Search Results (405)

To address the issues of low mechanical rock-breaking efficiency and severe tool wear in hard rock, this study investigates the mechanical deterioration and abrasivity response of granite subjected to rapid flame-jet heating followed by liquid nitrogen cooling, with rock pre-treatment in thermal-assisted rock breaking as the background. Fine-grained granite specimens were heated by flame jet to temperatures ranging between 200 and 600 °C and then subjected to natural cooling or sudden liquid nitrogen cooling. Physical parameter measurements, uniaxial compression tests, Brazilian splitting tests, and CERCHAR abrasivity tests were conducted using national standards to investigate the evolution of thermal damage and the effect of cooling path. The results show that the damage degree of granite continuously increases with increasing heating temperature, and the damage induced by liquid nitrogen cooling is greater than that induced by natural cooling. Visible cracks begin to appear on the specimen surface after 300 °C, while crack propagation and structural deterioration become more pronounced at 500–600 °C. Among the measured physical parameters, P-wave velocity is the most sensitive to damage, with a maximum attenuation rate of 60.6%. The deterioration of the physical structure further reduces the load-bearing capacity and deformation performance of granite. After liquid nitrogen cooling at 600 °C, the uniaxial compressive strength, tensile strength, and elastic modulus decrease to 92.6 MPa, 1.42 MPa, and 17.4 GPa, respectively, corresponding to reductions of 56.0%, 87.7%, and 69.3% compared with the untreated specimens. The tensile strength is the most sensitive mechanical parameter to liquid nitrogen cooling. The CERCHAR abrasivity index decreases from 3.81 to 2.12. Liquid nitrogen cooling advances the transition of granite abrasivity from high to medium from 400–500 °C to 300–400 °C. The integrated analysis indicates that the non-uniform temperature field generated by rapid flame-jet heating and the differences in thermal deformation among minerals promote the initiation of initial cracks. The additional shrinkage stress induced by liquid nitrogen cooling further drives crack propagation and coalescence, eventually leading to the coupled reduction in the strength, stiffness, and abrasivity of granite. The results provide laboratory-scale evidence for evaluating granite pre-treatment under rapid flame-jet heating and liquid nitrogen cooling and offer a reference for thermal-assisted mechanical rock breaking and standardized abrasivity reduction. However, the relationship between CAI and actual tool wear still requires further verification. Full article

Coal phase-out regions concentrate the distributional risks of the energy transition, yet the tools used to identify energy-poor households in these territories still rely mainly on income and welfare criteria. This study asks whether such criteria can identify the households that suffer. Drawing on a survey of 706 households across six municipalities of Western Macedonia, Greece, the core territory of the national lignite phase-out, we validate a four-item Thermal Stress Index (polychoric ω = 0.885; loadings = 0.71–0.88; no differential item functioning by gender, income, or survey wave) and test nine hypotheses and one descriptive benchmark on prevalence, mechanisms, typologies, and targeting. Winter thermal inadequacy reaches 22.9%, which sits above the 19.0% national EU-SILC figure, reported as descriptive context. Dwelling energy features dominate all socioeconomic predictors of severe thermal stress (pseudo-R-squared 0.482 against 0.024), and no direct tenure association remains once envelope quality is included, while the protective association of income operates primarily through dwelling quality and is not observed across the range of inefficient dwellings. Latent class analysis identifies a hidden energy poverty class, 19.5% of households with severe experiential deprivation, above-average income, and no payment problems. A machine learning targeting audit shows that administrative criteria alone identify severely stressed households and show no discriminative capacity for identifying severely stressed households (AUC = 0.517), whereas adding dwelling and financial-strain information raises discrimination to an area under the curve of 0.938. Finally, in this sample, income-based screening is weakly associated with the households reporting severe thermal deprivation. Full article

