Energy Characteristics Research Articles

A hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction

Efficient and accurate wind power prediction is crucial for enhancing the reliability and safety of power system. The data-driven forecasting methods are regarded as an effective solution. However, the inherent randomness and nonlinearity of wind power systems, along with the abundance of redundant information in measurement data, present challenges to forecasting methods. The integration of precise and efficient techniques for data feature decomposition and extraction is essential in conjunction with advanced data-driven forecasting models. Focus on the seasonal variation characteristics of wind energy, a hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction is proposed. The effectiveness and superiority of the proposed method in predictive accuracy are demonstrated through comprehensive multi-model experiment comparisons.

Investigation on energy and mass distribution characteristics of granules in the composite heat exchanger

A composite heat exchanger for high-temperature granule waste heat recovery is proposed. Granular mass and energy distribution within the composite heat exchanger are simulated via the CFD-DEM coupling method. The effects of granular size, cooling gas velocity, and granular mass flow rate on granular distribution and the temperature distribution are analyzed. Results demonstrated that under the combined action of airflow impact force and gravity, the granule produces an uneven distribution in time and space. Larger granule tends to be positioned closer to the gas inlet horizontally. Along the direction from the gas inlet to the gas outlet, granules exhibit a trend of decreasing size, mass, and temperature. The influence of gas velocity predominantly affects the area coverage rate, whereas the effect of granular mass flow rate is minimal. The area coverage rate initially increases with rising gas velocity and subsequently decreases, peaking at 73.8% at 12 m/s. After the heat exchange process reached a stable state, the number of contacting granules accounted for only 0.37% of the total granules, making heat conduction between granules negligible. Convective heat transfer dominates, accounting for approximately 86.52% of the total heat exchange, while radiation heat transfer accounts for about 13.48%.

CFD analysis of turbulent flow characteristics of charge inside the combustion chamber of a dual–fuel homogeneous charge compression ignition engine under varying swirl ratios

This paper discusses the effects of the swirl ratio on the distribution of turbulent kinetic energy (TKE), combustion and emissions characteristics of a dual-fuel HCCI (Homogeneous charge compression ignition) engine fed with n-dodecane (premixed) and ethanol (injection). The performance of the Internal combustion (IC) engine is investigated using STAR-CD. ECFM-3Z (Extended Coherent Flame Combustion Model-3Zones) model is considered for the computational fluid dynamics (CFD) simulations. This study also includes the influence of swirl ratio on pressure and temperature of the combustion and hence the NOx (Nitrogen oxides), soot and CO2 (Carbon dioxide) emissions. The pressure, temperature and emissions of the combustion have been dropped significantly by increasing the swirl ratio. There is an increase in the distribution of air-fuel and hence the corresponding combustion flame by increasing the swirl ratio. It is observed that the reduced emissions of the combustion were achieved in the case of swirl ratio 3 and the values of the NOx emission, soot and CO2 emission are 0.0024 g/kg fuel, 0.0022 g/kg fuel and 5.12 g/kg fuel respectively. Eventually, the paper deals with the significance of the swirl ratio on NOx and CO2 emissions with limited loss of the piston work.

Low-Temperature Plasma Generators with Improved Energy and Resource Characteristics for Surface Treatment of the Technological Parts of Equipment

Low-Temperature Plasma Generators with Improved Energy and Resource Characteristics for Surface Treatment of the Technological Parts of Equipment

Thermodynamic and Kinetic Insights into Azo Dyes Photocatalytic Degradation on Biogenically Synthesized ZnO Nanoparticles and their Antibacterial Potential

