Search Results (2,481)

Modeling the dynamic response of saturated marine soils is crucial yet computationally challenging for traditional methods. Meanwhile, purely data-driven models suffer from sparse data and lack of physical interpretability. To overcome these limitations, this study proposes an intelligent engineering framework based on a frequency-domain physics-informed neural network (FD-PINN) for the forward simulation and inverse parameter identification of saturated seabed soils. Constrained directly by physical laws during the learning process, FD-PINN remains highly reliable even when training data is sparse. By formulating the governing equations in the frequency domain, it directly predicts complex-valued displacement and pore-pressure phasors. Multiscale Fourier feature mappings mitigate spectral bias and capture boundary layers and high-frequency effects. For inverse problems, a phase-sensitive lock-in extraction strategy transforms time-domain measurements into robust frequency-domain targets, enabling the accurate and noise-tolerant identification of poroelastic parameters with clear physical meaning (nondimensional storage parameter S and permeability parameter $\Gamma$). Numerical experiments show that FD-PINN substantially outperforms conventional time-domain PINN, achieving relative $L^2$ errors of ${10}^{-2}\sim {10}^{-3}$ for single- and multi-frequency excitations typical of wave-induced loadings. In particular, $\Gamma$ is consistently recovered with sub-percent relative error, while S can be reliably identified with multi-frequency data. The framework offers a data-efficient, noise-robust approach for high-fidelity modeling and robust parameter inversion, which is particularly valuable in offshore environments where high-quality data is scarce. Full article

Synchronous Reluctance Motors (SynRM) have attracted much attention due to their advantages of simple structure and low cost. However, due to factors such as magnetic saturation and temperature changes, the parameters of SynRM exhibit nonlinear characteristics. Existing Maximum Torque per Ampere (MTPA) control strategies often do not fully consider the impact of nonlinear changes in motor parameters, making it difficult to achieve accurate MTPA control and resulting in reduced motor efficiency. This article analyzes the control errors caused by the nonlinear changes in inductance of SynRM and proposes an error compensation strategy based on virtual DC signal injection MTPA control. The error expression is reconstructed to achieve error compensation and improve the accuracy of MTPA control. The effectiveness of the proposed control strategy is verified by building a simulation model and a motor experimental platform. The experimental results show that the control strategy proposed in this paper can achieve a maximum current optimization rate of 5.01% while ensuring fast system responsiveness. Full article

Wi-Fi networks used in smart grids are essential for enabling communication between smart meters and data aggregation units. A key challenge, however, is the ability to hide the existence and traffic patterns of these communications, so that sensitive information exchanges cannot be easily detected or intercepted. Unfortunately, most existing solutions do not provide support for traffic prioritization and steganographic channel encryption. In this paper, we propose a novel covert channel with Quality of Service (QoS) and encryption support for smart grid environments based on the IEEE 802.11 standard. We introduce an original steganographic approach that leverages the backoff mechanism, the Enhanced Distributed Channel Access (EDCA) function, frame aggregation, and the StegoPaddingCipher algorithm. This design ensures QoS-aware traffic handling while enhancing security through encryption of the transmitted covert data. The proposed protocol was implemented and evaluated using the ns-3 simulator, where it achieved excellent performance results. The system maintained high efficiency even under heavily saturated network conditions with additional background traffic generated by other nodes. The proposed covert channel offers an innovative and secure method for transmitting substantial volumes of QoS-related data within smart grid environments. Full article

