Thermal Signature Research Articles

Multi-sensor-based process monitoring and quality assessment during laser forming of novel titanium foam to prevent cellular structure damage

Titanium foam finds its application in different fields like battery electrodes, heat exchangers, biological prosthetics, and lightweight structures for aeronautical parts. However, the inherent property of the foam to fail during mechanical loading conditions poses a challenge in providing final shape to these materials for practical applications. The present work investigates forming of Titanium foam (Ti Foam) using inline process monitoring for achieving controlled foam deformation while maintaining its quality without failure. Infrared (IR) pyrometer and laser-based displacement sensor were used to monitor the foam deformation behavior and thermal signature. The monitoring data were used to understand the process mechanism of laser forming. The bending mechanism within the foam was analysed with respect to solid sheet bending process. The correlation of the achieved bending angles, was attempted with the process parameters for surface, microstructural, elemental, and phase transformation. A critical analysis of Ti foam behavior, like surface melting, in situ oxidation, phase transformation, and formation of nano-structures on foam surface was addressed based on process parameter combinations. Micro-computed tomography (μCT) was carried out to investigate the pore deformation mechanism. Metallurgical characterisations for foam surface and phase analysis were carried out using X-ray photoelectron spectroscopy (XPS) and tunneling electron microscopy (TEM) to determine the chemical and crystallographic states of the laser-formed surface.

A Bayesian Approach for Forecasting the Probability of Large Earthquakes Using Thermal Anomalies from Satellite Observations

Studies have demonstrated the potential of satellite thermal infrared observations to detect anomalous signals preceding large earthquakes. However, the lack of well-defined precursory characteristics and inherent complexity and stochasticity of the seismicity continue to impede robust earthquake forecasts. This study investigates the potential of pre-seismic thermal anomalies, derived from five satellite-based geophysical parameters, i.e., skin temperature, air temperature, total integrated column water vapor burden, outgoing longwave radiation (OLR), and clear-sky OLR, as valuable indicators for global earthquake forecasts. We employed a spatially self-adaptive multiparametric anomaly identification scheme to refine these anomalies, and then estimated the posterior probability of an earthquake occurrence given observed anomalies within a Bayesian framework. Our findings reveal a promising link between thermal signatures and global seismicity, with elevated forecast probabilities exceeding 0.1 and significant probability gains in some strong earthquake-prone regions. A time series analysis indicates probability stabilization after approximately six years. While no single parameter consistently dominates, each contributes precursory information, suggesting a promising avenue for a multi-parametric approach. Furthermore, novel anomaly indices incorporating probabilistic information significantly reduce false alarms and improve anomaly recognition. Despite remaining challenges in developing dynamic short-term probabilities, rigorously testing detection algorithms, and improving ensemble forecast strategies, this study provides compelling evidence for the potential of thermal anomalies to play a key role in global earthquake forecasts. The ability to reliably estimate earthquake forecast probabilities, given the ever-present threat of destructive earthquakes, holds considerable societal and ecological importance for mitigating earthquake risk and improving preparedness strategies.

Geometrically-informed predictive modeling of melt pool depth in laser powder bed fusion using deep MLP-CNN and metadata integration

The laser powder bed fusion (LPBF) process has the ability to manufacture intricate geometries. However, the fabrication of complex geometries using the LPBF process for industrial applications remains challenging in terms of achieving consistent microstructure and mechanical properties. Experimental investigations show that in addition to process parameters, geometrical factors such as shape and size of parts impact the thermal history, microstructure, defect structure, and thus mechanical and fatigue properties. As a result, the standardization, qualification, and certification of additively manufactured (AM-ed) parts encounters substantial obstacles posed by the obscure impact of design parameters on component quality. In this paper, an artificial intelligence framework is proposed to predict the melt pool depth of the additively manufactured parts considering the geometrical information of the parts. More specifically, a deep Multilayer Perceptron and Convolutional Neural Network (MLP-CNN) framework is designed to predict melt pool depth for any part geometries when printing metallic parts via LPBF using metadata (i.e., numerical and image data). Quite often the melt pool depth generated during the AM processes is employed as a surrogate for thermal, defect- and micro-structural signatures. In melt pool depth prediction of complex geometries in LPBF, a digital twin environment using a finite element model (FEM) is developed and validated using experimental melt pool measurements for different geometries within multi-tracks and layers. The FEM was in agreement with experimentation with an error of less than 15%. Through the process simulation, a large dataset of melt pool depths was obtained for various part geometries and different process parameters. Next, the MLP-CNN framework was established to identify the parallel impact of part design and process parameters on melt pool depths. To enhance the performance and robustness of this model, data augmentation has been implemented by rotating and transferring geometries to artificially expand the dataset. Data augmentation helps to mitigate overfitting and promote better generalization, especially in the context of limited training data. After training, the proposed model is found to give accurate melt pool prediction even for new geometries not considered during training. The fusion of CNN and MLP has led the melt pool predictions for unseen geometries with an accuracy of 95%.

