Search Results (4,274)

The Fe–6.5 wt.% Si alloy is a promising soft magnetic material for electric motor applications owing to its high electrical resistivity and low core loss. However, the intrinsic brittleness of this alloy precludes fabrication of thin laminates using conventional rolling processes. Laser Powder Bed Fusion (LPBF) has therefore been considered as an alternative manufacturing route, offering both geometric flexibility and the inherent advantages of additive manufacturing. Nevertheless, successful LPBF processing of Fe–6.5 wt.% Si has remained challenging due to its high-silicon content. In this study, the Fe–6.5 wt.% Si alloy was modified by introducing 1 wt.% Cr, and LPBF process variables were optimized to yield defect-free parts. The effect of Cr addition on suppressing the disorder–order phase transformation during solidification was investigated through Thermo-Calc^® thermodynamic simulations and quantified via X-ray diffraction phase analysis. Crack morphology analysis from optical micrographs revealed a marked reduction in both solidification and liquation cracks, attributed to the role of Cr in mitigating silicon segregation and consequently lowering the fraction of ordered phases. Preheating the build plate to 200 °C was found to effectively eliminate vertical cracks by reducing thermal stresses within the parts; however, a limited number of horizontal cracks initiated at the sample edges and propagated inward, likely due to elevated thermal gradients at the perimeter. To address this issue, sacrificial walls were introduced at distances of 1.0 mm and 0.2 mm from the cube edges, locally reducing the cooling rates and effectively increasing the primary dendrite arm spacing (PDAS). The reduced cooling rate also led to lower lattice misorientation, confirmed by electron backscatter diffraction (EBSD), and a significant decrease in the crack length from ~2 mm to ~0.7 mm. Full article

Accurate historical estimates of forest carbon stocks are essential for greenhouse gas inventories and REDD+ Measurement, Reporting and Verification (MRV) systems, particularly in remote and persistently cloudy regions where field inventories and optical remote sensing are limited. This study presents a retrospective mapping framework with potential relevance for Tier-3 forest carbon estimation of forest volume and carbon stocks in the temperate forests of southern Chile using historical ALOS PALSAR L-band SAR data integrated with Chile’s Continuous National Forest Inventory (CNFI). Three pilot zones in Los Lagos, Aysén, and Magallanes were analysed, covering approximately 42,000 km² of native forests dominated by Lenga, Coihue de Magallanes, Siempreverde, Roble–Raulí–Coihue, Coihue–Raulí–Tepa, and Alerce forest types. Annual 25 m ALOS PALSAR mosaics were processed to derive HH and HV backscatter, HH/HV ratio, and Radar Forest Degradation Index (RFDI) layers, which were used as predictors in k-nearest neighbours (k-NN) models calibrated with inventory plots projected to the 2010 reference year. Model performance varied substantially among forest types and pilot zones, with test r² values ranging from 0.12 to 0.90 and RMSE values between approximately 100 and 300 m³·ha⁻¹; the highest r² values were associated with forest types represented by relatively small samples and should therefore be interpreted cautiously. m³·ha⁻¹ Stratification by altitude and restriction to moderate volume ranges improved predictive performance in several cases, highlighting the influence of ecological gradients and SAR signal saturation at high levels of biomass. Despite substantial pixel-level uncertainty, the methodology reproduced broad regional patterns of forest structure and carbon distribution. Results demonstrate the potential of combining historical ALOS PALSAR archives with national forest inventories to support spatially explicit historical carbon estimation in data-limited forest regions. Full article

A sensing apparatus was developed to quantify solids fraction within a 3 m test column, demonstrating real-time monitoring of tailings sedimentation. This integrated system employs a low-power infrared laser coupled with scattering detectors alongside a low-activity radioactive source and detector. Both methodologies utilize non-destructive principles to evaluate the concentration of solids. Specifically, X-ray transmission through the medium provides a measure of the solids fraction, as X-ray attenuation corresponds to the solids percentage. Concurrently, the optical component detects radiation backscatter from the sample. To ensure precision, both instruments underwent calibration using reference materials. Experimental evaluations were conducted using two configurations: a fixed array and a depth-profiling setup. The former utilized a 2.5 m plastic column with integrated sensors placed within a settling vessel to acquire data at discrete depths. Conversely, the depth-profiling configuration involved a submersible mobile unit lowered into the column to characterize the solids profile at arbitrary depths. Full article

