Search Results (1,674)

Reliable localization without GPS is a prerequisite for autonomous unmanned aerial vehicles (UAVs) operating inside warehouses, where a lightweight monocular camera paired with an inertial measurement unit (IMU) and onboard computer are the minimal sensing and processing an onboard platform can carry. This paper presents a tightly coupled monocular point-feature visual-inertial odometry (VIO) system for that setting, realized on a GTSAM fixed-lag factor graph with inverse-depth landmarks, on-manifold IMU preintegration, and an online loop-closure pose graph. The system is developed as the initial estimation stage of an autonomous stock-management UAV under development for indoor logistics warehouses. The decisive design element is the bootstrap: the metric, gravity-aligned initialization of a monocular estimator is well conditioned only under a translation-rich trajectory, a condition the near-zero-baseline pickup and takeoff transient that opens every indoor flight violates. Building on the visual-inertial alignment of VINS-Mono, we harden this step with a pre-bundle-adjust conditioning gate and a continuous-window initialization that refines the whole bootstrap window inside the smoother instead of freezing a single seed. On all eleven EuRoC MAV sequences, indoor flight tests recorded onboard a micro air vehicle in an industrial hall and two instrumented rooms, one fixed configuration per operating environment converges on every sequence, including three that otherwise diverge by tens to thousands of meters, and, driven by the same feature stream as locally run VINS-Mono and PL-VINS baselines, attains the better pure-odometry accuracy on nine of the eleven, with ATE RMSE of 0.12–0.37 m on the Machine Hall, a margin a paired signed-rank test confirms against VINS-Mono and leaves unconfirmed against PL-VINS at this sample size. We identify the stock fixed-lag marginalization as the principal consistency limitation and outline First-Estimates-Jacobian marginalization as the route to a more consistent estimator, establishing a characterized point-only baseline on one public benchmark as the starting point for subsequent on-platform work. Full article

Agricultural drip fertigation is a highly coupled dynamic process in which precision resource management depends on the coordinated performance of the entire equipment chain. Against the backdrop of global water scarcity and excessive fertilizer application, improving the full-process precision of mixing, injection, sensing, control, distribution, and terminal delivery has become a prerequisite for the wider adoption of fertigation. This review evaluates advanced process-monitoring technologies and closed-loop control architectures within modern cyber-physical fertigation systems, covering fertilizer solution preparation and mixing, injection devices, liquid- and solid-phase state sensing, intelligent control algorithms, and pipeline distribution with terminal emitters. Online mixing has evolved from gravity-based batch pre-mixing toward continuous metered injection with vortex-guided static mixing, electrical conductivity (EC) sensing with drift compensation and granular mass flow detection form the perceptual basis of closed-loop regulation, control has advanced from proportional–integral–derivative (PID) controllers through variable-universe fuzzy logic to artificial neural network (ANN) hybrids with metaheuristic optimization, and pipeline pressure regulation together with emitter anti-clogging strategies determine long-term distribution uniformity. A quantitative analysis shows that the attainable precision of the sensing–decision–execution chain is bounded by the coupling among sensor accuracy, process delays, control performance, and actuator response rather than by any single device. The review identifies five unresolved gaps—sensor reliability, multi-season field validation, interoperability, low-cost automation, and fertilizer-type adaptability—and recommends that future research prioritize low-cost Internet of Things (IoT) sensor arrays on low-power wide-area networks, edge–cloud collaborative control, and foundation-model-driven autonomous decision-making, co-designed as one coupled specification. Full article

