Search Results (278)

Sulfur-containing medium-carbon microalloyed steel blooms are widely used for high-load automotive components, and reducing surface defects is important for improving product yield and lowering downstream processing costs. To address surface defects such as star cracks and microcracks in the continuous casting of these steel blooms, this study redesigned the mold flux on the basis of the steel’s solidification characteristics and crack susceptibility and carried out a twin-strand industrial comparative casting trial. Thermodynamic and thermophysical analyses indicated that the relatively high contents of S, Mn, and Ti/N in the steel promoted the precipitation of MnS and TiN–MnS complex inclusions along grain boundaries, severely weakening grain boundary cohesion. Meanwhile, the high specific heat capacity and low thermal conductivity further intensified thermal stress concentration in the solidifying shell, rendering the steel highly susceptible to cracking. Evaluation of the originally used mold flux (Flux A) revealed that its high melting temperature (1189 °C), long melting time (106 s), high break temperature (1170 °C), and poor crystallization behavior resulted in an excessively thin liquid slag layer (<5 mm) within the mold, making it difficult to provide adequate lubrication and stable heat transfer; these were key external factors inducing surface defects. Accordingly, the optimized mold flux (Flux B) was designed and prepared by increasing the basicity from 0.95 to 1.1, raising the Al₂O₃ content from 9.48% to 11.16%, increasing the F content from 4.93% to 5.58%, and reducing the carbon content from 13.85% to 6.97%. The rheological and crystallization properties of the flux were optimized in a coordinated manner, allowing uniform heat transfer through the crystalline slag layer while maintaining adequate lubrication. Industrial comparative trials demonstrated that Flux B stabilized the liquid slag layer at 8–10 mm, increased slag consumption to 0.56 kg/t, and significantly reduced surface defects such as star cracks and microcracks on blooms. The ultrasonic testing acceptance rate for rolled products increased to 98.6%, thereby meeting stringent quality requirements for the continuous casting of sulfur-containing, medium-carbon, microalloyed steel blooms. Full article

Injecting CO₂ into gas reservoirs is a crucial approach for enhancing natural gas recovery and achieving CO₂ geological storage, where the gas–gas diffusion behavior between CO₂ and CH₄ directly influences gas mixing efficiency. Direct observation of the spatiotemporal evolution of concentration fields during diffusion remains insufficient. In this study, a gas–gas diffusion experimental system capable of multi-time and multi-space stratified sampling within a high-temperature high-pressure PVT cell was established based on real reservoir fluid compositions. Non-equilibrium diffusion experiments were conducted under different pressures, different initial CO₂ mole fractions, and different diffusion times. A diffusion model was developed according to Fick’s second law. The results suggest that the gas column can be divided into a natural gas zone, a transition zone, and a CO₂ zone by the dimensionless concentration gradient threshold. At 5 MPa, the transition zone width expands rapidly within the first 4 h (dimensionless width increases from 0 to 0.6902), after which growth slows. Increasing pressure significantly inhibits diffusion, reducing transition zone width and prolonging equilibration time. Rising initial CO₂ concentration also suppresses diffusion mixing, particularly in the later stage. Component profile analysis confirms that, under high pressures and high CO₂ concentrations, the diffusion flux across the interface is weakened. Compared to CH₄, the diffusion equilibration time of CO₂ is shorter and more sensitive to pressure changes. The obtained diffusion coefficients (CH₄: 2.92 × 10⁻⁸ to 4.79 × 10⁻⁸ m²/s; CO₂: 3.91 × 10⁻⁸ to 6.08 × 10⁻⁸ m²/s) are on the order of 10⁻⁸ m²/s, consistent with bulk-phase PVT literature data, validating the reliability of the experimental method and inversion model. This study lays an experimental foundation for predicting multi-component gas mass transfer under conditions of CO₂-enhanced gas recovery and CO₂ geological storage. Full article

