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Abstract The electroelastomer cylindrical actuators, a typical representation of soft actuators, have recently aroused increasing interest owing to their advantages in flexibility, deformability, and spatial utilization rate. Proprioception is crucial for controlling and monitoring the shape and position of these actuators. However, most existing flexible sensors have a modulus mismatch with the actuation unit, hindering the free movement of these actuators. Herein, a low-modulus strain sensor based on laser-induced cellular graphitic flakes (CGF) onto the surface of hollow TPU fibers (HTF) is present. Through the electrostatic self-assembly technology, the flexible sensor features a unique hybrid sensing unit including soft HTF as substrate and rigid CGF as conductive path. As a result, the sensor simultaneously possesses desirable modulus (~0.155 MPa), a gauge factor of 220.3 (25%

Highlights The layered arrangement and gradient distribution of magnetic MXene are firstly combined to improve the electromagnetic wave (EMW) RL min and broaden effective absorption bandwidth. Absorption, reflection, and transmission (A–R–T) power coefficient analysis is firstly used to guide the gradient distribution, so as to realize EMW incidence at low-concentration surface, loss at middle concentration interlayer and reflection at high-concentration bottom. The layered gradient composite (LG5-10-15) achieves complete absorption coverage of X-band at thickness of 2.00-2.20 mm with RL min of -68.67 dB.

ABSTRACT The developed laminar structure of shale makes it possess obvious anisotropic characteristics, and these anisotropic characteristics are one of the important factors leading to the strong and weak heterogeneous properties of shale. Additionally, there is a common phenomenon where the propagation of hydraulic fracture heights is limited in the hydraulic fracturing process of strongly heterogeneous shale reservoirs. To clarify the reasons for the limited height propagation of hydraulic fractures in strongly heterogeneous shale reservoirs, numerical simulation methods were used to study the propagation patterns of hydraulic fractures in shale reservoirs under different levels of anisotropy, flow rate, viscosity, and stress differences. The results show that as the anisotropy value increases and the heterogeneity becomes stronger, it becomes more difficult for hydraulic fractures to expand along the fracture height direction, and the fracture width at the fracture opening becomes larger. For strongly heterogeneous shale reservoir, the hydraulic fracture height can be increased within a certain range by increasing the flow rate, viscosity, and stress difference. When the upper limit value is exceeded, the hydraulic fracture height of the strong heterogeneous shale reservoir gradually becomes stable, and the increasing trend is no longer obvious. The strong or weak heterogeneity caused by the inherent anisotropic characteristics of shale reservoirs affects the development and transformation effectiveness of shale reservoirs. The research in this article will provide some reference material and guidance for the efficient development of shale reservoirs.

The use of high-temperature heat pumps to recover industrial waste heat has a high potential for energy conservation. High-temperature heat pumps require high critical temperatures, and the majority of the available working fluids are dry. However, when the dry working fluid is compressed from the saturated vapor phase, the compression process enters the two-phase region, resulting in a risk of liquid slugging that is detrimental to the operation of the compressor and high-temperature heat pump. Two improved vapor injection heat pump cycles (Cycle A and Cycle B) using isohexane, R1336mzz (Z), and R1233zd (E) as working fluids are proposed. The effects of compressor isentropic efficiency, evaporating temperature, and condensing temperature on the minimum superheating degree and heat pump performance are analyzed. The results indicate that, for cycle B, the evaporation temperature increases from 50 ℃ to 80 ℃. For R1336mzz(Z), the maximum COP(coefficient of performance) can be increased by 2.56%, and the maximum volumetric heating capacity (VHC) can be increased by 3.18%. For R1233zd(E), the maximum COP can be increased by 0.44%, and the maximum VHC can be increased by 0.54%. Cycle A has good adaptability to the isentropic efficiency. For cycle B, when the isentropic efficiency is higher than 0.6, isohexane is not suitable as a working fluid. When the isentropic efficiency is higher than 0.95, R1336mzz (Z) is also not suitable.

Along with the country’s vigorous promotion of new infrastructure construction and the rapid development of industrial Internet, industrial passive optical network (PON) technology is increasingly widely used in the industrial field. The policy background of industrial PON technology development was discussed in depth, its key technologies in broadband enhancement, network protection, deterministic delay, open intelligence, and security protection were elaborated, and the application practice of industrial PON in typical business scenarios was analyzed.

Abstract Bridge widening involves phased construction of adjacent structures to maintain uninterrupted traffic flow. This process exposes freshly placed longitudinal joints between staged deck constructions to vehicle-induced vibrations, potentially compromising their mechanical integrity. This study investigates the flexural behavior of ultra-high-performance concrete (UHPC) longitudinal joints under such vibrations through model tests. To simulate actual site conditions, we developed a novel vibration test setup that replicates the dynamic environment experienced by these joints during construction. Micro- and meso-scale tests were conducted to examine the flexural behavior of longitudinal joints following vibration exposure. Results revealed that vibration amplitude significantly influences fiber orientation and flexural strength of ultra-high-performance concrete (UHPC) wet joint specimens. Low-amplitude vibrations (3 Hz at 1 mm and 3 mm) enhanced fiber orientation, increasing flexural strength by 11.5% to 19.8% and ultimate load capacity by 17% compared to non-vibrated specimens. Conversely, high-amplitude vibrations (3 Hz at 5 mm) adversely affected fiber orientation, decreasing flexural strength by 23.9% and ultimate load capacity by 19% relative to non-vibrated specimens.

Aiming at the lack of research on the performance of deep learning models in predicting software refactoring in the current field, a deep learning-based software refactoring prediction evaluation method was proposed to assess the refactoring predictive performance of these models. Firstly, refactoring and non-refactoring labeled instances were collected from 303 Java projects using static analysis tools, and seven datasets comprising source code metrics were constructed for seven refactoring operations: extracting class, extracting subclass, extracting super class, extracting interface, moving class, renaming class, and moving and renaming class. Secondly, convolutional neural network (CNN), long short-term memory (LSTM) network, gated recurrent unit (GRU) model, multilayer perceptron(MLP), and autoencoder(AE) were trained and tested on the datasets. Finally, each model was evaluated based on accuracy, precision, recall, and F1-measure.The results show that the average accuracy, precision, recall, and F1-measure of the five deep learning models for predicting refactoring are all above 93%, with the highest accuracy in predicting the extract subclass refactoring, and the CNN model has a higher average accuracy compared to other models. The CNN model is efficient for software refactoring prediction evaluation, which provides reference for future utilization of deep learning models in assisting with completing refactoring recommendation tasks.

