In this study, a parametric analysis was conducted for the design of a suggested dual flapping hydrofoil turbine. A Navier–Stokes-based computational fluid dynamics code was utilized for the analysis while varying the pitch angle, reduced frequency, separation distance, and phase difference. The smallest pitch angle of 60° and the reduced frequency of 0.1 among the given ranges of the parameters were fixed for the first parametric analysis. After an assessment, the 90° front-lead with the longest distance of 6c and the 90° rear-lead with the shortest distance of 2c were chosen for further parametric analysis based on a suggested performance indicator and a margin for improvement. It was derived from a subsequent parametric analysis that a 70° pitch angle, 0.12 reduced frequency, and a 4c distance for the 90° front-lead was the final optimum with 59.48% efficiency and 55.44% fluctuation according to the performance indicator as well as the system length and power balance of dual hydrofoils.

Clean water and renewable energy sources are becoming increasingly important in the current era, as well as a future challenge, and one of the potential solutions is photocatalysis. In the current study, a simple one-step hydrothermal technique is employed to fabricate the pure and La-doped CuO (0%, 1%, 3%, 5%, and 7%) photocatalysts. The influence of varying La concentration on structure, morphology, and optical properties is determined by scanning electron microscope (SEM), X-ray diffraction (XRD), ultraviolet (UV)–visible spectroscopy, and photoluminescence. SEM showed that synthesized nanostructures are irregularly spherical and transform into needle-like nanostructures on increasing La concentration. XRD revealed the monoclinic phase with a crystallite size of 15–23 nm. The UV–visible spectrum exhibited a decrease in the band gap of La-doped CuO needle-like nanostructures from UV to visible light. The composition and purity of synthesized nanostructures are evaluated via the energy-dispersive X-ray spectrum which revealed that needle-like nanostructures are pure without any impurity traces. The synthesized nanostructures were used as a photocatalyst against methylene blue dye to examine their photocatalytic activity. The synthesized CuO-3La photocatalyst exhibited excellent photocatalytic performance of dye degradation and hydrogen production 95.3 μmol h−1 g−1 with more than 97% cyclic stability. Therefore, the synthesized La-doped CuO nanostructures are potential candidates for photocatalytic water splitting and hydrogen evolution.

Reducing loss and providing a secure power supply for customers have always been the main goal of distribution systems planners. Recently, the development of competitive electricity markets and responsive loads participation in such markets together with the integration of regional energy networks (RENs) have resulted in creating some challenges for RENs' owners to increase operating efficiency, and reduce investment costs. In this paper, to overcome these problems, a new modeling for coordinated planning of distribution networks and RENs in the presence of responsive loads is proposed and to achieve the optimal solution of the problem, the genetic algorithm is used. Operation uncertainties due to the installation of wind turbines and photovoltaic resources in RENs are considered. The probability-tree method is used to generate and model operation scenarios and their variable production, respectively. To validate and confirm the efficiency of the proposed model, numerical studies were applied on a 25-bus Institute of Electrical and Electronics Engineers standard distribution network, including two RENs equipped with responsive loads. The results show the fact that the flexibility of the demand side in the electrical sector due to the activity of responsive loads causes to increase in the installation capacity of energy resources and storages.

Rh-promoted YZr-supported Ni catalyst (5Ni/YZr) is investigated for DRM and characterized with X-ray diffraction, Raman, infrared spectroscopy, cyclic reduction–oxidation–reduction temperature programmed experiment, thermogravimetry, and transmission electron microscope. Over 5Ni/YZr, some active sites become inactive under the CO2 stream and limit H2 yield to ∼71%. Upon 4 wt% Rh addition over 5Ni/YZr; more than one type of stable active sites (Rh and Ni) generates, moderate basic sites are enhanced, wide ranges of CO2-interacted surface species (especially bidentate CO2-adsorbed species) are grown and graphitic carbon proportion over spent catalyst declines. This resulted in 87.35% H2 yield and 86.73% CO yield up to 420 min. 5Ni4Rh/YZr catalyst maintains ∼80% H2 yield at the end of 27 h of DRM reaction.