Under high-power disturbances such as HVDC blocking, stability strategies such as generator tripping are employed to ensure the frequency stability of the sending-end power grid. For renewable energy units, rapid emergency power reduction instead of direct tripping can quickly reduce active power and suppress frequency spikes, while maintaining grid connection to provide dynamic reactive power support, avoiding voltage collapse, and smoothly restoring power after a fault, thus improving the transient stability and resilience of a high-proportion renewable energy grid. However, the control performance of rapid emergency power reduction for wind turbines is limited by the converter’s overcurrent capacity and the unit-side load limit. Sudden large-scale active power reduction can easily cause motor speed fluctuations and mechanical stress accumulation, and may trigger current limiting and protection actions when the inverter current is saturated, or the DC bus voltage exceeds the limit, thus strictly limiting the range and duration of the adjustable power. To address the engineering requirements for rapid active power reduction in wind turbines, this paper proposes a control scheme based on low-voltage ride-through (LVRT) energy dissipation circuit reuse, and simultaneously conducts a special study on LVRT reuse conditions. When the unit receives a command to rapidly reduce active power, the scheme uses a percentage current duty cycle control strategy to drive the energy-consuming circuit to quickly dissipate excess energy. Simultaneously, it controls the pitch angle to increase at the maximum adjustment rate, thus completely eliminating excess power. This scheme leverages the existing LVRT hardware of the wind turbine to expand its functionality without requiring additional equipment. Furthermore, research on LVRT reuse conditions provides crucial support for the reliable operation of the scheme, demonstrating both outstanding economic efficiency and engineering practicality. Full article

Matrix Product States (MPSs) have become an indispensable symmetry-based representation for simulating quantum systems on near-term hardware by constraining entanglement entropy through a fixed bond dimension $\mathsf{\chi }$. This study identifies a critical “rank explosion” phenomenon that destabilizes this low-rank manifold during conditional quantum diffusion processes. We empirically demonstrate that the introduction of conditional guidance—essential for semantic control—injects global correlations that drive the effective Schmidt rank to increase by $4\times$ (from $\mathsf{\chi }=4$ to $16$), saturating the simulation limits and necessitating quantum circuits with approximately $1.8\times {10}^3$ Controlled-NOT (CNOT) gates. Such circuit depths fundamentally exceed the operational coherence budgets of Noisy Intermediate-Scale Quantum (NISQ) devices. To mitigate this structural instability, we propose Rank-Aware Conditional Synthesis (RACS), a sampling framework that maintains the latent trajectory within a prescribed MPS manifold through step-wise manifold projection and time-shift error correction. Experimental results on real-world semantic data reveal that RACS reduces reconstruction error, or Mean Squared Error (MSE) by 30.8% and enhances latent trajectory smoothness by 36.8% compared to conventional post hoc truncation. At a fixed hardware-efficient rank of $\mathsf{\chi }=4$, RACS achieves a +4.8% fidelity gain and exhibits superior robustness against depolarizing noise. By resolving the tension between conditional expressivity and entanglement constraints, RACS provides a principled, hardware-aware methodology for high-fidelity quantum generative modeling. Full article

Better understanding the controlling factors of shale oil quality including density and viscosity plays a key role in exploring these unconventional pay zones efficiently and profitably. The shale oil extracted from the middle Permian Lucaogou Formation (P₂l) of Santanghu Basin becomes denser and more viscous from the Tiaohu Sag to Malang Sag. It has been proven that oil quality is negatively correlated with saturated hydrocarbon content and positively correlated with aromatic/resin content. However, the underlying controls at the molecular levels are not yet clear. In order to reveal the fundamental controls, shale oil samples with varying density and viscosity were collected from these two sags, and molecular compositions of these samples were analyzed by using gas chromatography–mass spectrometry (GC–MS) for the saturated and aromatic hydrocarbons and electrospray ionization (ESI) Fourier transform ion cyclotron resonance mass spectrometry (FT–ICR MS) for heteroatom hydrocarbons in resin fraction. Thereafter, correlation analysis was performed between oil density and viscosity and geochemical parameters associated with saturated, aromatic and NSO-containing compounds. The experimental results indicate that the oil thermal maturity levels play a major role, since both density and viscosity present significant negative correlations (correlation coefficient > 0.5) with the maturity parameters of n-alkanes, terpanes, steranes and triaromatic steranes. Organic facies also play a partial role as indicated by the significant positive correlations between density and viscosity and the parameters of tricyclic terpanes, dibenzothiophene/phenanthrene, and methylated phenanthrenes. In resin fraction, density presents better correlations with acid compounds, including O_x (x = 5–9), N₁O_x (x = 0–2) and N₂O₃ species, and viscosity shows better correlations with basic N-containing compounds (N₁O₁, N₁O₃, and N₂O₁ species) and S-containing compounds (N₁S₁ and O₁S₁ species). This indicates that the cross-linking by acid oxygen-containing compounds and the intramolecular and intermolecular forces induced by basic N-containing compounds and sulfur-containing compounds play an important role in directing the P₂l shale oil quality. Moreover, the ratios of specific species with low-to-high double bond equivalents (DBEs) and the homologues with low molecular weight to high molecular weight both present significant negative correlations with density and saturated and aromatic maturity parameters. This highlights the effects of bond cleavage, cyclization and aromatization reactions with elevated thermal maturity in enhancing oil quality in the targeted pay zones. Most P₂l shale oil sources were deposited under the reducing lacustrine setting, containing mainly Type I/II kerogens. Shale oils from Tiaohu Sag are more matured than those from Malang Sag, which is supposed to be responsible for the better oil quality in Tiaohu Sag. This study provides the supporting evidence for regulating shale oil quality in the Santanghu Basin at the molecular levels, and should be helpful in identifying the sweet spots of shale oil plays in this area. Full article