The extensive use of azo dyes in textile and pharmaceutical industries pose significant environmental and health risks. This problem requires to be tackled forthwith through a cheap, environmentally friendly and viable approach to mitigate water pollution. In this context, the green synthesis method was used for synthesis of ZnO NPs. These biogenic ZnO NPs were characterized by UV-Vis and Fourier transform infrared spectroscopy (FTIR), powder X-ray diffraction (PXRD), high-resolution transmission electron microscopy (HR-TEM) coupled with energy-dispersive X-ray (EDX), dynamic light scattering (DLS) and Zeta potential (ZP) analysis. The characteristic bandgap energy (3.02 eV), crystallite size (18.6 nm), particle size (84 nm), hydrodynamic diameter (101 nm) and ZP (+33.9 mV) all indicated the successful synthesis of the stabilized NPs, which have an absorption edge at 373 nm. Based on the responsive energy band gap to visible light, these NPs demonstrated promising photocatalytic activity for the degradation of toxic dyes with efficiencies of 82.2 and 87.5 % for of methylene blue (MB) and methyl orange (MO), respectively, in only 2 h of sunlight exposure. To evaluate the reaction kinetics and thermodynamic parameters including the activation energy and rate constant, the degradation process was conducted at various temperatures. The effect of temperature showed the highest rate constant values of 0.022 and 0.025 min-1 at 90 oC, and activation energies of 4.1 and 3.8 KJ mol-1 for MO and MB, respectively. A possible degradation mechanism was proposed based on results of the radical scavenging experiments. The photocatalyst showed recyclability for five consecutive cycles with a simple regeneration. CMFE@ZnO NPs have also exhibited great antibacterial potential by inhibiting the growth of Gram-positive (S. aureus (13 mm) and B. subtilis (14 mm)) and Gram-negative (E. coli (17 mm) and P. multosida (15 mm)) bacterial strains. As a result, these CMFE@NPs may have great commercial importance in reducing the concentration of azo dyes and drug-resistant bacteria in textile and pharmaceutical industry effluents.

Characteristic evolution and energy variation during the generation of water droplet

Understanding water droplet characteristic is an important prerequisite for improving wet dust removal efficiency. Using the high-speed camera system, the process of water droplet generation under the different Ca2+ concentrations and injecting velocities was studied. The width and length of water droplet increased, whereas the ratio of droplet width and length decreased with generation time. The water droplet generation time decreased with injecting velocity increasing, whereas kept almost unchanged with Ca2+ concentration. The equivalent diameter of droplet decreased with injecting velocity, whereas presented first a slight decrease and then a slight increase with Ca2+ concentration. This result suggested that the injecting velocity effect was stronger than the Ca2+ effect on the water droplet generation time and size. Furthermore, the effective injecting force and capillary force were mainly forces to influence the droplet generation in force analysis. RF (ratio of capillary force and effective pressure force) was first used to evaluate the synergistic effect of capillary force and effective injecting force. The greater RF, the water droplet generation time was longer and water droplet diameter was larger. Furthermore, the relationship between surface energy per unit (E/S) of water droplet and RF was a negative correlation. Those results can provide valuable suggestions to the development theory of dust removal.

FSK energy modulation integrated primer fuze technology based on S-P topology

Abstract The wireless energy transmission technology is utilized in the integrated primer fuze device to achieve the integrated transmission of energy and information for weapon equipment. A wireless energy and information transmission system model is designed specifically for the characteristics of energy and information transmission of integrated priming fuze. The working principle of the system under S-P magnetic coupling resonance is analyzed, and the inverter circuit and rectifier circuit are further designed. To achieve synchronous transmission of energy and information, an energy modulation/demodulation method based on FSK is proposed. Simulation verifies the feasibility of the system design, showing that while the S-P system has a simple structure and constant voltage output characteristics, it belongs to first-order resonance. When transmitting information through frequency modulation, there will be a reduction in system transmission efficiency due to deviation from the resonance point, making it only suitable for systems with small energy transmission requirements.

Numerical and Experimental Investigation of Gas/Liquid Separator with Various Tip Clearance

Summary Gas/liquid separators (GLSs) are widely used in petroleum extraction and the chemical industry, as well as aerospace and other fields. Experimental studies and numerical simulations were conducted to investigate the impact of tip clearance (TP) on the separation performance and energy characteristics of a dynamic GLS. The Reynolds stress model (RSM) was used for the numerical simulation of the gas/liquid separation process, and the reliability and accuracy of the model were confirmed through comparison and analysis of experimental findings. The results demonstrate a linear correlation between TP and device performance under specific flow rate conditions. As TP increases, there is a corresponding decrease in separation efficiency, power of the liquid-phase outlet (LPO), and differential pressure at the inlet. This trend can be attributed to reduced maximum tangential velocity and increased TP, which lead to heightened backflow. Consequently, this impedes the outflow of the liquid phase post-separation, resulting in reduced separation efficiency and energy performance. Furthermore, at particular TPs, a significant decline in device performance is observed under conditions of high flow rates. This is primarily due to the intensified turbulence between the blades, which increases flow rates. Consequently, the disorder in the internal flow field escalates, leading to considerable energy losses and impacting the gas/liquid two-phase separation process. This study offers valuable insights into designing high-performance dynamic gas/liquid separation devices (DGLSDs), providing a robust theoretical foundation for future endeavors.