Arbitrary-amplitude nonlinear periodic electrostatic waves and the wave-breaking limit are considered in a one-dimensional relativistic electronegative plasma consisting of positive ions, negative ions, and a relativistically degenerate electron-fluid background. A cold, inertial fluid description is adopted for the ions, while the electrons are described by a relativistic Fermi–Dirac equation of state, which provides the required restoring physics through degeneracy rather than ordinary thermal pressure. After transforming to a travelling coordinate system, we reduce the general multicomponent plasma dynamical system to a pseudopotential energy form with a constant of motion. We then determine the allowed potential range, the associated asymmetric pseudopotentials, and the wave-breaking electric field for both linear and nonlinear waves on each of the two admissible branches. We find that arbitrary-amplitude nonlinear periodic waves are intrinsically asymmetric and that the maximum field strength is set by the effective charge-density boundary of each plasma species along the field direction. Parametric analysis suggests that the critical minimum field strength required for nonlinear wave formation may be controlled by increasing either the negative-ion mass ratio, the wave propagation speed, or the negative-ion concentration; however, each of these changes produces a distinct modification of the pseudopotential geometry. This illustrates that relativistic and interspecies effects are not merely responsible for quantitative deviations from the non-relativistic and single-species cases, but instead completely reshape the nonlinear phase space governing the persistence, deformation, and breaking of periodic electrostatic waves. Full article

Efficient laser cleaning of glazed ceramic tiles requires the ink layer to be removed without damaging the brittle glaze. We investigated the removal of acrylic ink using a 1064 nm, 10 ns Nd:YAG laser operating at 1 Hz. The lens-to-sample working distance L, pulse energy, and pulse number were varied, and the cleaned regions were evaluated by optical microscopy (OM), scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM–EDS), theoretical analysis, and COMSOL simulation. At L = 20 cm, the sample was close to the nominal focal plane, and the high local fluence removed the ink rapidly, but it also produced whitening, depressions, micro-pits, and glaze damage. Increasing L to 25–30 cm enlarged the measured spot diameter, lowered the average fluence, and widened the controllable cleaning range. Two low-damage conditions were identified at L = 30 cm: 30.80 J/cm² with 3 pulses and 41.00 J/cm² with 2 pulses. SEM–EDS showed that cleaning quality cannot be judged from exposed area or carbon content alone; morphology, preservation of the native glaze microstructure, the C/O ratio, and recovery of substrate-related elements must be considered together. Under the stated model assumptions, the calculated local temperature exceeded the acrylic decomposition temperature, and the thermoelastic stress reached tens to hundreds of MPa. These results make thermal decomposition and stress-assisted interfacial separation physically plausible. However, the present data do not separate thermoelastic stress from pressure-wave loading. Likewise, visible air breakdown and non-monotonic cleaning at high pulse energy only suggest possible plasma-related attenuation because plasma density and transmitted laser energy were not measured. The reported combinations should therefore be regarded as a system-specific process window rather than a universal optimum. Full article

Since its launch in 2015, the Sentinel-2 mission has become a cornerstone of moderate-resolution vegetation monitoring, enabling spatially explicit and temporally dense observations of terrestrial ecosystems. Its combination of 10–20 m spatial resolution, a revisit interval of less than five days, and a spectral configuration including red-edge and Short-Wave Infrared (SWIR) bands has transformed optical vegetation monitoring beyond coarse-resolution greenness products. This review synthesises the use of Sentinel-2 for vegetation monitoring, with emphasis on phenology and growth dynamics, biomass and carbon estimation, vegetation stress detection, and associated methodological developments. A systematic Scopus search identified 1700 publications, of which 1097 studies were retained following thematic and methodological screening. The results reveal rapid growth in Sentinel-2-based research after 2018, reflecting its transition into a widely adopted data source supported by cloud-based processing platforms and harmonised data products. Research output is concentrated in a limited number of journals and regions, with Europe and Asia dominating contributions, while other regions remain underrepresented. Phenology and growth monitoring, biomass and carbon assessment, and vegetation stress analysis emerged as the principal application domains. Across these themes, methodological development has shifted from vegetation indices towards machine learning, hybrid radiative-transfer modelling, and multi-sensor data fusion. The reviewed evidence indicates that no single methodological approach consistently outperforms others; rather, performance depends on the target variable, ecosystem characteristics, and the treatment of observational uncertainty. Sentinel-2 has transformed vegetation monitoring by enabling spatially explicit assessment of vegetation phenology, biomass, carbon dynamics, and stress across ecosystems. However, important challenges remain, including uncertainty propagation, limited sensitivity to early physiological stress, the absence of thermal observations, and uneven validation across ecosystem types. Future progress will depend on uncertainty-aware retrieval frameworks, physically informed hybrid models, multi-sensor integration, and expanded calibration and validation across underrepresented ecosystems. Full article

