Thermal Model Research Articles

Swift X-ray and UV observations of six Gaia binaries supposedly containing a neutron star

Recent observations have led to the discovery of numerous optically selected binaries containing an undetected component with mass consistent with a compact object (neutron star (NS) or white dwarf). Using the Neil Gehrels Swift Observatory, we carried out X-ray and UV observations of a small sample of these binaries. Four systems are wide (with an orbital period P$>300 d$), and were chosen because of their small distance (d$<$250 pc) and because the mass of the collapsed component favors a NS. Two others are compact systems (P$<0.9 d$) that show strong signs of containing a NS. The source 2MASS J15274848$+$3536572 was detected in the X-ray band with a flux of $5 $ erg cm$^ $ s$^ $ and a spectrum well fitted by a power law or a thermal plasma emission model. This source also shows a UV (2200 AA ) excess, which might indicate the presence of mass accretion. For the other targets, we derived X-ray flux upper limits of the order of $10^ $ erg cm$^ $ s$^ $ . These results are consistent with the hypothesis that the collapsed component in these six systems is a NS.

Computational study of the performance of a solar dryer for improvement in the shelf life of the food materials.

In this study, the thermal and drying characteristics of a thin layer food sample were investigated. An indirect type, simple, efficient, and economically feasible solar dryer was fabricated and used for food preservation. However, a dynamic model of a fabricated solar dryer was also presented to gain a better insight into the drying and thermal actions. This model consists of thermal modeling of the drying chamber, solar collector, and solar-dried food sample. The law of conservation of energy was applied to evaluate the temperature at different sections of the solar dryer with respect to drying time. All listed model equations were solved in the MATLAB environment. This study helps to examine the influence of solar radiation on the collector plate temperature, drying chamber temperature, food sample temperature, and performance parameters such as thermal efficiency with respect to drying time. Model data was found in good agreement with experimental data within a 4% error. It is concluded that the drying of food material is affected by air temperature, the collector temperature, mode of heat transfer, and material characteristics such as dimension and mass of the food sample.

Evidence for and Against Temperate Ice in Antarctic Shear Margins From Radar‐Depth Sounding Data

AbstractThe majority of ice mass loss from Antarctica flows through narrow, fast sliding regions of ice. The lateral boundaries of these regions, termed shear margins, are characterized by lateral shear strains in excess of ∼10−3 yr−1. Shear heating within these margins could warm ice significantly–even to the melting point–but other processes such as lateral advection of cold ice and fabric development compete with this effect. Radar observations can help constrain where temperate ice exists because englacial temperature increases electric conductivity which increases radar attenuation. We utilize the temperature‐dependent attenuation of ice to develop a novel method for constraining englacial temperature in shear margins by combining existing thermal models with very high frequency radar depth‐sounding data. We find evidence supporting temperate shear margins in 18 locations and find evidence for non‐temperate margins in 37 locations, notably in the Amundsen Sea Embayment.

Thermal Optimization Strategies for Li-Ion Batteries: Predictive Temperature Algorithm

Abstract Performance, safety, and longevity of batteries are all strongly impacted by thermal management, which is an essential component of battery design and operation. This work examines how accurate temperature control can result in significant improvements in performance and reliability with a focus on battery thermal heating. Predicting the temperature achieved by the battery during operation not only avoids conditions that lead to thermal runaway, but also guarantees that the battery is used optimally within an optimal temperature range. Within the optimal temperature range several advantages are observed. First, battery efficiency improves significantly as electrochemical processes occur more efficiently. Furthermore, by lowering the possibility of short circuits and improving overall battery safety, thermal stability aids in the prevention of undesirable phenomena like dendrite growth. By lessening the deterioration brought on by thermal degradation processes, thermal optimization also affects battery longevity. Based on experimental tests, a Finite Element Model (FEM) is developed. A model for thermal runaway propagation is established by combining thermal runaway and conduction models with an Arrhenius law-based combustion model. The study employed a cylindrical Li-Ion cell to conduct tests, taking into account three parameters: discharge rate (CRate), ambient temperature (Tamb), and initial battery temperature (T0). An algorithm based on the three variables was developed using the simulation results. The algorithm enables the accurate prediction of rising battery temperature during use, facilitating the setting of an optimal maximum discharge rate considering initial and ambient temperatures, thereby ensuring optimal performance within the desired temperature range.