Power control of an autonomous wind energy conversion system based on a permanent magnet synchronous generator with integrated pumping storage

Wind energy plays a crucial role as a renewable source for electricity generation, especially in remote or isolated regions without access to the main power grid. The intermittent characteristics of wind energy make it essential to incorporate energy storage solutions to guarantee a consistent power supply. This study introduces the design, modeling, and control mechanisms of a self-sufficient wind energy conversion system (WECS) that utilizes a Permanent magnet synchronous generator (PMSG) in conjunction with a Water pumping storage station (WPS). The system employs Optimal torque control (OTC) to maximize power extraction from the wind turbine, achieving a peak power coefficient (Cp) of 0.43. A vector control strategy is applied to the PMSG, maintaining the DC bus voltage at a regulated 465 V for stable system operation. The integrated WPS operates in both motor and generator modes, depending on the excess or shortfall of generated wind energy relative to load demand. In generator mode, the WPS supplements power when wind speeds are insufficient, while in motor mode, it stores excess energy by pumping water to an upper reservoir. Simulation results, conducted in MATLAB/Simulink, show that the system efficiently tracks maximum power points and regulates key parameters. For instance, the PMSG successfully maintains the reference quadrature current, achieving optimal torque and power output. The system’s response under varying wind speeds, with an average wind speed of 8 m/s, demonstrates that the generator speed closely follows turbine speed without a gearbox, leading to efficient power conversion. The results confirm the flexibility and robustness of the control strategies, ensuring continuous power delivery to the load. This makes the system a feasible solution for isolated, off-grid applications, contributing to advancements in renewable energy technologies and autonomous power generation systems.

Modification as a Method of Regulation of Energy Characteristics and Functionalization of Solid Surfaces

The surfaces of solids (gold, silver, polymers) were modified with adsorption layers of various compounds. Optimal modification conditions were determined using methods of contact angle measuring and quartz crystal microbalance. The degree of filling of surfaces with the adsorption layer was calculated and the data obtained were compared with the results of direct measurements of adsorption. The surface energy of the modifying layers was determined and the potential applications of modified solids as functional materials are demonstrated.

ADJUSTMENT OF THE ELEMENTS OF THE FLOW PART OF THE HIGH-EFFICIENCY OF PUMP- TURBINE

The problem of the development of pumped storage power plants in Ukraine is considered, especially in the conditions of military operations, which damaged the energy infrastructure and created capacity shortage. The pumped storage power plants will help stabilize the power system by storing energy during periods of low load and efficiently using it during peak needs or accidents. All this has a positive impact on the role of energy autonomy and the integration of renewable energy sources. Efficiency increase of the hydro-turbine equipment of the PSPP requires the improvement of the water passage of the reversible hydraulic machines. This work shows that the creation of high-efficiency reversible hydraulic equipment depends on the correct selection of the geometry of the pater passage elements of the reversible hydraulic machines, consequently ensure the necessary level of energy characteristics of the hydraulic equipment. The equation of the optimal mode was used for the calculated assessment of kinematic and energy characteristics, analysis of their formation and search for rational variants that provide the specified requirements for the runner energy characteristics of the reversible hydraulic machines. Calculations are carried out using dimensionless kinematic parameters, which simplifies the process and eliminates the need for complex calculations. The numerical analysis data on the influence of the hydrodynamic parameters of the water passage on the parameters of the optimal mode can be used both for profiling the blade system of the runner, with the aim of improving energy characteristics (increasing power, efficiency level, etc.), and for modifying the blade system. The numerical study method for finding optimal variants of the runner blade system is given. The proposed approach was used to estimate the kinematic and energy characteristics of water passages of Francis turbines, as well as high-head reversible hydraulic machines ОRО200 and ОRО500 (both for basic and modified variants of the water passage).