Tourism, cultural events, and trade exhibitions increasingly need real-time, privacy-risk-reducing methods for quantifying visitor behavior and satisfaction at physical stands. This article addresses a fragmented evidence base by (i) presenting a focused, design-oriented literature synthesis of multimodal sensing for stand-like environments and (ii) proposing a unified, deployment-oriented reference architecture. It analyses a 60-paper design corpus (2022–2026), together with selected benchmark/context references across RGB-D, thermal cameras, LiDAR, mmWave radar, microphone arrays, and multimodal fusion, and maps the analytic corpus to event-relevant key performance indicators (KPIs). The synthesis identifies gaps in the corpus: scarce stand-specific, multimodal KPI-labeled event datasets, conceptual inconsistencies in satisfaction inference, and limited direct evidence for commercially important KPIs such as feedback, conversion, and retention. In response, the article introduces the Stand Multimodal Behavior and Satisfaction Analysis (SMBSA) architecture, a five-layer edge-AI conceptual reference architecture with hierarchical fusion and candidate analytics heads for future validation of behavior and satisfaction KPIs under GDPR-aware, privacy-by-design requirements. Full article

Wildfires are significant ecological and environmental disasters, impacting forests, ecosystems, climate stability and human life. The visible-spectrum imagery-based traditional wildfire monitoring system can fail to perform well in the presence of smoke, haze and low lighting. A number of machine learning and deep learning techniques have been proposed, but most of the studies do not provide an integrated Short-Wave Infrared (SWIR) optical-electronic payload framework along with an intelligent optimization technique. The objective of this research is to design an intelligent SWIR-based optical-electronic payload architecture for accurate detection and remote sensing of wildfire and Earth applications via deep learning and optimization techniques. The proposed framework is based on Sentinel-2 SWIR satellite data layers with wildfire and non-wildfire samples. To enhance the quality of the images and the representation of their spectral domain, the following preprocessing operations are carried out: resizing, image normalization, SWIR band extraction, and data augmentation. The following spectral feature extraction techniques are then used: burn area analysis, vegetation stress analysis, and thermal anomaly detection. The framework also incorporates SWIR optical payload design, electronic subsystem development and SWIR InGaAs sensor modeling. Finally, a Hybrid Convolutional Neural Network (CNN)–Residual Network 50 (ResNet50) model optimized by Grey Wolf Optimization (GWO) is used for wildfire classification and hyperparameter tuning. The proposed framework achieved an accuracy of 91.03%, precision of 91.27%, recall of 91.03%, and F1-score of 91.01%. The wildfire detection capability, classification robustness, and convergence performance were enhanced through the integration of SWIR spectral analysis, hybrid deep learning and GWO. The proposed framework offers an effective and trustworthy solution for intelligent wildfire monitoring and Earth remote sensing applications with enhanced spectral sensing and classification performance. Full article