GRAPHITE FOAM STRUCTURES AS AN EFFECTIVE MEANS TO COOL HIGH-PERFORMANCE ELECTRONICS

Due to their unique heat transfer features, graphite foams are used in the current analysis to form heat sinks effective enough to dissipate extreme heat generated within high-performance electronics. The heat sinks proposed are formed from foamed-baffles arranged either in parallel or perpendicular to the coolant paths through the staggered slots in between to alleviate the penalty of pressure drop while maintaining high heat dissipation capability. Two different sorts of dielectric coolants namely, air and the FC-3283 electronic liquid developed by 3MTM, have been utilized to directly dissipate the heat generated. The feasibility of the currently proposed heat sinks has been examined numerically based on the volume averaging concept of porous media employing the local thermal non-equilibrium model to account for interstitial heat exchange between the foam solid matrix and the fluid particles flowing across. A wide range of design parameters has been tested including the heat sink configuration along with structural characteristics of the graphite foam used. It has been found that foam baffles oriented perpendicular to the path of coolant flow can dissipate heat by about 50% better than those parallel to it, but with higher pressure losses. It has also been found that heat dissipation capability, for a certain orientation of baffles, can be improved by up to 100% when the foam pore size is doubled with outstanding saving in pressure losses by up to 300%. The impact of operating conditions, including the coolant flowrate and the heat flux applied, has also been inspected. The currently proposed heat sinks have been found efficient to meet the thermal demands of high-performance electronics and sweep away the extreme heat generated there with reasonable cost of pressure drop, where the proper selection of design parameters in light of the operating conditions applied can prevent the emergence of hot spots entirely. Extreme operating conditions, i.e. with heat density of up to 10W/cm2 for air-cooled heat sinks and 100W/cm2 for those cooled with FC-3283, can be well managed when a heat sink is configured from baffles that are oriented perpendicularly to the coolant flow path and formed of graphite foam having low porosity (∅=0.8) and larger pore size 

Large time existence and asymptotic stability of the generalized solution to flow and thermal explosion model of reactive real micropolar gas

We study the long time behavior of the generalized solution of the flow and thermal explosion model of the reactive real micropolar gas. The dynamics of the chemical reaction involved and the usual laws of conservation of mass, momentum, angular momentum, and energy generate a complex governing system of partial differential equations. The fluid is nonideal and non‐Newtonian. In this work, we prove that the problem can be solved in an infinite time domain and establish the asymptotic properties of the solution. Namely, we conclude that for certain parameter values, the solution stabilizes exponentially to a steady‐state solution, while for others the stabilization occurs but at power decay rate. At the end, we conducted a few numerical tests whereby we experimentally confirmed theoretical findings about long‐term behavior of the solution.

Abstract PO1-07-12: Inverse modeling with surface temperature accurately detects the presence of breast cancer

Abstract Breast cancer affects over 250,000 women in the United States every year. Patient outcomes including overall survival significantly decline with large sized tumors and nodal involvement on initial presentation. The introduction of mammogram screening has been instrumental in the early detection of cancer. However, it has lower sensitivity in dense breast tissue and limited specificity which leads to unnecessary additional invasive testing. Several methods such as magnetic resonance imaging (MRI), computed tomography (CT) and ultrasound imaging are used as adjunctive methods. However, there is still a need for cost-effective techniques without additional radiation exposure for breast cancer screening for use with mammography. We propose an adjunctive screening method using surface temperature measurements and inverse breast modeling for early detection of breath cancer. Methods: We enrolled patients who presented with mammogram detected breast tumors that were confirmed to be cancerous lesions by biopsy. We used prone position steady state infrared imaging of bilateral breasts to measure surface temperatures and multi-view MRI images to create patient specific 3D breast models. The inverse technique applies Levenberg-Marquard algorithms (LMA) and utilizes commercial software for thermal transport modeling. The inverse technique predicts a heat generation map normalized for baseline surface temperatures to localize the presence of an underlying tumor. Results: A total of 25 breast tumors (diameter range from 5 to 27 mm) from 24 patients were included in the analysis with a median patient age of 67 years. One patient had bilateral breast tumors. Mammogram data showed inclusion of mixed breast tissue composition including dense and extremely dense breast tissue. LMA accurately detected the tumor in all 25 patients with maximum absolute errors of 7 mm in location of the tumor in the breast and 1.78 mm in diameter. The accuracy of detection was not affected by tumor histology which included invasive ductal and lobular carcinomas, ductal and lobular carcinoma in-situ and atypical ductal hyperplasia. No heat sensitive tumors were detected in the 23 contralateral breasts which acted as internal negative controls. Conclusion: Infrared temperature profiles and inverse modeling successfully detected malignant breast tumors with no missed tumors or false positive results and could be used as adjunctive screening along with mammography, especially in patients with dense breast tissue. Citation Format: Nithya Sritharan, Carlos Gutierrez, Isaac Perez-Raya, Jose-Luis Gonzalez-Hernandez, Alyssa Owens, Donnette Dabydeen, Lori Medeiros, Satish Kandlikar, Pradyumna Phatak. Inverse modeling with surface temperature accurately detects the presence of breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-07-12.