Extreme weather events increasingly affect the safety, durability, and operational performance of road infrastructure, creating the need for sustainable thermal management solutions. Among the available technologies, low-enthalpy geothermal systems offer significant advantages by providing continuous heating and cooling capabilities with reduced environmental impact compared to conventional maintenance practices. This study presents the methodology developed within the GEO-ROAD project to assess shallow geothermal resources across Spain and support the future deployment of geothermal road systems. The proposed framework integrates geological, thermal, and satellite-derived geophysical information through a unified GIS-based workflow, combining multivariate statistical analysis, map algebra, and automated geospatial processing to generate a regional geothermal potential model. In addition to conventional geological characterization, the methodology incorporates magnetic and gravity data from satellite missions, airborne surveys, and ground-based observations to improve the spatial representation of subsurface conditions. The resulting geothermal potential assessment constitutes a key component of the GEO-ROAD digital platform, where it will be combined with climatic risk maps and road infrastructure information to identify the most suitable locations for geothermal applications. By linking geothermal resource assessment with infrastructure-oriented decision-making, the proposed methodology provides a scalable and transferable framework for supporting the planning of sustainable and climate-resilient road thermal management systems. Full article

Tantalum and niobium are critical strategic rare refractory metals; however, most associated tantalum–niobium resources are characterized by ultra-low grade, finely disseminated grains, and severe argillization, which causes pronounced slime coating of gangue mica on valuable mineral surfaces and impedes efficient recovery via gravity separation. In this study, an innovative beneficiation route combining sodium silicate pre-dispersion conditioning with shaking-table gravity separation was proposed to recover a spodumene-dominant pegmatitic lithium ore containing trace associated Nb–Ta minerals, with mica as the major slime-forming gangue. Process mineralogy analysis revealed that the raw ore has a total (Nb,Ta)₂O₅ grade of only 0.019%, with the main valuable minerals being columbite-(Mn), columbite–tantalite, and tantalite, whereas layered mica minerals constitute the primary argillization gangue that readily generates micro-fine slimes smaller than 5 μm. Single-factor tests demonstrated that the optimal grinding fineness was 84.4% passing 200 mesh, and the optimal feed pulp density for gravity separation was 28.6%. Adjusting pulp concentration alone, without a dispersant, yielded a Nb₂O₅ concentrate grade of merely 0.144%, as severe slime coating greatly limited separation selectivity. Following the introduction of sodium silicate for pre-dispersion, the separation performance improved markedly at the optimal dosage of 300 g/t: the concentrate Nb₂O₅ grade reached 1.28% (8-fold higher than the blank test), and the Ta₂O₅ grade increased to 0.47% (85-fold higher than the blank test). Multi-scale characterization, including zeta potential measurements, ultraviolet–visible (UV–vis) diffuse reflectance spectroscopy, Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS), was employed to elucidate the dispersion mechanism of sodium silicate. The results confirmed that sodium silicate undergoes selective chemisorption on mica surfaces by forming Si–O–Al bonds with surface Al–OH active sites, which substantially increases electrostatic repulsion between mineral particles and eliminates mica slime coating on tantalum–niobium minerals. In contrast, sodium silicate exhibits only weak physical adsorption on tantalum–niobium mineral surfaces, with no evident chemical bonding. This work provides a low-cost, eco-friendly pretreatment–gravity separation coupling technology for the efficient enrichment of argillized ultra-low-grade tantalum–niobium associated ores and offers theoretical guidance for the green utilization of complex tantalum–niobium tailings and low-grade mineral resources. Full article