Aiming at the problems of unreliable commit message caused by developers not consistently recording refactoring operations, and language singularityin deep learning-based refactoring detection methods, a cross-language refactoring detection method RefCode was proposed. Firstly, refactoring collection tools were employed to collect commit messages, code change information, and refactoring types from different programming languages, the edit sequences were generated from the code change information, and all the data were combined to create a dataset. Secondly, the CodeBERT pre-training model was combined with the BiLSTM-attention model to train and test on the dataset. Finally, the effectiveness of the proposed method was evaluated from six perspectives. The results show that RefCode achieves a significant improvement of about 50% in both precision and recall compared to the refactoring detection method which only uses commit messages as inputs to the LSTM model. The research results realize cross-language refactoring detection and effectively compensate for the defect of unreliable commit messages, which provides some reference for the detection of other programming languages and refactoring types.

The transmission and analysis of massive video streams require significant edge bandwidth and computational resources, posing severe challenges to the current multimedia frameworks based on mobile edge computing (MEC). To address this issue, an adaptive offloading scheme based on a multi-stream collaborative optimization framework was proposed. Firstly, under the constraint of the long-term MEC energy budget, the processing cost of video tasks was minimized by optimizing the data stream selection decisions, server offloading decisions, bandwidth resource allocation, and computing resource allocation. Then, based on the Lyapunov optimization method, the long-term optimization problem was transformed into independent deterministic subproblems for each time slot, and the mixed-integer nonlinear programming problems for each time slot were solved by Markov approximation and KKT conditions. Simulation results indicate that the proposed scheme not only meets the long-term MEC energy constraint, but also significantly outperforms existing benchmark schemes in terms of cost performance.

In order to improve the corrosion resistance of steel materials treated by plasma electrolytic infiltration，annealed 20 steel was used as the experimental substrate.Micro-nanopores formed during the plasma electrolytic carbonitriding process were utilized as containers to load magnesium-iron layered double hydroxides (Mg-Fe-LDHs) as a corrosion inhibitor，and the effects of Mg-Fe-LDHs on the corrosion performance of 20 steel were investigated.First，formamide was used as the carbon and nitrogen source，and KCl was used as the conductive salt.These components were mixed with deionized water to form an electrolyte.Then，the samples were treated at a constant DC pulse voltage of 220 V for 9 min to produce a carbonitrided layer (denoted as PEC/N samples).Subsequently，the PEC/N samples were immersed in a Mg-Fe-LDHs precursor solution containing urea，MgSO4 and Na2CO3，and hydrothermally crystallized at 140 ℃for 10 h to obtain a composite infiltration layer (denoted as PEC/N-LDHs samples).The performance of the composite infiltration layers was analyzed using a microhardness tester，scanning electron microscopy (SEM)，X-ray diffraction (XRD) and electrochemical testing.Results showed that the microhardness of the composite infiltration layer reached approximately 900 HV，which was 4.6 times higher than that of the substrate.The carbonitrided layer of the PEC/N samples was about 20 μm，with a smooth and flat cross-section but a rough，porous and honeycomb-like surface.After hydrothermal synthesis of LDHs，the surface became smooth，lacking a visible honeycomb structure，and a large number of flake-like crystalline deposits appeared on the surface.The XRD spectra of the PEC/N samples showed absorption peaks corresponding to Fe3C，Fe5C2，α-Fe and Fe3N phases.After the in-situ loading of Mg-Fe-LDHs，new absorption peaks corresponding to the (003)，(006) and (009) crystal planes of Mg-Fe-LDHs appeared in the XRD spectra of the PEC/N-LDHs samples.Combined with SEM morphology analysis，it was confirmed that Mg-Fe-LDHs were successfully loaded，presenting a flake-like structure.Compared with 20 steel，the PEC/N samples exhibited improved corrosion potential (Ecorr) and corrosion current density (Jcorr)，reaching－0.451 V and 75.22 μA/cm2，respectively，although the lowfrequency impedance modulus (｜Z ｜0.01 Hz) showed no significant increase，reaching only 998.5 Ω·cm2.After loading Mg-Fe-LDHs，the PEC/N-LDHs samples demonstrated further improvements，with Ecorr，Jcorr and ｜Z ｜0.01 Hz reaching－0.355 V，39.11 μA/cm2 and 6 586.0 Ω·cm2，respectively，showing significant enhancement compared to both 20 steel and PEC/N samples.These results indicated that plasma electrolytic carbonitriding treatment of 20 steel could produce a carbonitrided layer with high hardness.Additionally，the hydrothermal loading of LDHs further improved the corrosion resistance of the composite infiltration layer without affecting its hardness.The PEC/N-LDHs composite infiltration layer thus achieved both high hardness and superior corrosion resistance.

A vapor-liquid adjustment evaporator exhibits superior heat transfer performance by adjusting vapor quality and mass flux. In this study, two vapor-liquid adjustment evaporators with circuitries of 4-2-4-6-4 (evaporator 1) and 5-4-3-4-4-4 (evaporator 2) are applied to heat pump water heaters (respectively referred to as systems A and B), and an experimental comparative study is conducted. The results show that compared with that in evaporator 1, the refrigerant is more uniformly distributed in evaporator 2, and its pressure drop is reduced by 10.91%. Under nominal working conditions, the heating capacity and power consumption of system B are reduced by 1.69% and 1.45%, respectively, compared to system A; the coefficients of performance (COPs) of the two systems are generally the same. The pressure at the compressor outlet of system B is 26.35-84.78 kPa lower than that of system A; this range is conducive to the safe operation of the compressor. At different ambient temperatures, the power consumption of the compressor of system B is lower than that of system A. When the ambient temperature is 30 ℃, the COP of system B is 2.1% higher than that of system A.

High-temperature thin-film strain sensors are advanced technological devices for monitoring stress and strain in extreme environments, but the coupling of temperature and strain at high temperature is a challenge for their use. Here, this issue is addressed by creating a composite ink that combines Pb2Ru2O6 and TiB2 using polysilazane (PSZ) as a binder. After direct writing and annealing the PSZ/Pb2Ru2O6/TiB2 film at 800 °C in air, the resulting thin film exhibits a low temperature coefficient of resistance (TCR) of only 281 ppm/°C over a wide temperature range from 100 °C to 700 °C, while also demonstrating high sensitivity with a gauge factor approaching 19.8. This exceptional performance is attributed to the intrinsic properties of Pb2Ru2O6, which has positive TCR at high temperature, and TiB2, which has negative TCR at high temperature. Combining these materials reduces the overall TCR of the film. Tests showed that the PSZ/Pb2Ru2O6/TiB2 film maintains stable strain responses and significant signal output even under varying temperature. These findings provide valuable insights for developing high-temperature strain sensors with low TCR and high sensitivity, highlighting their potential for applications in high-temperature strain measurements.