Nondestructive detection of fruit fly (Bactrocera dorsalis) infestation in Alphonso and Totapuri varieties of mango fruits by thermal imaging technique

AbstractThermal imaging is a noncontact and nondestructive sensing technique that provides thermal signatures of objects by detecting the infrared radiations emitted by them above 1 K. The nondestructive detection of internal defects and infestations has vast applications in the Food Industry. In the present experiment, a C3 thermal camera (FLIR systems) having a thermal sensitivity of <0.10°C was used for the detection of fruit fly infestation in mango fruits. The healthy mango fruits of both varieties had a uniform surface temperature with a variation of only ±0.1°C. The maximum temperature difference between the healthy and fruit fly infested regions in fruit fly infested Totapuri mango was found to be 4.56°C in the heated and dark conditions. The maximum difference in the surface temperature of 4.3°C was observed between the healthy and infested regions of the infested Alphonso mango under heated and dark conditions. The difference in temperature between the healthy and infested regions of mangoes can be attributed to the changes in the internal structure, thermal properties, and biochemical properties of the healthy and infested regions of the infested mango fruits. The statistical analysis showed a significant difference (p < 0.05) in surface temperature between the infested and healthy regions of fruit fly infested Alphonso and Totapuri mango fruits. This envisages that nondestructive fruit fly infestation in Alphonso and Totapuri varieties of mango fruits can be detected under active thermography.Practical ApplicationsThe quality of mango fruit can be described in terms of external and internal quality. The external quality parameters such as color, size, and weight are usually considered during the sorting of mangoes. The internal defects such as diseases, physiological disorders, and damage due to pests are also significant in mango processing. The visual inspection methods for detecting pest infestation in fruits are nonreliable, time‐consuming, and subjective. Therefore, there is a need for efficient, reliable, and accurate methods to detect fruit fly infestation in mango fruits. A nondestructive method for the detection of fruit fly infestation has the potential to increase fruit quality and acceptability, thereby benefiting processors, traders, and consumers. Thermal imaging has a distinct advantage over other nondestructive quality assessment techniques as it is noncontact, practically feasible, and economically viable.

Comparative study of plaque surface temperature and blood heat transfer in a stenosed blood vessel with different symmetrical configurations

The presence of macrophage cells inside plaque can lead to a change in plaque temperature, which can be measured by using arterial wall thermographic techniques to predict the severity of stenosis in the vessel without complicated surgery. This study aims to analyze the effect of plaque symmetricity with a similar degree of stenosis (DOS) on plaque surface temperature and blood heat transfer in a straight vessel. This analysis aims towards predicting the severity of stenosis in a straight blood vessel through plaque temperature as an indicator. Two cases are being analyzed here; case 1 and case 2 refer to having similar vessel dimensions and an overall degree of stenosis (DOS) of 70%, with the exception of case 1 having a symmetrically developed plaque while case 2 refers to an asymmetrically developed plaque. Euler-Euler multiphase method with the application of the granular model is being applied in this study. At peak systole (0.2 s into the 10th cardiac cycle) in a cardiac cycle, the increase in plaque surface temperature at exit is higher in case of a symmetrically developed stenosis compared to an asymmetric one but the reverse situation happens during end systole (0.5 s into the 10th cardiac cycle). Although the population of macrophages in a plaque is a deciding factor of the thermal signature of a plaque, the symmetricity variation also needs to be taken into consideration while plaque progression is being diagnosed through thermographic technique.