As the largest inland river basin in China’s extremely arid region, the stability of the groundwater–vegetatifon system in the Tarim River Basin is crucial for the consolidation of the ecological security barrier in the northwest. To reveal the evolution law of groundwater storage in the watershed from 2003 to 2024 and its response mechanism to vegetation dynamics, this study is based on GRACE gravity satellite, GLDAS land surface assimilation and MODIS remote sensing data. The Theil Sen trend analysis, Hurst index, spatiotemporal Granger causality test, and standardized multiple linear regression model are integrated to systematically analyze the spatiotemporal heterogeneity, future evolution trend, and multi-driving factor contribution pattern of groundwater storage (GWSA) in the watershed. The results showed that: (1) During the study period, the GWSA of the watershed showed a significant downward trend, with a rate of −3.5 mm/a, and experienced a spatial redistribution process of “comprehensive loss local recovery southern compensation northern loss”. The northern and peripheral regions faced new depletion risks. (2) The vegetation condition continues to improve, and the VCI gradually rises from the low to medium range, but the spatial heterogeneity increases synchronously; there is a significant spatial positive correlation between VCI and GWSA, with only a strong lag driving effect in the southwestern region (F > 40). The explanatory power of vegetation factors for groundwater in other regions is limited. (3) Future trend predictions show that over 70% of the region will continue in the direction of historical changes, and the continuous loss trend in the north is difficult to reverse. (4) There is significant spatial differentiation in the contribution rate of driving factors: vegetation conditions (VCI) are the dominant factor, controlling 57.53% of the watershed edge and eastern region; precipitation and temperature dominate the central region (24.94%) and southwestern desert areas (17.53%), respectively. The research results can provide scientific basis for differentiated ecological water delivery and refined management of water resources in the Tarim River Basin. Full article

Liquid Time-Constant networks (LNNs), recurrent models with adaptive, input-dependent time constants, were evaluated for water level prediction in an urban drainage system. The architecture was assessed on a ten-year measurement dataset from the Bellinge catchment and benchmarked against gated recurrent unit (GRU), long short-term memory (LSTM), temporal convolutional network (TCN), and multilayer perceptron (MLP) baselines. The best-performing LNN variant achieved the highest mean predictive accuracy in the benchmark (Nash–Sutcliffe efficiency, NSE = 0.849), with particularly accurate representation of the continuous response of the gravity-driven part of the network without substantial degradation during flash-flood events. The analysis showed that the adaptive time constants help distinguish system-wide hydraulic processes from local control actions while providing interpretable diagnostics of the model’s internal response scale. The principal challenge for the LNN was the intermittent operation of the pumping station; isolating the pump pathway in the dual-branch DB-LNN variant mitigated this performance degradation while preserving predictive accuracy at the remaining sensors. The ablation analysis indicated that architectural separation of the processing pathways reduced interference between the continuous hydraulic dynamics and the local switching dynamics of the threshold-controlled facility. Full article

Identifying favourable zones for geothermal exploration at the regional scale remains challenging, particularly in areas where conventional geophysical surveys are spatially limited or economically unfeasible. This study presents an integrated framework for delineating geothermal favourability across the Iberian Peninsula using global gravity and magnetic products combined with subsurface thermal information. EGM2008, WGM2012, EMAG2, and WDMAM2 were compared and harmonized through geostatistical modelling, anisotropic ordinary kriging, and common-grid processing. Potential-field transformations and spectral coherence analysis were used to derive a Geophysical Favourability Index (FI_geof). This index was integrated with temperature at 100 m depth using weighted fuzzy logic, applying FuzzyLinear and FuzzyLarge membership functions with a 60% FI_geof and 40% temperature weighting, to obtain the Geothermal Favourability Index (FI_geot). Quantitative comparison and cross-validation indicated that EGM2008 and EMAG2 were the most suitable primary reference products within their respective datasets, whereas WGM2012 and WDMAM2 provided complementary regional-scale information. The fuzzy integration identified the highest favourability mainly in Galicia and the Levante–Betic sector, where elevated FI_geot values coincide with heat-flow values of approximately 96–154 mW m⁻² and comparatively high geothermal gradients. Around 20% of the study area was classified within the highest favourability category. The resulting FI_geot should be interpreted as a regional screening and prioritization tool rather than as direct evidence of an exploitable geothermal resource. Overall, the proposed methodology provides a reproducible approach for identifying priority areas for further geothermal investigation in large and incompletely characterized regions. Full article

