Search Results (313)

The novel enhanced dynamic game method (EDGM) is proposed to advance game-based design approaches, with a focus on enhancing solution distribution, precision, and the ability to reveal the dynamic influence sensitivity of design variables on objective functions. An integrated mathematical model is developed by combining EDGM with PARSEC and CST parameterization methods, forming a systematic framework for offshore wind turbine airfoil optimization. Targeting airfoils with approximately 30% and 35% thickness, the study aims to improve annual energy production (AEP) and optimize the polar moment of inertia. Redesigned airfoils using the EDGM-integrated model exhibit significant enhancements in aerodynamic performance and anti-flutter capability compared to baseline airfoils DU97W300 and DU99W350. The methodology’s superiority is validated through analyses of pressure distributions, lift-to-drag ratios, and streamline patterns, as well as comparative evaluations using HV and Spacing metrics, demonstrating EDGM’s potential for broader engineering applications in complex multi-objective optimization scenarios. Full article

The quality of foundation pile is greatly influenced by human factors, and quality assessment is delayed. This paper introduces a new evaluation system based on Internet of Things (IoT) monitoring data of the foundation pile construction process. First, an IoT monitoring system of foundation pile construction process quality is established to monitor the key parameters for quality control in the foundation pile construction process, such as pile length, position, verticality, water–cement ratio, grouting volume, drilling/lifting speed, etc. Next, the absolute gray relational degree analysis method and the analytic hierarchy process (AHP) entropy-weighted combination weighting method are used to divide the monitoring data into different levels and determine the weight coefficients for quality indicators during foundation pile construction. Last, the IoT monitoring and evaluation system of the foundation piles construction process quality is applied to engineering. The results indicate that the monitoring system is convenient and efficient, and the quality evaluation method is reliable. The construction process quality of cement-mixing piles is rated as excellent. The construction process quality of bored piles Z0103 and Z0232 is excellent, and pile Z0012 is qualified. Full article

This study focuses on the optimization of valve assemblies in downhole rod pumping units (DRPUs), which remain the predominant artificial lift technology in oil production worldwide. The research addresses the critical issue of premature failures in DRPUs caused by leakage in valve pairs, i.e., a problem that accounts for approximately 15% of all failures, as identified in a statistical analysis of the 2022 operational data from the Uzen oilfield in Kazakhstan. The leakage is primarily attributed to the accumulation of mechanical impurities and paraffin deposits between the valve ball and seat, leading to concentrated surface wear and compromised sealing. To mitigate this issue, a novel valve assembly design was developed featuring a flow turbulizer positioned beneath the valve seat. The turbulizer generates controlled vortex motion in the fluid flow, which increases the rotational frequency of the valve ball during operation. This motion promotes more uniform wear across the contact surfaces and reduces the risk of localized degradation. The turbulizers were manufactured using additive FDM technology, and several design variants were tested in a full-scale laboratory setup simulating downhole conditions. Experimental results revealed that the most effective configuration was a spiral plate turbulizer with a 7.5 mm width, installed without axis deviation from the vertical, which achieved the highest ball rotation frequency and enhanced lapping effect between the ball and the seat. Subsequent field trials using valves with duralumin-based turbulizers demonstrated increased operational lifespans compared to standard valves, confirming the viability of the proposed solution. However, cases of abrasive wear were observed under conditions of high mechanical impurity concentration, indicating the need for more durable materials. To address this, the study recommends transitioning to 316 L stainless steel for turbulizer fabrication due to its superior tensile strength, corrosion resistance, and wear resistance. Implementing this design improvement can significantly reduce maintenance intervals, improve pump reliability, and lower operating costs in mature oilfields with high water cut and solid content. The findings of this research contribute to the broader efforts in petroleum engineering to enhance the longevity and performance of artificial lift systems through targeted mechanical design improvements and material innovation. Full article