Scholarly discourse surrounding the thin film composite organic solvent nanofiltration (TFC OSN) membrane field has largely been dominated by focusing on the optimization of the selective layer. However, this often leaves the porous support layer, with its innate solvent resistance, cost-effectiveness, and superior permeability, in the shadows. This study presents a novel OSN membrane utilizing a polyethylene (PE) battery separator as the porous substrate. The structural affinity between ethylene-vinyl alcohol and PE facilitates efficient hydrophilic modification, which allows for uniform and compact polyamide selective layer formation through interfacial polymerization. The HPE-NF-1.0 membrane exhibits rejections of 99.5 ​%, 96.7 ​%, 100 ​%, and 97.2 ​% for Methyl Orange, Rhodamine B, Congo red, and Rose Bengal, respectively. It also shows a solvent flux of 52.5 LMH in methanol and robust resistance against alcoholic solvents and DMF. Using PE as the porous substrate, we bypass intricate and time-demanding cross-linking processes and complex pore-preservation post-treatments, providing a simplified strategy for TFC OSN membrane fabrication.

Hyper-uric acid (UA)-induced kidney injury (HAKI) is caused by the deposition of excess blood UA into the kidneys. We confined molecules of uricase (URI), catalase (CAT), and curcumin (Cur) to a single structure (UC/Cur) while retaining their enzymatic activities via a cross-linking complexation reaction between tannic acid and FeCl3 for treating HAKI. Simultaneously, bovine serum albumin (BSA)-UC/Cur nanoparticles were successfully prepared by interlinking the disulfide bonds of BSA with the enzyme complex via Tris(2-carboxyethyl) phosphine(TCEP) to form sulfhydryl groups. BSA-UC/Cur significantly attenuated MSU-induced NLRP3 inflammasome pathway activation and apoptosis in NRK-52e cells by eliminating UA crystals and intracellular reactive oxygen species. More importantly, treatment with BSA-UC/Cur stabilized blood UA concentrations and lowered proximal tubular protein levels, mitochondrial swelling, and fibrotic areas, renducing the expression of matrix metalloproteinase (MMP)2, MMP9, and NLRP3 while, increasing the expression of tight-junction proteins ZO1 and occludin as well as that of TIMP-1, in HAKI model rats. In addition, BSA-UC/Cur nanoparticles reduced the subpopulation ratios of CD8+ T cells and M1 macrophages and increased those of M2 macrophages and Treg cells. Preliminary in-vivo trials showed that long-term intravenous treatment with BSA-UC/Cur is safe. Therefore, BSA-UC/Cur could be a potential nanotherapeutic agent for HAKI.

The high efficacy of metro network services not only enhances residents’ travel quality but also brings significant socio-economic benefits, thus is of great importance to urban land use and city development. Existing methods for measuring metro service efficacy often overlook metro network connectivity and rely heavily on subjective questionnaire data analysis from the user experience perspective. This paper proposes a method to measure metro network service efficacy from the user’s perspective. The approach first calculates the connectivity index of metro network and estimates the housing premium brought by metro network connectivity, which reveals users’ willingness to pay for metro network connectivity. This method objectively measures metro network service efficacy from the user’s perspective. Based on this, efficacy optimization methods are proposed, providing quantitative simulation methods for metro expansion, site selection, operation quality adjustments, etc., which are of great reference value to metro management departments and even urban sustainable development.

Abstract The first-order antisymmetric (A1) mode lamb wave resonator (LWR) based on Z-cut LiNbO3 thin films has attracted significant attention and is widely believed to be a candidate for next-generation reconfigurable filters with high frequency and large bandwidth (BW). However, it is challenging for traditional interdigitated electrodes (IDTs) based LWR filters to meet the requirement of a clean frequency spectrum response and enough out-of-band (OoB) rejection. To solve the problem, we propose LWRs with checker-shaped IDTs for the design of filters that meet the Wi-Fi 6E standard. By taking advantage of checker-shaped IDTs with unparalleled boundaries, the fabricated 6-GHz resonators successfully suppress higher-order A1 spurious modes, demonstrating a spurious-free impedance response and a high figure-of-merit (FOM) up to 104. Based on the demonstrated checker-shaped electrode design, the filter features a center frequency (f 0 ) of more than 6 GHz, a 3 dB BW exceeding 620 MHz, and an excellent OoB rejection >25 dB, consistent with the acoustic-electric-electromagnetic (EM) multi-physics simulations. Furthermore, through the capacitance-inductance matching network technology, the filter’s voltage standing wave ratio (VSWR) is successfully reduced below 2, showing an excellent 50 Ω impedance matching. This study lays a foundation for ultra-high-frequency and ultra-wideband filters for the Wi-Fi 6/6E application.

Purposes Hydrogen energy, as an efficient and clean secondary energy in the 21st century with its high heat value and extremely environmentally friendly combustion products, has become the most promising alternative energy source to replace traditional fossil fuels. The necessity of hydrogen development, promotion, and utilization under the dual-carbon goal of “carbon peaking in 2030 and carbon neutralvty in 2060” as well as the current hydrogen energy development policies and strategic layout in China are analyzed. Methods By investigating the research progresses and achievements of green hydrogen production technologies, the technology of hydrogen production by water splitting and its main devices are summarized, and the development status and trend of hydrogen production by water splitting and the related devices are reviewed. The research status of electrolytic cell and its important components (such as membrane electrode assembly, hydrogen tension bolt assembly and end pressure plate) and the main problems existing in key equipment are analyzed, and the future development trend of alkaline electrolytic cell and proton etchange membrane electrolytic cell are prospected. Conclusion This review provides a reference for the future development of hydrogen production equipment.

The dense deployment of Femto Base Stations (FBS) assisting Macro Base Stations (MBS) in a Heterogeneous Network (HetNet) resolves the coverage issue of 5G signal transmission. However, the imprudent layout of FBSs results in extensive energy consumption and increased signal interference among base stations. Regulating the transmission power of each base station in the HetNets through the main controller or MBS is essential to maximize the power efficiency of the entire HetNets while adhering to the constraints of basic signal throughput and fairness. To address this challenge, this paper proposes an Adaptive Acceleration Particle Swarm Optimization (AA-PSO) algorithm. This algorithm dynamically determines the inertia weight based on each particle’s optimal position and the global optimal position, and introduces the concept of time-varying parameters to control the learning rate, thus managing the search range and convergence speed of the particle swarm. The results demonstrate that the AA-PSO algorithm can efficiently determine the optimal transmission power of each base station in the HetNets, reduce interference between MBS and FBSs, as well as among FBSs, and ultimately improve the service efficacy of the entire network.