With the pervasive deployment of 5G communication systems and electronic devices, electromagnetic (EM) pollution has emerged as a critical environmental concern. Due to their wide availability, low cost, and ease of acquisition, biomass materials have been widely used in the preparation of electromagnetic wave absorption materials. Compared with traditional in situ impregnation methods, this study first employs chemical reagents to reduce the lignin content within balsa wood, thereby opening more pores and enhancing the loading capacity of iron salts. Subsequently, magnetic Fe₃O₄ particles are synthesized in situ, enabling the fabrication of magnetic wood-based composites. Compared with the non-impregnated pure carbonized samples, the reflection loss value of the samples with magnetic particles increased to −42.37 dB, corresponding to a matching thickness of 1.5 mm. This is much better than the −8.79 dB of the pure carbonized samples, and is attributed to multiple loss mechanisms. In addition, modern physical and chemical analysis instruments such as SEM, TEM, XRD, XPS, and Raman were used to characterize the physical and chemical changes of the materials. Finally, its applications in aerospace and thermal response were identified. Full article

The high sensitivity of HgCdTe infrared detectors makes them highly vulnerable to laser irradiation, yet the influence of pulse width on damage behavior in the short-wave infrared (SWIR) band remains insufficiently understood. In this study, we experimentally and numerically investigate the damage effects of SWIR pulsed lasers on HgCdTe focal plane array detectors, focusing on the role of pulse width. Three lasers with pulse widths of 5.5 ns, 0.6 ms and 2 ms are used to irradiate the detector, and the damage thresholds for spot damage, line damage, and complete failure are measured. Damage morphologies are characterized by optical microscopy and scanning electron microscopy. A finite-element thermal model is also established to calculate transient temperature distributions and theoretical damage thresholds. For the 0.6 ms pulse, the measured thresholds for spot damage, line damage, and complete failure are 5.7 J/cm², 65.4 J/cm², and 157.3 J/cm², respectively; for the 2 ms pulse, these increase to 12.1 J/cm², 149.3 J/cm², and 405 J/cm² due to energy dispersion. Microscopic analysis reveals that spot damage arises from melting of HgCdTe and indium bumps, line damage from partial damage to the read-out integrated circuit (ROIC) layer, and complete failure from melt-through of the ROIC layer. The spot damage threshold of the 5.5 ns pulse is 1.2 J/cm², while neither line damage nor complete failure occurs even with a 352.5 J/cm² laser pulse, indicating different damage mechanisms due to a thermal confinement effect. The simulation results agree well with the experimental observations. These findings clarify the pulse-width dependence of damage thresholds and provide practical guidance for detector hardening and photoelectric countermeasure design. Full article

Adjustable steam ejectors exhibit significant adaptability to various operating conditions. However, the coupling regulation mechanism between ejector performance and the internal flow field remains insufficiently understood, thereby limiting further optimization. The novelty of this study lies in elucidating the ejector’s performance regulation mechanism by examining the influence of spindle position on non-equilibrium condensation in wet steam. This approach clarifies the flow–thermal–phase-change coupling mechanism and interprets the resulting condensation suppression and shock wave dynamics. In this study, the effects of operating conditions and spindle position on ejector performance were quantitatively characterized. The flow-field evolution was further analyzed through key flow-field variables (pressure, Mach number, temperature, and condensate mass fraction). Moreover, the relationship between ejector performance and flow characteristics was investigated. The flow–thermal–phase-change coupling analysis reveals that the spindle effectively regulates steam ejector performance, internal thermodynamic behavior, and phase-transition processes by adjusting the equivalent throat diameter. Under a representative operating condition, compared with the baseline position (d_t = 5.66 mm), moving the spindle in the positive x-axis direction (to d_t = 5 mm) decreased the equivalent throat diameter and the motive-fluid mass flow rate by 11.7% and 22.6%, respectively. Consequently, the distance between adjacent shock waves gradually decreased along the flow direction (by approximately 14.1%), and the global maximum Mach number decreased sharply from 2.0 to 1.6 (a 20% reduction). The jet core was significantly shortened, while both the intensity and number of shock waves in the diffuser were reduced. Additionally, the local backflow near the wall of the mixing chamber’s contraction section was suppressed, resulting in a weaker temperature rise in the backflow region. The fluid temperature approached the outlet temperature more gradually, while the average flow-field temperature increased. Meanwhile, the condensate mass fraction in the mixing chamber was significantly reduced (from 0.1 to 0), and the entrainment ratio was enhanced. This configuration is suitable for applications requiring low discharge pressure, high motive pressure, or high suction pressure. Conversely, moving the spindle in the negative x-axis direction enlarged the equivalent throat diameter, which generated higher Mach numbers and stronger shock waves. This enlarged throat configuration enhances the ejector’s resistance to elevated discharge pressure and increases the critical discharge pressure, making it more suitable for high discharge pressure, low motive pressure, or low suction pressure conditions. Full article

