Search Results (148)

This study systematically evaluates the influence of copper (Cu) addition in gas-shielded solid wires on the microstructure and cryogenic toughness of X80 pipeline steel welds. Welds were fabricated using solid wires with varying Cu contents (0.13–0.34 wt.%) under identical gas metal arc welding (GMAW) parameters. The mechanical capacities were assessed via tensile testing, Charpy V-notch impact tests at −20 °C and Vickers hardness measurements. Microstructural evolution was characterized through optical microscopy (OM), scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD). Key findings reveal that increasing the Cu content from 0.13 wt.% to 0.34 wt.% reduces the volume percentage of acicular ferrite (AF) in the weld metal by approximately 20%, accompanied by a significant decline in cryogenic toughness, with the average impact energy decreasing from 221.08 J to 151.59 J. Mechanistic analysis demonstrates that the trace increase in the Cu element. The phase transition temperature and inclusions is not significant but can refine the prior austenite grain size of the weld, so that the total surface area of the grain boundary increases, and the surface area of the inclusions within the grain is relatively small, resulting in the nucleation of acicular ferrite within the grain being weak. This microstructural transition lowers the critical crack size and diminishes the density for high-angle grain boundaries (HAGBs > 45°), which weakens crack deflection capability. Consequently, the crack propagation angle decreases from 54.73° to 45°, substantially reducing the energy required for stable crack growth and deteriorating low-temperature toughness. Full article

The production of AISI 304 stainless steel (a corrosion-resistant alloy prone to solidification defects from high alloy content) particularly benefits from twin-roll strip casting—a short-process green technology enabling sub-rapid solidification (the maximum cooling rate exceeds 1000 °C/s) control for high-performance steels. However, the internal phenomena within its molten pool remain exceptionally challenging to monitor. This study developed a multiscale numerical model to simulate coupled fluid flow, heat transfer, and solidification in AISI 304 stainless steel twin-roll strip casting. A quarter-symmetry 3D model captured macroscopic transport phenomena, while a slice model resolved mesoscopic solidification structure. Laboratory experiments had verified that the deviation between the predicted temperature field and the measured average value (1384.3 °C) was less than 5%, and the error between the solidification structure simulation and the electron backscatter diffraction (EBSD) data was within 5%. The flow field and flow trajectory showed obvious recirculation zones: the center area was mainly composed of large recirculation zones, and many small recirculation zones appeared at the edges. Parameter studies showed that, compared with the high superheat (110 °C), the low superheat (30 °C) increased the total solid fraction by 63% (from 8.3% to 13.6%) and increased the distance between the kiss point and the bottom of the molten pool by 154% (from 6.2 to 15.8 mm). The location of the kiss point is a key industrial indicator for assessing solidification integrity and the risk of strip fracture. In terms of mesoscopic solidification structure, low superheat promoted the formation of coarse columnar crystals (equiaxed crystals accounted for 8.9%), while high superheat promoted the formation of equiaxed nucleation (26.5%). The model can be used to assist in the setting of process parameters and process optimization for twin-roll strip casting. Full article

Accurate and timely flood mapping is critical for informing emergency response and risk mitigation during extreme weather events. This study presents a synthetic aperture radar (SAR)-based approach for rapid flood extent mapping using Sentinel-1 imagery, demonstrated for Tropical Storm Imelda (17–21 September 2019) in southeastern Texas. Dual-polarization Sentinel-1 SAR data (VH and VV) were processed by computing the VH/VV backscatter ratio, and the resulting ratio image was classified using a supervised Random Forest classifier to delineate water and land. All Sentinel-1 images underwent radiometric calibration, speckle noise filtering, and terrain correction to ensure precision in flood delineation. The Random Forest classifier achieved an overall flood mapping accuracy exceeding 94%, with Cohen’s kappa coefficients of approximately 0.75–0.80, demonstrating the approach’s reliability in distinguishing transient floodwaters from permanent water bodies. The spatial distribution of flooding was strongly influenced by topography and land cover. Analysis of Shuttle Radar Topography Mission (SRTM) digital elevation data revealed that low-lying, flat terrain was most vulnerable to inundation; correspondingly, the land cover types most affected were hay/pasture, cultivated land, and emergent wetlands. Additionally, urban areas with low-intensity development experienced extensive flooding, attributed to impervious surfaces exacerbating runoff. A strong, statistically significant correlation (R² = 0.87, p < 0.01) was observed between precipitation and flood extent, indicating that heavier rainfall led to greater inundation; accordingly, the areas with the highest rainfall totals (e.g., Jefferson and Chambers counties) experienced the most extensive flooding, as confirmed by SAR-based change detection. The proposed approach eliminates the need for manual threshold selection, thereby reducing misclassification errors due to speckle noise and land cover heterogeneity. Harnessing globally available Sentinel-1 data with near-real-time processing and a robust classifier, this approach provides a scalable solution for rapid flood monitoring. These findings underscore the potential of SAR-based flood mapping under adverse weather conditions, thereby contributing to improved disaster preparedness and resilience in flood-prone regions. Full article