DESIGN OF HIGH HEAD RUNNERS OF FRANSIC TURBINES

The energy characteristics of the hydroturbine, reflecting the total effect of the interaction of the flow with the working bodies, allow us to judge the operation of the machine as a whole. Information about the energy qualities of individual elements of the flow space is provided by the energy balance. Using the data of the energy balance, it is possible to identify the most favorable conditions for the joint operation of the elements of the flow space, that is, to achieve their agreement to increase the level of efficiency – the most important energy indicator of the hydroturbine. In order to improve the energy performance of the designed hydroturbine, various analyzes are conducted, that is, the dependence of the kinematic and energy characteristics of the hydroturbine on its geometric parameters is investigated. Such an analysis is carried out to find the most rational options for the flow space. The paper presents the design of the flow space of the high head hydroturbine FR400, performed with the help of programs developed at the department "Hydraulic machines named after G. F. Proskura". The method of energy characteristics analysis, based on the application of dimensionless parameters, is described. To improve the energy indicators at the preliminary stage of the hydro turbine design, multivariate calculations of the influence of the geometric indicators of the runner on the formation of the energy indicators of the hydroturbine are carried out. To substantiate and analyze the results, a predictive universal characteristic of the hydroturbine is built. To analyze the formation of energy characteristics of hydroturbines, the general kinematic properties of spatial lattices, as well as the general regularities of the interaction of the fluid flow with the runner, were used. The analysis of energy losses in the flow space of the high head turbine Francis: the spiral case, the guide vane, the runner and the draft tube at the optimal operating mode of the hydroturbine, as well as the analysis of the effect of the geometric elements of the runner on the changes in energy losses in the flow space, was performed. The given results of the calculation study confirm that in order to increase the level of efficiency, while maintaining the indicators of the optimal mode, it is necessary to change both the position of the starting edge of the impeller and the law of the distribution of angles along it.

Research on Arc Fault Detection Based on Conditional Batch Normalization Convolutional Neural Network with Cost-Sensitive Multi-Feature Extraction.

An arc fault is a potential hazard in power systems, capable of causing serious safety accidents such as fires. Therefore, the timely detection of arc faults and implementation of circuit-breaking measures are crucial for ensuring safety, preventing fires, and maintaining the stable operation of power systems. Although existing studies have made progress in improving the accuracy of their detection, most methods have not proposed effective solutions that address the cost-sensitive problem of feature selection. Thus, a multi-feature method is proposed by combining time-domain, frequency-domain, energy, and spatial features, which are integrated into a CBN (conditional batch normalization) convolutional neural network for detection. The experimental results show that the proposed method outperforms traditional models in terms of its accuracy and misjudgment rate while maintaining a lower computational cost, demonstrating its superior detection performance. This provides an effective improvement for arc fault detection.

A friction energy-based damage model for discrete element simulation of fatigue damage evolution in concrete

The discrete results of concrete fatigue tests limit the research of concrete fatigue theory. Numerical simulation methods can model the damage of materials from multiple scales, which helps to reveal the fatigue damage mechanism and compensate for the inadequacy of physical tests. This study presents a novel damage model for simulating the fatigue damage evolution of cementitious materials within the framework of discrete element methods. The proposed friction energy-based fatigue damage model is underpinned by a clear fatigue damage mechanism and has only two independent parameters. The model underwent validation through a comparison between its predictions and the results of compression cycle tests performed on concrete specimens. The model reproduces the evolution characteristics of various fatigue damage indicators, including deformation, modulus, hysteretic energy, and number of cracks, and the fatigue damage accumulation rate presents sensitivity to the stress level. Furthermore, the model predicts a clear regularity in the fatigue damage thresholds, which is an important reference value for establishing fatigue failure criteria. The model can be used to predict fatigue life of fatigue tests with various maximum and minimum stress levels and the S-N curves obtained from the simulations fall within the range of test results.

Using Short Molecular Dynamics Simulations to Determine the Important Features of Interactions in Antibody-Protein Complexes.

