Search Results (43)

This study proposes an iterative method based on thermal equilibrium equations to calculate the radial temperature distribution of long-span overhead transmission lines under forced convection. This paper takes the ACSR 500/280 conductor as the research object, establishes the three-dimensional finite element model considering the helix angle of the conductor, and carries out the experimental validation for the LGJ 300/40 conductor under the same conditions. The model captures internal temperature distribution through contour analysis and examines the effects of current, wind speed, and ambient temperature. Unlike traditional models assuming uniform conductor temperature, this method reveals internal thermal gradients and introduces a novel three-stage radial attenuation characterization. The iterative method converges and accurately reflects temperature variations. The results show a non-uniform radial distribution, with a maximum temperature difference of 8 °C and steeper gradients in aluminum than in steel. Increasing current raises temperature nonlinearly, enlarging the radial difference. Higher wind speeds reduce both temperature and radial difference, while rising ambient temperatures increase conductor temperature with a stable radial profile. This work provides valuable insights for the safe operation and optimal design of long-span transmission lines and supports future research on dynamic and environmental coupling effects. Full article

The development of solar technologies and the widespread adoption of photovoltaic (PV) panels have significantly transformed the global energy landscape. PV panels have evolved from niche applications to become a primary source of electricity generation, driven by their environmental benefits and declining costs. However, the performance and operational lifespan of PV systems are often compromised by various faults, which can lead to efficiency losses and increased maintenance costs. Consequently, effective and timely fault detection methods have become a critical focus of current research in the field. This work proposes an innovative video-based method for the dimensional evaluation and detection of malfunctions in solar panels, utilizing processing techniques applied to aerial images captured by unmanned aerial vehicles (drones). The method is based on a novel mini-pattern matching algorithm designed to identify specific defect features despite challenging environmental conditions such as strong gradients of non-uniform lighting, partial shading effects, or the presence of accidental deposits that obscure panel surfaces. The proposed approach aims to enhance the accuracy and reliability of fault detection, enabling more efficient monitoring and maintenance of PV installations. Full article

Lithium-ion batteries (LIBs), crucial in modern advanced energy storage systems, inherently experience several side reactions during operation, with the formation of a solid electrolyte interface (SEI) and lithium plating being the most significant. These side reactions, which deplete lithium ions and lead to the clogging of negative electrode pores, considerably impair the battery’s cycle life and overall performance. This study introduces a numerical model for the battery aging process, grounded in existing research on SEI formation and its temperature-dependent aging kinetics. The model aims to elucidate how variations in the porosity of the negative electrode impact the battery’s cycle life. The study initially focuses on analyzing the principal mechanisms behind pore clogging in LIBs’ negative electrodes following extensive charge/discharge cycles. Subsequently, the study conducts numerical simulations to thoroughly investigate the effects of various non-uniform porosity structures in the negative electrode, encompassing both linear and gradient configurations, on the battery’s cycle life. Additionally, the investigation conducts a comparative analysis to determine how different gradients in porosity structures influence pore clogging. It also delves into a detailed exploration of heat generation associated with the linear porosity structure of the negative electrode. The results indicate that the accumulation of the SEI layer significantly reduces porosity. This reduction, in turn, affects the conductivity and alters the current density during the SEI reaction. Notably, the linear porosity structure exhibits a significant advantage over traditional structures, especially in terms of reducing pore clogging and minimizing irreversible heat generation. In summary, this study presents a multi-physics and detailed numerical model to evaluate the impact of variations in negative electrode porosity on the cycle life of LIBs. Furthermore, it provides essential theoretical support for battery design and performance optimization, particularly in the determination of pore structures and material selection. Full article