The “New Arctic” regime represents a prominent climatic feature of the Arctic Ocean under global warming, characterized by persistently low summer sea ice extent, a marked reduction in sea ice thickness, and an expansion of open water areas at high latitudes. As a key indicator of the Arctic sea ice system, the spatiotemporal evolution of sea ice thickness and its underlying driving mechanisms remain incompletely understood. Using reanalysis datasets and remote sensing observations, this study identifies major abrupt shifts in Arctic sea ice thickness under the New Arctic regime, reveals the spatiotemporal distribution characteristics of winter sea ice thickness, and examines the driving factors from both thermodynamic and dynamic perspectives. The results show that the evolution of Arctic sea ice thickness can be divided into three phases: a high-level period during the “Traditional Arctic” (1979–1992), a rapid thinning period during the New Arctic transition (1993–2012), and a low-level stabilization period in the New Arctic regime (2013–2023). The first EOF mode of winter sea ice thickness depicts a spatially consistent thinning pattern across the entire Arctic, with the most significant reduction occurring in the multi-year ice regions north of the Canadian Arctic Archipelago and Greenland. The second EOF mode exhibits an out-of-phase variation between the Atlantic and Pacific sectors of the Arctic, accompanied by a shrinking amplitude and weakened regional oscillations. The coupling between surface air temperature and sea ice thickness displays distinct phase dependence: their negative correlation is strongest during the transition period (r = −0.78, p < 0.001) but becomes statistically insignificant in the New Arctic regime. Sea ice motion speed exhibits an overall accelerating trend, which extends from the marginal seasonal ice zones toward the high-latitude multi-year ice regions, accompanied by a notably enhanced sensitivity of sea ice motion to wind forcing. Sea ice volume flux through the Fram Strait is primarily controlled by ice motion speed, whose contribution to the flux is approximately 2.6 times that of ice thickness. The recovery of ice drift speed offsets the thinning of sea ice cover, leading to a partial rebound in volume flux during the New Arctic steady state. This study identifies the evolutionary patterns and drivers of Arctic sea ice thickness under the New Arctic regime, providing a scientific basis for further understanding the changes in the Arctic climate system and associated air–sea ice interactions. Full article

This paper proposes a novel arch-shaped-magnet variable-flux memory machine (ASM-VFMM). The proposed machine adopts a dual-layer permanent magnet (PM) rotor structure. In the first layer, an arch-shaped magnet arrangement is utilized to increase the volume of low-coercive-force (LCF) magnets, which contributes to improved magnetic flux adjustment (MFA) performance. The second layer incorporates an asymmetric PM (APM) layout to create a parallel magnetic circuit, enabling further suppression of air-gap flux density at the weakened-flux state. The topological development of the proposed machine is first described, covering the conventional series magnetic circuit (SMC) structure, the intermediary APM structure, and the proposed ASM structure. A theoretical modeling analysis is then conducted for the three machines. This confirms the superiority of the proposed design regarding its MFA capability. A comprehensive electromagnetic performance evaluation is carried out for the proposed machine, alongside comparative assessments of the other two machines. The results show that the proposed design outperforms the other two machines in terms of magnetization performance, MFA range, and on-load magnetization stabilization capability. Notably, the proposed machine exhibits excellent overall efficiency characteristics, especially under high-speed operating conditions. Full article

Air–sea CO₂ flux (FCO₂) in the estuary–coastal continuum plays a vital role in global carbon sequestration; however, the mechanisms governing FCO₂ spatial heterogeneity during early spring remain poorly understood, particularly the roles of distinct dissolved inorganic carbon (DIC) sources. In March 2025, we investigated the FCO₂ spatial variability and DIC sources across the Yangtze River estuary and adjacent coastal areas using DIC concentration, pH, and δ¹³C_DIC analyses. The study area was a net CO₂ source (7.3 ± 8.7 mmol m⁻² d⁻¹), with the intensity declining progressively from the inner estuary to offshore areas. Physical mixing of three principal water masses established the following pattern: high-pCO₂ Changjiang Diluted Water and Yellow Sea Coastal Current drove CO₂ outgassing, while low-pCO₂ East China Sea Shelf Water weakened it. Quantitative apportionment revealed atmospheric CO₂ invasion as the dominant DIC source, followed by carbonate dissolution and organic matter degradation, with the latter declining from the inner estuary to offshore areas. The spatial variation in DIC source contributions further confirms that, superimposed on the physical mixing, biogeochemical processes—particularly biological activity—modulated reginal source intensities. This early-spring case captures a critical transitional window and highlights the necessity of integrating multi-factor regulation with DIC source partitioning to resolve carbon dynamics in the estuarine–coastal continuum. Full article