To address the insufficient accuracy of conventional permanent magnet synchronous motor (PMSM) models caused by neglecting magnetic saturation nonlinearity and periodic parameter disturbances, a nonlinear motor system model integrating a Physics-Informed Neural Network (PINN) is developed. By exploiting the differential relationships among incremental inductance, flux linkage, and magnetic energy, the voltage and torque equations considering rotor position variation are derived, and analytical expressions for the derivatives of incremental inductances are obtained. To reduce the computational burden of PINN in system-level simulations, linear and nonlinear approximation strategies based on incremental inductances and their derivatives are proposed, which significantly reduce the frequency of PINN calls while maintaining model accuracy. CPU/GPU collaborative computation and cross-frequency-domain scheduling are further implemented to improve simulation efficiency. Considering the influence of the test bench mechanical dynamics, an electromechanical–magnetic coupled simulation model is established. The accuracy of the proposed nonlinear motor model is validated through two-phase short-circuit tests as well as simulations and test bench experiments under sinusoidal and non-sinusoidal excitations. The results demonstrate that the proposed model accurately captures the nonlinear electromagnetic characteristics of PMSMs while significantly improving system simulation efficiency. Full article

Enhancing the vibroacoustic performance of underwater vehicles remains a critical challenge in marine engineering. Increasing geometric stiffness is a conventional strategy to suppress vibration, yet its effectiveness in reducing underwater sound radiation can be practically limited. This paper presents a numerical investigation of the vibroacoustic response of composite grillage sandwich structures, with a focus on separating the contributions of geometric stiffening and core damping. A coupled acoustic structural model is developed based on the equivalent single layer theory and implemented in a finite element framework, then validated against analytical benchmark solutions. The parametric study reveals a stiffness saturation phenomenon in the acoustic domain. Although increasing rib height significantly reduces the mean square velocity, the radiated sound power reaches a saturation plateau and can even show a slight rebound at higher frequencies. This behavior is attributed to an increase in structural phase velocity that shifts modal components toward a more efficient radiation regime, thereby increasing radiation efficiency. To address this limitation, the damping modulation role of the core material is examined. The results show that introducing a high damping core into the grillage skeleton suppresses broadband noise and resonance peaks, without a comparable rise in radiation efficiency that may accompany geometric stiffening. The study indicates that a hierarchical synergistic design strategy that uses geometric stiffness for load bearing and low frequency control, while leveraging core damping to mitigate the acoustic saturation limit, provides useful physical insight into more efficient noise control approaches than purely stiffness based approaches. Full article