Rail transit as a high-energy consumption field urgently requires the adoption of clean energy innovations to reduce energy consumption and accelerate the transition to new energy applications. As an energy-saving fluid machinery, the ejector exhibits significant application potential and academic value within this field. This paper reviewed the recent advances, technical challenges, research hotspots, and future development directions of ejector applications in rail transit, aiming to address gaps in existing reviews. (1) In waste heat recovery, exhaust heat is utilized for propulsion in vehicle ejector refrigeration air conditioning systems, resulting in energy consumption being reduced by 12~17%. (2) In vehicle pneumatic pressure reduction systems, the throttle valve is replaced with an ejector, leading to an output power increase of more than 13% and providing support for zero-emission new energy vehicle applications. (3) In hydrogen supply systems, hydrogen recirculation efficiency exceeding 68.5% is achieved in fuel cells using multi-nozzle ejector technology. (4) Ejector-based active flow control enables precise ± 20 N dynamic pantograph lift adjustment at 300 km/h. However, current research still faces challenges including the tendency toward subcritical mode in fixed geometry ejectors under variable operating conditions, scarcity of application data for global warming potential refrigerants, insufficient stability of hydrogen recycling under wide power output ranges, and thermodynamic irreversibility causing turbulence loss. To address these issues, future efforts should focus on developing dynamic intelligent control technology based on machine learning, designing adjustable nozzles and other structural innovations, optimizing multi-system efficiency through hybrid architectures, and investigating global warming potential refrigerants. These strategies will facilitate the evolution of ejector technology toward greater intelligence and efficiency, thereby supporting the green transformation and energy conservation objectives of rail transit. Full article

This study examines pantograph aerodynamic lift at 400 km/h, and uncovers the dynamic behaviors and mechanisms that influence pantograph–catenary performance. Using computational fluid dynamics (CFD) with a compressible fluid model and an SST k-ω turbulence model, aerodynamic characteristics were analyzed. Simulation data at 300, 350, and 400 km/h showed lift fluctuation amplitude increases with speed, peaking near 50 N at 400 km/h. Power spectral density (PSD) energy, dominated by low frequencies, peaked around 10 dB/Hz in the low-frequency band, highlighting exacerbated lift instability. Component analysis revealed the smallest lift-to-drag ratio and most significant fluctuations at the head, primarily due to boundary-layer separation and vortex shedding from its non-streamlined design. Turbulence energy analysis identified the head and base as main turbulence sources; however, base vibrations are absorbed by the vehicle body, while the head causes pantograph–catenary vibrations due to direct contact. These findings confirm that aerodynamic instability at the head is the main cause of contact force fluctuations. Optimizing head design is necessary to suppress fluctuations, ensuring safe operation at 400 km/h and above. Results provide a theoretical foundation for aerodynamic optimization and improved dynamic performance of high-speed pantographs. Full article

Reliable aerodynamic performance estimation is essential for both preliminary design and optimization in various aeronautical applications. In this study, a hybrid deep learning model is proposed, combining convolutional neural networks (CNNs) and operating directly on raw airfoil geometry, with parallel branches of fully connected deep neural networks (DNNs) that process operational parameters and engineered features. The model is trained on an extensive database of NACA four-digit airfoils, covering angles of attack ranging from −5° to 14° and ten Reynolds numbers increasing in steps of 500,000 from 500,000 up to 5,000,000. As a novel contribution, this work investigates the impact of random seed initialization on model accuracy and reproducibility and introduces a seed-based ensemble strategy to enhance generalization. The best-performing single-seed model tested (seed 0) achieves a mean absolute percentage error (MAPE) of 1.1% with an ${\mathrm{R}}^2$ of 0.9998 for the lift coefficient prediction and 0.57% with an ${\mathrm{R}}^2$ of 0.9954 for the drag coefficient prediction. In comparison, the best ensemble model tested (seeds 610, 987, and 75025) achieves a lift coefficient MAPE of 1.43%, corresponding to ${\mathrm{R}}^2$ 0.9999, and a drag coefficient MAPE of 1.19%, corresponding to ${\mathrm{R}}^2$ = 0.9968. All the tested seed dependencies in this paper (ten single seeds and five ensembles) demonstrate an overall ${\mathrm{R}}^2$ greater than 0.97, which reflects the model architecture’s strong foundation. The novelty of this study lies in the demonstration that the same machine learning model, trained on identical data and architecture, can exhibit up to 250% variation in prediction error solely due to differences in random seed selection. This finding highlights the often-overlooked impact of seed initialization on model performance and highlights the necessity of treating seed choice as an active design parameter in ML aerodynamic predictions. Full article