Multi-omics technologies enable parallel quantification of proteomic and metabolomic layers, yet enzyme abundance often shows weak or nonlinear correspondence under diverse biological conditions. This apparent discordance has been attributed to both technical limitations—such as dynamic range compression in LC-MS/MS, metabolite derivatization artifacts, and missing values in proteomic measurements—as well as intrinsic biological properties of metabolic network architecture. While technical factors contribute to cross-omic mismatch, accumulating evidence suggests that constraint-driven network behavior plays a major role in shaping this decoupling. Enzyme abundance constrains catalytic capacity; however, realized flux is selected within this capacity under distributed flux control, as formalized by flux control coefficients in metabolic control analysis, and is further modulated by enzyme kinetics (e.g., km and Vmax), post-translational modifications, substrate availability, and thermodynamic constraints. Metabolite pools, in turn, reflect the physicochemical state of the system, while specific metabolites can also act as regulatory effectors that modulate enzymatic activity and cellular signaling. Because metabolic networks are underdetermined, multiple flux configurations can satisfy identical protein abundance and metabolite concentration data. Static cross-layer correlation is therefore insufficient for mechanistic inference. We synthesize biological mechanisms—including post-translational regulation, allostery, thermodynamic buffering, spatial compartmentalization, feedback amplification, and redox gating—that weaken linear abundance–metabolite expectations. We further outline a constraint-based interpretation framework in which proteomics imposes capacity bounds, metabolomics informs reaction directionality and metabolite pool constraints, and flux-informed approaches reduce solution degeneracy by providing additional information on pathway activity. Moving beyond correlation requires integrating perturbation, temporal resolution, and constraint-aware modeling. Proteome–metabolome discordance should therefore be interpreted not as inconsistency, but as indicative of constraint-driven state selection within high-dimensional biochemical systems. Full article

With the increasing penetration of wind and solar renewable energy into modern power systems, grids exhibit ‘dual-high’ (i.e., a high proportion of both renewable energy and power electronic devices) and ‘dual-low’ (i.e., low equivalent rotational inertia and low short-circuit capacity) structural characteristics. This leads to critical challenges, notably insufficient short-circuit capacity, declining voltage and frequency stability, and weakened system damping. To address the stability requirements of new power systems, this study proposes and systematically investigates a variable-speed synchronous condenser based on AC excitation technology. The research encompasses the operational principles, starting mechanisms, and control strategies of the device, with a particular focus on analyzing its stator-flux-oriented vector control method and active–reactive power decoupling regulation mechanism. By independently adjusting the frequency, amplitude, and phase of the AC excitation on the rotor side, the system achieves a millisecond-level dynamic reactive power response, rapid frequency support, and self-starting capability without the need for external starting devices. To validate the effectiveness of the theoretical analysis and engineering practicality, this study presents grid-connected operational tests using a 3600 kVar engineering prototype at a wind farm. The test results demonstrate that the variable-speed synchronous condenser performs excellently in speed regulation, dynamic reactive power response, and primary frequency modulation. It effectively provides short-circuit capacity, enhances system damping, and significantly improves the voltage and frequency stability of power grids with high penetration of renewable energy. This study offers innovative technical pathways and empirical evidence for constructing a stability support system that meets the developmental needs of new power systems. It holds significant theoretical value and engineering guidance for promoting the smooth transition of power grids from synchronous machine-dominated to power electronics-based architectures. Full article