Borehole destabilization damage is an important factors affecting gas extraction efficiency. To derive the fracture development law, strain, and energy evolution characteristics of different borehole diameters, uniaxial compression experiments were conducted on prefabricated rock specimens with different borehole diameters. The results showed that the elastic energy and dissipation energy of the specimens with different pore diameters changed with the compression process, and the energy distribution inside the specimens. The results show that as the pore size of the specimen increases, the strain area damaged by tensile fracture gradually decreases and the strain area damaged by shear fracture gradually increases, and the damage of the dominant specimen gradually evolves from tensile fracture as the dominant factor to tensile fracture and shear fracture together as the dominant factor and finally to shear fracture as the dominant factor. For the whole compression process of pore size rock specimens, the total energy curve shows a nonlinear growth trend, and the elastic energy curve shows a nonlinear growth trend before the specimen damage and a cliff-type decrease after the specimen damage. From the perspective of energy distribution, the elastic energy storage limit of the specimen decreases with the increase of the specimen pore size, the energy distribution law inside the rock specimen with pores changes, and the total energy absorbed from the outside gradually changes to the dissipated energy, resulting in an increasing proportion of dissipated energy, indicating that the larger the pore size, the larger the plastic deformation, and the more obvious ductile damage characteristics of the specimen with pores will be shown. The research analyzes the causes of destabilization of rock samples with different hole diameters and provides some theoretical guidance for the study of gas extraction drilling stability.

It has been widely acknowledged that traditional packers will lose their elastic performance in the context of long periods of operation due to plastic deformation. This paper will introduce a swellable packer that can reduce the failure cases of production effectively. The deformation of the packer rubber in different media and temperatures has been analyzed. The pressure test of several packer rubber under different media is carried out in this paper. The reasonable expansion clearance between the rubber tube and the well wall is obtained by strength calculation to ensure the sealing reliability of the packer. Finally, the thermomechanical coupling calculation of the packer with different structural sizes is carried out. Experiments at different temperatures show that the higher saline concentration is associated with a lower expansion rate and a larger expansion rate in clear water. At the same time, the expansion of volume in clear water increases. In addition, the higher the external temperature is, the larger the temperature gradient is. When the temperature of the outer ring is between 100°C and 140°C, the internal temperature rises to 37°C under the thermomechanical coupling effect.

Hydrogen could play an important role in reducing the climate impact of the transport sector. This study explores the possibility of using existing biomethane infrastructure to enable the accelerated roll-out of hydrogen as a transport fuel in a Swedish context. The concept of multifuel filling stations for hydrogen and biomethane are examined based on four cases, where the hydrogen is produced either via electrolysis or biomethane reforming, at a smaller or larger scale, and through either centralised or decentralised production. The cases are compared using established life cycle assessment (LCA) methodology to establish their respective impact from a greenhouse gas (GHG) emission mitigation potential. The LCA results show generally good GHG performance for all production paths being studied with a range from −7 g CO2 eq./MJ hydrogen for hydrogen production based on biomethane via steam reformation (SMR) compared to +19 g CO2 eq. for production based on Swedish National Grid Mix via electrolyser. The SMR is the more efficient technology in mitigating GHG emissions, especially if system expansion is applied. In addition, sensitivity analyses also show that electrolyses production based on renewable wind power will decrease the impact significantly and vice versa that a European Average Electricity Grid Mix (EU – 28) would increase the impact significantly. The findings of this study underline the potential of the gradual introduction of hydrogen as a fuel for transport without the need for large investments in a dedicated fuel-specific distribution system. The concept could contribute to overcoming the current chicken-and-egg catch of achieving both scalable and profitable supply of hydrogen for transport as well as the vehicles using it as fuel.

