Search Results (772)

The weak-field, quasi-static regime of gravity is commonly described by the Newton–Poisson equation as an effective response law. We construct this response within a cost-first discrete variational framework. The Recognition Composition Law (RCL) uniquely selects a reciprocal closure cost within the restricted quadratic symmetric composition class; together with the discrete ledger axioms AX1–AX5 (including conservation) and standard DEC refinement, the Newton–Poisson baseline is then recovered in the instantaneous-closure limit. Conditional on Assumption AS1 (scale-free latency) and Assumption AS2 (causal frequency–wavenumber ansatz), allowing finite equilibration introduces fractional memory into the response, yielding a scale-free modification of the source–potential relation characterized by a power-law kernel $w_{\ker }\left(k\right)=1+C{(k_0/k)}^{\alpha }$ in Fourier space. The kernel exponent $\alpha =\frac{1}{2}(1-{\phi }^{-1})\approx 0.191$, where $\phi =(1+\sqrt{5})/2$, is derived from self-similarity of the discrete ledger closure; the amplitude $C={\phi }^{-2}\approx 0.382$ is identified as a hypothesis from a three-channel factorization argument. We evaluate this quasi-static kernel-motivated response against SPARC galaxy rotation curves under a strict global-only protocol (fixed $M/L=1$, no per-galaxy tuning, conservative ${\sigma }_{\mathrm{tot}}$), using a controlled multiplicative surrogate for the full nonlocal disk operator implied by the kernel. In this deliberately over-constrained setting, the surrogate interface achieves $\mathrm{median}({\chi }^2/N)=3.06$ over 147 galaxies (2933 points), outperforming a strict global-only NFW benchmark and remaining less efficient than MOND under identical constraints. The analysis is restricted to the non-relativistic, quasi-static sector and should be read as a falsifier-oriented galactic-regime consistency check of the scaling window, not as a relativistic completion or a claim of Solar System viability without additional UV regularization/screening. Full article

Autonomous traversal flight in unknown 3D environments remains challenging due to mapping bottlenecks and computational latency. Inspired by pigeons navigating cluttered forests through instantaneous visual perception rather than constructing global metric maps, this paper presents a pigeon-inspired depth-reasoning-driven decision framework for agile quadrotor traversal in unmapped spaces without explicit map construction. To ensure feasibility, we leverage a robust state estimation backbone enhanced by deep-learning-based feature matching, providing stable pose feedback under aggressive maneuvers. The core contribution is a pigeon-inspired depth-reasoning framework that translates raw sensory depth data into a hybrid optimization framework, integrating both hard safety constraints and soft geometric smoothness constraints, directly emulating the three avian mechanisms: gap selection via instantaneous depth gradients, path selection that minimizes posture changes, and a safety field driven by the looming effect. By bypassing time-consuming mapping and spatial discretization processes, the framework significantly reduces perception-to-control latency. Finally, validated via simulations and real-world experiments on a resource-constrained quadrotor platform, our map-less approach achieves superior decision frequencies and comparable safety margins to those of state-of-the-art map-based planners. This framework offers a practical, high-frequency solution for autonomous flight where computational resources and environmental knowledge are strictly limited. Full article

Carbon Fiber Reinforced Polymers (CFRP) are extensively utilized in high-performance engineering, yet localized structural discontinuities can severely compromise their integrity. This paper aims to achieve high-sensitivity characterization of such anomalies using a proposed acoustic shearography technique based on continuous acoustic excitation. A comprehensive finite element model (FEM) was developed to clarify the mechanical-energy coupling between the acoustic fields and localized surface strain field modulations. By exploiting ultrasonic energy coupling, the localized features of discontinuities were identified through full-field, non-contact optical measurement of localized phase distortions. Key parameters, including shearing amount, excitation frequency, driving voltage, and geometric characteristics of blind flat-bottom holes (BFBH), were systematically investigated. The results demonstrate a high correlation between FEM simulations and experimental observations quantitatively elucidating how defect diameter and hole depth modulate surface strain distributions. The proposed hybrid acoustic optical approach achieves near-instantaneous full field imaging within a millisecond timeframe typically under 200 ms. Additionally, the methodology leverages localized acoustic resonance to significantly boost the signal-to-noise ratio (SNR) resulting in highly quantified phase map contrast. Full article

