Search Results (3,525)

Semi-open impeller sewage pumps are widely used in fields such as municipal wastewater treatment. However, they often face performance degradation and operational instability when conveying solid–liquid two-phase flows containing solid particles. This study aims to systematically elucidate the influence mechanisms of particle diameter (0.5–3.0 mm) and volume fraction (1–20%) on the external characteristics and internal flow field of semi-open impeller sewage pumps, providing a theoretical basis for optimizing their design and operational stability. Using an 80WQ4QG-type sewage pump as the research subject, this study employed a combination of numerical simulation and experimental research. The standard k-ε turbulence model coupled with the Discrete Phase (Particle) approach was adopted for multi-condition solid–liquid two-phase flow simulations. Furthermore, two-way analysis of variance (two-way ANOVA) was utilized to quantify the main effects and interaction effects of the parameters. The results indicate that the pump head and efficiency generally exhibit a decreasing trend with increasing particle diameter or volume fraction, with particle diameter exerting a more pronounced effect (p < 0.01). When the particle diameter increased to 3.0 mm, the head decreased by 5.66%; when the volume fraction rose to 20%, the head decreased by 4.17%. It is noteworthy that the combination of a 0.5 mm particle diameter and a 20% volume fraction resulted in an abnormal increase in head, suggesting a possible flow pattern optimization under specific conditions. Analysis of the internal flow field reveals that coarse particles (≥1.5 mm) intensify the pressure gradient disparity between the front and rear shroud cavities of the impeller, thereby increasing the axial thrust. A high volume fraction (≥10%) promotes pronounced flow separation in the volute tongue region and exacerbates the risk of localized erosion at the outlet. Full article

In modern naval operations, the strategic value of naval mines has been increasingly emphasized, highlighting the need for intelligent and efficient deployment strategies. This study proposes integrated framework that combines mine burial rate estimation with reinforcement learning-based optimization to generate mine-laying routes that maximize burial effectiveness. An initial burial rate estimation simulator was developed using environmental factors such as sediment bulk density and shear strength estimated from sediment type and mean grain size to predict the burial rates of bottom-contact mines. The simulator was integrated into reinforcement learning frameworks—Deep Q-Network (DQN), and proximal policy optimization (PPO). The reinforcement learning methods were trained to autonomously explore the environment and generate routes that strategically utilize high burial regions while satisfying navigational constraints. Experimental results demonstrate that the reinforcement learning methods consistently generated routes with higher average burial rates while requiring significantly shorter computation time compared with the A* algorithm. These findings suggest that reinforcement learning, when coupled with environmental modeling, provides a practical and scalable strategy for improving the effectiveness, concealment, and autonomy of naval mine-laying operations. Full article

A state and fault estimator is designed in this paper for nonlinear complex networks using binary encoding schemes subject to parameter uncertainties, randomly switching couplings, randomly occurring deception attacks and bounded stochastic noises. A Markov chain is employed to reflect the randomly switching phenomena of topological structures (or outer coupling strengths) and internal coupling strengths in complex networks. Binary encoding scheme is utilized to adjust the measurement signal transmission, where the signal is quantized and encoded into a binary bit string which is transmitted via a binary symmetric channel. Random bit flipping resulted from channel noises and randomly occurring deception attacks launched by hacker may take place inevitably during the network transmission process, whose occurrences are represented by two sequences of Bernoulli distributed random variables. The influence of random bit flipping is viewed as an equivalent stochastic noise, which facilitates the estimator design afterwards. The malicious signal is characterized by a nonlinear function satisfying an inequality constraint condition. The received binary bit string is decoded and used for estimating the system state and the fault. This paper aims to design a state and fault estimator such that the estimation error dynamic system is exponentially ultimately bounded in mean square, and the ultimate upper bound is minimized. A sufficient condition is put forth that ensures the existence of the expected state and fault estimator via adopting statistical property analysis, Lyapunov stability theory and matrix inequality technique. An exponentially ultimately bounded state and fault estimator in mean square is designed for such a kind of complex networks using the matrix inequality method. The estimator gain parameter is readily obtained by tackling an optimization issue subject to matrix inequalities constraints using Matlab software. Finally, two simulation examples are carried on which validate the effectiveness of the proposed state and fault estimation approach. The work in this paper plays a role in enriching the research system of estimation for complex network, and providing theoretical guidance for engineering applications. Full article