In this paper, a lithium-ion battery State of Health (SOH) estimation algorithm is proposed based on the fusion of multidomain features and the application of a CatBoost model. The aim is to address the issue of low prediction accuracy in SOH caused by the utilization of single-feature extraction techniques. The algorithm encompasses the extraction of various features from the original charge–discharge data, including time-domain, frequency-domain, entropy, and time-series features. Following the evaluation of feature importance, a feature selection process is conducted to eliminate redundant features that provide a limited contribution to the predictive results. Subsequently, a multiple-set discriminative correlation analysis is employed to integrate high-dimensional features. To attain accurate predictions, the CatBoost model is further optimized through the utilization of a sparrow search algorithm. Experimental results demonstrate that the proposed algorithm achieves accurate SOH estimations within individual batteries, as evidenced by mean square error values consistently below 4e−4 and goodness-of-fit values exceeding or equal to 0.98. Additionally, the algorithm exhibits reliable prediction capabilities across different batteries operating under the same charge/discharge strategy. Comparative analysis indicates that the adoption of the multidomain feature fusion approach yields improved prediction accuracy in contrast to the utilization of a single feature extraction method.

A low-pollution single-tube microgas turbine combustor using different gas fuels was studied. The combustion performance of two kinds of landfill gas and natural gas was tested in a single-head combustor. The effects of fuel nozzle position, and the fuel distribution ratio between pilot and main combustion stage on pollutant emission were investigated under rated load condition. The flow field, temperature field, and pollutant generation characteristics with different fuel nozzle diameters and nozzle positions were analyzed by numerical simulation. The results show that: the combustor can form an obvious central recirculation zone, which is convenient for ignition and stable flame propagation; in the case of limited premixed length, the influence of fuel nozzle position on fuel–air mixing uniformity is less obvious than that of fuel nozzle diameter. The fuel–air mixing uniformity plays a decisive role in the temperature field and the generation of pollutants in the combustor. The combustor has good pollutant emission characteristics, and the NOx emission can be reduced to about 10 ppmv (15% O2 concentration) under the appropriate combination of fuel nozzle diameter and position, which provides a reference for the further optimization of low-emission combustor.

The capacity of lithium batteries varies under different temperature conditions. However, many studies still neglect the influence of temperature on battery capacity. Besides, some studies only considered the combination of the heat and electricity of the battery monomer and failed to study the performance of the battery pack in groups. This paper investigates a new method for dynamic situations that takes the influence of temperature on battery capacity into consideration. After acquiring the parameter through experiment, we can substitute the performance parameters into the thermoelectric coupling model and use MATLAB to realize the iterative calculation of thermoelectric coupling. By combining the grouping mode with the model, we can simulate the thermodynamic and electrical properties of the battery cell in the pack. The novelty is evident because the paper focused on the battery pack instead of a single cell and the lumped parameter thermal model is adopted. Besides, the method proposed in this paper considered the influence of temperature on battery capacity. The program of calculation process can be solidified on the vehicle system. After the simulation, we can get the available capacity of the battery pack at different initial temperatures, with different grouping modes and different inconsistency of parameters. The results predicted by MATLAB model are compared with the results of MATLAB-FLUENT thermoelectric coupling simulation. The result reflects that the prediction by the MATLAB model about the available capacity, temperature, and residual electricity is of good precision.