This paper presents a comprehensive analytical framework for investigating loss mechanisms and thermal behavior in high-speed magnetic field-modulated motors for flywheel energy storage systems. Through systematic classification of electromagnetic, mechanical, and additional losses, we reveal that modulator components constitute approximately 45% of total system losses at rated speed. Finite element analysis demonstrates significant spatial non-uniformity in loss distribution, with peak loss densities of 5.5 × 10⁵ W/m³ occurring in the modulator region, while end-region losses exceed central-region values by 42% due to three-dimensional field effects. Our optimized design, implementing composite rotor structures, dual-material permanent magnets, and integrated thermal management solutions, achieves a 43.2% reduction in total electromagnetic losses, with permanent magnet eddy current losses decreasing by 68.7%. The maximum temperature hotspots decrease from 143 °C to 98 °C under identical operating conditions, with temperature gradients reduced by 58%. Peak efficiency increases from 92.3% to 95.8%, with the η > 90% region expanding by 42% in the speed–torque plane. Experimental validation confirms model accuracy with mean absolute percentage errors below 4.2%. The optimized design demonstrates 24.8% faster response times during charging transients while maintaining 41.7% smaller speed oscillations during sudden load changes. These quantitative improvements address critical limitations in existing systems, providing a viable pathway toward high-reliability, grid-scale energy storage solutions with extended operational lifetimes and improved round-trip efficiency. Full article

Three-dimensional ocean observation is the foundation for accurately predicting ocean information. Although ocean observation sensor arrays can obtain internal data, their deployment is difficult, costly, and prone to component failures and environmental noise, resulting in discontinuous data. To address the severe missing data problem in three-dimensional ocean flow fields, this paper proposes an unsupervised model: Three-dimensional Spatio-Temporal Slim Weighted Generative Adversarial Imputation Network (3D-STA-SWGAIN). This method integrates spatio-temporal attention mechanisms and Wasserstein constraints. The generator captures the three-dimensional spatial distribution and vertical profile dynamic patterns through the spatio-temporal attention module, while the discriminator introduces gradient penalty constraints to prevent gradient vanishing. The generator strives to generate data that conforms to the real ocean flow field, and the discriminator attempts to identify pseudo-ocean current data samples. Through the adversarial training of the generator and the discriminator, high-quality completed data are generated. Additionally, a spatio-temporal continuity loss function is designed to ensure the physical rationality of the data. Experiments show that on the three-dimensional flow field dataset of the South China Sea, compared with methods such as GAIN, under a 50% random missing rate, this method reduces the error by 37.2%. It effectively solves the problem that traditional interpolation methods have difficulty handling non-uniform missing and spatio-temporal correlations and maintains the spatio-temporal continuity of the current field’s three-dimensional structure. Full article

Proton exchange membrane fuel cells (PEMFCs), recognized as promising sources of waste heat for space heating, domestic hot water supply, and industrial thermal applications, have garnered substantial interest owing to their environmentally benign operation and high energy conversion efficiency. Since the uniformity of oxygen diffusion toward catalytic layers critically governs electrochemical performance, this study establishes a three-dimensional, non-isothermal computational fluid dynamics (CFD) model to systematically optimize the cathode flow channel width distribution, targeting the maximization of power output through enhanced reactant homogeneity. Numerical results reveal that non-uniform flow channel geometries markedly improve oxygen distribution uniformity, reducing the flow inhomogeneity coefficient by 6.6% while elevating maximum power density and limiting current density by 9.1% and 7.8%, respectively, compared to conventional equal-width designs. There were improvements attributed to the establishment of longitudinal oxygen concentration gradients and we alleviated mass transfer limitations. Synergistic integration with gas diffusion layer (GDL) gradient porosity optimization further amplifies performance, yielding a 12.4% enhancement in maximum power density and a 10.4% increase in limiting current density. These findings validate the algorithm’s efficacy in resolving coupled transport constraints and underscore the necessity of multi-component optimization for advancing PEMFC design. Full article