The emergence of edge computing introduces significant opportunities to improve real-time responsiveness and reduce latency by deploying computational resources closer to end users, at the edge, compared to traditional centralized cloud computing. However, stochastic and fluctuating workloads pose challenges in maintaining Quality of Service, often leading to resource fragmentation, service node saturation, and energy inefficiencies. In addition, imbalances in service node utilization, arising from either under-utilization or over-utilization, degrade the overall system performance and lead to unnecessary operational costs. Furthermore, finding an optimal balance between total latency cost and load balancing in different network topologies remains a significant challenge. In this research, we propose and evaluate a workload-aware orchestration framework that integrates short-term workload forecasting with dynamic resource scaling to efficiently manage edge node infrastructure under dynamic processing demands. The framework employs heuristic schemes that consider both workload distribution and service proximity throughout the edge network to optimize the distribution of edge users’ service requests across service nodes. Simulation results on grid and irregular edge network topologies, utilizing both synthetic and real-world dataset, demonstrate that the proposed framework and the integrated heuristics outperform other benchmark approaches. Specifically, our framework achieves up to 20% lower load imbalance variance, maintains high resource utilization, decreases system reconfigurations and increases service reliability, providing a robust, low-overhead and adaptive solution for dynamic orchestration in edge computing environments and infrastructures. Full article

Curcumin, a natural polyphenol derived from Curcuma longa, is widely recognized for its therapeutic properties. However, its clinical utility is limited because of poor solubility, rapid degradation and hence low bioavailability. To overcome these issues, nanoformulation approaches, especially PEGylated liposomes, have been explored as advanced delivery systems. PEGylation, which involves attaching polyethylene glycol (PEG) to the liposomal surface, enhances circulation time by creating a steric shield that reduces protein interactions and clearance by the mononuclear phagocyte system (MPS). However, PEG can alter lipid membrane properties, which may in turn affect curcumin’s solubility and distribution within the liposomal bilayer, ultimately reducing its loading efficiency. To ensure that PEG-modified liposomes can be effectively loaded with curcumin, we investigated curcumin–membrane interactions in saturated (DMPC) and unsaturated (POPC) liposomes, both in the presence and absence of PEG. Based on dissociation constants (K_d) obtained from fluorescence spectroscopy measurements, we found that PEGylated DMPC liposomes exhibit the strongest binding affinity for curcumin. Fluorescence quenching experiments showed that curcumin adopts a transbilayer orientation in all membranes examined. Curcumin’s location within PEGylated and non-PEGylated liposomal membranes was further confirmed by examining its effects on membrane properties, including fluidity, polarity, and oxygen transport. These effects were investigated using electron paramagnetic resonance (EPR) spectroscopy with spin labels. The results indicate that PEG does not impose major changes on membrane properties. Curcumin, however, was found to reinforce the liposomal membranes, increase their polarity, and reduce oxygen availability. Overall, the findings suggest that liposomes, particularly those composed of PEGylated DMPC, are effective vehicles for curcumin delivery. Full article

This study investigates the influence of parametric uncertainty in the van Genuchten–Mualem (VGM) model on hydrological simulations and proposes a deterministic, soil-focused calibration strategy within the MOHID-Land model. The approach was applied to the Pedro do Rio watershed to quantify the impact of VGM parameters, typically estimated via pedotransfer functions, on streamflow performance and to reduce uncertainty through targeted calibration. A one-at-a-time sensitivity analysis using the 95% Prediction Uncertainty (95PPU) metric identified the saturated water content (θ_s) and pore-size distribution (n) as the most influential parameters. Calibration scenarios adjusting these parameters, especially Scenario S45 (+30% θ_s, +20% n), significantly improved model performance, increasing the Nash–Sutcliffe Efficiency (NSE) from 0.20 to 0.66 on a daily scale and to 0.80 on a monthly scale during the validation period. Subsequent hydrodynamic refinements raised the daily NSE to 0.72, while monthly performance remained unchanged. The results underscore that soil parameter uncertainty plays a central role in long-term water balance representation, while hydrodynamic parameters primarily influence short-term dynamics in steep, responsive basins. Overall, the proposed strategy provides a computationally efficient alternative to fully automatic calibration methods, delivering robust performance while maintaining physical consistency, particularly in data-scarce environments. Full article