The blind hyperspectral unmixing of altered minerals holds significant indicative importance for the exploration of sandstone-type uranium deposits. Nevertheless, the distinctive backscattering and multiphase characteristics are typically underestimated by existing methods, resulting in limited accuracy in the unmixing performance of complex mixtures. This study presents a physics-informed Swin Transformer Network (PIST−Net) for the blind hyperspectral unmixing of hematite, goethite, biotite, and chlorite. The proposed model includes a lightweight Swin Transformer encoder for the long-range modeling of spatial and spectral features. Furthermore, a dual-branch decoder with adaptive physical parameters was introduced in the spectral reconstruction section. In this decoder, the backscattering prediction head independently estimates the backscattering factor for each endmember, accounting for the true behavior of the mineral materials. As a key parameter of the Hapke model, the learnable strategy can reduce the spectral error in the single-scattering albedo (SSA) space to improve the accuracy of abundance estimation. The results show that PIST−Net consistently outperformed all six competing models on the altered mineral (AM) dataset and the NASA Reflectance Experiment Laboratory (RELAB) dataset. For mixtures composed of 2–4 endmembers, the mean RMSE of estimated abundances ranges from 0.0312 to 0.1037. Full article

Industrial pure copper sheets as a crucial electronic material have currently attracted extensive attention from scholars due to the rapid development of the information technology industry. However, past investigations into the regulation discipline of the microstructure and mechanical properties of pure copper have not paid sufficient attention due to the inevitably low strength induced by the lack of alloying elements. In this study, a typical T2 copper sheet was fabricated by a severe cold-rolling process with a deformation amount of 83% followed by different annealing temperatures ranging from 200 to 500 °C, and the influence of annealing temperature on the evolution of microstructure, mechanical and physical properties and crystallographic orientation (CRO) was investigated systematically. The microstructure features and micro-texture of the studied T2 copper sheet were characterized by optical microscopy (OM) and scanning electron microscopy equipped with electron back-scattered diffraction (EBSD) techniques throughout the entire process from the initial state to the deformed state and annealed state, and the tensile property and electrical conductivity were tested by utilizing a universal testing machine and a digital micro-ohmmeter. Results indicate that the yield strength and tensile strength of the studied T2 copper sheet are both decreased with increasing annealing temperature, accompanied by an increase in electrical conductivity, and the maximum conductivity of up to 98.2% IACS can be reached at the annealing temperature of 500 °C. With the increase in annealing temperature, the degree of recrystallization becomes increasingly sufficient, and the volume fraction of recrystallized grains is increased from ~17.8% to ~35.7% with the annealing temperature increased from 200 to 500 °C. The texture component of the studied T2 copper sheet processed by severe cold rolling with a deformation amount of 83% is characterized by a deformation texture composed of copper texture and S texture, and is then transformed into a texture that predominantly consists of Cube texture under the application of annealing treatment, and the maximum intensity value of Cube texture is enhanced with the increase in annealing temperature. Full article

Hydrogen (H²) is a promising energy carrier, but its wide flammability range requires rapid and reliable leak detection. In this study, we developed a non-contact stand-off ultraviolet (UV) light detection and ranging (lidar) system that simultaneously acquires Raman and Rayleigh–Brillouin backscattering signals for long-range H² measurement. A 360 nm UV excitation source was used, and the system was evaluated at distances of 1, 3, 5, 10, 20, and 30 m using standard gases containing 10–1000 ppm H². Quantitative analysis based on partial least squares (PLS) regression showed high linearity across the full distance range, with coefficients of determination (R²) of 0.97–0.98 and standard errors of calibration (SECs) of 40–70 ppm. The Rayleigh–Brillouin channel provided a useful complementary signal, particularly at longer distances, improving the robustness of concentration prediction when combined with the Raman response. These results demonstrate the feasibility of real-time, long-range H² monitoring in large spaces and support the use of combined Raman and Rayleigh–Brillouin backscattering for safety monitoring in hydrogen-related facilities. Full article

Soil moisture (SM) is a core state variable of terrestrial hydrological and land–atmosphere interactions. Machine learning-based downscaling and retrieval frameworks that integrate multi-source remote sensing and auxiliary datasets have become mainstream approaches for generating high-spatial-resolution SM products. However, the spatial domain dependence evolution law governing the relative importance of these multiple predictors remains insufficiently quantified. This study constructs an integrated XGBoost and SHAP interpretability framework to reveal how the contribution and driving mechanisms of predictors shift across spatial domains. We compiled global in-situ SM observations from 24 international soil moisture network (ISMN) monitoring networks spanning 2017–2024. Predictors were classified into five categories: Sentinel-1A radar backscatter, vegetation indices, ERA5-Land meteorological forcing, topographic geospatial variables, and static soil texture attributes. Two modeling approaches were adopted: independent local network models representing the regional domains and a unified composite model representing the global domain. Model performance metrics demonstrate that the global composite model yields robust generalization with minimal overfitting, while individual regional models exhibit domain-specific retrieval differences due to varying land surface conditions. Pearson correlation analyses confirm that physical covariances remain nearly consistent across different domains, whereas cross-category correlations vary with spatial domain and local landscape backgrounds. SHAP-based feature importance quantification reveals clear domain-dependent differences among dominant predictors. This work quantitatively verifies the spatial domain dependence of parameter importance in machine learning-based SM retrieval, providing guidance for domain-adaptive predictor selection and interpretable high-resolution SM modeling under diverse land surface conditions. Full article

