Search Results (476)

Frame aggregation is central to modern IEEE 802.11 networks, yet the existing performance models fail to capture how it behaves under usual unsaturated traffic. Some rely on a predefined service-time distribution; others cover only narrow unsaturated cases, such as stations withholding transmission until K packets accumulate or stations being modeled as if they always have a packet queued. This paper develops a performance model for 802.11 networks with frame aggregation under unsaturated traffic in which the aggregation size and service time emerge dynamically from the offered traffic load, the random backoff process, and the number of stations rather than from any of these simplifying assumptions. Beyond throughput, the model derives closed-form estimates of the average aggregation size, service time, and per-station queue length directly from the steady-state distribution of a three-dimensional Markov chain. Performance evaluations across two physical-layer rates (867 and 150 Mbps), two queue capacities, and different numbers of stations show that the proposed model produces throughput and aggregation-size estimates that closely match an event-driven simulator, while the service time and queue-length estimates reflect the model’s own assumption. Full article

The wake effect inside wind farms reduces the inflow wind speed and increases the turbulence intensity of downstream turbines, resulting in power loss and increased fatigue loads. Active yaw control can mitigate wake interference through collaborative optimization of turbine yaw angles. However, most existing methods rely on steady-state wake models, which fail to capture the dynamic delay characteristics of wakes and usually lead to excessive yaw actuation losses. To address these issues, this paper constructs a dynamic wake model suitable for real-time control based on the OFF dynamic wake framework (OnWARDS, FLORIDyn, and FLORIS), adopting an improved three-dimensional analytical wake model at the lowest level. On this basis, a finite control set model predictive control (MPC) active yaw controller is designed. Aiming to maximize power generation and minimize yaw loss, the controller realizes rolling optimization of yaw actions combined with ARIMA-based wind direction prediction and particle swarm optimization. Simulations on the 4 × 4 turbine array of the Horns Rev I wind farm show that the proposed method increases the total power by 2.25%, which is 0.79% higher than that obtained by the deadband controller. It results in lower power loss for upstream turbines and higher power gain for downstream turbines, reduces the total yaw travel by nearly 1000° compared with the deadband controller, and produces smaller power fluctuations under sharply changing wind directions. Full article

Rapid urbanization has led to habitat fragmentation in peri-urban areas, continuously eroding the ecological foundation of sustainable food systems in urban–rural transition zones and posing a real threat to regional food security. Against the backdrop of urbanization disturbances, traditional nature-based solutions have limitations in addressing socioecological nonlinear responses, whereas digital tools offer new governance pathways for enhancing food system resilience. To elucidate the intrinsic mechanisms through which digital technology empowers the resilience of peri-urban food systems, this study, which is grounded in ecological wisdom theory, constructs a system dynamics model that integrates “digital technology-ecological perception-ecological wisdom capital” in a three-dimensional linkage. This model simulates the dynamic process through which sustainable food systems in urban–rural transition zones resist the risks of habitat fragmentation and achieve synergistic steady-state evolution. According to the simulation results, a synthesized steady-state transition in sustainable food systems can be regarded as a self-organizing phase transition process. During resource metabolism, system elements show strong nonlinear symbiotic and mutually beneficial features. Further, there is a significant time-lag effect on improving food system resilience through digital technology empowerment and policy coordination. Also, the effects of governance are not immediately visible. Further, as an important instrumental empowerment carrier, urban–rural spatial and information barriers can be broken through means like digital ecological monitoring. Moderate investment in this regard can promote the acceleration of the system’s self-organizing phase transition. Also, this can enhance resilience against disturbance from habitat fragmentation while ensuring food production and supply. Finally, the ecological carrying capacity of core food production spaces does not increase monotonically. This means that the system possesses an adaptive cyclical fluctuation mechanism, with a periodic oscillatory evolution of carrying capacity. This study breaks through static analytical paradigms, fills the quantitative research gap on the resilience evolution of peri-urban food systems driven by the integration of digital technology and ecological wisdom, and can provide scientific evidence and decision-making support for food–ecological collaborative governance in China’s urban–rural transition zones. Full article