In modern precision manufacturing systems, multilayer metal structures are key to achieving high-performance devices. However, during actual processing, they are highly prone to interlayer thermal stress concentration and defects such as interface delamination. To thoroughly elucidate and address this stress evolution issue, this study proposes a two-temperature model based on thermomechanical coupling. A thorough analysis of the thermal–mechanical coupling behavior of copper/aluminum two-layer metal films under femtosecond laser irradiation was conducted, investigating non-equilibrium heat transfer within the two-layer material and the resulting stress evolution. The results indicate that stress waves dynamically modulate the temperature distribution, revealing the critical role of thermo-mechanical coupling in energy transfer. Further studies show that stress waves undergo reflection and transmission at material interfaces, with their phases influenced by the acoustic impedance of the materials. When stress waves propagate from a medium with high acoustic impedance to one with low acoustic impedance, the phase of the transmitted wave remains unchanged, while the phase of the reflected wave reverses. Stress unloading occurs during the phase transition; tensile stress at the interface due to reflection can induce delamination, while horizontal stress tends to initiate cracks. This work contributes to the analysis of stress evolution during laser processing of multilayer metals. Full article

Hydrothermal alteration mapping is a critical component of porphyry copper exploration because alteration assemblages provide important vectors toward mineralization. This study presents a systematic evaluation of supervised machine learning algorithms for delineating hydrothermal alteration zones using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) short-wave infrared (SWIR) surface reflectance data (AST_07XT). The investigation focuses on the Nain region within the central Urumieh–Dokhtar Magmatic Arc (UDMA), Iran, a major metallogenic belt hosting numerous porphyry copper systems. Representative spectral endmembers corresponding to Al–OH-bearing and Mg–OH-bearing hydrothermal alteration minerals were extracted using Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), and n-dimensional visualization techniques. These endmembers were subsequently used to train and evaluate a comprehensive suite of supervised machine learning classifiers, including linear, kernel-based, tree-based, ensemble, probabilistic, boosting, and neural-network algorithms for pixel-wise hydrothermal alteration mapping. Model performance was evaluated using multiple statistical metrics, including overall accuracy (OA), average accuracy (AA), precision, recall, F1-score, Cohen’s kappa coefficient, area under the ROC curve (AUC), spatial cross-validation accuracy, uncertainty analysis, and spatial agreement analysis. Among the evaluated classifiers, SVM_Linear, SVM_RBF, LDA, and MLP achieved the highest classification performance, with overall accuracies exceeding 94% and strong spatial consistency between classified maps. The resulting alteration maps display spatially coherent distributions of Al–OH and Mg–OH minerals that are consistent with established hydrothermal alteration zoning models in porphyry–epithermal systems. The mapped hydrothermal alteration zones show strong spatial correspondence with known mineralized areas and alteration patterns within the Urumieh–Dokhtar Magmatic Arc, confirming the geological reliability of the classification results. Uncertainty analysis further indicates high model confidence across most alteration zones, with higher uncertainty values mainly restricted to transitional and spectrally heterogeneous regions. The results demonstrate that integrating ASTER SWIR imagery with supervised machine learning algorithms provides a robust, scalable, and transferable framework for regional-scale hydrothermal alteration mapping and mineral exploration in porphyry copper provinces. Full article