Soil moisture in arid areas serves as a vital indicator for assessing hydrological scarcity and ecosystem vulnerability, particularly in Northwest China (NW China), where water resource deficits critically exacerbate environmental fragility. Soil moisture retrieval through remote sensing techniques proves essential for formulating sustainable strategies to enhance local environmental management. This study presents an innovative fusion framework integrating Sentinel-2 optical data and Radarsat-2 PolSAR (Polarimetric Synthetic Aperture Radar) data to establish a three-dimensional (3D) optical–radar feature space. The feature space synergistically combines SAR backscattering coefficients (HH polarization modes), polarimetric decomposition (volume scattering components of van Zyl), and optical remote sensing indices (MSAVI and NDVI). Through systematic analysis of feature space partitioning patterns across soil moisture gradients, the Optical–Radar Soil Moisture Retrieval Index (ORSMRI) was proposed, and fitting analysis was conducted by measured soil moisture. The results confirmed consistency between ORSMRI-derived retrieved soil moisture and measured soil moisture, with ORSMRI1 attaining R² = 0.797 (RMSE = 3.329%) and ORSMRI2 reaching R² = 0.721 (RMSE = 3.905%). The soil moisture in the study area was retrieved by applying the proposed ORSMRI and utilizing its linear correlation with soil moisture. The distribution of soil moisture showed a trend of being higher in the south than in the north, and higher in the west than in the east. Specifically, low soil moisture is generally concentrated in the northern and southwestern parts of the oasis, while high soil moisture is primarily concentrated in the central part of the oasis. Full article

Rapid and accurate leaf area index (LAI) determination is important for monitoring daylily growth, yield estimation, and field management. Because of low estimation accuracy of empirical models based on single-source data, we proposed a machine-learning algorithm combining optical and microwave remote-sensing data as well as the random forest regression (RFR) importance score to select features. A high-precision LAI estimation model for daylilies was constructed by optimizing feature combinations. The RFR importance score screened the top five important features, including vegetation indices land surface water index (LSWI), generalized difference vegetation index (GDVI), normalized difference yellowness index (NDYI), and backscatter coefficients VV and VH. Vegetation index features characterized canopy moisture and the color of daylilies, and the backscatter coefficient reflected dielectric properties and geometric structure. The selected features were sensitive to daylily LAI. The RFR algorithm had good anti-noise performance and strong fitting ability; thus, its accuracy was better than the partial least squares regression and artificial neural network models. Synergistic optical and microwave data more comprehensively reflected the physical and chemical properties of daylilies, making the RFR-VI-BC05 model after feature selection better than the others ( r = 0.711, RMSE = 0.498, and NRMSE = 9.10%). This study expanded methods for estimating daylily LAI by combining optical and radar data, providing technical support for daylily management. Full article

This study examined the surface-grinding-induced microstructural modifications and corrosion attacks in a penetrating form of a high-Mn–low-Cr casting steel slab under humid environments. Various experimental and analytical findings from field-emission scanning electron microscopy, electron backscatter diffraction, transmission electron microscopy, and electrochemical analyses revealed that the abrasive grinding process led to the formation of a surface deformed region, comprising a recrystallized fine grain layer and multiple streamlines. Corrosion initially occurs preferentially along the boundary areas where Cr(Mn)₂₃C₆ particles are precipitated. Moreover, the corrosion products (Fe-based oxy/hydroxides) with a high volumetric expansion ratio detach readily from the surface deformed regions, facilitating the easy penetration of corrosive media. In contrast to conventional low-alloyed steels, which exhibit uniform corrosion behavior, corrosion-assisted penetrating attacks on ground high-Mn–low-Cr casting steel slabs occur more severely and frequently during the summer/dry season (i.e., relative humidity levels around 60% to 80%, rather than 100%) when a thin water film can form on the steel surface. Based on the result, effective technical strategies in terms of metallurgical and environmental aspects to mitigate the risk of corrosion-assisted penetrating attack of high-Mn–low-Cr casting steel were discussed. Full article