As a neutron shielding material for spent fuel storage， Ni-Cr-Mo-Gd alloy has broad application prospects， but it is prone to cracking during thermal working. In order to optimize the hot deformation process parameters of the alloy，this paper focuses on the study of Ni-Cr-Mo alloy， investigating the microstructural changes induced by the addition of Gd. Isothermal hot compression experiments were conducted at deformation temperatures of 1000 ℃-1200 ℃ and strain rates of 0.01 s-1-5 s-1 to calculate the relevant material constants and the activation energy for thermal deformation. Thermal working map was established to determine thermal deformation window， while the influence of Gd element on the thermal deformation behavior of the alloy was analyzed in conjunction with the microstructure. The results indicate that the addition of 1.2% Gd to the Ni-Cr-Mo alloy reduces the deformation activation energy from 472.15 kJ/mol to 422.9 kJ/mol. This results in higher energy consumption efficiency during thermal deformation and more comprehensive microstructure evolution. The plastic instability zone gradually shifts from high to low temperatures， expanding the safe deformation zone of the alloy at low temperatures of 1 000 ℃-1 060 ℃ and low strain rates of 0.01 s-1-0.32 s-1. Optimal thermal deformation zone for alloy is determined to be a true strain of 0.5 at temperatures of 1 113 ℃-1 164 ℃ and strain rates of 0.01 s-1-0.2 s-1. Gd precipitates as the intermetallic compound GdNi5 at grain boundaries or dendrite interfaces. The presence of GdNi5， as a hard brittle phase， leads to significant strain accumulation during the thermal deformation process， resulting in higher stored energy in the microstructure， thereby promoting recrystallization of the surrounding deformed grains and reducing the residual strain in the microstructure.

Abstract This study investigated how structural parameters (including injection ducts and exhaust nozzle inner diameters) affect the internal flow field and dilution ratio of diesel particulate sampling diluters. Increasing air injection duct diameter increased the injection chamber pressure and decreased the air velocity peak, mixed gas flow velocity, sample temperature, and mixing rate. Excessively small tube diameters caused uneven and discontinuous flow field distributions, while substantial air blockage rendered the flow state poor. Increasing nozzle inner diameters increased the exhaust flow area and the sample temperature, but decreased the velocity of the exhaust and gas mixtures and the pressure drop. Compared with a 2.0 mm inner diameter, 2.5 and 3.0 mm diameters decreased the peak velocity by 11.18% and 14.41%, respectively, and mixing slowed significantly. Inner nozzle diameters of

Abstract The coalbed methane (CBM) productivity is directly determined by the fracture permeability during hydraulic fracturing, which is regulated by the distribution of proppants. The proppant may be unevenly distributed in the fracture because of variables like the architecture of the fracture and the characteristics of the sand‐carrying fluid. This study used two types of random functions to produce different ununiform distributions of proppant clusters in large‐scale fractures, with the aim of investigating the effect of these distributions on the overall permeability of the fracture. A model of fluid‐structure coupling is proposed. The closure of large‐scale fractures under in‐situ stress is analyzed using solid mechanics and the penalty function; the CBM flowing in proppant clusters and the high‐speed channel between them is simulated using Darcy's law and the Navier–Stokes equation, respectively; and the overall permeability of fractures is computed using the fluid pressure drop throughout the fracture and the fluid flowing velocity in the fracture's outlet. Since most CBM flows along high‐speed channels between the proppant clusters, the simulated findings show that the overall permeability of fractures with an uneven distribution of proppant clusters is significantly higher than that of the proppant cluster itself. As CBM becomes more discretely distributed, the proportion of CBM flowing within the proppant cluster continuously drops. As the permeability of the proppant cluster increases, the volume ratio of proppant clusters decreases, and the distribution of proppant clusters becomes more discrete, the overall permeability of the fracture continuously increases.

Abstract Simultaneously achieving high sensitivity and detection speed with traditional solid-state biosensors is usually limited since the target molecules must passively diffuse to the sensor surface before they can be detected. Microfluidic techniques have been applied to shorten the diffusion time by continuously moving molecules through the biosensing regions. However, the binding efficiencies of the biomolecules are still limited by the inherent laminar flow inside microscale channels. In this study, focused traveling surface acoustic waves were directed into an acoustic microfluidic chip, which could continuously enrich the target molecules into a constriction zone for immediate detection of the immune reactions, thus significantly improving the detection sensitivity and speed. To demonstrate the enhancement of biosensing, we first developed an acoustic microfluidic chip integrated with a focused interdigital transducer; this transducer had the ability to capture more than 91% of passed microbeads. Subsequently, polystyrene microbeads were pre-captured with human IgG molecules at different concentrations and loaded for detection on the chip. As representative results, ~0.63, 2.62, 11.78, and 19.75 seconds were needed to accumulate significant numbers of microbeads pre-captured with human IgG molecules at concentrations of 100, 10, 1, and 0.1 ng/mL (~0.7 pM), respectively; this process was faster than the other methods at the hour level and more sensitive than the other methods at the nanomolar level. Our results indicated that the proposed method could significantly improve both the sensitivity and speed, revealing the importance of selective enrichment strategies for rapid biosensing of rare molecules.

Highlights Si/C Composite and Nanostructure Engineering: Advanced Si/C composites and multidimensional nanostructures address key challenges in silicon anodes, like volume expansion and unstable SEI, enhancing LIBs performance. Artificial SEI, Prelithiation, and Binders: Focus on stable artificial SEI layers, efficient prelithiation, and cutting-edge binders to improve Coulombic efficiency and reduce capacity loss, enhancing Si anode durability and efficiency. Real-World Application and Scalability: Analysis of these strategies highlights scalability and commercial viability, transitioning Si-anode technologies to practical, high-performance LIBs applications.

As a clean energy source, shale gas plays a crucial role in mitigating the supply–demand imbalance of natural gas and in facilitating the transition to a low-carbon economy. This study employs a system dynamics model to forecast future production trends in shale gas in China, analyze its implications for the natural gas supply–demand structure, and explore pathways for sustainable development. Firstly, by integrating the characteristics of China’s shale gas resources, market dynamics, and policy frameworks, the key factors influencing production are identified, and their interrelationships are systematically analyzed. Subsequently, a causal loop diagram is constructed using the VENSIM software(VENSIM PLE 9.3.5 x64), a set of representative variables is selected, and the logical relationships among these variables are established through a multivariate statistical analysis, culminating in the development of a production forecasting model for China’s shale gas (stock and flow diagram). Finally, based on parameter assumptions, this study predicts the production trends in shale gas in China under multiple scenarios. The forecasting results reveal that China’s shale gas production is expected to grow at an average annual rate of 3.32% to 8.02%, with production under the reference scenario projected to reach 724.22 × 108 m3 by 2040. However, the growth of shale gas production over the next two decades remains limited, accounting for a maximum of 12.07% of the total natural gas consumption, underscoring its transitional role in the low-carbon transformation. To address these challenges, this study proposes four policy recommendations: (1) prioritize the development of shallow, high-quality gas-bearing blocks while gradually transitioning to deeper formations; (2) intensify technological innovation in deep shale gas extraction to enhance recovery rates and mitigate production decline rates; (3) implement flexible production subsidies and moderately increase natural gas sales prices to incentivize production and optimize resource allocation; and (4) strengthen ecological conservation and improve water resource management to ensure the sustainable development of shale gas.