Accurate mapping of rubber plantations is essential for sustainable land management and forest conservation in tropical regions. However, existing methods face two major challenges: persistent cloud cover limits the effectiveness of optical remote sensing in tropical areas, and regional phenological heterogeneity hinders the transferability of fixed-parameter approaches. This study proposes a Phenology-Adaptive Rubber Plantation Mapping (PARM) framework that integrates Sentinel-1 SAR time-series data with optimally selected spectral indices through a cascading constraint architecture. The framework operates as a structurally coherent system wherein SAR-derived phenological anchors explicitly govern downstream optical analysis across three internally dependent modules. First, three key phenological nodes—leaf-off start (LOS), fastest greening point (FGP), and full canopy point (FCP)—are extracted directly from SAR VH-polarization backscatter time series, enabling cloud-independent extraction of phenological temporal anchors. Second, the Jeffries–Matusita (JM) distance, evaluated within SAR-constrained phenological windows, is employed to identify the optimal vegetation and water indices for each region from six candidate spectral indices. Third, a time-weighted Rubber Plantation Discrimination Index (RPDI) is constructed using the selected indices and locally extracted phenological nodes, thereby amplifying the coupled signals of canopy greenness and moisture dynamics during critical phenological transitions. The framework was validated in Hainan Island and Vietnam, two regions with contrasting phenological regimes, using a spatial-block partitioning protocol (leave-one-subregion-out combined with DBSCAN-based clustering) designed to prevent samples from the same plantation from occurring in both training and test subsets. Within the Dynamic World forest mask, PARM achieved overall accuracies of 92.04% and 91.24%, respectively (93.57% and 91.00% on the fully held-out Qionghai City and Gia Lai province subregions), with Kappa coefficients exceeding 0.81 in both regions, consistently outperforming schemes based on raw spectral bands, individual spectral indices or direct multi-source time-series stacking. Error structure analysis revealed that residual classification failures are primarily associated with landscape fragmentation, stand immaturity, and residual cloud contamination, delineating the generalizability boundaries of the framework. These results demonstrate that tightly coupling SAR-based phenological characterization with adaptive optical index selection through a cascading constraint architecture provides a reliable foundation for rubber plantation mapping in cloud-prone tropical regions. Full article

This study comparatively investigates the coarse-grained heat-affected zone (CGHAZ) responses of two industrial X65 seamless pipeline steels with distinct composition–microstructure characteristics under simulated girth-welding thermal cycles. One steel exhibits a predominantly bainitic initial microstructure, whereas the other consists of a ferrite–bainite dual-phase microstructure. Low-temperature Charpy impact testing, microhardness measurements, scanning electron microscopy (SEM), transmission electron microscopy (TEM), electron backscatter diffraction (EBSD), prior-austenite grain reconstruction, and JMatPro 13.0-based continuous cooling transformation (CCT) calculations were employed to evaluate their heat-input sensitivity and microstructural evolution. At heat inputs of 7–10 kJ/cm, both steels maintained high impact toughness at −20 °C, with average absorbed energies of approximately 250 J. A pronounced difference emerged at 15 kJ/cm the bainite-dominated steel retained relatively high impact toughness and higher crack-initiation and -propagation energies, whereas the ferrite–bainite steel exhibited a marked toughness reduction. At higher heat inputs of 20–30 kJ/cm, both steels showed substantial toughness deterioration associated with severe prior-austenite grain growth and coarsening of the bainitic transformation products. Microstructural and crystallographic analyses showed that the bainite-dominated steel generally retained finer prior-austenite grains and more refined crystallographic features under the investigated thermal cycles. Detailed characterization at 15 kJ/cm further revealed finer prior-austenite grain, packet, and block structures, together with more tortuous crack-propagation paths. JMatPro calculations predicted a lower bainitic transformation temperature for this steel, which is consistent with the experimentally observed tendency toward finer bainitic transformation products. The superior CGHAZ toughness retained by the bainite-dominated steel is therefore associated with the combined effects of alloy composition, initial metallurgical state, transformation behavior, and hierarchical crystallographic refinement rather than the initial microstructure alone. The results highlight the importance of coupled composition–transformation–microstructure effects in determining the welding heat-input tolerance of industrial X65 seamless pipeline steels. Full article