Tethered aerostats serve as critical platforms for aerial observation and communication; however, research on their lateral stability under varying wind conditions remains limited. In this study, a comprehensive approach combining dynamic modeling and computational fluid dynamics (CFD) simulations is employed to systematically analyze the lateral dynamic characteristics of an inverted Y-tail tethered aerostat. A nonlinear lateral dynamic model incorporating aerodynamic effects and added inertial terms is developed, and transient CFD simulations are conducted to examine the system’s dynamic responses under different wind directions and wind speeds. The study particularly evaluates the influence of key parameters such as payload position and the main tether point configuration. The results indicate that optimizing payload distribution can significantly enhance stability, manifested by reductions in yaw peaks and roll oscillation amplitudes. Furthermore, it is found that the yaw motion is more sensitive to wind-direction variations, while the roll motion is influenced by the coupled effects of both wind speed and direction. This research provides a valuable theoretical basis and a validated simulation framework for improving the structural design and operational stability of tethered aerostat systems in realistic wind environments. Full article

Designing cost-effective, reliable diagnostic sensor suites for complex assets remains challenging due to conflicting objectives across stakeholders. A holistic framework that integrates the Normalised Diagnostic Contribution Index (NDCI)—which scores sensors by separation power, severity sensitivity, and uniqueness—with a Multi-Objective Sensor Optimisation Framework (MOSOF) is presented. Using a high-fidelity virtual aircraft model coupling engine, fuel, electrical power system (EPS), and environmental control system (ECS), NDCI against minimum Redundancy-maximum Relevance (mRMR) is benchmarked under a rigorous nested cross-validation protocol. Across subsystems, NDCI yields more compact suites and higher diagnostic accuracy, notably for engine (88.6% vs. 69.0%) and ECS (67.7% vs. 52.0%). Then, a multi-objective optimisation reflecting an airline use-case (diagnostic performance, cost, reliability, and benefit-to-cost) is executed, identifying a practical Pareto-optimal ‘knee’ solution comprising 12–14 sensors. The recommended suite delivers a normalised performance of ≈0.69 at ≈USD36k with ≈145 kh MTBF, balancing the cross-subsystem information value with implementation constraints. The NDCI-MOSOF workflow provides a transparent, reproducible pathway from raw multi-sensor data to stakeholder-aware design decisions, and constitutes transferable evidence for model-based safety and certification processes in Integrated Vehicle Health Management (IVHM). The limitations (simulation bias, cost/MTBF estimates), validation on rigs or in-service fleets, and extensions to prognostics objectives are discussed. Full article

The rapid proliferation of connected and autonomous vehicles in the 6G era demands ultra-reliable and low-latency computation with intelligent resource coordination. Unmanned Aerial Vehicle (UAV)-assisted Mobile Edge Computing (MEC) provides a flexible and scalable solution to extend coverage and enhance offloading efficiency for dynamic Internet of Vehicles (IoV) environments. However, jointly optimizing task latency, user fairness, and service priority under time-varying channel conditions remains a fundamental challenge.To address this issue, this paper proposes a novel Multi-Agent Priority-based Fairness Adaptive Delayed Deep Deterministic Policy Gradient (MA-PF-AD3PG) algorithm for UAV-assisted MEC systems. An occlusion-aware dynamic deadline model is first established to capture real-time link blockage and channel fading. Based on this model, a priority–fairness coupled optimization framework is formulated to jointly minimize overall latency and balance service fairness across heterogeneous vehicular tasks. To efficiently solve this NP-hard problem, the proposed MA-PF-AD3PG integrates fairness-aware service preprocessing and an adaptive delayed update mechanism within a multi-agent deep reinforcement learning structure, enabling decentralized yet coordinated UAV decision-making. Extensive simulations demonstrate that MA-PF-AD3PG achieves superior convergence stability, 13–57% higher total rewards, up to 46% lower delay, and nearly perfect fairness compared with state-of-the-art Deep Reinforcement Learning (DRL) and heuristic methods. Full article

A complex operating environment poses significant challenges to the design of ramjet combustion chambers as high-enthalpy wind tunnels and their associated high-temperature, high-pressure combustion chambers continue to advance. This study developed a thermal–fluid–structure coupling finite element (FE) model based on the computational fluid dynamics (CFD) numerical simulation method to simulate the service conditions of combustion chambers under varying structures. Subsequently, FE simulation results were used to study the influences of combustion chamber structure on fluid flow characteristics, variation in cooling water pressure, temperature and stress of a combustion chamber wall. The results showed that after cooling water entered the chamber as a stable jet, it impacted the wall surface and formed a bidirectional vortex flow, which then entered the cooling water channels. Modifying the slope of a cooling water channel can effectively reduce pressure within the combustion chamber. It is noteworthy that the inlet equivalent stress of a combustion chamber decreases with an increasing slope, whereas outlet equivalent stress increases correspondingly. Finally, through comprehensive analysis, the optimal slope of a cooling water channel was determined to be 0.3°. This work provides essential theoretical insights for optimizing the design of combustion chambers. Full article