Premature seal failure induced by the unevenness of interstage pressure distribution in multi-stage brush seals significantly compromises the sealing efficiency of Air-Turbo Rocket (ATR) engines operating under high-pressure (megapascal-level) differential conditions. Conventional pressure equalization designs for such seals often result in significant leakage rate increases. This study addresses the pressure imbalance phenomenon in four-tooth three-stage brush composite seals through a novel fractal–geometric porous-media model, rigorously validated against experimental data. Systematic investigations were conducted to elucidate the effects of structural parameters and operational conditions on both sealing performance and pressure distribution characteristics. Key findings reveal that, under the prototype structure parameter, the first-, second-, and third-stage brush bundles account for 18.3%, 30.0%, and 43.3% of the total pressure drop, respectively, with grate teeth contributing 8.4%, demonstrating an inherent pressure imbalance. Axial brush spacing exhibits a minimal impact on the pressure distribution, while the gradient thickness settings of the brush bundles show limited influence. Radial clearance optimization and gradient backplate height adjustment effectively regulate pressure distribution, albeit with associated leakage rate increases. Structural modifications based on these principles achieved only a 5.8% leakage increment while reducing the maximum bundle pressure drop by 23%, demonstrating effective pressure balancing. A simplified analysis of entropy reveals that the fundamental mechanism governing the pressure imbalance stems from non-uniform entropy generation caused by aerodynamic damping dissipation across sequential brush stages. These findings establish a dampened dissipation-based theoretical framework for designing high-performance multistage brush seals in aerospace applications, providing critical insights for achieving an optimal balance between leakage control and pressure equalization in extreme-pressure environments. Full article

In recent years, non-pneumatic tires have been gaining popularity, which can be seen in the increase in research results and proposals from world-class tire manufacturers (mainly as technology demonstrators). The possibility of eliminating the need to maintain compressed air is a major factor in the development of non-pneumatic tires and their usage in vehicles. Articles and patents were reviewed in relation to the load transfer mechanism, the design of non-pneumatic tire components, and recommendations for materials. Non-pneumatic tire top loaders are a desirable type of this type of wheel compared to bottom loaders, because they transfer loads over a larger part of the wheel, which increases their load capacity. Most non-pneumatic tires consist of a rim, an elastic structure, and a shear beam/band with a tread. The rim is used to secure the elastic structure and can be fitted with vibration dampers in the form of circumferential rubber rings. The gradient elastic structure, in comparison with the homogeneous structure (same thickness or dimensions of the elements), allows the range of axle displacements to be adjusted to the desired level without the need to increase the size of the wheel, and also influences the change in the location of the maximum stresses. The shear beam/ band mimics the properties of compressed air used in pneumatic tires. The shear beam/ band made as a webbing geometry ensures uniform pressure in the contact patch. The reinforced composite shear beam/ band ensures adequate bending strength with low energy losses and a small thickness of the beam/ band. Materials commonly used in the tire industry are used as reinforcement for the shear beam/ band, which was illustrated by the results of our own research. Full article

Ground-based cloud image features high-spatiotemporal resolution, presenting detailed local cloud structures and valuable weather information, which are crucial for meteorological forecasting. However, the inherent fuzziness and dynamism of ground-based clouds have hindered the development of effective prediction algorithms, resulting in low accuracy. This paper presents CloudPredRNN++, a novel method for predicting ground-based cloud dynamics, leveraging a deep spatiotemporal sequence prediction network enhanced with a self-attention mechanism. Initially, a Cascaded Causal LSTM (CCLSTM) with a dual-memory group decoupling structure is designed to enhance the representation of short-term cloud changes. Next, self-attention memory units are incorporated to capture the long-term dependencies and emphasize the non-stationary characteristics of cloud movements. These components are integrated into cloud dynamic feature mining units, which concurrently extract spatiotemporal features to strengthen unified spatiotemporal modeling. Finally, by embedding gradient highway units and adding skip connection, CloudPredRNN++ is constructed into a hierarchical recursive structure, mitigating the gradient vanishing and enhancing the uniform modeling of temporal–spatial features. Experiments on the sequence ground-based cloud dataset demonstrate that CloudPredRNN++ can predict the future cloud state more accurately and quickly. Compared with other spatiotemporal sequence prediction models, CloudPredRNN++ shows significant improvements in evaluation metrics, improving the accuracy of cloud dynamics forecasting and alleviating long-term dependency decay, thus confirming the effectiveness in ground-based cloud prediction tasks. Full article