This study presents a high-resolution geomorphological and habitat map of the Sinuessa coastal sector (Tyrrhenian Sea), revealing the presence of an extensive and exceptionally shallow coralligenous bank developed between 5 and 16 m water depth. Multibeam bathymetry, side-scan sonar backscatter, sediment analyses, and Remotely Operated Vehicle (ROV) observations were integrated within a Geographic Information System (GIS) framework to characterize seabed morphology, acoustic facies, and associated benthic habitats. ROV surveys document a diverse macro- and epimegabenthic community, including both sciaphilous and photophilous taxa, as well as several protected and structuring species. Water depth alone does not discriminate among the mapped substrate classes (Kruskal–Wallis, p = 0.578), whereas acoustic backscatter, slope, and terrain ruggedness all do (p < 0.01), indicating that depth-independent controls govern the distribution of the bioconstruction. We hypothesize that persistently elevated turbidity and terrigenous input from the Volturno and Garigliano river systems reduce light penetration and generate, at 5–16 m, optical conditions comparable to those normally found at greater depths. This hypothesis is consistent with the geomorphological, sedimentological, and biological evidence presented here and with published oceanographic observations in the Gulf of Gaeta, but it has not been verified by in situ optical measurement, which we identify as the priority for future work. Relative backscatter intensity correlates significantly with mean grain size (Spearman ρ = −0.710, p < 0.001) and with gravel and mud content, and the four mapped classes differ significantly in backscatter, slope, and terrain ruggedness. These findings provide new insights into the environmental controls on coralligenous development and highlight the ecological relevance of shallow, turbidity-driven coralligenous systems within highly impacted Mediterranean coastal areas, with direct implications for habitat conservation and spatial management. Full article

Synthetic Aperture Radar (SAR) backscatter serves as a key tool for tracking surface water dynamics; however, single-source data dependencies introduce systematic bias tied to the specific physical limitations of the signal. A primary challenge in SAR analysis is the backscatter ambiguity created by ‘water look-alike’ surfaces, which frequently result in false-positive water detections. We show that integrating interferometric repeat-pass coherence significantly enhances the robustness of hydrological mapping in environments where backscatter is prone to signal ambiguity. Using global-scale C-band Sentinel-1 (S1) VV-polarized one-year mosaics (December 2019 to November 2020), we first analyzed normalized backscatter and coherence signatures across major land cover and land use (LULC) classes. To benchmark the complementary value of these data streams, a tile-based minimum-error thresholding approach was applied to detect permanent water surfaces across five challenging global test sites. This evaluation was conducted without post-processing or masking to isolate the fundamental strengths of each dataset. The results indicate that coherence is an optimal complement to backscatter in arid and bare soil regions, where it vastly outperforms backscatter in mapping inland water surfaces. Crucially, since the spatial overlap of False Positives and False Negatives between datasets is minimal, the inherent complementarity of the datasets is proven here via a logical AND fusion rule, which significantly mitigates commission errors and yields substantial improvements in the aggregated F1-score and IoU performance. Analysis-ready L-band NISAR products could contribute to a more comprehensive approach for operational, large-scale surface water assessments. Full article

Orientation rotation in grain-boundary regions plays a critical role in controlling the crystallographic texture of metallic materials. In this study, the ideal λ texture ({001}<uv0>) in non-oriented silicon steel is chosen as the target orientation. The oriented stability in grain-boundary regions during cold rolling is systematically investigated by combining crystal plasticity simulations and quasi in situ electron backscatter diffraction (EBSD) experiments. Oriented stability is defined as the rate of change in the misorientation angle between an arbitrary orientation and the target orientation, thereby quantifying the rotational tendency relative to the target in grain-boundary regions. The results reveal that the oriented stability in grain-boundary regions is highly sensitive to both the initial and neighboring orientations. For initial orientations near the critical boundary separating convergence and divergence zones, the oriented stability is highly susceptible to neighboring orientations, with some neighboring orientations even reversing the rotation direction. In contrast, when the initial orientation is far from this critical boundary, the influence of neighboring orientations becomes weaker. Furthermore, the concept of contributed oriented stability is introduced to statistically evaluate the effect of different neighboring texture components in polycrystals. This work elucidates the underlying mechanism of orientation rotation in grain-boundary regions, and provides a new theoretical framework and a quantitative strategy for optimizing favorable textures. Full article