Effective gate length determination of AlGaN/GaN HEMTs from direct measurements of thermal signatures

Determining junction temperature and two-dimensional temperature profile is critical for high-power GaN-based high electron mobility transistors to optimize performance, improve device reliability, and better thermal management. Here, we have demonstrated that resistance temperature detectors of the same material as the gate contact delineated between gate-to-source and gate-to-drain regions can accurately profile the temperature along the channel. The temperature profile is asymmetric and skewed toward the drain side, and the degree of asymmetry is used to determine the effective gate length experimentally. A two-dimensional thermodynamic model along with drift-diffusion transport matches well with the experimental data, validating the temperature profile and effective channel length extraction under bias. The vertical depth profiling of the temperature is also determined by identifying the isothermal profile through the resistance temperature detectors. The isothermal lines are largely circular in the GaN region from isotropic two-dimensional heat diffusion, with the pinch-off region acting as a heating filament. The isothermal circular profile turns elliptical in the SiC substrate due to its higher thermal conductivity.

Detection of Land Surface Temperature anomalies using ECOSTRESS in Olkaria geothermal field

Geothermal systems can be used to produce low-emission energy throughout the day and night, regardless of the weather conditions. These features make geothermal systems a sustainable and reliable energy source, which can be exploited on a much larger scale than it is now. Remote sensing techniques can support detecting areas potentially suitable for geothermal energy production, thereby reducing the costs of preliminary exploration. The Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) can provide nighttime thermal imagery, which can be used for geothermal anomaly detection. This paper presents a method for automated detection of geothermal anomalies using nighttime ECOSTRESS data of the study area in Olkaria, Kenya. The proposed detection method is a kernel-based one, and includes adaptions of kernel size for the cases of large geothermal anomalies. The accuracy of the method is verified with reference data acquired during field work. A producer’s accuracy of 82% is achieved, which is on average 56% points better than in randomised anomaly maps. The possible sources of errors in detection are heat capacity of surfaces, terrain features and vegetation masking the thermal signatures. The high producer’s accuracy proves potential for application in global mapping of geothermal anomalies.

Transitions in surface thermal signatures during the evolution of long-lived eddies in the global ocean

Mesoscale eddies are quasi-circular ocean currents accompanied by dynamic and thermodynamic variations, and are classified as anticyclonic (AEs) and cyclonic eddies (CEs) according to their rotation direction. Eddies transition between surface cold CEs/surface warm AEs (“conventional” eddies) and surface warm CEs/surface cold AEs (“unconventional” eddies) during their lifetimes. However, the characteristics and mechanisms of these transitions remain unclear. In this study, satellite and in-situ data were used to explore the spatiotemporal variation and vertical structures of “conventional” and “unconventional” eddies during the evolution of long-lived eddies (>1 year) in the global ocean from 1993 to 2015. On average, long-lived eddies are “unconventional” for about 40% of their lifetimes, and these “unconventional” eddies are concentrated in the South Atlantic Ocean and off the western and southern coasts of Australia. “Unconventional” eddies show distinct temporal variation and subsurface temperature structures. Generally, cold AEs and warm CEs last <3 months and are more active in summer than in winter. They have cold or warm cores within the mixed layer depth of the water column, which is affected by eddy–wind interactions via eddy-induced Ekman pumping. However, some cold AEs in the South Atlantic and warm CEs in the South Indian Ocean can last for >3 months and display weak seasonal variation. In addition, their cold and warm cores can extend to ∼200 and ∼300 m, respectively, and are related to subduction and the Leeuwin Current System.

Brochosome-inspired binary metastructures for pixel-by-pixel thermal signature control.

Microscale thermal signature control using incoherent heat sources remains challenging, despite recent advancements in plasmonic materials and phase-change materials. Inspired by leafhopper-generated brochosomes, we design binary metastructures functioning as pixel twins to achieve pixelated thermal signature control at the microscale. In the infrared range, the pixel twins exhibit distinct emissivities, creating thermal counterparts of "0-1" binary states for storing and displaying information. In the visible range, the engineered surface morphology of the pixel twins ensures similar scattering behaviors. This renders them visually indistinguishable, thereby concealing the stored information. The brochosome-like pixel twins are self-emitting when thermally excited. Their structure-enabled functions do not rely on the permittivities of specific materials, which distinguishes them from the conventional laser-illuminated plasmonic holographic metasurfaces. The unique combination of visible camouflage and infrared display offers a systemic solution to microscale spatial control of thermal signatures and has substantial implications for optical security, anticounterfeiting, and data encryption.