With the rapid development of hydrogen pipelines, their safety issues have become increasingly prominent. In order to evaluate the properties of pipeline materials under a high-pressure hydrogen environment, this study investigates the hydrogen embrittlement sensitivity of X70 welded pipe in a 10 MPa high-pressure hydrogen environment, using slow strain rate testing (SSRT) and low-cycle fatigue (LCF) analysis. The microstructure, slow tensile and fatigue fracture morphology of base metal (BM) and weld metal (WM) were characterized and analyzed by means of ultra-depth microscope, scanning electron microscope (SEM), electron backscattering diffraction (EBSD), and transmission electron microscope (TEM). Results indicate that while the high-pressure hydrogen environment has minimal impact on ultimate tensile strength (UTS) for both BM and WM, it significantly decreases reduction of area (RA) and elongation (EL), with RA reduction in WM exceeding that in BM. Under the nitrogen environment, the slow tensile fracture of X70 pipeline steel BM and WM is a typical ductile fracture, while under the high-pressure hydrogen environment, the unevenness of the slow tensile fracture increased, and a large number of microcracks appeared on the fracture surface and edges, with the fracture mode changing to ductile fracture + quasi-cleavage fracture. In addition, the high-pressure hydrogen environment reduces the fatigue life of the BM and WM of X70 pipeline steel, and the fatigue life of the WM decreases more than that of the BM as well. Compared to the nitrogen environment, the fatigue fracture specimens of BM and WM in the hydrogen environment showed quasi-cleavage fracture patterns, and the fracture area in the instantaneous fracture zone (IFZ) was significantly reduced. Compared with the BM of X70 pipeline steel, although the effective grain size of the WM is smaller, WM’s microstructure, with larger Martensite/austenite (M/A) constituents and MnS and Al-rich oxides, contributes to a heightened embrittlement sensitivity. In contrast, the second-phase precipitation of nanosized Nb, V, and Ti composite carbon-nitride in the BM acts as an effective irreversible hydrogen trap, which can significantly reduce the hydrogen embrittlement sensitivity. Full article

In this study, we investigate the usefulness of the spectral whitening procedure, devised by one of the authors as a preprocessing stage of envelope-detected single-look synthetic aperture radar (SAR) images, in application contexts where phase information is relevant. In the first experiment, each of the raw datasets of an interferometric pair of COSMO-SkyMed images, representing industrial buildings amidst vegetated areas, was individually (1) synthesized by the SAR processor without Fourier-domain Hamming windowing; (2) synthesized with Hamming windowing, used to improve the focalization of targets, with the drawback of spatially correlating speckle; and (3) processed for the whitening of complex speckle, using the data obtained in (2). The interferograms were produced in the three cases, and interferometric coherence and phase maps were calculated through 3 × 3 boxcar filtering. In (1), coherence is low on vegetation; the presence of high sidelobes in the system’s point-spread function (PSF) causes the spread of areas featuring high backscattering. In (2), point targets and buildings are better defined, thanks to the sidelobe suppression achieved by the frequency windowing, but the background coherence is abnormally increased because of the spatial correlation introduced by the Hamming window. Case (3) is the most favorable because the whitening operation results in low coherence in vegetation and high coherence in buildings, where the effects of windowing are preserved. An analysis of the phase map reveals that (3) is likely to be facilitated also in terms of unwrapping. Results are presented on a TerraSAR-X/TanDEM-X (TSX-TDX) image pair by processing the interferograms of original and whitened data using a non-local filter. The main results are as follows: (1) with autocorrelated speckle, the estimation error of coherence may attain 16% and inversely depends on the heterogeneity of the scene; and (2) the cleanness and accuracy of the phase are increased by the preliminary whitening stage, as witnessed by the number of residues, reduced by 24%. Benefits are also expected not only for differential InSAR (DInSAR) but also for any coherent analysis and processing carried out performed on SLC data. Full article

Synthetic aperture radar (SAR) technology has become an important means of flood monitoring because of its large coverage, repeated observation, and all-weather and all-time working capabilities. The commonly used thresholding and change detection methods in emergency monitoring can quickly and simply detect floods. However, these methods still have some problems: (1) thresholding methods are easily affected by low backscattering regions and speckle noise; (2) changes from multi-temporal information include urban renewal and seasonal variation, reducing the precision of flood monitoring. To solve these problems, this paper presents a new flood mapping framework that combines semi-automatic thresholding and change detection. First, multiple lines across land and water are drawn manually, and their local optimal thresholds are calculated automatically along these lines from two ends towards the middle. Using the average of these thresholds, the low backscattering regions are extracted to generate a preliminary inundation map. Then, the neighborhood-based change detection method combined with entropy thresholding is adopted to detect the changed areas. Finally, pixels in both the low backscattering regions and the changed regions are marked as inundated terrain. Two flood datasets, one from Sentinel-1 in the Wharfe and Ouse River basin and another from GF-3 in Chaohu are chosen to verify the effectiveness and practicality of the proposed method. Full article