The “stereo height assignment method” developed for NASA and NOAA for GOES-R ABI Atmospheric Motion Vectors (AMVs), a purely geometric method using the parallax observed from different satellites, has been included in the NWCSAF AMV product (NWCSAF GEO-I HRW, High Resolution Winds) as an additional height assignment option for AMVs in the region jointly observed by MTG-I and GOES-East over the Atlantic Ocean. Stereo and the alternative non-stereo height assignment (“Cross Correlation Contribution (CCC)”) are compared with ECMWF ERA5 reanalysis winds and EarthCARE ATLID Mie Attenuated Backscatter (MAB) curtains. For low-level clouds, both methods generally conform well with apparent cloud tops in MAB curtains. For higher clouds, more differences are seen between stereo and non-stereo heights. Compared with ERA5 winds, stereo shows the most improvement above 6 km. However, the stereo method produces 70–90% less AMVs since additional high-quality matches are needed from both FCI and ABI imagery. An updated HRW will be released to NWCSAF users in 2027 as version “NWCSAF GEO-I v2027.” The combined provision of both stereo and non-stereo CCC height assignment methods will enable further studies (already planned) of the AMV best-fit level for different satellite channels and cloud types, heights and depths. Full article

Flood events in agricultural floodplains reflect not only rainfall intensity but the vulnerability of the affected area at the moment of the event. This study examines the January–February 2026 flood in Larache Province, Morocco, through an integrated remote sensing workflow combining Sentinel-1 SAR, CHIRPS precipitation, and Dynamic World land cover in Google Earth Engine, processed via the rgee R package. Flood extent was mapped using SAR backscatter change detection and cross-checked against rainfall dynamics, yielding about 6660 ha of inundation (2.4% of the province), concentrated along the main Loukkos river corridor and adjacent floodplain around Ksar El Kebir, with smaller scattered patches to the south. Land cover was assessed across four temporal windows (spring 2025, pre-event, post-event, and spring 2026) to evaluate how the landscape entered the event and how it recovered. A significant share of normally cultivated land was in a bare-soil state before the flood, a condition that the literature associates with increased runoff. Post-flood analysis across 25 sample areas grouped into three geomorphic zones shows spatially uneven recovery, with cropland still below seasonal norms in spring 2026. These patterns are consistent with structural land-use conditions (wetland loss, intensive seasonal agriculture, drought-degraded soils) that may have amplified an already severe event. The findings support cover cropping, updated flood-hazard zoning, and targeted wetland restoration to reduce vulnerability in the Loukkos floodplain and comparable Mediterranean alluvial floodplains. Full article

High-frequency broadband acoustics can provide fine spatial resolution for near-range fish measurements, but the performance and limitations of beam-position-resolved backscatter measurements require careful evaluation. This proof-of-concept study examined one commercially sourced, dead, previously frozen specimen of each of three cultured fishes: golden pompano (Trachinotus ovatus; 24.4 cm), mandarin fish (Siniperca chuatsi; 29.1 cm), and large yellow croaker (Larimichthys crocea; 31.2 cm). A 650–750 kHz narrow-beam system was referenced to a 10.3 mm tungsten-carbide sphere, and matched-filter pulse compression and 1° stepwise scanning were used to estimate a beam-position-resolved backscatter metric along each body. At broadside incidence, the section-summed backscatter indices were −33.61, −22.45, and −33.07 dB for the T. ovatus, S. chuatsi, and L. crocea specimens, respectively. The section-summed abdominal backscatter index, in the region occupied by the swimbladder in the post-thaw X-ray images, exceeded the arithmetic mean of the head and tail group indices by 9.71 ± 1.84 dB (range: 8.27–11.86 dB). Tailward beam positions fell below the noise floor at approximately 12.5% of the expected scan positions for S. chuatsi and 22.2% for L. crocea. A 15° departure from broadside reduced the section-summed index by 3.73–11.43 dB. Kirchhoff-ray-mode (KRM) simulations based on post-thaw dual-view X-ray geometry were broadly consistent with the specimen-level contrast observed among the preserved specimens, but were 0.92–2.74 dB lower than the corresponding broadside section-summed measurement indices at 700 kHz. These differences are not a quantitative validation because the measured and modeled estimators, frequency weighting, geometry, and tissue parameters were not equivalent. These results demonstrate the feasibility of a calibrated beam-position workflow for preserved specimens, while not establishing live-fish target strength, species benchmarks, or biomass-estimation performance. Full article