Synthetic aperture radar (SAR) ship detection is severely limited by the artifacts caused by motion. Due to the complex six-degree-of-freedom (6-DOF) motion of ships, the ship imaging exhibits aberration phenomena including spatial blurring, discrete ghosting, and Lorentz linear blurring. Traditional detectors rely on the identification of static spatial features. When the phase coherence is disrupted, they tend to fail. To overcome this problem, we propose a multimodal fusion framework based on physical principles. This framework establishes a theoretical connection between the ship hydrodynamic response and imaging degradation through short, long, and ultra-long coherence processing intervals (CPI). The framework adopts a cascaded architecture: first, a lightweight YOLOv8 performs rapid global screening, followed by a signal backtracking mechanism that extracts high-fidelity time-frequency domain (TFD) and range instantaneous Doppler (RID) features from the original distance compressed data. In the second-level detection, these physical features are adaptively fused with spatial intensity through a YOLOv8 network integrated with the convolutional block attention module (CBAM) to reduce the false detection rate. The validation on high-fidelity simulations and real GF-3 datasets shows that this method consistently achieves an average precision (mAP) of over 95%, outperforming several widely used detectors, and demonstrates strong generalization ability in extreme imaging conditions, suitable for maritime detection scenarios. Full article

When the Risley prism pair is used for target tracking, the nonlinear relationship between beam deflection and prism rotation makes tracking performance highly dependent on precise and stable motor control over a wide speed range. Although the brushless DC motor serves as the preferred drive source, its inherent commutation torque ripples directly induce beam pointing jitter, severely degrading overall tracking accuracy and stability. To address these issues, this paper proposes a three-vector-based model predictive direct speed control method. This approach establishes a direct speed-to-torque control channel by generating reference active power through dynamic equations, eliminating the need for fitting a constant flux linkage and parameter tuning. Simultaneously, combined with three-vector optimization and seven-segment modulation strategies, it achieves a dynamic balance between high-frequency, instantaneous electromagnetic power fine-tuning and inherent mechanical inertia of the rotor. Simulation results demonstrate that the proposed method exhibits superior speed stability compared to the conventional double-vector-based model predictive power control method and maintains high-precision dynamic tracking over a wide speed range. Ultimately, it leads to an average reduction of over 60% in the time-weighted absolute tracking error integral under various target trajectories, providing an effective solution for drive control of target tracking in Risley prism systems. Full article

To explore the spectral characteristics of near-field vibration signals from multi-hole millisecond-delay blasting in open-pit mines and the modulation effect of delay time on blasting energy distribution, field blasting vibration tests with multi-gradient delays were conducted taking an open-pit coal mine in Xinjiang as the engineering background. Particle Swarm Optimization (PSO) optimized Variational Mode Decomposition (VMD) and Hilbert-Huang Transform (HHT) were introduced for the refined processing and frequency band energy ratio analysis of the measured signals, and field vibration control tests were subsequently carried out. The results show that compared with the traditional Empirical Mode Decomposition (EMD), the PSO-optimized VMD can effectively overcome the mode aliasing phenomenon. By extracting the high-frequency Intrinsic Mode Function (IMF7) that characterizes the instantaneous detonation impulse, the actual delay time was successfully inverted to be 10.47 ms. The inter-hole delay time significantly affects the time-frequency distribution of vibration energy. Under the 25 ms delay condition, the energy ratio of the high-frequency band is the highest, and the low-frequency energy accumulation degree is the lowest, which is most conducive to shortening the vibration duration and accelerating energy attenuation. Control tests further confirmed that adopting a 17 ms delay in the near-slope area can effectively control the peak particle velocity (PPV) in the near field, while adopting a 23 ms delay in the middle and far areas can further reduce the low-frequency energy concentration. The research results demonstrate a dynamic matching strategy for millisecond delays based on spatial distance differences, which has important guiding significance for realizing safe and efficient blasting vibration control in open-pit mines. Full article