Fault fracture zones can act as preferential groundwater flow paths and significantly modify the seepage field around tunnels. To investigate the influence of the fault–tunnel intersection angle on pore water pressure distribution in tunnel surrounding rock, a three-dimensional steady-state Darcy seepage model was established using the F4 fault section of the Yinggeling Tunnel as a representative engineering background. Four cases were considered: a fault-free tunnel and tunnels intersecting fault fracture zones at fault–tunnel intersection angles of 45°, 90°, and 135°. Pore water pressures were extracted at the tunnel crown, invert, and left and right sidewalls at radial distances of 0.2 m and 10 m from the excavation boundary to characterize the near-field and intermediate-to-far-field responses. The results show that the fault fracture zone acts as a preferential drainage pathway and reduces the pore water pressure around the tunnel. Under the baseline permeability condition, the 90° intersection case produces the strongest pressure-relief effect, with peak pore pressure reduction ratios of 23.66–24.24%, followed by the 45° case with reductions of 20.54–22.22%, whereas the 135° case shows a weaker reduction of 4.74–5.36%. Sensitivity analysis indicates that the 90° case generally maintains the strongest pressure-relief effect under most fault-to-rock permeability ratios, although the differences among some intersection-angle cases decrease at high permeability ratios. The near-field surrounding rock exhibits rapid pressure dissipation controlled by tunnel drainage and fault-guided flow, whereas the intermediate-to-far field shows a smoother and more attenuated response. These findings clarify the seepage-control mechanism of the fault–tunnel intersection angle and provide a reference for waterproofing and drainage design in tunnels crossing fault fracture zones. Full article

Distributed maximum correntropy Kalman filters improve robustness to non-Gaussian noise, but existing variants generally introduce consensus through average or weighted fusion without explicitly separating the innovation residual from the state-disagreement residual in a dimensionally consistent objective. This paper proposes a Distributed Maximum Correntropy Kalman Filter with Innovation and Consensus Weighting Terms (DMCKF-IW-CWT). The innovation and consensus residuals are normalized separately and mapped by Gaussian kernels, after which the resulting information matrices are incorporated into a fixed-point local update. Posterior covariance intersection (CI) is then used to fuse neighboring estimates without requiring the unavailable cross-covariances. A sufficient contraction condition is given for the fixed-point iteration. In a five-node benchmark with 500 independent Monte Carlo runs and 1000 sampling steps, the proposed method obtains overall, transient, and steady-state MAEs of 0.172210, 0.188271, and 0.168195, respectively, corresponding to reductions of 0.254%, 0.526%, and 0.178% relative to DMCKF-W; the paired 95% confidence intervals of all three differences remain below zero. The consensus RMS is further reduced by 5.371%. Additional tests involving five noise families, packet loss and communication noise, a four-state nonlinear model, and systems with up to eight states and twenty nodes confirm the numerical convergence and extensibility of the framework. Full article

GaN power devices used in high-power-density converters face significant thermal-management challenges because substantial heat is generated within a compact active region and transferred through the device–Printed Circuit Board (PCB) interface. This study investigates the influence of PCB dielectric-material selection on the coupled thermal and electrical behavior of a 48 V/12 V GaN half-bridge converter. Flame Retardant 4 (FR4), Hydrocarbon ceramic laminate material RO4000 series (4003) (RO4003), and polybenzoxazole (PBO) were compared using a reduced steady-state thermal-resistance network, three-dimensional finite-element simulations in Ansys Icepak, parasitic-capacitance extraction in Ansys Q3D, and switching simulations in LTspice. Both analytical and numerical models produced the same thermal-performance ranking, with PBO providing the lowest junction temperature. Under identical geometry, power dissipation, and boundary conditions, the Finite Elements Method (FEM) results showed a reduction in the maximum junction temperature from 225 °C for FR4 to 159 °C for PBO. The extracted layout-associated capacitances were also reduced by approximately 30–38% with PBO relative to FR4. This decrease produced a slight reduction in the switching-node falling time and lowered the calculated transistor loss from 3.118 W to 3.102 W. The results show that PCB dielectric selection is primarily a thermal-design parameter, while its electrical influence remains modest under the investigated operating conditions. Full article