Cooling and optimizing urban heat island based on a thermal knowledge-informed multi-type ant colony model

In the context of rapid urbanization and global warming, the urban heat island (UHI) intensifies the risk of heat-related mortality, endangering the health of urban residents. Urban greening effectively mitigates severe urban heating climates, but increasing green space without restrictions is undesirable due to the scarcity of urban land. Accurately characterizing the scope and intensity of UHI and determining the spatial location of the area that needs to be optimized are necessary. In this study, an inverse S-shaped function was used to fit the urban-rural temperature attenuation, whose parameters explicitly describe the properties of UHI. Additionally, a thermal knowledge-informed multi-type ant colony model was proposed to cool UHI automatically. A case study of Wuhan showed that: (1) the fitting effect of the inverse S-shaped function is desirable with the adjusted R2 exceeding 0.97, and the derived parameters with clear physical meanings avoid subjectivity in describing thermal characteristics; (2) high-level heat island of the main urban areas can be reduced by 7.7%–8.5% after land use optimization; and (3) a comparison with the traditional multi-type ant colony model verifies that the model proposed in this study can avoid excessive dispersion of the optimized pixels whose land use types are modified and achieve more reasonable and stable optimization results. This study provides useful exploratory tools for sustainable urban planning, heat mitigation solutions, and other urban retrofitting.

Optimization of MTI structure based on material characteristics under extreme aerodynamic heating environment

Thermal insulation structure is a key factor to protect a high-speed aircraft to work safely and complete various tasks. The multilayer thermal insulation (MTI) structure has attracted much attention because of its light weight and good thermal insulation effect. The performance of an MTI structure is not only related to its physical sizes, but also closely related to the material optimization and temperature influences. A transient nonlinear thermal transfer model of the MTI structure is established, and a numerical solution strategy of the nonlinear thermal transfer model is proposed. Considering material selection, introducing the temperature influence of materials, and taking the geometric dimensions and equivalent mechanical properties of the MTI structures as constraints, an optimization frame of the MTI structures is established. Then two intelligent methods are adopted to solve the problem. Using the aerodynamic heating environment of X-43 flight trajectory, the results of a typical high-speed aircraft show that the proposed optimization framework can reduce the structural mass density from 13.95 kg‧m−2 to 9.10 kg‧m−2 by about 34.8 %. The temperature effect analysis shows that the temperature variation has an important influence on the optimization results. If the temperature effect on material properties is not considered, the optimized design scheme may not meet the temperature design constraints (The maximum temperature of the inner surface is 410 K, far exceeding the maximum allowable temperature of 320 K) which further leads to structural failures. Finally, the reliability and rationality of the optimization scheme are verified by a finite element model (FEM). The equivalent modulus of the optimized MTI structure is 146 GPa and the mass area density of the MTI structure is 7.7 kg‧m−2. The optimization design method of an MTI structure proposed in the current paper provides a technical support and lays a foundation for the overall design of a high-speed aircraft.

Design and multi-criteria optimization and financial assessment of an innovative combined power plant and desalination process

Geothermal power generation programs are crucial due to their long-term sustainability and environmentally friendly characteristics, particularly for potential energy-based applications in the future. Innovative designs can yield improve efficien by mitigating irreversibility, resulting in enhanced power production. Hence, this study investigates an innovative cascade thermal design model that employs geothermal resources to enhance the efficiency and output of low-temperature power generation systems, specifically through the integration of organic flash and organic Rankine cycles. Additionally, this model introduces a novel cogeneration approach by incorporating a desalination unit based on humidification-dehumidification processes, aiming to concurrently produce electricity and fresh water. Employing a combination of thermodynamic analysis and financial assessment, the system's performance was simulated and optimized in MATLAB, using the Multi-Objective Particle Swarm Optimization (MOPSO) method. A sensitivity analysis preceded the optimization, leading to the development of three distinct optimization scenarios focused on balancing power and freshwater production, maximizing exergetic efficiency and net present value, and optimizing fixed capital investment for maximum financial viability. The results highlight the second scenario as particularly effective, achieving a power generation of 254.3 kW, an exergetic efficiency of 44.84%, and a net present value of $405,099. Conversely, the third scenario offers the best balance between freshwater production capacity (0.504 kg/s), fixed capital investment ($820,822), and a payback period of 7.12 years. This research demonstrates the potential of integrating advanced thermal models with geothermal resources for sustainable and efficient energy and freshwater production, marking a significant step forward in the development of eco-friendly cogeneration systems.