Laser-induced damage of sol–gel SiO₂ antireflection coatings remains a key reliability issue in high-power laser systems because porous networks, residual hydroxyl groups, and defect-related absorption centers can trigger localized heating and stress concentration under nanosecond irradiation. In this work, continuous-wave CO₂ laser conditioning was used as a localized post-treatment method to regulate the microstructure of sol–gel SiO₂ coatings on fused silica substrates. The revised manuscript clarifies the processing window, scanning parameters, laser damage testing protocol, and the sample-specific nature of the reported LIDT values. Laser conditioning induces partial densification of the porous coating, dehydration of Si-OH groups, relaxation of the Si-O-Si network, and enhancement of mechanical properties. Under the optimized conditioning condition, the surface roughness decreases from 14.08 nm to 9.76 nm, and the LIDT at 1064 nm increases from 4.8 J/cm² to 7.0 J/cm². The LIDT values are discussed as a relative microstructure–property comparison for the present coating system rather than as the upper technological limit of sol–gel silica coatings. Combined FTIR analysis, thermal simulation, morphology observation, and damage probability analysis indicate that the improvement originates from the combined effects of reduced defect absorption, moderated porosity, improved heat dissipation, and enhanced resistance to thermally induced cracking. The results provide a mechanism-guided strategy for using CO₂ laser conditioning to tune sol–gel silica coatings while also identifying the need for further validation on higher-LIDT coatings and at application-relevant wavelengths. Full article

This work investigates, for the first time, nonlinear wave dynamics and chaos in nanocomposite micropipes conveying a viscous fluid, reinforced with graphene origami (GOr), and subjected to thermal loading. It extends the previous study by considering the influence of a transverse load and fluid viscosity, both of which were ignored previously. The Painlevé integrability of the governing equation is tested using the Ablowitz–Ramani–Segur (ARS) algorithm. Our findings prove the non-integrability of the governing equation, motivating a qualitative dynamical approach. Bifurcation theory is applied to multiple possible forms of the transverse load. In the absence of a transverse load, neither periodic nor solitary axial wave displacements exist. This is guaranteed by applying Bendixson’s criterion and confirmed through phase portraits. However, with a specific form of the transverse load, bifurcation analysis analytically provides the existence conditions for periodic, super-periodic, and solitary axial displacement waves. Furthermore, it is shown that kink and anti-kink solutions are absent. Explicit exact solutions are constructed in terms of elliptic functions, and their consistency and validity are verified through orbital degeneracy. The key material parameters’ impacts—GOr weight fraction, temperature change, hydrogen coverage, and shear layer stiffness—on the wave profiles are inspected numerically and eludicated physically. When an additional periodic transverse load is inserted, the system manifests quasi-periodic behavior at frequencies with small loads, transitioning to chaotic motion as the frequency grows. Both Lyapunov exponents and a Poincaré section are utilized to confirm this chaotic behavior. Our findings show the impact of fluid viscosity and the transverse load structure are significant in GOr-reinforced microtubes and highlight their relevance for advanced fluid-conveying systems. Full article

The laser irradiation effect on Charge-Coupled Devices (CCDs) has attracted wide attention in photoelectric countermeasures and imaging system hardening. This review provides a systematic analysis of the phenomena and mechanisms of laser-induced dazzling and damage effects on CCD sensors. It summarizes experimental and theoretical research progress with continuous-wave (CW), pulsed, and composite lasers, revealing distinct interaction mechanisms such as thermal effects, dielectric breakdown, and plasma ablation. The review also covers quantitative evaluation methods for assessing laser irradiation effects. This work provides a comprehensive reference for future studies. Full article