The last few years have seen the rapid proliferation of machine learning methods to design binding proteins. Although these methods have shown large increases in experimental success rates compared to prior approaches, the majority of their predictions fail when they are experimentally tested. It is evident that computational methods still struggle to distinguish the features of real protein binding interfaces from false predictions. Short molecular dynamics simulations of 20 antibody-protein complexes were conducted to identify features of interactions that should occur in binding interfaces. Intermolecular salt bridges, hydrogen bonds, and hydrophobic interactions were evaluated for their persistences, energies, and stabilities during the simulations. It was found that only the hydrogen bonds where both residues are stabilized in the bound complex are expected to persist and meaningfully contribute to binding between the proteins. In contrast, stabilization was not a requirement for salt bridges and hydrophobic interactions to persist. Still, interactions where both residues are stabilized in the bound complex persist significantly longer and have significantly stronger energies than other interactions. Two hundred and twenty real antibody-protein complexes and 8194 decoy complexes were used to train and test a random forest classifier using the features of expected persistent interactions identified in this study and the macromolecular features of interaction energy (IE), buried surface area (BSA), IE/BSA, and shape complementarity. It was compared to a classifier trained only on the expected persistent interaction features and another trained only on the macromolecular features. Inclusion of the expected persistent interaction features reduced the false positive rate of the classifier by two- to five-fold across a range of true positive classification rates.

How Does a Dry General Circulation Model Represent Atmospheric Blocking?

Abstract While dry dynamics has been a key framework for understanding blocking events, recent studies have highlighted the significant role of moist processes in blocking life cycles. However, it remains unclear whether moist processes introduce unique characteristics in the blocking life cycle that cannot be captured by dry dynamics or whether they are a source of extra energy for synoptic eddies that are needed to form realistic blocking circulations. Our approach to address the above question is to perform a long-term simulation of a dry General Circulation Model (GCM) with synoptic eddy energy and mean flow characteristics close to the winter climatology of ERA5 reanalysis. Blocking frequencies are found to be reduced by about one-third in the model compared to ERA5 using a blocking detection based on Potential Vorticity (PV). This moderate underestimation of blocking frequency in the dry model is due to rarer favourable conditions to initiate a blocking anticyclone. The model needs episodes of weaker eastward flows than in ERA5 to compensate for the weaker westward expansion of the blocking anticyclone associated with the smaller divergent winds. The main characteristics of the blocks (intensity, size, duration) are similar in the two datasets despite some slight structural differences: ERA5 blocks are more Ω-shaped and blocks in the dry model are more dipole-shaped. Even though the origins of the air parcels forming a blocking anticyclone are very different in the two datasets, the dry model compensates for its less efficient transport of low-PV air from low levels by transporting more efficiently low-PV air from lower latitudes at upper levels.

Evaluation of molecular inclusion of azole antifungals by β-cyclodextrin using computational molecular approach

Fungal infection is an emerging global concern highlighting diseases like pneumonia, invasive candidiasis, chronic pulmonary aspergillosis, and meningitis. But major concern is development of antifungal drug resistance, necessitating novel pharmacological solutions. Azoles, particularly fluconazole and related compounds, are emphasized for their systemic efficacy via inhibition of CYP51, altering fungal cell membrane sterols. So, in this work we theoretically investigated the effect of complexation of azoles with β-cyclodextrin (β-CD), focusing on improving solubility and bioavailability. Using molecular docking, the interaction between azoles and β-CD is analyzed, predicting stability and binding energies. Docking studies elucidate specific binding modes and hydrogen bonding interactions, while PM3 calculations provide insights into electronic structures and properties such as HOMO–LUMO energy gaps, chemical potential, hardness, and electrophilicity. Our findings indicate that fluconazole-β-CD complexes, particularly FCZ-βCD2, exhibit stability and promising development potential due to low energy and favorable binding characteristics. The antifungal spectrum of all the inclusion complexes was predicted using the PASS web server which proved that that the complexes are more effective against fungal pathogens than bacterial pathogens. This preliminary theoretical study highlights β-CD’s potential as a carrier to enhance the therapeutic efficacy of antifungal drugs, addressing key challenges in treating fungal infections through improved solubility and bioavailability.