High penetration of renewable energy sources (RES) in power systems introduces substantial source-load uncertainty and flexibility challenges, leading to misalignments between economic optimization and environmental sustainability. An edge-side electricity-carbon coordinated hybrid trading mechanism was proposed to enhance flexibility in microgrid clusters. A three-layer time-varying carbon emission factor (CEF) model is developed to quantify negative emissions as tradable Chinese Certified Emission Reductions (CCERs). An endogenous economic equilibrium point enables dynamic switching between Incentive-Based Demand Response during high-carbon periods and Price-Based Demand Response during low-carbon periods, based on marginal profit comparisons. A Wasserstein distance-based distributionally robust CVaR (WDR-CVaR) strategy constructs a data-driven ambiguity set to optimize decisions under worst-case distributional shifts in edge-side data. Simulations on a modified IEEE 33-bus system show that the mechanism increases the Multi-Energy Aggregator’s (MEA) expected profit by 12.3%, reduces carbon emissions by 17.6%, with WDR-CVaR demonstrating superior out-of-sample performance compared to sample average approximation methods. The approach internalizes environmental values through carbon-electricity coupling and edge intelligence, providing a resilient framework for low-carbon distribution network operations. Full article

The strong vibration excited by the tank-liquid sloshing of the field sprayer can result in uneven spraying, vehicle-body cartwheel, and the break of the boom during running process. So, it is crucial to investigate the stability of a field-sprayer boom under hazardous operating conditions on a specified ground surface, focusing on the coupled effects of tank-liquid sloshing, boom-connection stiffness, and nozzle jetting-force characteristics. A fluid–structure interaction framework combining volume of fluid (VOF)-based sloshing simulation, finite element modeling, and full-scale experiments is developed. It is shown that high liquid-filling ratios significantly amplify transient sloshing forces during braking and swerving, inducing strong direction-dependent boom vibrations and a distinct resonance band near 50–60 Hz. Increasing connection stiffness raises natural frequencies and reduces damping, thereby enlarging vibration amplitudes. The jetting-force amplitude attenuates X-direction vibration, while frequency variation produces notable resonance excitation aligned with the harmonics of the boom. Simulation and experimental results demonstrate strong consistency, validating the proposed model. The findings reveal key coupling mechanisms governing boom stability and provide practical guidance for structural optimization and vibration suppression in field sprayers. Full article

Microwave, millimeter-wave, and terahertz devices are fundamental to modern 5G/6G communications, automotive imaging radar, and sensing systems. As essential RF front-end elements, passive microwave array components on static platforms remain constrained by fixed geometry and single-frequency excitation, leading to limited spatial resolution and weak interference suppression. Phase-steered arrays offer angular control but lack range-dependent response, preventing true two-dimensional focusing. Frequency-Diverse Array Multiple-Input Multiple-Output (FDA-MIMO) architectures introduce element-wise frequency offsets to enrich spatial–spectral degrees of freedom, yet conventional linear or predetermined nonlinear offsets cause range–angle coupling, periodic lobes, and restricted beamforming flexibility. Existing optimization strategies also tend to target single objectives and insufficiently address target- or scene-induced perturbations. This work proposes a nonlinear frequency-offset design for passive microwave arrays using a Dingo–Gray Wolf hybrid intelligent optimizer. A multi-metric fitness function simultaneously enforces sidelobe suppression, null shaping, and frequency-offset smoothness. Simulations in static scenarios show that the method achieves high-resolution two-dimensional focusing, enhanced interference suppression, and stable performance under realistic spatial–spectral mismatches. The results demonstrate an effective approach for improving the controllability and robustness of passive microwave array components on static platforms. Full article

The purpose of this study is to investigate the buckling behavior and failure mechanism of the boom of large-scale elevating jet fire trucks, so as to provide support for its safety design and service life improvement. In terms of research methods, a combination of double-version control tests and refined finite element simulations was adopted to carry out a systematic study. The research results show that the boom base plate exhibits typical sinusoidal wave buckling deformation when the load coefficient is between 0.45 and 0.5, and the wavelength is highly consistent with the theoretical prediction; under the critical load, the strain amplitude shows a significant nonlinear jump, which confirms the buckling mechanism of the coupling between geometric nonlinearity and material plasticity; under the ultimate load, the structure undergoes local buckling failure, the failure location is in good agreement with the simulation prediction, and the test results are highly consistent with the simulation results within the engineering allowable range, which verifies the reliability and applicability of the model. The research conclusion is the establishment of evaluation criteria for buckling failure of box-type knuckle arms: visible buckling waves appear, and the strain exceeds 40%. Based on this conclusion, optimizing the width-thickness ratio of the plate, strengthening the web constraint and improving the manufacturing process can effectively enhance the anti-buckling performance of the thin-walled box structure. Full article