In this study, a novel direct torque control (DTC) strategy is proposed to mitigate the torque ripple issue inherent in switched reluctance motors (SRMs), which is caused by the double salient pole configuration and the pulse power supply mode. The strategy is based on the prediction and optimization of a long-time-domain model. Central to this method is the development of a multi-step predictive optimization framework. By incorporating hysteresis control, the conventional approach of minimizing instantaneous error in predictive control is shifted towards minimizing tracking error over an extended time frame. A dual-objective evaluation function is also introduced, which simultaneously optimizes both torque smoothness and switching frequency, ensuring their collaborative enhancement. To validate the proposed method, a 6/4-pole SRM simulation model was implemented using MATLAB/Simulink 2024B, and comparisons were made with traditional methods. The results demonstrate that this strategy significantly reduces torque pulsation and lowers the system’s switching frequency, even under varying operational conditions such as different rotational speeds and sudden load variations. Consequently, this approach not only guarantees improved dynamic performance but also enhances the motor’s efficiency and stability. Full article

Non-orthogonal multiple access (NOMA) has become one of the main enabling technologies for next-generation cellular networks. The ability to allocate multiple users on the same frequency resources simultaneously leads to improved spectral efficiency. This paper examines power allocation and user pairing for NOMA networks with an objective to enhance the sum spectral efficiency (sum capacity, bps/Hz) while guaranteeing the target rate of the far user. Two benchmark methods were used to evaluate the performance of the proposed scheme: (1) fixed power allocation, in which fixed power coefficients are allocated to the near and far users, and (2) random power allocation, where random coefficients are assigned to the users. However, these static methods fail to adapt to instantaneous channel conditions and may lead to reduced performance for the weak user and inefficient power utilization. To manage these limitations, a novel interference-limited power allocation (IL-PA) scheme is proposed. In the IL-PA, the power allocation coefficients are dynamically allocated to users according to an interference threshold. The proposed scheme guarantees that the interference induced by the near user does not exceed a predefined interference threshold; thus, the target rate of the far user is achieved. The proposed interference threshold is derived theoretically to enhance the overall system capacity and optimize the signal-to-interference-plus-noise ratio (SINR). Additionally, a user pairing scheme, which separates users into two groups according to their channel gains, is proposed to reduce complexity while preserving good performance. The simulation results show that the proposed power allocation and user pairing scheme outperforms the benchmark methods in terms of overall capacity. Full article

Safe and energy-aware navigation is still difficult for unmanned surface vehicles (USVs), especially in cluttered waters where obstacles, smooth motion, and wind or current effects must be considered at the same time. If these issues are handled separately, the path may become longer and the vehicle may turn more often, which raises propulsion effort and hurts stability. To reduce these problems, a hybrid path planning method called ${\theta }^{\ast }$-APF-Q is proposed, and it combines global planning, learning-based decisions, and local adjustment in a three-layer structure. First, an any-angle ${\theta }^{\ast }$ global planner is employed to generate a near-optimal backbone trajectory by line-of-sight pruning, thereby reducing redundant waypoints and limiting detours. Second, an enhanced tabular Q-learning model is executed in an expanded eight-direction action space, and policy learning is guided by a multi-objective reward that jointly encourages distance reduction, alignment with ocean current and wind-induced forces for energy saving, smooth heading variation to suppress excessive steering, and maintenance of a safety margin near obstacles. Third, an adaptive artificial potential field (APF) module is used for real-time local correction, providing repulsion in high-risk regions and assisting trajectory smoothing to reduce unnecessary turning operations. A decision bias strategy further couples instantaneous APF forces with long-term state–action values, while the influence weight is adaptively adjusted according to environmental complexity. The algorithm is validated on the randomly generated marine grid maps and on the real-world satellite map scenario, with comparisons against a conventional four-direction Q-learning baseline. Across randomized tests, average path length, turning frequency, and the composite energy indicator are reduced by 22.3%, 55.6%, and 26.4%, respectively, and the success rate increases by 16%. The results indicate that integrating global guidance, adaptive learning, and local reactive decision making supports practical, energy-aware USV navigation. Full article

