas condition (humidified and dry), and stack temperature are studied focused on understanding the trend of high and low frequency resistance. The minimum resistance and temperature mapping for cross-section designs at different operating conditions is utilized for parametric optimization. Overall, it is recommended to operate the stacks at minimum resistance obtained just before the peak power density and its corresponding temperature ∼40 °C. Finally, a data-driven hybrid model integrating EIS and artificial intelligence is presented with root mean square error of ∼0.98.

Holographic thermal mapping in volumes using acoustic lenses

Acoustic holographic lenses (AHLs) show great potential as a straightforward, inexpensive, and reliable method of sound manipulation. These lenses store the phase and amplitude profile of the desired wavefront when illuminated by a single acoustic source to reconstruct ultrasound pressure fields, induce localized heating, and achieve temporal and spatial thermal effects in acousto-thermal materials like polymers. The ultrasonic energy is transmitted and focused by AHL from a transducer into a particular focal volume. It is then converted to heat by internal friction in the polymer chains, causing the temperature of the polymer to rise at the focus locations while having little to no effect elsewhere. This one-of-a-kind capability is made possible by the development of AHLs to make use of the translation of attenuated pressure fields into programmable heat patterns. However, the impact of acousto-thermal dynamics on the generation of AHLs is largely unexplored. We use a machine learning-assisted single inverse problem approach for rapid and efficient AHLs’ design to generate thermal patterns. The process involves the conversion of thermal information into a holographic representation through the utilization of two latent functions: pressure phase and amplitude. Experimental verification is performed for pressure and thermal measurements. The volumetric acousto-thermal analyses of experimental samples are performed to offer a knowledge of the obtained pattern dynamics, as well as the applicability of holographic thermal mapping for precise volumetric temperature control. Finally, the proposed framework aims to provide a solid foundation for volumetric analysis of acousto-thermal patterns within thick samples and for assessing thermal changes with outer surface measurements.

Highly efficient electrocatalytic degradation of methylparaben using BiOx-doped Ti/β-PbO2 anode: Comprehensive electrochemical study and degradation mechanism

Electrochemical degradation of methylparaben (MPB) was successfully performed using Ti/β-PbO2-BiOx anode. The structure of the fabricated electrode was characterized using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), thermal gravimetric analysis (TGA), X-ray diffraction (XRD), and mapping techniques. The results confirmed the successful preparation of the electrode with favorable morphological and structural properties. This research includes optimization of operating parameters such as solution pH, applied current density, initial MPB concentration and electrolysis time. The results indicate that the prepared electrode has high electrochemical performance and thermal stability. Under optimal conditions, current density of 4.8 mA/cm2, pH = 5 and initial concentration of 0.5 mM, the maximum degradation efficiency of 98.9 % was obtained. In this work, also, based on the data obtained from LC-MS analysis, a detailed mechanism for the degradation of MPB was proposed. In another section of this research, the electrochemical behavior of MPB on glassy carbon electrode was comprehensively studied using cyclic voltammetry at different pH values. The data obtained from this study provide significant insight into the electrochemical behavior of MPB, its pH-dependent properties and adsorption activities. The results of this section can also be used to better optimize the conditions of MPB degradation.

Influence of different causes on thermal runaway characteristic of LiFePO4 battery

To solve the current battery safety issues and accident investigation problems. Thermal runaway experiments triggered by nail penetration, hot box, flame heating and heating plate were carried out on a commercial 8 Ah pouch LiFePO4 battery. Recorded real-time phenomena, voltage and temperature. Then we discussed the TR process in the light of the latest mechanism study. The local TR is triggered by nail penetration within 3 s. The hot area above 700 °C and the spreading of internal TR was detected. LiFePO4 battery thermal runaway will generally emit white smoke, no fire. And it requires more attention to explosion risk. If the combustible gas is ignited, jet fire will appear, but the injection pressure is not extreme. Thermal runaway triggered by local heating is inconsistent with a voltage drop. A mapping method of thermal runaway parameters radar map is designed, which can indicate the danger degree of TR with shapes. Through comparison, some characteristics are obtained for the judgment of battery accident causes. This research can provide a basis for LFP battery safety evaluate and accident investigation.

High-density thermal sensitivity maps of the body of people with multiple sclerosis: Implications for inclusive personal comfort systems