The hard roof in coal mines will induce strong pressure problems for the working face and the lanes, which will seriously affect the safe and efficient production of the mine. For these issues, our team developed a new technology of cutting hard roof by composite blasting. With the new technology, a penetrating process is key to the directionally cut roof. Thus, an arbitrary Lagrange–Euler method is proposed to calculate the penetrating process. In this method, it was taken that the Jones–Wilkins–Lee constitutive model, Johnson–Cook constitutive model, and Holmquist–Johnson–Cook constitutive model to build a numerical model, by LS-DYNA software, of the process of the penetrating the hard roof. Finally, the following conclusions were obtained: (1) The velocity variation law of metal liner from head to tail is revealed. The speeds of the metal liner's head and tail are 3500 and 450 m/s, respectively. (2) The shape of the channel formed by shaped charge jets is like a funnel, whose mouth's depth and diameter are 33 and 49 mm, respectively. The funnel's narrow diameter is 7.5 mm. (3) With the increase of the channel depth, the rock damage area changes in three different states: slow increase, rapid increase, and linear increase. Then, a shovel-shaped geometric model of rock damage zone is established, whose key size parameters in the model are given.

Aiming at the problems of noise interference and too many network parameters for power quality disturbances' (PQDs') classification based on deep learning, the lightweight convolutional neural network combining maximum likelihood Kalman filter and continuous wavelet transform is proposed. In this proposed method, the disturbed PQD signals are denoised by maximum likelihood Kalman filter, and then the denoised PQDs are converted to time-frequency diagrams, which can provide rich time and frequency domain information, and finally the lightweight convolution neural network is used for automatically extracting and classifying multiple PQDs. To verify the effectiveness and superiority of the proposed method, a variety of PQDs were tested under different noise levels, the experiment results indicate that the average classification accuracy can reach more than 99% even in the case of 10 dB noise. Compared with the existing classification methods, the accuracy and noise immunity ability are improved. Additionally, the proposed method has decided advantages, as evidenced by its low parameter count of 0.73M and short average test time with only 0.7 ms.

In the nuclear magnetic resonance (NMR) test of coal, when the spinning frequency of magic-angle spinning (MAS) is less than the frequency range of chemical shift anisotropy, serious aromatic carbon spinning sidebands will appear. Existing solutions to the sideband effect, such as changing the MAS frequency, inserting total suppression of sidebands (TOSS) pulse sequences, or simply defining the peak after chemical shift of 200 ppm as the sideband peaks generated by aromatic carbon peak, multipling the identified sideband integral by 2 and adding to the main peaks of protonated aromatic carbon and aromatic bridgehead carbon. None of these methods can reasonably correct for the sideband effect and cause errors to accurately quantifying the carbon structure parameters. Compared with 13C nuclear magnetic resonance (13C NMR) spectrum without sideband suppression (13C CP-MAS NMR) and 13C NMR spectrum under sideband suppression conditions (13C CP-MAS/TOSS NMR), according to the chemical shifts of the main peaks of four aromatic carbons, namely protonated aromatic carbon, aromatic bridgehead carbon, alkylated aromatic carbon and oxygen-linked aromatic carbon, combined with the MAS frequency, the first- and second-level sideband peaks generated by four types of aromatic carbons were accurately located and quantified, and they were added to the corresponding aromatic carbon main peaks in 13C CP-MAS/TOSS NMR spectrum, thus realizing the accurate correction of sideband effect of the solid-state 13C NMR spectrum of coal samples. The relative area of corrected aliphatic carbon, carbonyl (carboxyl) carbon, and various aromatic carbons were recalculated, and more accurate carbon structure parameters were obtained, which is significant for studying the coal structure from a microscopic perspective.

Maximizing the utilization of an available source serves as the ideal approach, provided that only technical factors are considered. For sources with low heat flux, however, cost-effective solutions are more suitable due to the minimal net power generated, regardless of the effectiveness of the energy conversion. In such cases, utilizing low-threshold technology may be the most fitting solution, the layout of these cycles should be simple and inexpensive. In the case of organic Rankine cycles (ORCs)-based power cycles, this means the omission of superheaters or recuperative heat exchangers and the use of simple expanders and small heat exchangers. Simplifying the design, however, requires additional considerations about the elementary steps of the cycle. This work presents a procedure to select favorable working fluids for ORC while considering the expander's internal efficiency. The criteria for favourability is to have a nonideal expansion process starting and ending in (or very near) saturated vapor states to avoid problems related to wetness/dryness between the given maximal and minimal expansion temperatures. It is demonstrated that the design can be simplified under the simultaneous working fluid and expander selection method presented in this study, regardless of the type and isentropic efficiency of the expander. The resulting methodology applies the novel classification of working fluids using the sequences of their characteristic points on temperature-entropy space. The proposed approach is illustrated with a case study finding optimal working fluid for an ORC system fitted to industrial waste heat, a low-temperature geothermal, and a cryogenic heat source.