Soil moisture is one of the main factors affecting microwave radar backscatter from the ground. While there are other factors that affect backscatter levels (for instance, surface roughness, vegetation, and incident angle), relative variations in soil moisture can be estimated using space-based, medium resolution, multi-temporal synthetic aperture radar (SAR). Understanding the distribution and identification of water-saturated areas using SAR soil moisture can be important for wetland mapping. The SAR soil moisture retrieval algorithm provides a relative assessment and requires calibration over wet and dry periods. In this work, relative soil moisture indicators are derived from a time series of the RADARSAT Constellation Mission (RCM) SAR compact polarimetric (CP) data over reclaimed areas of an oil sands mine in Alberta, Canada. An evaluation of the soil moisture product is performed using in situ measurements showing agreement from June to September. The surface scattering component of m-chi CP decomposition and the RL SAR products demonstrated a good agreement with the field data (low RMSE values and a perfect alignment with field-identified wetlands). Full article

The Leaf Area Index (LAI) plays a crucial role in assessing the health of forest ecosystems. This study utilized ICESat-2/ATLAS as the primary information source, integrating 51 measured sample datasets, and employed the Sequential Gaussian Conditional Simulation (SGCS) method to derive surface grid information for the study area. The backscattering coefficient and texture feature factor from Sentinel-1, as well as the spectral band and vegetation index factors from Sentinel-2, were integrated. The random forest (RF), gradient-boosted regression tree (GBRT) model, and K-nearest neighbor (KNN) method were employed to construct the LAI estimation model. The optimal model, RF, was selected to conduct accuracy analysis of various remote sensing data combinations. The spatial distribution map of Dendrocalamus giganteus in Xinping County was then generated using the optimal combination model. The findings reveal the following: (1) Four key parameters—optimal fitted segmented terrain height, interpolated terrain surface height, absolute mean canopy height, and solar elevation angle—are significantly correlated. (2) The RF model constructed using a combination of ICESat-2/ATLAS, Sentinel-1, and Sentinel-2 data achieved optimal accuracy, with a coefficient of determination (R²) of 0.904, root mean square error (RMSE) of 0.384, mean absolute error (MAE) of 0.319, overall estimation accuracy (P₁) of 88.96%, and relative root mean square error (RRMSE) of 11.04%. (3) The accuracy of LAI estimation using a combination of ICESat-2/ATLAS, Sentinel-1, and Sentinel-2 remote sensing data showed slight improvement compared to using either ICESat-2/ATLAS data combined with Sentinel-1 or Sentinel-2 data alone, with a significant enhancement in LAI estimation accuracy compared to using ICESat-2/ATLAS data alone. (4) LAI values in the study area ranged mainly from 2.29 to 2.51, averaging 2.4. Research indicates that employing ICESat-2/ATLAS spaceborne LiDAR data for regional-scale LAI estimation presents clear advantages. Incorporating SAR data and optical imagery and utilizing diverse data types for complementary information significantly enhances the accuracy of LAI estimation, demonstrating the feasibility of LAI inversion with multi-source remote sensing data. This approach offers an innovative framework for utilizing multi-source remote sensing data for regional-scale LAI inversion, demonstrates a methodology for integrating various remote sensing data, and serves as a reference for low-cost high-precision regional-scale LAI estimation. Full article

Wireless technologies are revolutionizing communications, with recent deployments, such as 5G, playing a key role in the future of the Internet of Things (IoT). Such progress is leading to an increasingly higher number of wirelessly connected devices. These require increased battery use and maintenance, consequently straining current powering solutions. Since most wireless systems rely on radiofrequency (RF) waves for communications and feature low-power technologies, it is increasingly feasible to develop and implement wireless power transfer solutions supported by RF. In this paper, a simultaneous wireless information and power transfer (SWIPT) solution targeting small mobile devices is presented. This solution uses beamforming to mitigate the path loss associated with the RF power propagation. It relies on an RF backscattering tracking algorithm to power moving devices. The feasibility to power wearable devices is demonstrated by tracking a walking individual (approximately 5 km/h) at a distance of 0.5 m while transferring a minimum of 6 dBm to a wearable device using 2 GHz RF signals. Simulations were used to determine the viability of such a solution to deliver useful power levels to a 1.2 × 1.4 m² working area without exceeding specific absorption rate (SAR) limits. Full article