In this work, the light curve of the Seyfert galaxy Mrk 6 constructed from photometric observations in the B, V, and $R_{\mathrm{c}}$ filters over the period from 5 April 2016 to 1 February 2026 is presented and analyzed. Over the entire monitoring interval (2016–2026), the variability amplitude of the light curve reaches $\mathrm{\Delta }B=1.9$ mag, $\mathrm{\Delta }V=1.5$ mag, and $\mathrm{\Delta }{R}_{\mathrm{c}}=1.4$ mag. During 2024–2026, the galaxy exhibits synchronous photometric variability in the B, V, and $R_{\mathrm{c}}$ filters with an amplitude of ∼0.3 mag. The study also uses spectroscopic observations obtained on 15 and 22 November 2025 and 16 February 2026 at the Shamakhy Astrophysical Observatory (Azerbaijan), as well as on 9 January 2026 at the Fesenkov Astrophysical Institute (Kazakhstan). The fluxes in the H$\beta$ emission line were calibrated using the [O III] $\lambda 5007$ Å line, ensuring consistent relative calibration of the spectral data. A comparison of the optical spectra reveals a pronounced transformation of the H$\beta$ line profile between November 2025 and January 2026. The broad component, clearly present in November 2025, becomes strongly suppressed and nearly disappears in January 2026, while the narrow emission lines remain stable. This behavior is consistent with a changing-look transition, indicating a temporary weakening of the broad-line region emission. The radius of the broad-line region $R_{\mathrm{BLR}}$ was taken to be equal to the average time delays (lags), amounting to ≈20 light days for the H$\beta$ emission and ≈28 light days for the H$\alpha$. Full article

Against the backdrop of accelerated terrestrial hydrological cycling and the increasing concurrence of drought-heatwave compound extremes under global warming, regional land-atmosphere coupling has emerged as a central mechanism shaping climate feedbacks and trajectories of ecosystem carbon uptake. However, prior studies spanning climatic regimes, observational scales, and data sources have often yielded contradictory conclusions. Here, we challenge these fragmented perspectives by constructing an integrated LST-SM-ET-GPP chain that jointly represents land surface temperature, soil moisture, evapotranspiration, and gross primary productivity, thereby linking water availability, surface energy balance, and plant physiological processes within a unified framework. We synthesize a conceptual diagnostic roadmap for interpreting land-atmosphere coupling across observations and models. When ecosystems operate in humid, energy-limited environments, radiative and advective controls should be prioritized to diagnose system forcing. By contrast, as the system becomes water-depleted, attribution must shift to a nonlinear regime transition framework governed by a critical soil moisture threshold. This threshold mechanism implies that, once the system enters the moisture-limited regime, even modest declines in soil moisture can trigger a rapid weakening of evaporative cooling, substantially amplifying LST anomalies and strongly suppressing GPP. The competitive regulation of stomatal conductance by atmospheric demand (vapor pressure deficit, VPD) and terrestrial supply (rootzone soil moisture) further explains why the “dominant” controlling factor can dynamically reverse across hydrothermal states, timescales, and stages of extreme-event evolution. Notably, the steady-state coupling assumption may break down under flux “flooring” during extreme drought, or when structural buffering such as deep root water uptake is present, delineating strict applicability bounds for existing diagnostic frameworks. Finally, current assessments remain constrained by multiple uncertainties, particularly the lack of ET partitioning constraints, representativeness biases arising from clear-sky observations and sampling-depth limitations, and systematic errors in Earth system model simulations during the warm season. Full article