This study presents the optimization of the heat transfer coefficient of a micro bare tube heat exchanger. A physical and mathematical model of a micro bare tube heat exchanger was built in Matlab using the simplified ε-number of transfer unit method. Using a temperature of minus 30°C and a 0.5–1.0 mm tube outer diameter, a 1.7–8.0 mm longitudinal tube pitch, a 1.7–5 mm transverse tube pitch, and a 1.0–5.0 m/s velocity at minimum free flow area, with carbon dioxide as the refrigerant, a comparative variation analysis was performed to optimize the heat transfer coefficient of a micro-bare-tube heat exchanger. The results demonstrate that the heat transfer coefficient increases as the inlet air velocity is increased from 1.0 to 5.0 m/s, with a final gain of 93.17%. The growth rate of the heat transfer coefficient steadily decreases with increasing inlet air velocity and gradually approaches zero. The effect of the gradual decrease of the tube outer diameter from 1.0 to 0.5 mm on the heat transfer coefficient is 22.52% greater than that of the gradual decrease of the transverse tube pitch from 2.2 to 1.7 mm. The study also carried out an optimization analysis on the distribution of four different variables in the heat exchanger. With the use of a genetic algorithm, the study found an optimal distribution to maximize the heat transfer coefficient. The following parameter values resulted in the maximum heat transfer coefficient: a maximum inlet air velocity of 5.0 m/s, a minimum tube outer diameter of 0.5 mm, a 1.7 mm longitudinal tube pitch, and a 1.7 mm transverse tube pitch.

Optimizing the efficiency of conventional heat exchangers is critical for improving the performance of various processes. This study proposed increasing the heat dissipation buffer space of heat exchangers by filling the gap between the heat exchanger and the shell with phase-change materials for optimizing phase-change heat exchangers. Comparative simulation analyses were performed by investigating the difference between the internal and external diameters of the inner ring ribs of the heat exchanger, the flow rate of the cooling liquid, the spacing distance, and the number of the inner ring ribs as independent variables. The results revealed that the heat transfer efficiency of heat exchangers can be improved by adding the inner ring rib structure to the heat exchange copper tube. The difference between the inner and outer diameters of the inner ring rib considerably influences heat dissipation. Furthermore, a sensitivity coefficient of 0.2457 can be obtained. The distance and number of inner ring ribs and the flow rate of cooling liquid exhibit certain effects on the heat transfer efficiency of the heat exchanger. The sensitivity coefficients were 0.1477 and 0.0935. The heat dissipation efficiency of the coil heat exchanger was improved by 3.8% by adding inner ring ribs in the coil heat exchanger channel.

The micro turbine engine (MTE) plays a vital role in the aerospace sector. However, traditional research and design models no longer suffice to accommodate the highly complex operating conditions of the MTE. Therefore, this paper briefly analyzes the concept and development process of digital twin technology and integrates it into the research and design of the MTE. This integration takes into account the recent leapfrog developments in information technology and digital intelligence technology. Utilizing digital twin technology to model the core components of the MTE allows for effective structural optimization, online monitoring, and timely problem detection in support of extending the overall lifespan of the engine. Multiple algorithms are used throughout the development, design, and usage phases of each component to merge into a cohesive whole, providing robust support for the MTE's overall development, production, and manufacturing. Digital twin technology facilitates accurate performance prediction, reliability evaluation, and advanced design optimization for the MTE. This, in turn, reduces the design cycle and research design cost more effectively. Lastly, we propose the future application and development trend of digital twin technology in the core components of the MTE.