Shallow Thermal Anomalies and Their Role in the Breakup Evolution Along the Conjugate Margins of the Fram Strait (Svalbard and Eastern North Greenland), Indicated by Low‐Temperature Thermochronology

AbstractWe investigated highly mature sedimentary rocks exposed along both sides of the Fram Strait in the northern North Atlantic using apatite fission track and (U‐Th)/He thermochronology to obtain information on the thermal imprint of rifting and continental breakup processes along a sheared margin. Our data showed that the conjugate margins experienced several heating episodes, which we explain as resulting from heat transfer along segments of the De Geer Fracture Zone, a large continental transform system which connected magmatic centers north and south of the Fram Strait. Heating occurred prior to and during the Eurekan intraplate orogeny, which occupied the position of the present‐day Fram Strait during the Eocene. Heat transfer may have caused or contributed to lithospheric weak zones, which focussed deformation during intraplate orogeny. Movements along the transform fault system continued during the Oligocene, after the end of the Eurekan Orogeny, causing further structural weakening of pre‐existing fault zones. These were exploited during the final continental breakup leading to the opening of the Fram Strait. No unambiguous thermal signature associated with this latest stage of breakup was detected. Our data underline recent studies on the importance of structural inheritance and continental transform faults for the prolonged and complex processes of continental rifting and breakup.

Use of thermal drone in detection and assessment of larval mass temperature in decomposed rabbit carcasses.

Manual ground searches and cadaver dogs are traditional methods for locating remains, but they can be time- and resource-intensive, resulting in the decomposition of bodies and delay in victim identification. Therefore, thermal imaging has been proposed as a potentially useful tool for detecting remains based on their temperature. This study investigated the potential of a novel search technique of thermal drones to detect surface remains through the detection of maggot mass temperatures. Two trials were carried out at Selangor, Malaysia, each utilizing 12 healthy male Oryctolagus cuniculus European white rabbits and DJI Matrice 300 RTK drone China, equipped with a thermal camera; Zenmuse H20T to record the thermal imaging footage of the carcasses at various heights (15, 30, 60-100 m) for 14 days for each trial. Our results demonstrated that the larval masses and corresponding heat emissions were at their largest during the active decay stage; therefore, all the carcasses were observable in thermal images on day 5 and remained until day 7. Statistical analyses showed that (1) no statistically significant differences in thermal images between clothed and unclothed subjects (p > 0.05); (2) 15 m above ground level was proven to be the optimal height, as it showed the greatest contrast between the carcass heat signature and the background (p < 0.005). Our data suggested the potential window of detection of thermal signatures was detectable up to 7 days post-deposition. This could be an important guideline for the search and recovery teams for operational implementation in this tropical region.

An Approach to Large-Scale Cement Plant Detection Using Multisource Remote Sensing Imagery

The cement industry, as one of the primary contributors to global greenhouse gas emissions, accounts for 7% of the world’s carbon dioxide emissions. There is an urgent need to establish a rapid method for detecting cement plants to facilitate effective monitoring. In this study, a comprehensive method based on YOLOv5-IEG and the Thermal Signature Detection module using Google Earth optical imagery and SDGSAT-1 thermal infrared imagery was proposed to detect large-scale cement plant information, including geographic location and operational status. The improved algorithm demonstrated an increase of 4.8% in accuracy and a 7.7% improvement in MAP@.5:95. In a specific empirical investigation in China, we successfully detected 781 large-scale cement plants with an accuracy of 90.8%. Specifically, of the 55 cement plants in Shandong Province, we identified 46 as operational and nine as non-operational. The successful application of advanced models and remote sensing technology in efficiently and accurately tracking the operational status of cement plants provides crucial support for environmental protection and sustainable development.