We developed an arbitrary Lagrangian–Eulerian (ALE)-based multiphysics model for evaporation from a contact-line-pinned sessile drop of neat water subject to a vertically oriented sinusoidal alternating current (AC) electric field applied across parallel-plate electrodes. The framework fully couples electrostatics, incompressible flow, heat transfer with evaporative cooling, and transient vapour transport in air, and includes an instantaneous, voltage-controlled electrowetting contact-angle response under constant-contact-radius conditions. Validation against published data shows that the model captures both pinned-droplet evaporation and electrically induced deformation. Because Maxwell traction scales with the squared electric-field magnitude, droplet height and contact angle exhibit a robust 2:1 frequency-doubled response, producing two peak–trough events per voltage period. The resulting periodic deformation drives oscillatory interfacial shear and internal recirculation, yielding a synchronous double-peaked evaporative-flux waveform. Gas-side analysis quantifies a time-varying diffusion-layer thickness via a characteristic diffusion length; two thinning events per period coincide with flux maxima, indicating that AC enhancement is dominated by periodic compression of the vapour boundary layer and reduced gas-side mass-transfer resistance. Increasing voltage amplitude (0–60 kV) strongly accelerates volume loss, while frequency has a secondary effect: the cycle-averaged flux rises from 1 to 10 Hz but decreases slightly at 20 Hz due to phase lag and weaker boundary-layer modulation. Full article

Ripple currents on the direct current (DC) bus in variable frequency drive (VFD) systems originate from motor load current fluctuations and the high-frequency switching of power devices. The resulting Joule heating within the DC-link capacitors is a primary driver of lifespan degradation. To address the lack of systematic models for multi-phase H-bridge inverters and the over-design caused by empirical methods, this paper proposes a novel analytical method that incorporates the 2kπ/N phase difference of parallel units for precise ripple current quantification. First, a dynamic DC-link capacitor model is established based on a single-phase H-bridge inverter, and the expressions for the instantaneous, average, and root mean square (RMS) input currents are derived. Furthermore, by introducing the 2kπ/N phase difference (where k = 0, 1, …, N − 1) among N parallel H-bridge units, a universal analytical expression for the RMS input current and its harmonic spectrum in a multi-phase system is obtained. The analysis reveals that ripple current harmonics concentrate at 2m × f_sw (where m is a positive integer and f_sw is switching frequency) and their sidebands (2m × f_sw ± f_o, f_o is output fundamental frequency), and the coupling influence of modulation index and power factor angle on ripple amplitude is quantitatively characterized. A 12 × 160 kW twelve-phase H-bridge inverter is taken as a case study, and MATLAB (v2023b) simulations and hardware experiments demonstrate that the theoretical calculations are in close agreement with the simulated and measured results, with the errors of input current harmonic amplitudes all below 5%. Compared with traditional empirical design, the proposed method reduces the capacitor volume and cost by approximately 15–20% while ensuring system reliability. This method is directly extensible to other multi-phase inverter topologies, providing a theoretical foundation for the accurate selection of DC-link capacitors. Full article