Current research on the vibration characteristics of fastener clips primarily employs modal experiments combined with finite element simulations; however, limited attention has been given to the dynamic vibration behavior of clips during actual train operations. This study investigates both the quasi-static and dynamic vibration characteristics using an integrated approach of finite element simulation and dynamic testing. Based on the Vossloh W300-1 fastener system, a three-dimensional model is established. Modal and frequency response analyses, together with field test validation, reveal two significant vibration modes within 0–1000 Hz: a first-order mode at 500 Hz and a second-order mode at 560 Hz. These modes are characterized by vertical overturning of the clip arm. Dynamic testing demonstrates that the dominant frequency of the arm acceleration is strongly correlated with the second-order natural frequency, confirming that wheel–rail excitation readily triggers second-order mode resonance. The study further shows that, at train speeds of 200–350 km/h, rail corrugation with wavelengths of 99.2–173.6 mm induces high-frequency excitation at 560 Hz, resulting in resonance fatigue of the clip. As a mitigation measure, regular rail grinding is recommended to eliminate corrugation at critical wavelengths. Additionally, optimizing the clip structure to avoid resonance frequency bands is proposed. These findings elucidate the coupling mechanism between the vibration characteristics of the clip and dynamic loads, providing theoretical support for the safety evaluation of high-speed rail fastener systems and the vibration-resistant design of clips. Full article

The dynamics of gas–liquid two-phase flow at fracture junctions are crucial for optimizing fluid transport in the complex fracture networks of coal seams, particularly for coalbed methane (CBM) extraction and gas hazard management. This study presents a comprehensive numerical investigation of transient air–water flow in a two-dimensional, symmetric, cross-shaped fracture junction. Using the Volume of Fluid (VOF) model coupled with the SST k-ω turbulence model, the simulations accurately capture phase interface evolution, accounting for surface tension and a 50° contact angle. The effects of inlet velocity (0.2 to 5.0 m/s) on flow patterns, pressure distribution, and energy dissipation are systematically analyzed. Three distinct phenomenological flow regimes are identified based on interface morphology and force balance: an inertia-dominated high-speed impinging flow (Re > 4000), a moderate-speed transitional flow characterized by a dynamic balance between inertial and viscous forces (∼1000 < Re < ∼4000), and a viscous-gravity dominated low-speed creeping filling flow (Re < ∼1000). Flow partitioning at the junction—defined as the quantitative split of the total inflow between the main (straight-through) flow path and the deflected (lateral) paths—exhibits a strong dependence on the Reynolds number. The main flow ratio increases dramatically from approximately 30% at Re ∼ 500 to over 95% at Re ∼ 12,000, while the deflected flow ratio correspondingly decreases. Furthermore, the pressure loss (head loss, ΔH) across the junction increases non-linearly, following a quadratic scaling relationship with the inlet velocity (ΔH ∝ V₀^1.95), indicating that energy dissipation is predominantly governed by inertial effects. These findings provide fundamental, quantitative insights into two-phase flow behavior at fracture intersections and offer data-driven guidance for optimizing injection strategies in CBM engineering. Full article

Hazardous gas detection requires portable, low-power sensors with high sensitivity, where micro-heater design is critical for semiconductor metal oxide (SMO) sensors. This study presents a standardized evaluation framework for quantitatively comparing patterned micro-heaters under equal-power conditions, ensuring objective comparison across geometries. Two key metrics—power efficiency and temperature uniformity—were defined, normalized, and integrated into a single optimal score through weighted summation. The framework was validated through coupled electro-thermal simulations and experiments on six geometries, including spiral and meander patterns. Results demonstrated that the framework enables accurate identification of designs combining low power consumption with high temperature uniformity. Notably, the meander-based design showed superior efficiency and uniformity, demonstrating its suitability for practical applications. This framework thus offers a rational tool for micro-heater design, supporting the development of reliable, energy-efficient devices for portable and Internet of Things (IoT) applications. Full article

At present, the continuous growth of renewable energy integration and power grid load demand has placed higher requirements on the transmission capacity and power flow control capability of power systems. Owing to its flexible and controllable power flow characteristics, DC transmission technology has been introduced into AC grid structures, making AC/DC hybrid power grids an important development trend. However, the increasingly prominent power flow security issues caused by the complex coupling characteristics between AC and DC systems pose new challenges. First, this paper conducts an in-depth analysis of the operating mechanisms and power flow coupling characteristics of AC/DC hybrid transmission sections under various operating conditions. To address the dual challenges of insufficient utilization of transmission capacity and power flow security, a novel AC-like AC/DC power flow coordinated optimization strategy is proposed. Based on phase angle coordinated control, the autonomous response capability of the DC system is leveraged to perform real-time control and optimization of transmission power on lines, maximizing the capacity utilization of AC/DC hybrid transmission section while satisfying security and stability requirements. Finally, simulation studies based on a transmission network containing two four-machine AC systems verify that the proposed strategy fully meets the security and stability requirements of AC/DC hybrid power grids, providing reliable technical support for the coordinated development of future AC/DC grids. Full article