Wetlands play a vital role in the global carbon cycle and serve as critical carbon sink systems. However, increasing human disturbances and land-use changes have led to widespread wetland degradation, severely weakening their carbon sequestration capacity. This study investigated the Huixian Wetland in the Li River Basin of Southwest China to examine the impacts of wetland degradation on soil physicochemical properties, organic carbon fractions, and carbon fluxes. Based on vegetation and environmental conditions, the wetland was classified into four degradation gradients: non-degraded (ND), slightly degraded (SD), moderately degraded (MD), and heavily degraded (HD), and their spatial differences were systematically analyzed. The results showed that with increasing degradation, soil moisture, total nitrogen, and total phosphorus significantly decreased, whereas soil bulk density and electrical conductivity exhibited an increasing trend. Total organic carbon and active organic carbon fractions, including readily oxidizable organic carbon, light fraction organic carbon, microbial biomass carbon, and dissolved organic carbon, exhibited a pronounced decreasing trend along the degradation gradient, with the decline being most evident in the HD area. Among the labile carbon fractions, microbial biomass carbon (MBC) and light fraction organic carbon (LFOC) exhibited the most drastic declines in heavily degraded areas, indicating their high sensitivity as early warning indicators of wetland degradation. Observations of CO₂ fluxes revealed that from April to September, the net ecosystem exchange (NEE) was negative across all areas, indicating that the wetland functioned as a carbon sink overall. However, NEE values increased with higher degradation levels, suggesting a progressive decline in the carbon sequestration capacity of the wetland; ecosystem respiration (ER) peaked in July and increased with the degree of degradation. The findings indicate that wetland degradation leads to soil environment deterioration, reduction in organic carbon storage, and enhanced CO₂ emissions, ultimately weakening its carbon sink function. To enhance carbon sequestration capacity and maintain ecological functions, sustainable management strategies such as hydrological restoration and vegetation reconstruction are recommended. This study provides a scientific basis for wetland ecological conservation and carbon management in the context of climate change. Full article

The electric cylinder has become a research hotspot in the future because of its high energy efficiency and excellent dynamic performance. The electric cylinder is driven by a permanent magnet synchronous motor (PMSM). However, the existing high-performance control strategies of permanent magnet synchronous motor, such as sliding mode variable structure control (SMC), model predictive control (MPC), and load torque feedforward, often face the challenge of unknown load torque when improving dynamic performance. The traditional load observation methods of PMSM involve the dq-axis inductance, which neglects the impact of inductance variation in interior PMSM (IPMSM) caused by the cross-coupling effect, flux weakening, or magnetic saturation effect. In this paper, a super-twisting sliding mode robust load observer (ST-RLO) is proposed, which performs load torque observation without reliance on inductance parameters. The feasibility and stability of the observer are analyzed theoretically. Experiments are carried out. The results show that compared with the conventional Luenberger load observer (CLLO) involving inductance, a better observation of the load torque is achieved by the ST-RLO, which has a better robustness for inductance variations and mismatching of inductance and inertia parameters. Full article

The influence of air–sea heat fluxes on the evolution of marine heatwaves (MHWs) in the Mediterranean was examined over the 1982–2024 summer periods. MHW detection was performed on detrended sea surface temperatures (SSTs), and the application of a minimum spatial coverage threshold of 15% of the Mediterranean Basin provided a catalogue of the most extreme MHW events. Analysis of composite surface flux anomalies shows that latent heat flux (LHF) anomalies dominate the contribution of the air–sea heat flux budget to MHW variability, with negative LHF anomalies before an event and positive LHF anomalies after an event. An alternative MHW detection method which defines MHW events from time series of the principal components (PCs) of MHW intensity was used. This method revealed distinct atmospheric patterns associated with the different phases of an MHW event. Before an MHW event, weakened winds reduce outgoing LHF, trapping heat within the ocean. After an MHW event, a steepening humidity gradient and strengthened winds increase outgoing LHF and heat release into the atmosphere. These results highlight the significant role that LHF plays in the interactions between MHW events and the atmosphere, and the contrasting contributions of wind speed and humidity gradient during MHW onset and decline. Full article