Nitrogen (N) fertilization plays a key role in pasture productivity but also contributes to environmental losses, especially under tropical conditions. This study evaluated the effects of four N rates (0, 50, 75, and 100 kg N ha⁻¹) as urea on soil N dynamics, ammonia (NH₃) volatilization, nitrous oxide (N₂O) emissions, and biomass accumulation in Brachiaria brizantha cv. Piatã, cultivated in a clayey Oxisol in the Brazilian Savanna. The experiment was conducted over two pasture growth cycles during the late summer and early fall. NH₃ volatilization increased with the N rate and showed significant differences in the initial samplings of both cycles. N₂O emissions were low, strongly influenced by rainfall, and resulted in emission factors ≤ 0.3%. Soil NH₄⁺ and NO₃⁻ concentrations did not differ statistically among treatments. Biomass production increased over time on Cycle 2 but plateaued at greater doses, with no significant differences between treatments. The limited biomass response suggests physiological saturation or environmental constraints. Findings indicate that N losses and use efficiency are shaped by rainfall and plant demand. Full article

Proportional–integral–derivative (PID) controllers are always a preferred choice of control strategy in industrial and biomedical systems due to their simplicity, reliability, and easy implementation. However, the systematic tuning of PID parameters for nonlinear, constrained, and safety-critical systems remains challenging, particularly in the presence of disturbances and actuator limitations. This paper presents a unified surrogate-based optimization framework for tuning PID controllers for linear and nonlinear dynamical systems. The tuning problem is formulated as a constrained optimization task, where performance objectives and safety requirements are explicitly incorporated into the cost function. A surrogate-based optimization via clustering (SBOC) approachis employed to efficiently explore the PID parameter space while reducing the number of expensive closedloop simulations. The proposed framework is first applied to the first- and second-order linear time-invariant systems to check its feasibility and then to the nonlinear systems to demonstrate its robustness under nonlinearity and saturation. The approach is further applied to safety-critical systems considering the case of glucose regulation in type 1 diabetes under realistic meal disturbances and insulin delivery constraints. The simulation results show that the surrogate-optimized PID controller achieves stable regulation with improved tracking performance while strictly satisfying safety requirements, including control effort penalties to limit actuator wear and the avoidance of hypoglycemia and hyperglycemia in glucose regulation problems. Full article

There has been no experimental work on CuCrO₂-ZnSnN₂ heterojunctions (HJs), though theoretical work shows that their photoelectric conversion efficiency is around 20%. Here, CuCrO₂ thin films and p CuCrO₂-n ZnSnN₂ HJs are prepared by varying the sputtering power of the Cu-Cr alloy target while the other parameters are held constant. The as-deposited Cu_xCr_yO_z thin films are amorphous, with CuCrO₂ as the major phase. The CuCrO₂ thin films are p-type conductive, with an optical band gap of about 3.64–3.84 eV. The ZnSnN₂ thin films are wurtzite and n-type conductive. The dark current density J versus voltage V curve measurements show that all the HJs showed rectification, while only the samples deposited at 40 and 50 W had a photo-induced current. Further analysis shows the HJs deposited at 40 W have the lowest shunt conductance, saturation current density, and trap density, implying an effect of fabrication conditions on the properties of HJs. Full article

Surface-mounted permanent magnet synchronous motors (SPMSMs) are widely used in high-performance electric vehicles due to their power density; however, conventional field-oriented control (FOC) relies on simplified models in which electromagnetic torque is described as a function of the quadrature current component, together with constant parameters and idealized trajectories in the $i_d-i_q$ plane, limiting adaptability and reducing efficiency and operating range under real conditions. This work introduces a flux linkage vector decomposition approach for SPMSMs, in which the permanent-magnet flux is decomposed into d- and q-axis components under core saturation and integrated into an extended field-oriented control framework. An extended FOC strategy is proposed that incorporates flux linkage vector decomposition, nonlinear magnetic saturation, cross-coupling effects, and nonlinear dependencies of electrical parameters, along with resolver angle correction and dynamic modulation index management. These enhancements modify torque and voltage trajectories by shifting the voltage-limit center and improving the definition of the MTPA, FW, and MTPV regions to better match real motor behavior, enabling performance improvements. Experimental validation on an automotive powertrain using a vehicle control unit (VCU) and precalculated lookup tables (LUTs) demonstrates improvements of up to 13.5% in low-speed torque, 13.7% in high-speed power, and efficiency gains of 4–8% across operating conditions. Full article