Solid gravity energy storage (SGES) has emerged as a promising long-duration energy storage option, but systematic safety comparisons among its principal technology pathways remain limited. This study develops a unified expert-based framework for the comparative safety screening of vertical tower-based SGES (VT-SGES), vertical shaft-based SGES (VS-SGES), inclined cable-driven SGES (IC-SGES), and inclined rail-based SGES (IR-SGES). The principal methodological contribution is an integrated evaluation architecture that combines a three-dimensional, nine-indicator safety hierarchy, group AHP weighting, criterion-specific anchored scoring, non-compensatory critical-indicator screening, and multi-method robustness analysis. Ten experts completed three consultation rounds, and the valid pairwise judgments were aggregated using the geometric mean. Structural safety received the highest criterion weight (0.5788), while structural load response and critical-component reliability (0.3127), long-term service stability (0.1718), and start-up and braking safety (0.1528) were the three most influential indicators. The aggregate pathway scores (mean ± SD) were 4.4203 ± 0.1440 for IR-SGES, 3.9688 ± 0.1212 for IC-SGES, 3.1463 ± 0.1689 for VS-SGES, and 3.0690 ± 0.1320 for VT-SGES, yielding the ranking IR-SGES > IC-SGES > VS-SGES > VT-SGES. Kendall’s coefficient of concordance was 0.916 (p < 0.001), and the critical-indicator screen identified C5 and C9 as priority mitigation items for VT-SGES. Criterion-weight scenarios, 100,000-run weight–score perturbations, leave-one-expert-out analysis, rank-reversal calculation, and a TOPSIS cross-check supported the stability of the first two positions and identified the condition-dependent ordering of VS-SGES and VT-SGES. By coupling compensatory aggregation with critical-indicator screening and robustness testing, the framework provides a transparent and reproducible basis for comparative safety screening and technology-pathway selection in SGES. Full article

This work presents a microwave attitude sensing method and device based on localized perturbation of a split-ring resonator (SRR). The sensor comprises a planar SRR, parallel microstrip feed lines and a metallic disk that can move along a circular trajectory. When the sensor’s orientation is modified in a plane perpendicular to the ground, the metallic disk moves within the constrained structure under the influence of gravity and changes its position relative to the SRR, modulating the local near field and the microstrip coupling state. Consequently, variations in angle are observed across multiple S-parameter channels. The mechanism is validated through simulation and experimental measurements. The measured S-parameters are used to construct a circular residual mixture-of-experts Gaussian process regression (MoE-GPR) model, which is developed for 360° angle reconstruction. In leave-one-angle-out (LOAO) validation on data sampled at 2.5° intervals, the proposed reconstruction method achieves a mean absolute error (MAE) of 0.700°. When trained on data sampled at 10° intervals and tested on a dataset sampled at 2.5° intervals, the proposed method achieves an MAE of 1.125°, demonstrating its generalization across different angular sampling conditions. As no active electronics are required at the moving sensing element, the proposed configuration has potential for integration with RF sensing and communication platforms, as well as for inclination sensing referenced to gravity, orientation detection and structural health monitoring. Full article

Although the mineralogical form of occurrence of critical metals is widely recognised as a key factor controlling their recovery during beneficiation, this relationship has rarely been verified directly on freshly mined ore and its primary beneficiation products from Central Asian polymetallic deposits. This raises the research question of how the mineralogical mode of occurrence of Bi, In, Cd, Co, Se, Te and Re governs their distribution between gravity and flotation products. Accordingly, the aim of this study was to establish how the mineralogical form of occurrence of these critical metals determines their distribution among gravity-concentration and flotation products, using ores from the Zhuantobe and Strezhanskoe deposits (Kazakhstan) as a case study. To this end, the mineralogical features and distribution patterns of critical metals during gravity and flotation beneficiation of polymetallic ores from these deposits were investigated by optical microscopy, X-ray diffraction, and SEM-EDS, while metal distribution among beneficiation products was determined by chemical analysis. Sphalerite, galena, pyrrhotite, and silver tellurides were identified as the main carriers of the critical metals, with bismuth occurring as an isomorphic admixture in sphalerite (3.69 wt.%) and galena (1.85 wt.%). During flotation, distribution was governed by mineralogical affinity: cadmium and indium were preferentially concentrated in the zinc concentrate (56.31% and 15.44% recovery, respectively), bismuth in the copper–lead concentrate (23.03%), and selenium and rhenium in the copper-bearing products (23.60% and 37.05%). Correlation analysis of the gravity-concentration products confirmed a close association of cadmium with sphalerite (R² = 0.9998), bismuth with galena and sphalerite (R² = 0.9674), and cobalt with iron-bearing sulfides (R² = 0.9144). These results demonstrate that the distribution of critical metals is governed primarily by their mineralogical form of occurrence rather than by bulk ore content, providing a basis for technologies for the complex processing of polymetallic ores. Full article