Integrating few-shot personalized thermal comfort model and reinforcement learning for HVAC demand response optimization

Integrating few-shot personalized thermal comfort model and reinforcement learning for HVAC demand response optimization

Development of a capillary temperature control system for capillary electrophoresis instruments designed for spaceflight applications.

Capillary temperature control during capillary electrophoresis (CE) separations is key for achieving accurate and reproducible results with a broad array of potential methods. However, the difficulty of enabling typical fluid temperature control loops on portable instruments has meant that active capillary temperature control of in situ CE systems has frequently been overlooked. This work describes construction and test of a solid-state device for capillary temperature control that is suitable for inclusion with in situ instruments, including those designed for space missions. Two test articles were built, a thermal mass model (TMM) and a functional model (FM). The TMM demonstrated that temperature gradients could be limited using the proposed control scheme, and that our thermal modeling of the system can be relied on for future adaptations of physical geometries of the system. The FM demonstrated CE analytical performance while under active temperature control and that the device was compatible with the harsh thermal-vacuum environments that might be encountered during space flight.

Emergence of rapid solidification microstructure in additive manufacturing of a Magnesium alloy

Abstract Bioresorbable Mg-based alloys with low density, low elastic modulus, and excellent biocompatibility are outstanding candidates for temporary orthopedic implants. Coincidentally, metal additive manufacturing (AM) is disrupting the biomedical sector by providing fast access to patient-customized implants. Due to the high cooling rates associated with fusion-based AM techniques, they are often described as rapid solidification processes. However, conclusive observations or rapid solidification in metal AM — attested by drastic microstructural changes induced by solute trapping, kinetic undercooling, or morphological transitions of the solid-liquid interface — are scarce. Here we study the formation of banded microstructures during laser powder-bed fusion (LPBF) of a biomedical-grade Magnesium-rare earth alloy, combining advanced characterization and state-of-the-art thermal and phase-field modeling. Our experiments unambiguously identify microstructures as the result of an oscillatory banding instability known from other rapid solidification processes. Our simulations confirm that LPBF-relevant solidification conditions strongly promote the development of banded microstructures in a Mg-Nd alloy. Simulations also allow us to peer into the sub-micrometer nanosecond-scale details of the solid-liquid interface evolution giving rise to the distinctive banded patterns. Since rapidly solidified Mg alloys may exhibit significantly different mechanical and corrosion response compared to their cast counterparts, the ability to predict the emergence of rapid solidification microstructures (and to correlate them with local solidification conditions) may open new pathways for the design of bioresorbable orthopedic implants, not only fitted geometrically to each patient, but also optimized with locally-tuned mechanical and corrosion properties.

Compilation of Apatite Fission-Track Data from the Northeast Atlantic Realm: A Jigsaw Puzzle with Missing Pieces

Abstract The northeast (NE) Atlantic is one of the best-studied geological regions in the world, incorporating a wide array of geological phenomena including extensional tectonism, passive margin development, orogenesis, and breakup-related volcanism. Apatite fission-track (AFT) thermochronology has been an important tool in studying the onshore evolution of the NE Atlantic for several decades. Unfortunately, large regional-scale studies are rare, making it difficult to study geological processes across the whole region. In this work, a compilation of published AFT data is presented from across Fennoscandia, the British Isles, East Greenland, and Svalbard, with the goal of providing an accessible overview of the data and how this vast body of work has improved our understanding of the region’s evolution. Alongside a review of previous literature, interpolated maps of fission track age and mean track length (MTL) highlight regional trends in the data that may result from major first-order processes and areas of low sample density that should be targeted for future study. Additionally, in the absence of metadata required for thermal history modeling, apparent exhumation rate estimates are calculated from available elevation profiles and the timing of major exhumation events inferred from “boomerang plots” of fission track ages against MTL values. Across Fennoscandia, data suggests that the opening of the NE Atlantic and exhumation of the margin have clearly played a major role in the thermal history of the upper crust. The remaining areas of Britain, Ireland, East Greenland, and Svalbard all present more complex trends consistent with a combination of the NE Atlantic’s opening and the interplay between specific bedrock geology of sampling sites and localized geological processes. Areas of low sample density include southern Britain, NE Britain, southeast Greenland, southern Svalbard, and Eastern Fennoscandia, each of which provides the natural laboratory required to answer many unresolved questions.