Battery thermal management systems (BTMSs) are essential for maintaining the performance, efficiency, durability, and safety of electric-vehicle battery packs. Although fin-enhanced air-cooled BTMSs offer a simple and leakage-free cooling solution, their practical implementation is often limited by increased weight, insufficient temperature uniformity, and restricted heat-dissipation capability under high thermal loads. This study numerically investigates a compact air-cooled BTMS for two types of cylindrical lithium-ion batteries using aluminum and polypropylene (PP-$\beta$) circumferential fins in inline and staggered cell arrangements. Unlike previous fin-based air-cooling investigations, the present study combines a compact 2 × 4 battery pack with transverse and longitudinal center-to-center cell pitches of 1.2D, a direct comparison between metallic and lightweight polymer fins, and an assessment of two 18650 battery types with different capacities, thermophysical properties, and heat-generation characteristics. A three-dimensional steady-state conjugate heat-transfer model was developed in ANSYS Fluent to evaluate the effects of fin number, fin material, cell arrangement, ambient temperature, and inlet airflow velocity under discharge rates ranging from 1 C to 4 C. The results reveal that increasing the number of fins consistently reduced the maximum cell temperature but increased the pressure drop. The inline configuration generally achieved a lower maximum temperature and higher Nusselt number (Nu), whereas the staggered arrangement maintained a substantially lower pressure drop. Relative to the corresponding finless configurations, the Nu increased by 64.4–71.2% for the inline arrangement and 86.4–98.1% for the staggered arrangement. Polypropylene fins provided thermal performance close to that of aluminum fins in terms of maximum temperature while reducing the total fin mass by approximately 44.8%; however, aluminum fins maintained better temperature uniformity. These findings quantify the trade-offs among thermal performance, pressure drop, compact cell spacing, and system weight, providing design guidance for compact fin-enhanced air-cooled BTMSs. Full article

We investigate the dissipative dynamics of a one-dimensional sawtooth-shaped Bose–Hubbard model subjected to an external magnetic flux and staggered single-particle dissipation. By combining the Lindblad master equation with a mean-field decoupling and further reducing the dynamics to an effective three-site model, we derive the nonlinear evolution equations that govern the system. Our results reveal that the magnetic flux, acting through the next-nearest-neighbor hopping, determines the preferential direction of particle flow, while the imbalance in dissipation forces the steady-state population to accumulate at lattice sites with weaker loss. Furthermore, we find that two-particle dissipation accelerates the relaxation process when it becomes negative (i.e., gain), whereas positive two-particle loss suppresses localization. These findings demonstrate that directional localization and relaxation dynamics can be controlled by the sign of the next-nearest-neighbor hopping t′ and the magnetic phase, providing a tunable scheme for engineering dissipative quantum states in optical lattices. Full article

Converter-dominated power systems increasingly require flexible resources that can support frequency while preserving a physically interpretable energy trajectory. Thermal-energy-storage (TES)-based virtual energy storage systems (VESSs) can shift electrical demand within thermal-energy and comfort constraints, and have therefore attracted extensive interest. However, existing studies commonly coordinate requested or normalized power without fully connecting it to actuator execution and the electrical-to-thermal energy path. Command-level sharing cannot be directly equated with executed physical power, and controller storage cannot be combined with joule-valued hardware energy without dimensional separation. Therefore, this paper proposes a physically coupled and energy-traceable virtual asynchronous machine (VAM) control method for TES-based VESSs. First, a loss-resolved averaged model establishes the point-of-common-coupling (PCC)–converter–DC-link–actuator–TES physical chain and separates the hardware Hamiltonian from the dimensionless control Lyapunov function. Second, a neighbor-coupled marginal controller is embedded in a command–projection–execution chain so that frequency regulation and weighted sharing are evaluated using the executed service. Third, a constraint-handling mechanism combines directional headroom gating, actuator saturation and ramp limits, thermal comfort bounds, and request-inactive state reset to maintain executable trajectories under the declared constraints. Simulations under a sustained $120\mathrm{kW}$ disturbance show that primary-only control retains a $-0.08883\mathrm{Hz}$ steady-state offset, whereas the proposed nominal case restores frequency. In the constrained case, the 30 s terminal trend remains above the prescribed limit, while both terminal windows of the 60 s run satisfy the restoration criterion; the final-window mean error and dimensionless eligible-unit sharing spread are $-6.317\times {10}^{-5}\mathrm{Hz}$ and $6.564\times {10}^{-5}$, respectively. The model-internal electrical–thermal balance achieves a dimensionless relative RMS residual of $6.2361\times {10}^{-8}$. Because the PCC voltage/current pair is reconstructed from the same power source, this residual quantifies model-internal consistency rather than independent measured closure. These results demonstrate constrained frequency restoration, executed-power coordination, and energy traceability within the averaged-model scope. Full article