Advanced analysis has been shown to improve material efficiency in statically indeterminate steel-framed structures compared with member-based linear elastic design methods. However, limited research has investigated its applicability to geometrically nonlinear steel structures where residual stresses are induced by the bending process. In this study, the material optimization potential of advanced analysis has been quantified for two arch-based structures by comparing the volume of steel required to satisfy the criteria of both the system and member-based analysis methods in accordance with AS 4100:2020. The two structures were analyzed using the finite element analysis software Strand7 (R3.1.6) and subjected to combined gravity and wind loading in alignment with the serviceability and ultimate limit states specified in AS 1170.0:2002. System behavior was analyzed through the Arc-length plastic zone method. The results indicate that in one of the arch-based structures, advanced analysis can improve material utilization by 8.1%. Provided that future research both validates the use of the reduced stiffness method for treatment of initial geometric imperfections and verifies system reliability factors for structures with curved geometries, advanced analysis presents a practical design method for this structure. Comparison of the two case studies found that advanced analysis has the potential to improve material efficiency only when linear elastic failure is governed by ultimate limit state criteria. It is therefore evident that the material optimization findings of this research cannot be generalized to all arch-based structures, as they are contingent upon the geometry of the model analyzed, the loading scenarios considered, and the deflection limits adopted. Full article

The Weibei Plain, characterized by its complex stratified aquifer system and extensive brine resources, faces severe groundwater salinization. Unraveling the precise evolutionary mechanisms of diverse hydrochemical types across varying depths and geomorphological zones remains a significant challenge. This study synthesizes a multi-batch hydrochemical dataset with multi-isotopic tracers (δ²H, δ¹⁸O, δ¹¹B, δ⁸¹Br, δ³⁷Cl) to establish a comprehensive groundwater evolutionary model from the piedmont plain to the coastal marine plain. The results indicate distinct hydrochemical zonation governed by geographic geomorphology and historical marine transgressions. Salinization in transitional waters is primarily driven by physical mixing and reverse cation exchange rather than extreme evaporative fractionation. Crucially, isotopic mass balance definitively reveals that deep brine (depth > 60 m) originates not from modern seawater intrusion, but from the extreme surface evaporation of ancient paleo-seawater. This paleo-brine underwent profound isotopic exchange during its gravity-driven downward migration, evidenced by intense clay mineral adsorption (yielding extreme δ¹¹B enrichment up to 64.42‰) and secondary evaporite dissolution. Furthermore, the regional cone of depression formed by intensive brine extraction has profoundly altered deep hydrodynamics, inducing overflow and membrane ultrafiltration across massively thick clay aquitards. This process distinctly drives the isotopic fractionation observed in deep brackish waters. The analysis process in this study combines the isotope method with the regional geomorphological zoning, which can provide a reference for the analysis of groundwater evolution characteristics in other coastal aquifers. Full article