This article provides an in-depth review of selected technical chains, with particular emphasis on link chains and their load transmission mechanisms. It explores structural and functional characteristics, highlighting how chain geometry affects stress distribution, fatigue life, and performance under various loading conditions. The study includes a detailed classification of chains by type, material, and application, ranging from steel-based lifting and transport chains to lightweight, corrosion-resistant polymer types. Manufacturing methods and connection techniques are also discussed, underscoring the importance of proper assembly for mechanical reliability. Special attention is given to the role of materials, particularly the emergence of polymer composites reinforced with glass or carbon fibers, which offer promising alternatives to conventional metals. Although such composites exhibit advantageous properties—such as low weight, corrosion resistance, and energy efficiency—their application remains limited, insufficient load-bearing capacity, and the absence of standardized design guidelines. The review identifies critical knowledge gaps in the field, especially concerning shaping, dimensioning, and normative requirements for polymer-based load-bearing chains. It also highlights the lack of focused research on chain-specific geometries and the need for numerical simulations to optimize link design. The article concludes by emphasizing the importance of developing sustainable, durable, and standardized chain systems—particularly those utilizing recycled or novel materials—to meet both technical demands and environmental goals. This work supports future innovation in the design of advanced chain structures and provides a foundation for expanding the use of high-performance composites in civil and urban engineering applications. Full article

The translation of motion lift, as an important performance metric of a reversing six-link loader working device, is influenced by multiple factors, such as the mechanical structure, system components, and operational experience. To ensure that the loader’s motion lift performance is optimized, this paper takes the fork trajectory and the horizontal angle between the bucket cylinder and the ground as the main optimization objectives. Kinematic modeling and multi-objective optimization are conducted to reduce the influence of external factors on the motion lift process. Firstly, a parametric model of the reversing six-link mechanism is established based on its geometric and symmetric characteristics, and the expressions for the fork’s motion trajectory and the cylinder–ground angle are derived. Then, an optimization model is constructed with the aim of minimizing both the translational error during fork lifting and the horizontal angle of the bucket cylinder. An improved multi-objective genetic algorithm is employed for the global search and optimization. Inspired by the principle of symmetry, the algorithm incorporates a structured search strategy that enhances convergence efficiency and solution balance. A multi-criteria decision function is further applied to identify the optimal solution from the Pareto front. Finally, a real-vehicle experiment validates the optimization results. The findings confirm that the proposed method significantly improves the translational performance of the fork and effectively controls the horizontal angle of the cylinder while also enhancing the driver’s visibility and coordination of the entire system. These results provide a theoretical and engineering basis for the symmetry-informed multi-objective performance optimization of loader working devices. Full article

Fuel electro-hydraulic servo valves are core components in the fuel control system of aero-engines, and their performance directly affects thrust regulation and power output precision. Due to the combustibility of the working medium in fuel systems and the lack of effective circulation filtration, the retention of micron-sized particles within the valve gap can lead to valve spool jamming, which is a critical reliability issue. This study, based on fractal theory and the liquid–solid two-phase flow model, proposes a parametric model for non-ideal surface valve gaps and analyzes the dynamics of particles subjected to drag, lift, and buoyant forces on rough surfaces. By numerically analyzing flow field models with different roughness levels and comparing them with an ideal smooth gap model, the migration characteristics of particles were studied. To verify the accuracy of the model, an upscaled experimental setup was built based on similarity theory, and PIV experiments were conducted for validation. Experimental results show that the particle release position and valve surface roughness significantly affect particle migration time. The weight of the release position on particle migration time is 63%, while the impact of valve surface roughness is 37%. In models with different roughness levels, the particle migration time increases more rapidly for roughness values greater than Ra0.4, while for values less than Ra0.4, the increase in migration time is slower. Furthermore, the study reveals that particle migration trajectories are independent of flow velocity, with velocity only affecting particle migration time. This research provides theoretical support for enhancing the reliability of fuel electro-hydraulic servo valves and offers a new perspective for the design of highly reliable hydraulic components. Full article