The size distribution of rock fragments significantly influences subsequent operations in geotechnical and mining engineering projects. Thus, accurate prediction of this distribution according to the relevant blasting design parameters is essential. This study employs artificial intelligence methods to predict the fragmentation of open-pit bench blasting. The study employed a dataset comprising 97 blast fragment samples. Random forest and XGBoost models were utilized as base learners. A prediction model was developed using the stacking integrated strategy to enhance predictive performance. The model’s performance was evaluated using the coefficient of determination (R2), the mean square error (MSE), the root mean square error (RMSE), and the mean absolute error (MAE). The results indicated that the model achieved the highest prediction accuracy, with an R2 of 0.943. In the training set, the model achieved MSE, RMSE, and MAE values of 0.00269, 0.05187, and 0.03320, while in the testing set, these values were 0.00197, 0.04435, and 0.03687, respectively. The model was validated using five sets of actual blasting block data from a northeastern mining area, which yielded more accurate prediction results. These findings demonstrate that the stacking strategy effectively enhances the prediction performance of a single model and offers innovative approaches to predicting blasting block size.

As mining operations extend to greater depths, they encounter critical challenges, including increased distances and substantial energy losses. To address the challenges of cold-energy loss in deep mine cooling systems and improve the working environment for miners, a long-distance sleeve-type insulated pipe system was developed. This system aims to mitigate thermal energy loss caused by heat transfer between the pipe and surrounding soil throughout the water transport path from the source to the deep mine in boreholes. A heat transfer analysis model was developed to assess the impact of variables such as transport time, water flow rate, inlet temperature, and insulation materials on the temperature of cold water. The study reveals that the temperature of cold water increases rapidly during transportation before reaching a stable state. Implementing modifications such as increasing the inlet temperature, enhancing the water flow rate, or utilizing materials with lower thermal conductivity can effectively mitigate temperature rises. Additionally, the novel sleeve-type design enhanced the pipe’s pressure-bearing capacity, reduced the required pipe length by 4752 m and minimized energy loss compared to traditional systems. In practical applications, after 45 h, the supply and return water temperatures increased by 0.45 °C and 0.38 °C, respectively, while maintaining cooling energy loss below 12%. This innovative solution improves mine cooling efficiency and provides guidance to reduce cold-energy loss.

In order to address the safety construction issues of tunnels in karst areas, this study investigated the stability and instability time prediction of the roof of karst tunnels based on catastrophe theory. By establishing a discrimination equation for the sudden instability of the tunnel roof arch based on the elastic beam model and considering factors such as the self-weight of surrounding rocks and the position of caves, the calculation formula for the safety thickness of the roof of the karst tunnel was obtained. The study analyzed the impact of relevant factors on the safety thickness of the roof. Furthermore, a new method for predicting the instability of the tunnel roof arch was proposed, and it was validated through engineering examples. The results indicate that the water pressure in caves, the size of caves, the elasticity modulus of surrounding rocks, and the position of caves have extremely adverse effects on the safety of the arch roof. The calculation formula for the safety thickness of the roof of the karst tunnel derived from the theory of sudden change demonstrates feasibility and high accuracy in practical engineering applications. The established model for predicting roof instability can effectively forecast the time of roof arch instability in karst tunnels.

At present, the use of mobile LiDAR systems (MLS) to collect environmental information and generate roadside pole-shaped object inventories is limited by equipment costs and has poor real-time performance. Although LiDAR-based simultaneous localization and mapping (SLAM) techniques have been widely applied in the navigation field, research on simultaneous real-time localization and creation of roadside pole-shaped object inventories remains absent. In this regard, this paper proposes an approach that utilizes LiDAR technology to achieve vehicle localization and create roadside pole-shaped object inventories complete with absolute locations. The aim is to devise an accurate and robust system for vehicle localization and the creation of roadside pole-shaped object inventories. Firstly, LiDAR was integrated with inertial measurement units (IMU) and global navigation satellite system (GNSS), to achieve accurate pose estimations and simultaneous generation of global maps. Secondly, an optimized fusion positioning algorithm based on sliding windows is constructed, to enhance system robustness through effectively integrating data from multiple sensors. Then, a method for creating pole-shaped object inventories is proposed using an SLAM feature extraction algorithm, thereby reducing the computational expense for simultaneous vehicle positioning and roadside pole-shaped object inventory creation. Finally, extensive evaluations are conducted using real datasets covering various road scenarios, including urban and suburban areas. The experimental results demonstrated the centimeter-level vehicle positioning accuracy of the proposed system in real-time automatic creation of roadside pole-shaped object inventories, boasting an average positioning error within 3 cm.

Highlights An ultraconformable skin-like integrated wireless charging micro-supercapacitor (IWC-MSC) could be wireless charged to store electricity into high capacitive micro-supercapacitors (11.39 F cm−3), and fits well with human surface. Building blocks of IWC-MSC skin are all evaporated by liquid precursor, and each part of the device attached firmly benefitting from the liquid permeation, forming a compact and all-in-one configuration. The electrode thickness easily regulated varying from 11.7 to 112.5 μm by controlling the volume of electrode solution precursor.

This paper develops a system–component integrated design method for a closed Brayton cycle in a nuclear-powered emergency power vehicle, optimizing the thermodynamic performance by varying the maximum operating temperature and pressure, minimum operating temperature, helium–xenon gas molar mass, and PCHE parameters to maximize the specific power and thermal efficiency. The key results are as follows: (1) The maximum allowable pressure decreases with the temperature, and the specific power increases for both the SRC and the IRC without considering the ultimate heat sink. (2) The PCHE weight is minimized at a helium–xenon gas molar mass of 25 g/mol, while the turbomachine’s weight decreases with an increasing molar mass, leading to an overall system weight reduction. (3) The thermal efficiency decreases with lower minimum operating temperatures, optimizing at 350 K due to a precooler weight increase. (4) The thermal efficiency plateaus after a certain number of PCHE channels, with the recuperator effectiveness significantly impacting the performance. (5) The SRC, with a specific power and a thermal efficiency of 194.38 kW/kg and 39.19%, is preferred over the IRC for the SIMONS due to its mobility and rapid deployment. This study offers a comprehensive analysis for optimizing closed Brayton cycle systems in emergency power applications.