To obtain an optimal range of structural parameters for dry-gas seals with good performance, this study employed advanced sensing technology to monitor and analyze the internal flow characteristics of dry-gas seals in real time. Additionally, the validity of the calculation program was verified through experimentation. Using steady-state performance parameters as evaluation indices, a calculation model with lubrication characteristics was developed. The results indicate that when there are 12 grooves, the gas film pressure distribution is uniform and has a high value. At pressures greater than 2 MPa, the opening force, leakage, and gas film stiffness change significantly due to enhanced dynamic pressure effects with high-pressure differences, which reduces the local contact forces and frictional forces. At a constant speed, decreasing the gas film thickness increases the pressure difference while increasing both the opening force and film stiffness; however, at higher rotational speeds where the gas flow becomes non-uniform, the stability of the gas film is affected, leading to increased frictional forces. When there are between 10 and 16 grooves with depths ranging from 5.0 to 6.0 μm, dynamic pressure effects caused by pressure gradients become apparent, resulting in good dry-gas sealing performance being achieved. This research provides a theoretical reference for optimizing the design of dry-gas seals, as well as their steady-state seal performance. Full article

Dielectrophoresis (DEP) is an advanced microfluidic manipulation technique that is based on the interaction of polarized particles with the spatial gradient of a non-uniform electric field to achieve non-contact and highly selective manipulation of particles. In recent years, DEP has made remarkable progress in the field of microfluidics, and it has gradually transitioned from laboratory-scale research to high-throughput manipulation in practical applications. This paper reviews the recent advances in dielectric manipulation and separation of microparticles and biological cells and discusses in detail the design of chip structures for the two main methods, direct current dielectrophoresis (DC-DEP) and alternating current dielectrophoresis (AC-DEP). The working principles, technical implementation details, and other improved designs of electrode-based and insulator-based chips are summarized. Functional customization of DEP systems with specific capabilities, including separation, capture, purification, aggregation, and assembly of particles and cells, is then performed. The aim of this paper is to provide new ideas for the design of novel DEP micro/nano platforms with the desired high throughput for further development in practical applications. Full article

Due to the tool-less fabrication of parts and the high degree of geometric design freedom, additive manufacturing is experiencing increasing relevance for various industrial applications. In particular, the powder bed fusion of metals using a laser beam (PBF-LB/M) process allows for the metal-based manufacturing of complex parts with high mechanical properties. However, residual stresses form during PBF-LB/M due to high thermal gradients and a non-uniform cooling. These lead to a distortion of the parts, which reduces the dimensional accuracy and increases the amount of post-processing necessary to meet the defined requirements. To predict the resulting residual stress state and distortion prior to the actual PBF-LB/M process, this paper presents the finite-element-based simulation tool AscentAM with its core module and several sub-modules. The tool is based on open-source programs and utilizes a sequentially coupled thermo-mechanical simulation, in which the significant influences of the manufacturing process are considered by their physical relations. The simulation entirely emulates the PBF-LB/M process chain including the heat treatment. In addition, algorithms for the part pre-deformation and the export of a machine-specific file format were implemented. The simulation results were verified, and an experimental validation was performed for two benchmark geometries with regard to their distortion. The application of the optimization sub-module significantly minimized the form deviation from the nominal geometry. A high level of accuracy was observed for the prediction of the distortion at different manufacturing states. The process simulation provides an important contribution to the first-time-right manufacturing of parts fabricated by the PBF-LB/M process. Full article