Bioinspired morphing offers a powerful route to higher aerodynamic and hydrodynamic efficiency. Birds reposition feathers, bats extend compliant membrane wings, and fish modulate fin stiffness, tailoring lift, drag, and thrust in real time. To capture these advantages, engineers are developing airfoils, rotor blades, and hydrofoils that actively change shape, reducing drag, improving maneuverability, and harvesting energy from unsteady flows. This review surveys over 296 studies, with primary emphasis on literature published between 2015 and 2025, distilling four biological archetypes—avian wing morphing, bat-wing elasticity, fish-fin compliance, and tubercled marine flippers—and tracing their translation into morphing aircraft, ornithopters, rotorcraft, unmanned aerial vehicles, and tidal or wave-energy converters. We compare experimental demonstrations and numerical simulations, identify consensus performance gains (up to 30% increase in lift-to-drag ratio, 4 dB noise reduction, and 15% boost in propulsive or power-capture efficiency), and analyze materials, actuation, control strategies, certification, and durability as the main barriers to deployment. Advances in multifunctional composites, electroactive polymers, and model-based adaptive control have moved prototypes from laboratory proof-of-concept toward field testing. Continued collaboration among biology, materials science, control engineering, and fluid dynamics is essential to unlock robust, scalable morphing technologies that meet future efficiency and sustainability targets. Full article

With the global maritime industry accelerating toward carbon neutrality, the adoption of alternative marine fuels has emerged as a pivotal pathway for achieving net-zero emissions. To identify the most promising fuel transition solution for multi-purpose heavy-lift vessels (MPHLVs), which are widely used for transporting large and complex industrial equipment and have specialized structural requirements, this study conducted a comprehensive techno-economic analysis based on a fleet of 12 MPHLVs. An eight-dimensional technical adaptability framework was established, and six types of marine fuel were evaluated. Concurrently, a total cost assessment model was developed using 2024 operational data of the fleet, incorporating the fuel procurement, the carbon allowances under the EU ETS, the FuelEU Maritime compliance costs, and the IMO Net-Zero penalties. The results show that methanol as an alternative fuel is the most compatible decarbonization pathway for this specialized vessel type. A case study of a 38,000 DWT methanol-fueled MPHLV further demonstrates engineering feasibility with minimal impact on cargo capacity, and validates methanol’s potential as a technically viable and strategically transitional fuel for MPHLVs, particularly in the context of stricter international decarbonization regulations. The proposed evaluation framework and engineering application offer practical guidance for fuel selection, ship design, and retrofit planning, supporting the broader goal of accelerating low-carbon development in heavy-lift shipping sector. Full article

Aiming at the requirements of rapidity, high precision, and robustness for the longitudinal trajectory control of the receiver aircraft in autonomous aerial refueling, a direct lift control (DLC) strategy that integrates incremental nonlinear dynamic inversion (INDI) and nonlinear extended state observer (NESO) is proposed. First, a control strategy for generating direct lift through the coordinated action of the flaperons and elevators is presented, and a longitudinal dynamics model is established. Secondly, based on the INDI and DLC methods, the rapid tracking and control of altitude are achieved. Finally, an NESO is designed. The observer gains are designed through the pole placement method and the robust optimization method to achieve the estimation of states such as airspeed, angle of attack, pitch rate, and pitch angle, as well as unknown force and moment disturbances. The estimated force and moment disturbances are used to implement the active disturbance rejection control. Simulation results show that the strategy has no altitude tracking error under normal operating conditions, and the altitude tracking error is less than 0.2 m under typical disturbance conditions, indicating high control accuracy. Under disturbance conditions, the estimation errors of true airspeed, angle of attack, pitch angle, and pitch angular velocity are less than 0.3 m/s, 0.12°, 0.1°, and 0.2°/s, respectively, demonstrating the high-precision estimation capability of the observer. The NESO exhibits high accuracy in state estimation, the rudder deflection is smooth, and the anti-disturbance capability is significantly better than traditional methods, providing an engineered solution for the longitudinal control of the receiver aircraft. Full article