Inclusive thermal comfort solutions should accommodate the need of clinical groups such as people with Multiple Sclerosis (pwMS), who experience abnormal thermal sensitivity. The aim of this study was to develop high-density body maps of temperature sensitivity in pwMS to inform the design of patient-centred personal comfort systems.Fourteen pwMS (6 M/8 F; 48.6 ± 10.0 y) and 13 healthy individuals (CTR; 5 M/8 F; 47.8 ± 10.4) underwent a quantitative sensory test in a thermoneutral environment, during which they rated their local thermal sensations arising from the application of warm (39°C) and cold (27°C) stimuli to 115 bilateral body sites across the face, torso, upper and lower limbs. We used a z-transformation to create maps of hypo- and hyper-sensitivity for each individual MS participant using normative CTR data.We found that 50% of pwMS (N = 7/14) presented a loss of cold sensitivity over the upper limb, and a loss of warm sensitivity over the feet. Furthermore, 36% of pwMS (N = 5) presented warm hyper-sensitivity over the upper limb. Finally, cold sensitivity loss and warm sensitivity gain were more evenly distributed and affected a greater proportion of skin sites in MS (i.e. cold hypo-sensitivity = 44% of tested sites; warm hyper-sensitivity = 14%) than warm sensitivity loss (i.e. 10%), which was more focused on sites such as the feet.Our findings highlight the need to consider “thermosensory corrective power” when designing personal comfort systems, to accommodate either thermosensory loss or gain in pwMS. Our approach to clinical body mapping may support this process and help meeting the unique thermal needs of vulnerable individuals.

Definition of a thermal conductivity map for geothermal purposes

The use of geothermal energy is spreading globally due to its many advantages, especially for heating and cooling. The correct design of a geothermal system requires knowledge of the parameters of the subsoil rocks, and particularly the thermal conductivity (k), which is the intrinsic ability of a material to transfer thermal energy as a result of a temperature gradient. A thermal conductivity map of the geological formations is time-consuming to produce, but can be of great help when selecting the location of a low-enthalpy geothermal installation, resulting in significant savings and an increase in the efficiency of that installation. The preferred option for determining k is an in situ thermal response test, but laboratory methods may be an alternative if it is not available or affordable. In this work, the needle thermal probe method has been used to measure the k of representative outcropping rocks in Oviedo (NW Spain), since it allows to obtain a rapid determination, its cost is comparatively low and it can be implemented in a portable device. 162 measurements have been carried out on a total of 27 samples, ranging from 0.2 (clay) to 5.4 W m−1 K−1 (quartzite). A relationship has been found between the k of the rocks and their characteristics, such as mineralogy, anisotropy or geological age and a thermal conductivity map was created.

Facial and ocular thermal mapping in black-and-gold howler monkey (Alouatta caraya) by infrared thermography: An ex situ study.

This study used infrared thermography (IRT) for mapping the facial and ocular temperatures of howler monkeys, to determine parameters for the diagnosis of febrile processes. There are no published IRT study in this species. Were evaluated images of a group of monkeys kept under human care at Sorocaba Zoo (São Paulo, Brazil). The images were recorded during 1 year, in all seasons. Face and eye temperatures were evaluated. There are statistically significant differences in face and eye temperatures. Mean values and standard deviations for facial and ocular temperature were respectively: 33.0°C (2.1) and 36.5°C (1.9) in the summer; 31.5°C (4.5) and 35.3°C (3.6) in the autumn; 30.0°C (4.3) and 35.6°C (3.9) in the winter; 30.8°C (2.9) and 35.5°C (2.1) in the spring. The IRT was effective to establish a parameter for facial and ocular temperatures of black-and-gold howler monkeys kept under human care.

Automated detection and tracking of photovoltaic modules from 3D remote sensing data

This study addresses the growing demand for increased performance and reliability of photovoltaic (PV) installations by developing innovative monitoring technologies. The strategy consists of flying an unmanned aerial vehicle (UAV) equipped with a dual camera (RGB and thermal) over the PV plant of interest, followed by the generation of photogrammetric 3D models derived from the overlapped aerial images. The resulting datasets involve orthoimages and point clouds by processing RGB and thermal imagery. The key contribution of this study is twofold: (1) the thermal image mapping on dense and high-resolution point clouds that represent the status and geometry of PV solar modules, and (2) the automatic identification of individual solar panels in 3D space and their thermal characterization along their oriented surface. Then, the vector layer of each PV panel is projected onto the 3D thermal point cloud to extract the thermal values associated with each panel. To evaluate the capability of the proposed method, it was replicated in different scenarios, considering rural and urban environments with different light conditions and PV structures. The results demonstrate the robustness of our method, which achieves a remarkably high detection rate, around 99.12% of true positives, and a low false positive rate, close to 0.88%. Consequently, this method means an advance over previous work by proposing a comprehensive and automated solution for individual and highly detailed monitoring of each solar panel from 3D remotely sensed data. This study opens up new frontier research related to real-time monitoring of photovoltaic modules, an inspection of solar photovoltaic cells, the simulation of solar resources and forecasting, the development of digital twins, solar radiation modelling, and analysis of modular floating solar farms under wave motion.

Prediction of flow stress in Mg-3Dy alloy based on constitutive equation and PSO-SVR model

This study conducted hot compression experiments on as-cast Mg-3Dy alloy under deformation parameters of 380 °C–470 °C and 0.001–1 s−1. The microstructure of the alloy was observed using EBSD, and the flow stress of the Mg-3Dy alloy was predicted using the Arrhenius model and the particle swarm optimization-support vector regression (PSO-SVR) model. The organizational analysis results showed that the main recrystallization mechanism in the alloy is the discontinuous dynamic recrystallization (DDRX) mechanism. The generation of twins in the alloy was mostly the result of local stress action. The optimal processing window for this alloy was determined to be 380 °C–470 °C and 0.001–0.01 s−1 through the thermal processing map. The prediction accuracies of the Arrhenius model and PSO-SVR model were evaluated using the correlation coefficient R2 and mean squared error MSE. The results showed that the PSO-SVR model significantly outperforms the Arrhenius model in prediction accuracy, with R2 value of 0.99982 and MSE of 0.074.