We propose novel spectrometer designs that aim to enhance the measured spectral range of ions on a finite-sized detector. In contrast to the traditional devices that use a uniform magnetic field, in which the deflection of particles increases inversely proportional to their momentum, in a gradient magnetic field, the deflection of particles will decrease due to the reduction of the magnetic field along their propagation. In this way, low-energy ions can reach the detector because they are deflected less, compared to the uniform field case. By utilizing a gradient magnetic field, the non-linear dispersion of ions in a homogeneous magnetic field approaches nearly linear dispersion behavior. Nonetheless, the dispersion of low-energy ions, using a dipole field, remains unnecessarily high. In this article, we discuss the employed methodology and present simulation results of the spectrometer with an extended ion spectral range, focusing on the minimum detectable energy (energy dynamic range) and energy resolution. Full article

The global issue of oil spreading in water poses a significant environmental challenge, emphasizing the critical need for the accurate determination and monitoring of oil content in aquatic environments to ensure sustainable development of the environment. However, the complexity arises from challenges such as oil dispersion, clustering, and non-uniform distribution, making it difficult to obtain real-time oil concentration data. This paper introduces a sophisticated system for acquiring induced fluorescence spectra specifically designed for the quantitative analysis of oil pollutants. The paper involved measuring the fluorescence spectra across 20 concentration gradients (ranging from 0 to 1000 mg/L) for four distinct oil samples: 92# Gasoline, Mobil Motor Oil 20w-40, Shell 10w-40 engine oil, and Soybean Oil. The research focused on establishing a relationship model between relative fluorescence intensity and concentration, determined at the optimal excitation wavelength, utilizing the segmented Random Sample Consensus (RANSAC) algorithm. Evaluation metrics, including standard addition recovery, average recovery, relative error, and average relative error, were employed to assess the accuracy of the proposed model. The experimental findings suggest that the average recovery rates for the four samples ranged between 99.61% and 101.15%, with the average relative errors falling within the range of 2.04% to 3.14%. These results underscore the accuracy and efficacy of the detection methodology presented in this paper. Importantly, this accuracy extends to scenarios involving heavier oil pollution. This paper exhibits exceptional sensitivity, enabling precise detection of diverse oil spills within the concentration range of 0~1000 mg/L in water bodies, offering valuable insights for water quality monitoring and sustainable development of the environment. Full article

Natural gas hydrate reservoirs, with shallow burial, poor cementation, and low strength, are prone to submarine landslides triggered by hydrate decomposition during extraction. Prior studies have inadequately considered factors such as the dynamic decomposition of hydrates during depressurization, and its impacts on the reservoir’s geomechanical properties. In this paper, a coupled thermal–hydraulic–mechanical–chemical mathematical model of hydrate decomposition is proposed, and the dynamic geomechanical response and the effect of hydrate decomposition on seafloor settlement and slope destabilization during the process of depressurization mining are analyzed by combining the strength discount method with the example of a hydrate-bearing seafloor slope in the Shenhu area. Furthermore, the study employs an orthogonal experimental design along with range and variance analysis to gauge the impact of critical factors (degree of hydrate decomposition, seawater depth, hydrate reservoir burial depth, hydrate reservoir thickness, and slope angle) on slope stability. The findings suggest that hydrate decomposition is non-uniform and is influenced by stratigraphic temperature gradients and gravity. In the region where hydrate decomposition occurs, the decrease of pore pressure leads to the increase of effective stress. Additionally, the decomposition of hydrates decreases the shear modulus of sediments, leading to deformation and reduced permeability in the affected area. Over a three-year period of depressurization mining, the significantly reduced safety factor increases the risk of landslides. Various factors play a role in the control of submarine slope stability, with slope inclination being the primary factor, followed by the degree of hydrate decomposition, reservoir thickness, burial depth, and seawater depth. Among these factors, hydrate burial depth and seawater depth have a positive correlation with submarine slope stability, while increases in other factors generally decrease stability. These research findings have important implications for the safe exploitation of slopes that contain hydrates. Full article