The vortex-induced vibration of a circular cylinder and two inline circular cylinders near a plane wall at a Reynolds number of 150 is numerically investigated by using a self-developed immersed boundary method called the local domain-free discretization (DFD) method. The cylinders are elastically mounted with a mass ratio of 8/π and a 0 damping ratio and can only vibrate in the transverse direction. The reduced velocity varies from 2 to 9, with an interval of 1. Three gaps, e=0.1D, 1D, and 2D (D is the cylinder diameter), are investigated for the case of an isolated cylinder and two inline cylinders while the center-to-center spacing (L) is 1.5D for the two-inline-cylinders case. A model for the collision of the cylinders with the wall is adopted in which the bouncing back is forced when the gap between the cylinder and the plane wall is smaller than 0.02D. It is observed that the existence of the plane wall significantly affects the cylinder response both in the one-isolated-cylinder and two-inline-cylinders cases. The features, including vibration amplitudes, frequencies, fluid forces, the maximal or minimal gap between the cylinder bottom and the plane wall, and the vortex shedding patterns, are explored in detail. Interactions between the front and rear cylinders and differences between the one-isolated-cylinder and two-inline-cylinders cases are discussed. The research has immense significance for the design of near-wall cylindrical structures, such as the deep-water pipeline system on the seafloor.

A centrifugal pump incorporating two inlets and a double-layered impeller is proposed for transporting a mixture of sand and water. The double-layered impeller (primary impeller) encircles a secondary impeller. To reveal the operating and flow characteristics of such a pump, numerical work is conducted with a validated numerical method. The effects of the feed rate of sand and the rotational speed of the impeller are investigated. The results show that the pump efficiency is not monotonically related to the solid volume fraction. At a feed rate of sand of 2.10 m3/min and a rotational speed of 950 rpm, the lowest pump efficiency is reached. In the volute chamber, vortices of various sizes are evidenced. With increasing rotational speed, the overall solid volume fraction in the pump decreases. Meanwhile, when the solid volume fraction attains 0.28, sand particles tend to accumulate near the outer rim of the volute chamber. The axial force acting on the primary impeller increases with the rotational speed. Under different operating conditions, the radial forces point unanimously toward the third and fourth quadrants.

Reconstructing the three-dimensional thermal structure of the ocean under typhoon conditions presents significant challenges due to the scarcity of observational data, particularly in subsurface regions, and the limitations of existing observation methods in terms of spatial and temporal resolution. Accurate reconstruction of these structures is crucial for understanding the energy exchange between the ocean and typhoons, as this exchange directly influences typhoon intensity and trajectory. To address these challenges, this study introduces a fully connected transformer network (FCT), which integrates fully connected layers with a transformer model. The FCT model leverages the attention mechanisms inherent in the transformer architecture to effectively extract and integrate multi-scale ocean dynamical features. Using data from Typhoon Lekima in 2019, this study reconstructs ocean thermal structures at various depths and achieves an RMSE of 1.03 °C and an MAE of 0.83 °C when validated against Argo data. Furthermore, the model’s robustness was demonstrated through five-fold cross-validation, with the validation loss exhibiting minor fluctuations across folds but remaining stable overall, with an average validation loss of 0.986 °C, indicating the model’s generalizability. Sensitivity analysis also revealed the model’s resilience to variations in key input variables, showing minimal impact on output even with perturbations of up to 10% in input data. In addition, the study incorporates content analysis of typhoon-related news reports from 2011 to 2020, revealing a predominance of political topics, which underscores the central role of government in disaster response, with economic and ecological topics following. This integrated approach not only enhances our understanding of the interactions between ocean thermal structures and typhoon dynamics but also provides valuable insights into the societal impacts of typhoons, as reflected in media coverage, contributing to improved disaster management strategies.

To address the inherent limitations of Future in asynchronous programming frameworks, JDK 1.8 introduced the CompletableFuture class, which features approximately 50 different methods for composing and executing asynchronous computations and handling exceptions. This paper proposes an automatic refactoring method that integrates multiple static analysis techniques, including visitor pattern analysis, alias analysis, and executor inheritance structure analysis, to conduct precondition checks. Distinct from existing Future refactoring methods, this approach considers custom executor types, thereby extending its applicability. Using this method, the ReFuture automatic refactoring plugin was implemented within the Eclipse JDT framework. The method was evaluated in terms of the number of refactorings, refactoring time, and error introduction, alongside a side-by-side comparison with the existing method. The refactoring outcomes for nine large applications, including ActiveMQ, Hadoop, and Elasticsearch, show that ReFuture successfully refactored 639 out of 813 potential code structures, achieving a refactoring success rate of 64.70% without introducing errors. This tool effectively facilitates the refactoring to CompletableFuture and enhances refactoring efficiency compared to manual methods.

The transport of fission products in molten salt reactors has attracted much attention. However, few codes can completely describe the transport characteristic, though the migration of fission products in the molten salt reactor is essential to estimate the source term, decay heat, and radiation shielding. This study built a program named ThorFPMC (Thorium Fission Products Migration Code) that can handle the multi-physics transport characteristic based on the flow burnup code ThorMODEc (Thorium MOlten Salt Reactor Specific DEpletion Code). A problem-related depletion chain compression method was applied to decrease the order of the solve matrix. The matrix exponential and splitting methods were applied to solve the steady state and transient calculation, respectively. Error analysis showed that for a specific problem, the simplified depletion chain matrix index method could solve the fission products migration equation with an arbitrary time-step with high speed (s) and high precision (10−4); the splitting method could reach a precision of 10−2 level for the full fuel depletion chain, multi-nodes, and transient problems. Compared to the Strang splitting method, the perturbation splitting method has higher precision and less time consumption. In summary, the developed programmer could describe the migration effect of fission products in molten salt reactors, which provides a significant tool for the design of molten salt reactors.

Highlights The tailored KCoMnNiMgZnF3-HEC cathode delivers extremely high discharge capacity (22,104 mAh g−1), outstanding long-term cyclability (over 500 h), preceding majority of traditional catalysts reported. Entropy effect of multiple sites in KCoMnNiMgZnF3-HEC engenders appropriate regulation of 3d orbital structure, leading to a moderate hybridization with the p orbital of key intermediate. The homogeneous nucleation of Li2O2 is achieved on multiple cation site, contributing to effective mass transfer at the three-phase interface, and thus, the reversibility of O2/Li2O2 conversion.