With the continuous penetration of renewable energy and power electronic equipment into modern power systems, the occurrence frequency of composite power quality disturbances has increased significantly. The accurate classification of various composite disturbances under strong noise remains a critical technical challenge. The existing single time–frequency transformation methods cannot simultaneously capture transient time-domain details and fine frequency-domain features of steady-state harmonics, while mainstream deep learning classification networks contain redundant parameters and introduce excessive computational overhead, failing to meet the real-time deployment requirements of power edge terminals. To address these limitations, a lightweight Coordinate Attention ResNet network named ResNet–LCA is proposed based on the dual-modal time–frequency fusion of the Continuous Wavelet Transform and Short-Time Fourier Transform. First, the two transforms are implemented separately to generate two groups of complementary time–frequency maps, which are concatenated along the channel dimension to fully extract the coupling features between the steady-state harmonics and the transient impulses. Second, a Haar wavelet subband mean aggregation module is designed for dimensionality reduction with negligible information loss. This module eliminates the channel redundancy introduced by the multimodal fusion and reduces the overall computational overhead at the input stage. Finally, a lightweight residual network integrated with Coordinate Attention is constructed, with Grouped Half-Convolution adopted to compress the model parameters. CA offsets the feature attenuation induced by the lightweight structural design and further improves the model’s noise immunity. A simulation verification was carried out on a simulated dataset covering 25 types of single and superimposed composite disturbances. At a signal-to-noise ratio of 20 dB, the proposed method achieved an average classification accuracy of 97.92%, with only 5.32 M total parameters and a single-sample GPU inference latency of 0.33 ms. Compared with standard ResNet-18 under 20 dB noisy conditions, the total parameter volume was reduced by 52.7%, the inference latency was shortened by 0.13 ms, and the classification accuracy was improved by 0.60 percentage points. The proposed method achieves coordinated optimization of classification accuracy, noise immunity and inference efficiency, and it can provide lightweight technical support for online intelligent power quality monitoring at the edge nodes of microgrids and islanded power systems. Full article

To address the challenge of balancing junction temperature prediction accuracy and computational efficiency for high-power multi-chip IGBT modules in automotive applications during complex electro-thermal conversion processes, this study proposes an improved three-dimensional thermal network model based on equivalent power loss injection. Firstly, the effective heat conduction area of each packaging layer under actual heat flow distribution is extracted through three-dimensional finite element simulation, and the single-chip self-heating network parameters are constructed. Secondly, targeting the thermal cross-coupling effect among multiple chips, an elliptical thermal diffusion model is applied to accurately define the thermal coupling region, and a dynamic equivalent power loss compensation mechanism is introduced. Efficient decoupling of multi-heat-source interference is achieved without increasing the state-space dimension of the model. An experimental benchmarking results comparison indicates that the absolute error of junction temperature prediction by this model under steady-state operating conditions is 0.5 °C. Further comparative analysis under the full CLTC-P (China Light-duty Vehicle Test Cycle for Passenger Car) cycle verifies that the improved model not only overcomes the shortcomings of the traditional Foster model, which severely underestimates the transient peak junction temperature and alternating stress amplitude, but also effectively filters out non-physical overshoots caused by short-term ultra-narrow pulses, thus reasonably estimating the device’s maximum junction temperature within the real physical boundary. This method provides efficient theoretical support for accurate dynamic junction temperature predictions and reliability evaluations of electric vehicles under complex operating conditions. Full article