Experimental and numerical pore-scale characterization of multi-mode heat transfer in porous ceramics exposed to a transverse heat flux

We present experimental and computational approaches to characterize the multimode heat transfer in an open-cell Si-SiC foam exposed to a transverse heat flux. The experimental setup consists of a 5×5×10 cm3 parallelepipedal 10ppi foam (83% porosity) placed within a rectangular channel, in which airflow (0-8 g.s−1) was established. The pressure drop across the foam was measured and infrared cameras were used to obtain the temperature of the heater plate and the thermal maps of the foam at the outlet and on the top. The computational approach is a 3D pore scale model of flow and multi-mode heat transfer in the channel subjected to the same conditions. A X-ray tomography technique (50 µm resolution) was used to scan the foam structure and subsequent segmentation and binarization of the data resulted to a digitalized volume of the 1000×1000×2000 voxels and about 101 million cells after meshing. The computations were performed using ANSYS Fluent. Laminar or k-ε turbulence models with enhanced wall treatment were used depending on the airflow rate. Finally, the comparison of the numerical results with experimental data shows that the relative deviation of pressure drop is less than 7.1% and that of outlet foam temperature is less than the experimental uncertainties (5-20%). Using similarity with fins, the effectiveness of foam is evaluated around 2.2.

Exploring BTI aging effects on spatial power density and temperature profiles of VLSI chips

The Long-term reliability of a chip, encompassing factors like bias temperature instability (BTI), plays a substantial role in the chip's operational efficiency and overall lifespan. Most studies primarily center around performance-related aspects like delay and timing impacts, and fewer studies are performed on reliability impacts on the spatial power density and thermal profiles of the chips. In this study, we propose to investigate the BTI impacts on the spatial power density and temperature profiles of VLSI chips for the first time. We assessed the BTI aging impact on the on-chip spatial power density and temperature for two widely used circuit functional blocks (dual port RAM, Discrete Cosine Transform (DCT) block) at T = 130◦C and T = 25◦C to account for the worst-case BTI degradation, using degradation-aware cell libraries for a 10-year aging scenario. Furthermore, we showcased the essential role of BTI aging-aware timing analysis in evaluating the impact of BTI aging on total power, on-chip spatial power density, and thermal maps. Neglecting this aspect can result in a substantial underestimation of the results related to the parameters mentioned above. We developed a power map generation method from the circuit layout and power analysis from EDA tools. We demonstrate that both circuits’ maximum power density reduction is approximately 12 % and 20 %, respectively. Furthermore, to analyze the BTI impact on spatial temperature, we built the heat transfer model using a multiphysics tool to imitate a real chip (Intel i7-8650U) and performed thermal simulations to evaluate the spatial thermal map. The resulting maximum temperature reduction for both these circuits is approximately 10 % and 12 %, respectively, which is quite significant.Our analysis has further unveiled that, in the context of a specific circuit, the position of maximum power density and the occurrence of a hot spot remains consistent over time, unaffected by aging. However, it's important to note that these positions can vary between different circuits, primarily influenced by the workload the circuit is currently handling. Furthermore, our findings demonstrate that the effects of Bias Temperature Instability (BTI) aging are significantly more pronounced when the circuit operates at higher temperatures (T = 130◦C) compared to lower operating temperatures (T = 25◦C).

Heat transfer during droplet impact on a cold superhydrophobic surface via interfacial thermal mapping

AbstractUndesired heat transfer during droplet impact on cold surfaces can lead to ice formation and damage to renewable infrastructure, among others. To address this, superhydrophobic surfaces aim to minimize the droplet surface interaction thereby, holding promise to greatly limit heat transfer. However, the droplet impact on such surfaces spans only a few milliseconds making it difficult to quantify the heat exchange at the droplet–solid interface. Here, we employ high‐speed infrared thermography and a three‐dimensional transient heat conduction COMSOL model to map the dynamic heat flux distribution during droplet impact on a cold superhydrophobic surface. The comprehensive droplet impact experiments for varying surface temperature, droplet size, and impacting height reveal that the heat transfer effectiveness () scales with the dimensionless maximum spreading radius as , deviating from previous semi‐infinite scaling. Interestingly, despite shorter contact times, droplets impacting from higher heights demonstrate increased heat transfer effectiveness due to expanded contact area. The results suggest that reducing droplet spreading time, as opposed to contact time alone, can be a more effective strategy for minimizing heat transfer. The results presented here highlight the importance of both contact area and contact time on the heat exchange between a droplet and a cold superhydrophobic surface.