Multiline observations of hydrogen, helium, and carbon radio-recombination lines toward Orion A: A detailed dynamical study and direct determination of physical conditions

We present a study of hydrogen, helium, and carbon millimeter-wave radio-recombination lines (RRLs) toward ten representative positions throughout the Orion Nebula complex, using the Yebes 40m telescope in the Q band (31.3 GHz to 50.6 GHz) at an angular resolution of about $45 (sim 0.09\,pc). The observed positions include the Orion Nebula (M42) with the Orion Molecular Core 1, M43, and the Orion Molecular Core 3 bordering on NGC 1973, 1975, and 1977. While hydrogen and helium RRLs arise in the ionized gas surrounding the massive stars in the Orion Nebula complex, carbon RRLs stem from the neutral gas of the adjacent photo-dissociation regions (PDRs). The high velocity resolution ($0.3\ $) enables us to discern the detailed dynamics of the RRL emitting neutral and ionized gas. We compare the carbon RRLs with SOFIA/upGREAT observations of the ii m $ line and IRAM 30m observations of the 13CO (J=2-1) line (the complete map is presented here for the first time). We observe small differences in peak velocities between the different tracers, which cannot always be attributed to geometry but potentially to shear motions. Using the far-infrared ii and ii intensities with the carbon RRL intensities, we can infer physical conditions (electron temperature $T_ e $ and electron density $n_ e $, converted to hydrogen nuclei density $n_ H $ by dividing by the carbon gas-phase abundance $ A C $) in the PDR gas using nonlocal thermal equilibrium excitation models. For positions in OMC1, we infer $n_ e cm^ $ and $T_ e K $. On the border between OMC1 and M43, we observe two gas components with $n_ e cm^ $ and $n_ e cm^ $, and $T_ e K $ and $T_ e K $. In M43, we infer $n_ e cm^ $ and $T_ e K $. The Extended Orion Nebula southeast of OMC1 is characterized by $n_ e cm^ $ and $T_ e K $, while OMC3 has $n_ e cm^ $ and $T_ e K $. Our observations are sensitive enough to detect faint lines toward two positions in OMC1, in the BN/KL PDR and the PDR close to the Trapezium stars, that may be attributed to RRLs of C$^+$ or O$^+$. In general, the RRL line widths of both the ionized and neutral gas, as well as the ii and 13CO line widths, are broader than thermal, indicating significant turbulence in the interstellar medium, which transitions from super-Alfv\'enic and subsonic in the ionized gas to sub-Alfv\'enic and supersonic in the molecular gas. At the scales probed by our observations, the turbulent pressure dominates the pressure balance in the neutral and molecular gas, while in the ionized gas the turbulent pressure is much smaller than the thermal pressure.

Development of a variable refrigerant flow system emulator to host the second World Championship in Cybernetic Building Optimization

This paper introduces an emulator developed to assess the operational characteristics of variable refrigerant flow (VRF) for the second World Championship in Cybernetic Building Optimization (WCCBO). The emulator utilizes BACnet communication and provides a realistic simulation for evaluating energy conservation and comfort in buildings with VRF systems. Herein, we discuss the building specifications for calculation, operation of the emulator, calculation method for the vertical temperature distribution, dissatisfactory rate calculation, and consideration of championship rules. Notably, a thermal preference model was developed for predicting the thermal sensation of occupants and adjusting the dissatisfaction rate based on their ability to control the indoor environment. In addition, we developed a method for calculating the total scores during the WCCBO and devised a suitable network structure for score registration. The results of this study highlight the importance of personal control and impact of drafts on thermal comfort. This paper presents a meta-level methodology to determine the best operation for each specific VRF system for a future world championship, whose planning is underway and will be conducted to accumulate information on optimal operations.