This study assesses the technical feasibility of utilizing aggregated domestic freezers in Turkey as a distributed resource for frequency regulation. A dynamic thermal–electrical model was developed to simulate freezer responses under frequency deviation scenarios representative of real-world grid conditions. The modeled sample of 100,000 deep freezers (80 W each) can deliver approximately 3.2 MW of instantaneous down-regulation under a 40% initial duty cycle. Extrapolating to the estimated 4.7 million eligible freezers nationwide yields a total potential headroom of roughly 150–225 MW, depending on duty-cycle assumptions. The compressor duty cycle and allowable temperature range were identified as key factors influencing both regulation capacity and endurance. Although linear reference temperature control enabled effective participation in FCR-N within the simulated timeframes, it also led to cycle synchronization and peak loads following disturbances. Implementing strategies such as randomized reconnection delays could mitigate these effects. The wide availability of domestic freezers, minimal consumer impact, and broad geographic distribution suggest that this resource represents a promising complement to existing frequency regulation assets, particularly in enhancing grid stability amid increasing renewable energy penetration. Full article

A novel approach for detecting preliminary signals designating upcoming entrance of a loaded system to the critical stage of impending fracture is assessed. The approach is based on the analysis of a time series of the cumulative number of acoustic events, the amplitude of which exceeds the respective average value of all the events recorded during loading. Using the “sliding window” technique, the average slope of the evolution of this time series is quantified, either against conventional or natural time (the latter provides a more detailed view of the stage before macroscopic fracture, during which the “information” gathered is very densely packed in a short interval). For the needs of this study, data from a previously published experimental protocol are exploited. The protocol comprised notched, beam-shaped specimens, made of either plain or fiber-reinforced concrete, under three-point bending. It is concluded that the slope of the evolution of the above time series systematically attains a value equal to unity slightly before the applied load attains its peak value. The results of the present analysis are in qualitative agreement with the respective ones based on either the instantaneous frequency of generation of acoustic events or the Euclidean distance between the sources of acoustic signals. Full article

Seismic attributes are widely used to enhance the interpretation of structural, stratigraphic, and lithologic features in subsurface data. Their effectiveness, however, can be limited by noise, resolution constraints, and processing artifacts. This study suggests new seismic attributes computed using 2D-Variational Mode Decomposition (2D-VMD), which are specifically Mode-Weighted Spectral Discontinuity (MWSD) (in Module and Phase modes), VMD-Directionality Coherence (VDC), Instantaneous Frequency Concentration (IFC-VMD), and Instantaneous Bandwidth Dispersion (IBD-VMD). The proposed 2D-VMD-based attributes are compared with seven key conventional seismic attributes: dip, azimuth, chaos, coherence (semblance), curvature (mean curvature), instantaneous frequency, and instantaneous bandwidth (Hilbert transform). Through applications on simulated and real seismic data, each method is compared in terms of its ability to enhance attribute stability, resolution, and interpretability while mitigating limitations such as noise sensitivity and loss of detail. Results indicate that MWSD (Module) is optimal for amplitude stability, MWSD (Phase) for phase-sensitive applications, VDC for high-resolution structural delineation, IFC-VMD for complex geological settings, and IBD-VMD for abrupt feature changes. The findings demonstrate that these new 2D-VMD-based techniques provide significant advantages over traditional approaches and that combining complementary methods can further improve seismic interpretation outcomes. Full article

The increasing integration of inverter-based distributed energy resources (DERs) significantly reduces power system inertia, posing critical challenges to transient stability. Traditional fault ride-through strategies, relying on passive and localized rules, often fail to provide effective coordinated support in low-inertia grids. To address these limitations, this paper proposes a Transient Dynamic Features Adaptation Distributed Cooperative Control (TDA-DCC) framework. This approach integrates a dynamic context-aware policy network based on multi-head attention mechanisms to extract temporal features from local observations, allowing agents to anticipate transient dynamics rather than merely reacting to instantaneous states. A multi-agent deep deterministic policy gradient algorithm is employed to optimize a global multi-dimensional objective function encompassing frequency, voltage, and rotor angle stability. Furthermore, to ensure engineering reliability, a hybrid execution architecture is introduced, which embeds a deterministic safety monitor to switch between the intelligent policy and a robust backup controller during extreme anomalies. Case studies on a modified IEEE 39-bus system demonstrate that the proposed method significantly enhances transient stability margins and robustness against sensor failures compared to conventional baselines. Full article