AZ91D is a lightweight, representative commercial magnesium alloy known for its excellent castability and specific strength. However, the mechanical properties of as-cast AZ91D remain limited by inherent brittleness, relatively low strength, and microstructural inhomogeneity caused by enrichment of secondary phases at grain boundaries. In this study, AZ91D/Csf (short carbon fiber at 0, 2.5, and 5 wt.%) composites were prepared by gravity casting with mechanical stirring, followed by post-casting T4 heat treatment and equal-channel angular pressing (ECAP). Material characterization included optical microscopy (OM), field-emission scanning electron microscopy (FESEM), energy-dispersive spectroscopy (EDS), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), uniaxial tensile testing, and microhardness tests. The results demonstrate that T4 treatment reduced intermetallic β-Mg₁₇Al₁₂ segregation and homogenized the microstructure, whereas one-pass ECAP further refined the grains. Mechanically, these two processes enable the (AZ91D/5 wt.% Csf) composite to achieve higher ultimate tensile strength (280.7 MPa by T4/280.2 MPa by T4 + one-pass ECAP), larger maximum strain (12.1% by T4/5.4% by T4 + one-pass ECAP), and higher microhardness (63.9 HV by T4/78.1 HV by T4 + one-pass ECAP). Compared to as-cast AZ91D, these findings demonstrate that T4 treatment provides a better strength–ductility balance via solid solution, whereas one-pass ECAP preferentially enhances surface microhardness by plastic deformation. This study highlights the performance of AZ91D/Csf composites and their potential for lightweight, high-strength-demand applications. Full article

Reliability assessments of subsea systems are generally performed at two levels: structural reliability analysis of individual components and functional reliability analysis of the overall system using generic failure-rate databases. This study develops a component-to-system multi-scale framework that integrates these two levels for a subsea separation system operating at 3000 m water depth. At the component level, a Gaussian process regression (GPR) surrogate is developed from 474 finite element simulations of a vertical gravity separator. First-order reliability method (FORM) and Monte Carlo simulation (MCS) are then employed to assess the structural reliability, followed by a time-variant reliability analysis that accounts for corrosion effects. At the system level, the structural reliability model is integrated with functional failure rates through a Bayesian network that considers five equipment items and relevant risk-influencing factors. The surrogate model accurately predicts collapse pressure with an R² value of 0.996. The intact separator achieves a reliability index of 4.55, satisfying the DNV high-safety-class target, with the structural failure mode contributing only 0.0034% of the separator failure rate. Under a corrosion rate of 0.4 mm/year, the reliability index decreases to 3.12 over a 25-year service period. The structural failure rate crosses the DNV medium-safety-class target of 10⁻⁴ per year at year 12, increasing the structural contribution to the overall system failure frequency to 0.33%. Sensitivity analysis indicates that initial ovality and wall thickness are the most influential parameters affecting structural reliability and should therefore be prioritized in design and integrity management strategies. The framework is demonstrated on this physics-consistent dataset; validation against independent nonlinear finite element analyses and experimental collapse data is identified as the necessary next step before the results are used for design. Full article

As a key tectonic zone formed by the India–Eurasia collision, the eastern Tibetan Plateau has complex crustal structures and intense tectonic activity. Its crustal stability is closely linked to regional geohazards and the safety of major engineering projects. This study assessed crustal stability using nine multi-source datasets, including terrestrial gravity, Bouguer gravity anomalies, seismic data, active faults, terrain indicators, and annual precipitation. A hybrid weighting framework coupling the Analytic Hierarchy Process (AHP) and CRITIC method was established, and factor analysis was further adopted to cross-verify the rationality of index weights. Moderately unstable and unstable zones appear as alternating bands with distinct linear extensions. These unstable areas are mainly distributed around Jiuquan–Zhangye–Wuwei, Xining–Haidong, Yushu–Garzê, Mianyang, and Chengdu. Statistically, stable, moderately stable, moderately unstable, and unstable zones account for 20.74%, 35.47%, 28.78%, and 15.01%, respectively. The results provide a scientific reference for regional planning and infrastructure site selection in tectonically active regions. Full article