High-performance speed regulation of interior permanent magnet synchronous motor (IPMSM) drives in electric vehicle (EV) applications becomes particularly challenging in the field-weakening region, where voltage constraints, parameter variations, and nonlinear aerodynamic loads significantly affect the closed-loop stability. To address these challenges, this paper proposes a stability-aware adaptive fractional-order speed control framework for EV traction systems. The framework integrates a fractional-order PI (FOPI) core to provide iso-damping robustness, a bounded fuzzy gain-scheduling mechanism for real-time adaptation, and an offline multi-objective optimization layer for systematic parameter tuning. A Lyapunov-based qualitative analysis is provided to justify closed-loop ultimate boundedness under adaptive gain modulation and field-weakening constraints. The fuzzy scheduler is explicitly structured to regulate the error energy dissipation rate by modulating the proportional and integral gains while preserving the gain boundedness. The controller parameters are optimized using a diversity-driven fractional-order multi-objective PSO algorithm to balance the tracking accuracy and control effort. The proposed framework was validated using a high-fidelity MATLAB/Simulink–CarSim 2023 co-simulation platform under the aggressive US06 driving cycle. The results demonstrated a zero-overshoot transient response, robustness against a 2.5× inertia mismatch, and sustained performance under flux-linkage and inductance variations in deep field-weakening operation. Compared with conventional PI-based strategies, the proposed approach reduced the speed RMSE by 82%, lowered the current THD from 18.5% to 3.2%, and reduced the cumulative DC-link current-squared index by 6.7%. These results validate the practical robustness and computational feasibility of the proposed stability-aware framework for EV traction control. Full article

To accurately understand and investigate carbon fluxes in cropland ecosystems, this study adopted a machine learning ensemble model for estimation. Focusing on the Jinzhou station of the ChinaFLUX, we integrated eddy covariance carbon flux observations with multi-source satellite remote sensing data to construct a machine learning-based cropland carbon flux estimation model. For environmental driver selection, a strategy combining correlation analysis with ecological mechanism understanding was employed to screen LST, NDVI, and NDMI as model input variables, effectively avoiding multicollinearity issues. Using footprint-weighted integrated data from 2005 to 2014 for model training and validation, a Stacking ensemble model was constructed with the RF model serving as the meta-learner to stack the predictions of RF, CART, and GBM. The ensemble model further reduced the prediction error (RMSE = 39.82), maintaining an R² > 0.9 in most years and effectively improving predictive performance during anomalous years where single models underperformed. Based on these findings, the model was applied to analyze the spatiotemporal evolution of NEE in Jinzhou croplands from 2005 to 2014. The analysis revealed that while the region functioned overall as a carbon sink, it exhibited significant spatiotemporal heterogeneity. Spatially, the distribution followed a pattern of “strong intensity in the northeast and center, and weak intensity in the northwest and southwest.” Temporally, the sink intensity underwent significant interannual oscillations characterized by a “strengthening–weakening–re-strengthening–declining” trajectory. The high-precision prediction method proposed in this study is of great significance for revealing spatiotemporal variations in carbon sources/sinks, guiding green agricultural development, and supporting relevant policy formulation. Full article

This paper presents a robust sensorless control strategy for a dual-inverter doubly fed induction motor (DFIM) designed for high-performance electric vehicle (EV) traction systems. The proposed scheme eliminates the mechanical speed sensor by employing a sliding-mode observer (SMO) for real-time estimation of rotor speed and flux, ensuring accurate feedback under load disturbances and thereby enhancing reliability while reducing implementation cost. The DFIM is powered by two voltage-source inverters that independently control the stator and rotor windings through space vector pulse-width modulation (SVPWM). A power-sharing strategy optimally distributes the electromagnetic power between the two converters, ensuring smooth transitions between sub-synchronous and super-synchronous operating modes. Furthermore, a stator-flux-oriented vector control (SFOC) scheme incorporating a graphical torque optimization algorithm is developed to maximize torque while satisfying inverter and machine constraints across both base-speed and flux-weakening regions. The stability of the SMO-based estimation and closed-loop control is rigorously validated using Lyapunov theory. Comprehensive MATLAB R2024b/Simulink simulations conducted under the WLTC-Class 3 driving cycle confirm high accuracy and robustness, showing fast dynamic response, precise speed estimation, and smooth torque behavior across the full speed range. The results demonstrate that the SMO-based DFIM drive offers a cost-effective and reliable solution for next-generation EV traction applications. Full article