This paper explores methods to enhance the reproducibility of Josephson junctions, which are crucial elements in superconducting quantum technologies, when employing the Dolan technique in 30 kV e-beam processes. The study explores the influence of dose distribution along the bridge area on reproducibility, addressing challenges related to fabrication sensitivity. Experimental methods include e-beam lithography, with electron trajectory simulations shedding light on the behavior of backscattered electrons. Wedescribe the fabrication of various Josephson junction geometries and analyze the correlation between the success rates of different lithography patterns and the simulated distribution of backscattered electrons. Our findings demonstrate a success rate of up to 96.3% for the double-resist 1-step low-energy e-beam lithography process. As a means of implementation strategy, we provide a geometric example that takes advantage of simulated stability regions to administer a controlled, uniform dose across the junction area, introducing novel features to overcome the difficulties associated with fabricating bridge-like structures. Full article

The nephrite belt in the Altun Mountain–Western Kunlun Mountain region, which extends about 1300 km in Xinjiang, NW China, is the largest nephrite deposit in the world. The Qiemo region in the Altun Mountains is a crucial nephrite-producing area in China, with demonstrated substantial prospects for future exploration. While existing research has extensively investigated secondary nephrite deposits in the Karakash River and native black nephrite deposits in Guangxi Dahua, a comprehensive investigation of black nephrite from original deposits in Xinjiang is lacking. Margou black-toned nephrite was recently found in primary deposits in Qiemo County, Xinjiang; this makes in-depth research on the characteristics of this mine necessary. A number of technical analytical methods such as polarizing microscopy, Ultra-Deep Three-Dimensional Microscope, electron microprobe, back-scattered electron image analysis, X-ray fluorescence, and inductively coupled plasma mass spectrometry were employed for this research. An experimental test was conducted to elucidate the chemical and mineralogical composition, further clarifying the genetic types of the black and black cyan nephrite from the Margou deposit in Qiemo, Xinjiang. The results reveal that the nephrite is mainly composed of tremolite–actinolite, characterized by Mg/(Mg + Fe²⁺) ratios ranging from 0.86 to 1.0. Minor minerals include diopside, epidote, pargasite, apatite, zircon, pyrite, and magnetite. Bulk-rock rare earth element (REE) patterns exhibit distinctive features, such as negative Eu anomalies (δEu = 0.00–0.17), decreasing light REEs, a relatively flat distribution of heavy REEs, and low total REE concentrations (1.6–38.9 μg/g); furthermore, the Cr (6–21 μg/g) and Ni (2.5–4.5 μg/g) contents are remarkably low. The magmatic influence of granite appears to be a fundamental factor in the genesis of the magnesian skarn hosting Margou nephrite. The distinctive black and black cyan colors are attributed to heightened iron content, mainly associated with FeO (0.08~6.29 wt.%). Analyses of the chemical composition allow Margou nephrite to be classified as typical of magnesian skarn deposits. Full article

Nb-Ti high-strength low-alloy pipeline steel was subjected to a six-pass rolling process followed by the coiling process at different temperatures between 600 and 650 °C using the thermo-mechanical testing system Gleeble 3500 (Gleeble, New York, NY, USA). This experimental steel was subjected to 72% heavy reduction through a thermos-mechanical controlled process. Thereafter, the microstructures were observed using optical microscopy, scanning electron microscopy, electron backscatter scanning diffraction, and transmission electron microscopy coupled with energy dispersive spectrometry and selected area electron diffraction. For the selected three coiling temperatures of 600, 625, and 650 °C, acicular ferrite, polygonal ferrite, and pearlite were observed, and morphology and statistical analysis were adopted for the study of precipitates. Based on the estimation by the Ashby–Orowan formula, the incremental strength through precipitation strengthening decreases with coiling temperatures and reaches 26.67 Mpa at a coiling temperature of 600 °C. Precipitation-time-temperature curves were obtained to explain the transformation of precipitates. The (Nb, Ti)(C, N) particles tended to precipitate in the acicular ferrite with [011]_{(Nb, Ti)(C, N)}//[011]_α-Fe orientation. The lower coiling temperature provided enough driving force for the nucleation of precipitates while inhibiting their growth. Full article