High energy and rate capable supercapacitor of polyaniline / vanadium pentoxide nanocomposite and its green electrolyte

The concept of hybrid supercapacitors of combining the high energy density (E) of batteries and high power densities (P) of supercapacitors is better achieved with the PANI53.84 %/V2O546.15 % nanocomposite (PV). As it exhibited a supercapacitor performance on par with that of Li – ion batteries. This high energy features of PV are achieved by the green approach of using the by-product obtained in the synthesis of electrode material as its electrolyte with and without modification. The energy storage parameters of PV in the presence of 1 M H2SO4 (SA) as electrolyte, are very unique as they increased in quantity with increase in No. of energy storage/delivery cycles. The PV displayed an exceptional durability up to 20,500 cycles at 0.4 V s1, and specific capacity (Q) of 592.4 C g1, an E of 98.73 W h kg 1 (in the order of Li-ion batteries) and a P of 1.200 kW kg1 at 1 A g1 after 10,800 cycles in the presence of SA. A highest rate capability of 65.45 % up to 15 A g1 is achieved when the by-product of PANI (SL of PANI) is used as the electrolyte for PV. When the by-product of PV is used as its electrolyte after its acidification with conc. methane sulphonic acid (MSA+SLPV), the Q of 388.0 C g1, an E of 64.66 W h kg1 and a P of 1.200 kW kg1 were achieved at 1 A g1. The MSA+SLPV also features the energy enhancement with increase in number of days.

Acoustic emission for real-time monitoring of interfacial erosion-corrosion of austenitic stainless steel in polluted phosphoric acid environment

Erosion-corrosion is a complex problem causing severe damage of austenitic stainless-steel equipment used in phosphoric acid production. Herein, time-resolved analyses of the acoustic emission (AE) signal together with the corrosion potential and weight loss were performed to online monitor and evaluate the dynamic degradation and depassivation of the 904L stainless steel under the effect of abrasive SiC particles. Important insights into the erosion-corrosion process are gained from the analysis of the AE waveform and its parameters. The characteristic root mean square (RMS) voltage and acoustic energy of AE signals revealed the self-healing difficulty of the passive film, of which the waveform of AE signals showed the appearance of imperfect continuous high intensity waveform, ranging from 0.1 to 0.4 mV. Evaluation of the average frequency spectrum showed that the amount of SiC particles alters the damage mechanism from AE events dominated by ploughing to AE events driven by micro-cutting. This suggests that the imperfect continuous waveform is possibly a precursor to the emergence of new acoustic sources (burst type): sudden jumps of chips from the cutting lips. This response resulted in a quasi-linearity in the mass loss of the alloy with the respective acoustic response at high particle loading (24 g L−1). The non-linear erosion-corrosion behavior suggests that the depassivation-repassivation events are dependent. These results render the combined AE and electrochemical analysis an effective sustainable approach for the online investigation of the synchronously changing erosion and corrosion rates.

The influence of joint distribution characteristics on the mechanical properties, fracture mechanisms, and energy characteristics of rock masses under stress conditions

The mechanical properties, fracture mechanisms, and energy characteristics of jointed rock masses under stress conditions are crucial theoretical underpinnings for the monitoring and reinforcement of rock engineering. In this study, rock mass images with various joint distribution characteristics are constructed. By integrating mesoscopic damage mechanics, statistical strength theory, and continuum mechanics, and using digital image processing within the DIC-refined RFPA method, the jointed rock mass images owning different joint distribution characteristics are rendered into non-uniform numerical models. Their strength and deformation characteristics, fracture features, and energy evolution patterns under stress condition are investigated. Further, the impact of joint distribution characteristics on micro-crack quantity indexes (MCQIs) and micro-crack energy indexes (MCEIs) is examined, and then they are organized into rankings. The study reveals that, when subjected to both lateral pressure and vertical compression condition, the compressive strength (CS) and equivalent deformation modulus (EDM) are lower for columnar jointed rock masses (CJRMs) and rock masses with X-type cross cracks (RMXCCs), while they are larger for intermittent jointed rock masses (IJRMs) and rock masses with V-type cross cracks (RMVCCs). The MCQIs and MCEIs appear earlier on the strain axis for RMXCCs and rock masses with T-type cross cracks (RMTCCs). The magnitudes of MCQIs and MCEIs for IJRMs and RMTCCs are lower, while they are higher for CJRMs and rock masses with trident-type cross cracks (RMTRCCs). Under the concurrent normal stress and shear condition, whether the magnitude of MCQIs in rock masses with en-echelon joints (RMEJs) is higher than that in CJRMs depends on the specific joint dip angles. These findings can serve as a foundational framework for monitoring, reinforcing, and operating maintenance of rock engineering.