A Review of Techniques and Bio-Heat Transfer Models Supporting Infrared Thermal Imaging for Diagnosis of Malignancy

The present review aims to analyze the application of infrared thermal imaging, aided by bio-heat models, as a tool for the diagnosis of skin and breast cancers. The state of the art of the related technical procedures, bio-heat transfer modeling, and thermogram post-processing methods is comprehensively reviewed. Once the thermal signatures of different malignant diseases are described, the updated thermographic techniques (steady-state and dynamic) used for cancer diagnosis are discussed in detail, along with the recommended best practices to ensure the most significant thermal contrast observable between the cancerous and healthy tissues. Regarding the dynamic techniques, particular emphasis is placed on innovative methods, such as lock-in thermography, thermal wave imaging, and rotational breast thermography. Forward and inverse modeling techniques for the bio-heat transfer in skin and breast tissues, supporting the thermographic examination and providing accurate data for training artificial intelligence (AI) algorithms, are reported with a special focus on real breast geometry-based 3D models. In terms of inverse techniques, different data processing algorithms to retrieve thermophysical parameters and growth features of tumor lesions are mentioned. Post-processing of infrared images is also described, citing both conventional processing procedures and applications of AI algorithms for tumor detection.

Assessment of the Performance and Defect Investigation of PV Modules after Accelerated Ageing Tests

Photovoltaic (PV) modules' degradation behaviour, together with outdoor field condition and fault diagnostics, consist valuable data in evaluating efficiency and establishing long-term reliability of a PV system. However, since PV modules commonly come with 25 (even over) years of warranty, testing modules in field for that long period is not feasible. Thus, due to time constraints, many accelerated aging tests have been recently introduced for testing reliability and durability of PV modules. Scope of the presented study is the assessment of the performance degradation and fault (defect) propagation mechanisms with regard to three monocrystalline silicon (mc-Si) PV modules, through a specific thermal cycle accelerated ageing test. The parameters that were experimentally evaluated towards the accelerated ageing process of this study, were: i) the thermal signature evolution and/or propagation of any diagnosed defects, especially in two modules, by means of infrared (IR) thermographic measurements, ii) the overall performance degradation of each module, by means of electrical I-V measurements, together with iii) specific morphological characteristics, by means microscopy imaging. The intended study gave useful and promising results in assessing the effect of the applied thermal cycles upon the modules’ thermal behaviour, electrical efficiency and morphology.

Fatigue limit estimation of metals based on the thermographic methods: A comprehensive review

AbstractInfrared thermography has been under review in the last 30 years due to its versatility and potential in the detection of the thermal signature associated with intrinsic energy phenomena due to dissipative processes, specifically those relying on mechanical fatigue. Nowadays, it is a well‐established technique that can support mechanical and structural engineers to implement a damage‐tolerant design, assess the residual life, and finally characterize the fatigue behavior of materials. The aim of this work is to review all thermography‐based approaches and procedures for fatigue limit estimation by rapid tests, drawing considerations on the applicability of thermal methods in fatigue assessment of mechanical components, proposing the capabilities of different thermal indices in fatigue assessment, and discussing the pros and cons of each method as well as the open points. On one hand, this review intends to sum up what has already been done in the field; on the other hand, it provides a guideline to direct new researches toward issues that should be resolved or understood.

Conversion of waste poly(vinyl chloride) to branched polyethylene mediated by silylium ions.

Full dechlorination of poly(vinyl chloride) (PVC) in a controlled manner to yield useful polymeric and chlorinated products is of great interest for the processing of PVC waste. Forming polyethylene (PE) without corrosive by-products would allow for a pre-treatment of PE wastes that are often contaminated with PVC. Herein, full dechlorination of PVC has been achieved via generation of silylium ions in situ, to furnish PE products. Complete dechlorination of PVC can be achieved in 2 hours, yielding organic polymer that has similar spectroscopic and thermal signatures of branched PE, with no observable chlorine. The degree of branching can be tuned between 31 and 57 branches per 1000 carbons, with melting temperatures ranging from 51 to 93 °C. This method is applicable to not only pure PVC, but also commercial PVC products. Depending on if the PVC products are separated from plasticizers, different melting points of the resulting PE are observed. PVC dechlorination in the presence of PE waste is also shown. This is the first report of being able to cleanly convert PVC waste to PE in high yields and tune the thermal properties of the PE product, highlighting the remarkable control that silylium ion mediated transformations enables compared to past chemical methods.