Proton exchange membrane fuel cells (PEMFCs) are critical parts of new-age green hydrogen energy systems where reactant distribution and water management determine performance and reliability. A three-dimensional, steady-state, and single-phase model of a self-humidified low-temperature PEMFC was developed in COMSOL Multiphysics to compare parallel, single-serpentine and double-serpentine bipolar plate flow fields under identical active area membrane electrode assembly, material properties and operating conditions, so that flow field geometry was the only variable. The model is verified via grid independence and validated in terms of published experimental polarization data with mean absolute deviation under 2%. At 0.1 relative humidity of the cathode inlet, the single-serpentine flow field provides 717 mA cm⁻² current density at 0.6 V and 595.7 mW cm⁻² peak power density in contrast to 582 mA cm⁻² and 492.3 mW cm⁻² for the double-serpentine and 577 mA cm⁻² and 463.2 mW cm⁻² for the parallel flow field. These two designs therefore behave almost identically in electrochemical terms but differ hydraulically; their peak channel pressure drops, being 3.8 and 0.8 kPa against 14 kPa for the single-serpentine design. Once pumping power is included, the single-serpentine design remains the best net power choice below an active area of approximately 54 cm². Full article

To address the problems of increased bilateral synchronization error, accumulated beam attitude deviation, and degraded operating stability of a dual-motor-driven lifting beam under eccentric loading, this paper proposes a coordinated synchronization–attitude control method based on online eccentric-load estimation and dynamic differential allocation. First, a two-dimensional dynamic model incorporating overall vertical translation and small-angle beam rotation is established. On this basis, the control task is decomposed into trajectory tracking in the common channel and synchronization–attitude regulation in the differential channel. Second, an online equivalent eccentric-load moment estimator is introduced to extract the dominant eccentric-load effect through differential-channel residuals and first-order low-pass filtering. Then, a dynamic differential allocation mechanism jointly driven by the estimated moment and beam attitude is constructed to adaptively adjust the left–right driving-force difference while maintaining the total lifting force. Furthermore, synchronization-error feedback, attitude feedback, and eccentric-load compensation are unified in the differential control law. Finally, comparative simulations and experiments under step and preset eccentric-loading conditions show that, for an additional mass of 10 kg placed 0.45 m from the nominal beam center, the proposed method reduces the experimental tracking RMSE to 4.31 mm, limits the peak tilt angle to 0.64°, and reduces the steady-state synchronization error to 1.48 mm. These results demonstrate improved tracking accuracy, synchronization consistency, attitude stability, and adaptability to persistent eccentric loading. Full article

The paper examines the possibility of compensating one of the significant systematic factors in turning that affects the quality of machined surfaces—namely, the dimensional wear of cutting inserts during finish turning. Predictive wear models are developed in which the process is approximated using either a linear or an exponential function. The wear prediction error is determined. Based on data from the authors’ experimental studies and other published sources, the duration and intensity of the initial and steady-state wear stages are established. A corrected predictive function is presented, consisting of a nonlinear initial segment and a linear steady-state segment. A design variant of a measuring probe for monitoring the current wear of the insert cutting edge, applicable under production conditions, is also proposed. Full article

Geothermal energy extraction using existing wellbore systems provides a promising approach for sustainable heat utilization; however, the long-term thermo-hydro-mechanical (THM) responses associated with different working fluids remain insufficiently understood. In this study, a three-dimensional coupled THM model was developed to compare geothermal heat extraction using water and pressurized CO₂ under identical geological and operational conditions. The model integrates Darcy flow, heat transfer, and linear elastic deformation to investigate the evolution of hydraulic, thermal, and mechanical fields over a 100-year operation period. The results show that the hydraulic fields rapidly reach quasi-steady states, whereas thermal responses continuously evolve due to cold-front propagation from the injection well. Compared with water, pressurized CO₂ exhibits stronger fluid mobility and produces a larger thermal influence region, resulting in different heat extraction characteristics under the same mass-flow-rate condition. Thermal cooling induces reservoir contraction and stress redistribution; however, the calculated stress and displacement variations remain within a stable range throughout the simulation period. The comparison demonstrates that pressurized CO₂ can enhance long-term thermal utilization while maintaining acceptable geomechanical stability under the investigated conditions. These findings provide insights into the selection of working fluids for wellbore-based geothermal systems and highlight the importance of coupled THM evaluation for long-term reservoir performance assessment. Full article