The cambered deflectors in aquacultural facilities are applied to enhance hydrodynamic efficiencies or enable flow fields to be fully developed. Given the anticipated improvements with the bio-inspired profiles or tandem configurations, the hydrodynamics of cambered deflectors with the above features are investigated at $Re=1\times {10}^5$. The relationship between force coefficients and local flow behaviors for both bionic and non-bionic isolated deflectors, as well as tandem deflectors, is revealed using $k-\omega$ SST simulation. The dependencies of force coefficients on gap (G), stagger (S), and inclination angles ($\theta$) in tandem deflectors are illustrated using an updated metamodeling workflow with simulated data. It is demonstrated that the variations of force coefficients over angles of attack are related to flow physics in boundary-layer regions. The non-bionic isolated deflector with the $\theta ={10}^{\circ }$ prevails as the decent performances of $C_L$ and $\gamma$ globally, which is chosen in the following studies. Regarding tandem deflectors, $\theta$ plays a more vital role in drag coefficients ($C_D$) and lift coefficients ($C_L$), while the influence of S is not quite considerable compared to G. Aiming for cost minimizations and lift improvements, an optimized tandem case is obtained and justified with the superiorities in flow fields. This study has provided novel insights into the designs and optimizations of cambered deflectors in aquacultural engineering. Full article

Deep coalbed methane wells often encounter challenges such as inefficient sand transport and sand accumulation in the horizontal sections during drainage, which significantly impact the stability of gas production and the efficiency of the gas lift system. To investigate the sand-carrying mechanisms in the horizontal sections of deep coalbed methane wells, this study develops a theoretical model for critical sand-carrying velocity based on gravitational, buoyant, drag, and pressure gradient forces. Additionally, a visualized experimental system was constructed using a multiphase pipe flow platform. By varying parameters such as liquid flow rate, gas–liquid ratio, gravel particle size, and pipe inclination, the critical conditions for sand transport were examined, and the dominant factors influencing sand transport in horizontal wellbore sections were identified. The experimental results indicate that water flow rate and particle size are inversely correlated with the gas volume required for sand transport, whereas inclination angle is positively correlated. The proposed model was validated against experimental data, showing a prediction error within 15%, thereby confirming its accuracy and engineering applicability. These findings offer theoretical guidance and technical references for efficient drainage and stable gas production in horizontal wellbore sections of deep coalbed methane wells. Full article

The rapid advancement of modern megapolises has led to a dearth of surface space, and, in response, engineers have begun to trial substitutes below ground level. Shafts are generally used to provide temporary access and permanent work to the subsurface for tunnelling, as well as for lifts or ventilation purposes. In urban areas, one important design issue is the prediction of the excavation-induced displacements by open caisson shaft construction. Settlements and ground movements associated with open caisson shafts are influenced by the choice of construction method, soil composition, and excavation geometry. Compared with other geotechnical construction events, for instance, tunnelling, the literature relating to the ground deformations induced from open caisson shafts are comparatively limited. This review offers an evaluation of several case studies that utilize experimental and computational modeling techniques to provide clearer insights into earth pressure distribution and induced surface and subsurface soil displacements, as well as the associated ground deformations during open caisson shaft construction. The modeling test results are compared to the state of the practice ground deformation prediction theories and measured results from field monitoring data. Findings indicate that the lateral earth pressure distribution aligns closely with the theoretical predictions based on Terzaghi’s and Berezantzev’s models, and lateral earth pressure diminishes gradually until the onset of active wall displacement. Current modeling techniques generally fail to properly represent in situ stress states and large-scale complexities, emphasizing the need for hybrid approaches that combine physical and numerical methodologies. In future studies, modern approaches, including artificial intelligence (AI) monitoring (e.g., PINNs, ACPP), multi-field coupling models (e.g., THMC), and transparent soil testing, hold profound potential for real-time prediction, optimization, and visualization of soil deformation. Numerical–physical coupling tests will integrate theory and practice. Improving prediction reliability in complicated soil conditions such as composite and heterogenous strata using different modeling techniques is still unclear, and further investigation is therefore needed. Full article