Origami-Inspired Vibrotactile Actuator (OriVib): Design and Characterization.

The use of vibrotactile feedback, in place of a full-fledged force feedback experience, has recently received increased attention in haptic communities due to their clear advantages in terms of cost, expressiveness, and wearability. However, designers and engineers are required to trade off a number of technical challenges when designing vibrotactile actuators, including expressiveness (a wide band of actuation frequency), flexibility, and the complexity of the manufacturing process. To address these challenges, we present the design and characterization of an origami-inspired flexible vibrotactile actuator, named OriVib, with a tunable resonance frequency (expressiveness), an origami-inspired design (flexible, soft contact with the human body), and a streamlined manufacturing process (low-cost). Based on its characterization, the fabricated OriVib actuator with 54 mm diameter can produce up to 1.2 g vibration intensity where the vibration intensity increases linearly from 6-11 V input. The resonance frequency is tunable through the characteristic diameter (the resonance frequency decreases in an almost inversely proportional fashion as the diameter increases). As for the thermal signature, the OriVib actuator maintains its temperature below 38 oC when actuated within 6-8 V. In terms of repeatability, the OriVib maintained an average vibration intensity of 0.849 g (standard deviation 0.035 g) for at least 2 million cycles. These results validate the effectiveness of the OriVib actuator to offer an expressive, low-cost, and flexible vibrotactile actuator.

Intraoperative thermal mapping of mammary tumors in dogs.

In this study, videothermometry's application in detecting mammary tumors in dogs is explored in-depth. The research hypothesizes that this technique can effectively identify cancerous tissues during surgery by analyzing thermal patterns. The methodology involved comparing thermal imaging results from dogs with palpable mammary nodules against a control group, focusing on capturing real-time thermal patterns. Results were significant, showing distinct thermal patterns in carcinomas. This indicates videothermometry's capability in accurately identifying micro metastases and differentiating between neoplastic and non-neoplastic changes. The study concludes that videothermometry has considerable potential in enhancing surgical precision, especially in tumor resection and safety margin definition, but emphasizes the need for further research to thoroughly understand the thermal signatures of various mammary tumors in dogs.

Experimental and CFD study of the surface thermal signatures and buoyant trajectory of the submerged thermal wakes

Experimental and CFD study of the surface thermal signatures and buoyant trajectory of the submerged thermal wakes

Mechanical, Pneumatic and Thermal Energy Storages for Micro-Air Vehicles

The growing demand for high-power propulsion systems with high energy density for micro-air vehicles (MAVs) has motivated a worldwide search for alternatives to the present conventional propulsion units which are mainly internal combustion engines (ICEs) and electric motors. Here, we evaluate the advantages of alternative mechanical energy-based storage system having high energy density and high power density characteristics. Additional key requirements for such an alternative propulsion system are high power for taking off and maneuverability, efficient energy conversion during cruise flights, easy speed control, allowing high-altitude operation, low noise signature, low thermal signature, low pollutants emission and easy restarting when needed. The various excellent features of both the internal combustion engine and the electric motor have placed them as the leading means for propulsion systems. However, the breathing difficulties of the ICEs at high-altitude conditions, their relatively low reliability and their high noise signature encouraged the search for alternative solutions. Although electric motors overcome these major drawbacks, the energy density of their energy source is much lower than that of the hydrocarbon fuels (more than an order of a magnitude) and their ability to function in missions requiring long flight durations is significantly inferior. Here, we examine alternative means of energy storage systems. Alternative mechanical energy storages including elastic (different types of springs), compressed air, thermal (phase-change materials and cryogenic reservoirs) and kinetic (flywheels) were analyzed and examined. Promising emerging technologies which are based on exceptional materials like specially designed elastomers and carbon nanotubes (CNTs) have been critically reviewed here. The carbon nanotubes are known for their very high energy density, where the energy can be delivered directly to the aircraft propeller with a remarkably high conversion efficiency.