Physics-Informed Approximation of Internal Thermal History for Surface Deformation Predictions in Wire Arc Directed Energy Deposition

Abstract This work presents a physics-informed fusion methodology for deformation detection using multi-sensor thermal data. A challenge with additive manufacturing (AM) is that abnormalities commonly occur due to rapid changes in the thermal gradient. Different non-destructive in-situ thermal sensors capture parts of the thermal history but are limited by the visible temperature spectrum and sensor field of view of the fabrication process. Various sensors mitigate problems with the loss of thermal history information; however, it brings forth challenges with integrating different data streams and the need to interpolate the internal thermal history. This study develops a thermal data-informed heat flux methodology that fills the gap in fusing numerical temperature approximation with data-driven knowledge of the surface of additive manufactured (AM) components. First, this study fuses infrared (IR) thermal data complexities during the AM process with the Goldak double ellipsoidal heat flux to model the energy input into the component. Second, a thermal physics-informed model input (PIMI) is created with thermal data-informed heat flux to capture internal thermal history. Lastly, regression convolutional neural network (CNN) captures the relationship between the three-dimensional thermal gradient and surface deformation. The rapid thermal gradient formation and identification of deformation is a key step toward using thermal history data and machine learning to improve quality control in AM. The proposed surface deformation detection model achieved an MSE of 1.14 mm and an R2 of 0.89.

Prediction Model for Trends in Submarine Cable Burial Depth Variation Considering Dynamic Thermal Resistance Characteristics

Fault problems associated with submarine cables caused by variations in their burial depth are becoming increasingly prominent. To address the difficulty of detecting the burial depth of submarine cables and trends in its variation, a prediction model for submarine cable burial depth was proposed which considers the dynamic characteristics of thermal resistance. First, a parallel thermal circuit model of a three-core submarine cable was established, and a formula for calculating the submarine cable’s burial depth was derived based on a formula for calculating the submarine cable’s core temperature. Then, the calculation result was corrected by considering the dynamic characteristics of the thermal resistance of the submarine cable’s structural materials. On this basis, feature vectors associated with the seabed cable burial depth calculation data and time nodes were mined by a convolutional neural network and used as the input parameters of a long short-term memory network for optimization and training, and a prediction model for trends in seabed cable burial depth variation was obtained. Finally, an example analysis was carried out based on the actual electrical parameter data of submarine cables buried by an offshore oil and gas platform. The results showed that the prediction model for trends in variations in the burial depth of submarine cables based on the CNN-LSTM neural network can achieve high prediction accuracy and prediction efficiency.

Study of Rock Damage Constitutive Model Considering Temperature Effect Based on Weibull Distribution

The deformation and damage process of rocks is accompanied by crack extension and penetration. The rock strength criterion, as a macroscopic characterization of the rock strength microelement, is the basis for establishing the damage constitutive modeling of rock. Aiming at the problem of the Hoek–Brown (H–B) strength criterion having a large strength prediction value under high confining pressure, the H–B strength criterion is corrected by considering the influence of the initial cracks on the development of the rock strength, and its applicability is verified. Based on the damage theory, assuming that the rock strength microelement obeys the Weibull distribution and considering the influence of residual strength, the damage correction coefficient is introduced, and a thermal damage statistical constitutive model that can reflect the whole process of the development of initial cracks inside the rock is established. The degree of penetration up to the damage is established, and the method of determining the parameters of the model is given. The theoretical curves of the established model are compared and analyzed with the curves of a conventional triaxial compression test of rock samples, and the study shows that the statistical constitutive model of the thermal damage of rock, established based on the modified H–B strength criterion, can better simulate the stress–strain relationship of rock under a conventional triaxial test. It also verifies the reasonableness and applicability of the model, which is expected to provide a basis for the exploitation of deep resources and the safety assessment of underground engineering.

Novel Entropy for Enhanced Thermal Imaging and Uncertainty Quantification

This paper addresses the critical need for precise thermal modeling in electronics, where temperature significantly impacts system reliability. We emphasize the necessity of accurate temperature measurement and uncertainty quantification in thermal imaging, a vital tool across multiple industries. Current mathematical models and uncertainty measures, such as Rényi and Shannon entropies, are inadequate for the detailed informational content required in thermal images. Our work introduces a novel entropy that effectively captures the informational content of thermal images by combining local and global data, surpassing existing metrics. Validated by rigorous experimentation, this method enhances thermal images’ reliability and information preservation. We also present two enhancement frameworks that integrate an optimized genetic algorithm and image fusion techniques, improving image quality by reducing artifacts and enhancing contrast. These advancements offer significant contributions to thermal imaging and uncertainty quantification, with broad applications in various sectors.