Abstract The hydraulic turbine in turbine mode (TMHT) has significant advantages in residual energy recovery, but rapid optimization of its runner parameters has always been a challenge. To address this issue, the optimization algorithm ISMA‐BPNN is proposed based on the improved slime mold algorithm (ISMA) and back propagation neural network (BPNN). First, an efficiency characteristic neural network (ECNN) and a water head characteristic neural network (HCNN), which take the geometric parameters of the runner as input, and the efficiency and water head as outputs, respectively, are constructed by combining the orthogonal test‐based sample data, computational fluid dynamics (CFD), and BPNN. Then, the slime mold algorithm is improved and the optimal runner geometric parameters are obtained based on the ISMA, ECNN, and HCNN, to achieve rapid optimization of the TMHT runner. Finally, the CFD‐based numerical calculation accuracy is verified through real machine tests, and the feasibility of the ISMA‐BPNN‐based rapid optimization strategy for TMHT performance is further verified through CFD numerical simulation.

Highlights Covalent organic frameworks (COFs) show enormous potential for building high-performance electrochemical sensors due to their high porosity, large specific surface areas, stable rigid topology, ordered structures, and tunable pore microenvironments. The basic properties, monomers, and general synthesis methods of COFs in the electroanalytical chemistry field are introduced, with special emphasis on their usages in the fabrication of chemical sensors, ions sensors, immunosensors, and aptasensors. The emerged COFs in the electrochemiluminescence realm are thoroughly covered along with their preliminary applications.

The necessity for a shift to alternative forms of energy is highlighted by both approaching consequences of climate change and limited availability of fossil fuels. While a large portion of energy required can be generated by solar and wind, a diverse, sustainable energy generation mix is still necessary to meet our energy needs. By capturing otherwise lost heat energy and turning it into valuable electrical energy, thermoelectric can play a significant part in this. Using the Seebeck effect, thermoelectric generators (TEG) have established their capability to transform thermal energy into electrical energy directly. Furthermore, because they do not include chemical compounds, they are silent in operation and can be built on various substrates, including silicon, polymers, and ceramics. Moreover, thermoelectric generators have a long operational lifetime, are position independent, and may be integrated into bulky, flexible devices. However, the low conversion efficiency of TEG has confined their broad application, hampering them to an academic subject. Until now, recent developments in thermoelectric generators and devices are presuming the technology to catch its place among state-of-the-art energy conversion systems. This review presents the commonly used methods for producing thermoelectric modules (TEMs) and the materials currently studied for TEMs in bulk and printed thermoelectric devices.

Abstract The increasing demand for high‐performance devices on heat dissipation makes it approach the bottleneck even for metals with high thermal conductivities. The coating of only one layer of graphene, the heat dissipation performances of Cu, Ag, and Al can be further enhanced, e.g., with a maximum temperature reduction by ≈9% for a Cu foil is demonstrated. Molecular dynamics (MD) analysis of spectral phonon transmission reveals that low‐frequency phonons play a significant role in the thermal transport within the Cu/single‐layer graphene (SLG) system, and the high‐frequency phonons exhibit substantial mismatch. It suggests that the thermal anisotropy of graphene enables a rapid heat dispersion in the in‐plane direction and provides an effective thermal insulation in the out‐of‐plane direction. The thermal conductivity calculations demonstrate an enhanced participation of phonons in heat conduction by the graphene layer, indicating a novel heat conduction mechanism in the Cu/single‐layer graphene system. These findings highlight the positive impact of graphene on the heat conduction of metals, and they will hold crucial implications for the design and application of graphene‐based thermal devices is believed.

The future intelligent era that will be brought about by 5G technology can be well predicted. For example, the connection between humans and smart wearable devices will become increasingly more intimate. Flexible wearable pressure sensors have received much attention as a part of this process. Nevertheless, there is a lack of complete and detailed discussion on the recent research status of capacitive pressure sensors composed of polymer composites. Therefore, this article will mainly discuss the key concepts, preparation methods and main performance of flexible wearable capacitive sensors. The concept of a processing “toolbox” is used to review the developmental status of the dielectric layer as revealed in highly cited literature from the past five years. The preparation methods are categorized into types of processing: primary and secondary. Using these categories, the preparation methods and structure of the dielectric layer are discussed. Their influence on the final capacitive sensing behavior is also addressed. Recent developments in the electrode layer are also systematically reviewed. Finally, the results of the above discussion are summarized and future development trends are discussed.

Electronic skin and flexible wearable devices have attracted tremendous attention in the fields of human-machine interaction, energy storage, and intelligent robots. As a prevailing flexible pressure sensor with high performance, the piezoresistive sensor is believed to be one of the fundamental components of intelligent tactile skin. Furthermore, graphene can be used as a building block for highly flexible and wearable piezoresistive sensors owing to its light weight, high electrical conductivity, and excellent mechanical. This review provides a comprehensive summary of recent advances in graphene-based piezoresistive sensors, which we systematically classify as various configurations including one-dimensional fiber, two-dimensional thin film, and three-dimensional foam geometries, followed by examples of practical applications for health monitoring, human motion sensing, multifunctional sensing, and system integration. We also present the sensing mechanisms and evaluation parameters of piezoresistive sensors. This review delivers broad insights on existing graphene-based piezoresistive sensors and challenges for the future generation of high-performance, multifunctional sensors in various applications.

In this paper, the temperature field variation and cumulative oil production rate over time with fracture number, fracture width and gas injection flow rate were investigated using Fluent software. A mathematical model of heat transfer within oil shale and a three-dimensional mathematical model of its in situ heating and fracturing were established. The simulation results showed that Model II had the highest oil shale heating rate at different fracture numbers, being 26.32% higher than that of Model I. When exploring fracture width, Model I completed all fractures in the oil shale region in 190 days. Model IV was 15 days slower than Model I with the heating rate being 7.89% lower, while Model V was 10 days faster than Model I with the heating rate being 5.26% higher. Increasing the fracture width of the oil shale region appropriately could help to increase the oil shale in-situ heating and fracturing rate. Considering gas injection flow rate, the higher the gas flow rate, the faster the increase of the oil shale area temperature and the shorter the time to reach the 10-day peak oil production rate. The peak was also larger and the fracturing of the oil shale area took place more quickly.