Nowadays, the load monitoring system is an important element in smart buildings to reduce energy consumption. Nonintrusive load monitoring (NILM) is utilized to determine the power consumption of each appliance in smart homes. The main problem of NILM is how to separate each appliance's power from the signal of aggregated consumption. In this regard, this paper presents a combination between particle swarm optimization (PSO) and artificial neural networks (ANNs) to identify electrical appliances for demand-side management. ANN is applied in NILM as a load identification task, and PSO is used to train the ANN algorithm. This combination enhances the NILM technique's accuracy, which is further verified by experiments on different datasets like Reference Energy Disaggregation Dataset, UK Domestic Appliance-Level ElectricityUK-DALE, and Indian data for Ambient Water and electricity Sensing. The high accuracy of the proposed algorithm is verified by comparisons with state of the art methods. Compared with other approaches, the total mean absolute error has decreased from 39.3566 to 18.607. Also, the normalized root mean square error (NRMSE) method has been used to compare the measured and predicted results. The NRMSE is in the range of 1.719%–16.514%, which means perfect consistency. This demonstrates the effectiveness of the proposed approach for home energy management. Furthermore, customer behavior has been studied, considering energy costs during day hours.

This study aims to model a hybrid power system that can continuously generate power by switching between two possible thermal sources: solar radiation and combustion energy from synthesis gases. The system comprised a hybrid energy receiver, solar dish, Stirling generator, fluidized-bed gasifier, boiler, and water tank. The solar dish was a dual-reflection solar collector that used two mirrors, namely the main and subordinate concentrators, to concentrate a broad expanse of solar radiation onto a hybrid energy receiver. The fluidized-bed gasifier was employed for the production of synthesis gases. The synthesis gases were combusted to provide an auxiliary heat source for the Stirling generator when solar radiation was insufficient. Solar radiation or combustion energy was alternatively introduced into the hybrid energy receiver and converted to power by a 1-kW-scale beta-type Stirling engine. In this manner, the Stirling generator could serve as a base-load power plant regardless of solar conditions. In this study, a complete quantitative model was developed for a demonstration plant by incorporating thermodynamic and dynamic models of the beta-type Stirling engine, a ray-tracing model for the dual-reflection solar dish, an energy model of the hybrid energy receiver, and experimental data for the fluidized-bed gasifier. The performance response of the system during switching between solar radiation and combustion energy was predicted. The modeling results indicated that switching can result in a continuous power output ranging from 600 to 1200 W. With synthesis gas combustion as the auxiliary heat source, the hybrid Stirling power system can be operated continuously, and the overall power output is increased by 109.82% compared to a conventional concentrated solar power system that only uses solar radiation.

The power electronic converters and grid-connected filters were important components of the permanent magnet direct drive wind power generation system whose performance directly determines the quality of wind power generation. In past modeling, analysis, and control studies, capacitive and inductive components were often treated as integral-order components. However, the inductance and capacitance components in the actual permanent magnet direct drive wind generator were fractional-order components, and their electrical characteristics will change with the change of order, which had an important impact on the dynamic and static characteristics of the system. In this paper, the mathematical model of the fractional-order LCL (FOLCL) filter was derived. Through simulation, it could be seen that the FOLCL filter can avoid resonance fundamentally. At the same time, the fractional-order PI (FOPI) controller was introduced into the machine-side current converter, and the parameters of the FOPI controller of the outer speed loop and the inner current loop were adjusted by using the time-domain optimization method. The results showed that the efficiency of the FOPI controller was significantly better than that of the integer-order PI controller in realizing maximum wind energy capture. It provides theoretical support and practical application value for the stable operation of the wind power generation system.