Abstract Conventional manufacturing techniques to fabricate microfluidic chips, such as soft lithography and hot embossing process, have limitations that include difficulty in preparing multiple-layered structures, cost- and labor-consuming fabrication process, and low productivity. Digital light processing (DLP) technology has recently emerged as a cost-efficient microfabrication approach for the 3D printing of microfluidic chips; however, the fabrication resolution for microchannels is still limited to sub-100 microns at best. Here, we developed an innovative DLP printing strategy for high resolution and scalable microchannel fabrication by dosing- and zoning-controlled vat photopolymerization (DZC-VPP). Specifically, we proposed a modified mathematical model to precisely predict the accumulated UV irradiance for resin photopolymerization, thereby providing guidance for the fabrication of microchannels with enhanced resolution. By fine-tuning the printing parameters, including optical irradiance, exposure time, projection region, and step distance, we can precisely tailor the penetration irradiance stemming from the photopolymerization of the neighboring resin layers, thereby preventing channel blockage due to UV overexposure or compromised bonding stability owing to insufficient resin curing. Remarkably, this strategy can allow the preparation of microchannels with cross-sectional dimensions of 20 μm × 20 μm using a commercial printer with a pixel size of 10 μm × 10 μm; this is significantly higher resolution than previous reports. In addition, this method can enable the scalable and biocompatible fabrication of microfluidic drop-maker units that can be used for cell encapsulation. In general, the current DZC-VPP method can enable major advances in precise and scalable microchannel fabrication and represents a significant step forward for widespread applications of microfluidics-based techniques in biomedical fields.

To improve the problem of difficulty in forming a complete and dense conversion film on the copper surface when using phytic acid alone，the conversion films containing phytic acid (PA) and different azole derivatives were prepared on copper surface by impregnation method.The hydrophobicity，corrosion resistance and surface morphology of the conversion films were characterized by contact angle tester，electrochemical workstation，scanning electron microscope and energy dispersive spectroscopy (EDS).The film formation mechanism of PA+BTA conversion film with the best corrosion resistance was analyzed using X-ray electron spectroscopy (XPS).Results showed that the corrosion resistance of conversion films formed by adding different azole derivatives was improved.The contact angle of the conversion film with benzotriazole (BTA) and phytic acid reached maximum value (135.51 °)，and the corrosion current density reached minimum value (2.050 × 10-7 A/cm2)，while the impedance value exceeding 90 kΩ.By observing the SEM morphology of PA+BTA conversion film，it was found that the conversion film was evenly distributed and dense on the surface of copper substrate.XPS analysis of the PA+BTA conversion film showed that both PA and BTA were involved in the formation of the conversion film.PA-Cu and BTA-Cu complexes were formed on the surface of copper substrate，which could effectively protect the substrate.

The carbon emissions trading market is an essential tool for addressing climate change. The carbon emissions trading market has a relatively short history, and the research and management of risks in this market require further development. This paper takes as its research object 1272 pieces of English literature studies published by international scholars and featured on the Web of Science between 2002 and 2024. It uses CiteSpace software to categorize changes in the trends related to carbon market risk research based on time, space, and keyword clustering mapping. The results reveal the following: (1) In terms of the timeline, the risk evolution of the international carbon market is divided into an embryonic period (2002–2007), a developmental period (2008–2018), and a prosperous period (2019–2024); (2) from the perspective of spatial distribution, carbon market risk research institutions are multipolar, with China, the United States, and the United Kingdom, among other countries, issuing more studies on the topic; these studies mainly emerge from universities and research institutions; and (3) in terms of research hotspots, they revolve around four disciplinary issues, namely, primary research related to carbon market risk, carbon market risk categories, carbon market risk measurement, and response programs.

The low specific speed centrifugal pump plays a crucial role in industrial applications, and ensuring its efficient and stable operation is extremely important for the safety of the whole system. The pump must operate with an extremely high head, an extremely low flow rate, and a very fast speed. The internal flow structure is complex and there is a strong interaction between dynamic and static components; consequently, the hydraulic excitation force produced becomes a significant factor that triggers abnormal vibrations in the pump. Therefore, this study focuses on a low specific speed centrifugal pump and uses a single-stage model pump to conduct PIV and pressure pulsation tests. The findings reveal that the PIV tests successfully captured the typical jet-wake structure at the outlet of the impeller, as well as the flow separation structure at the leading edge of the guide vanes and the suction surface. On the left side of the discharge pipe, large-scale flow separation and reverse flow happen as a result of the flow-through effect, producing a strong vortex zone. The flow field on the left side of the pressure chamber is relatively uniform, and the low-speed region on the suction surface of the guide vanes is reduced due to the reverse flow. The results of the pressure pulsation test showed that the energy of pressure pulsation in the flow passage of the guide vane occurs at the fBPF and its harmonics, and the interaction between the rotor and stator is significant. Under the same operating condition, the RMS value distribution and amplitude at fBPF of each measurement point are asymmetric in the circumferential direction. The amplitude of fBPF near the discharge pipe is lower, while the RMS value is higher. A complex flow structure is shown by the larger amplitude and RMS value of the fBPF on the left side of the pressure chamber. With the flow rate increasing, the energy at fBPF of each measurement point increases first and then decreases, while the RMS value decreases, indicating a more uniform flow field inside the pump.

We propose an accurate method for modeling acoustic wave propagation. The spatial derivatives are calculated using Fourier transform to reduce spatial numerical dispersion. The standard staggered grid is adopted to suppress the non-causal ringing artifacts as in the traditional pseudo-spectral method. Moreover, to eliminate time dispersion arising from the discretization of the time derivative, an additional time-dispersion elimination term is introduced. As a result, the present method not only retains the advantages of the conventional pseudo-spectral method such as coarser spatial sampling or higher spatial derivative approximation accuracy, but also achieves higher temporal derivative approximation accuracy due to the adoption of the additional time-dispersion elimination term. Numerical examples demonstrate that the temporal dispersion elimination process can be contaminated by spatial numerical dispersion. Thus, the temporal and spatial numerical dispersions should be handled simultaneously, as proposed in this paper, to achieve accurate acoustic simulation.

This study proposes a concrete dam underwater apparent defect detection algorithm named YOLOv8s-UEC for intelligent identification of underwater defects. Due to the scarcity of existing images of underwater concrete defects, this study establishes a dataset of underwater defect images by manually constructing defective concrete walls for the training of defect detection networks. For the defect feature ambiguity that exists in underwater defects, the ConvNeXt Block module and Efficient-RepGFPN structure are introduced to enhance the feature extraction capability of the network, and the P2 detection layer is fused to enhance the detection capability of small-size defects such as cracks. The results show that the mean average precision (mAP0.5 and mAP0.5:0.95) of the improved algorithm are increased by 1.4% and 5.8%, and it exhibits good robustness and considerable detection effect for underwater defects.