bluuebunny/crossref_metadata_2025 huggingface dataset:
Hierarchical ion interactions in the direct air capture of CO2 at air/aqueous interfaces
Authors: Premadasa Uvinduni I. , Kumar Nitesh , Stamberga Diana , Bocharova Vera , Damron Joshua T. , Li Tianyu , Roy Santanu , Ma Ying-Zhong , Bryantsev Vyacheslav S. , Doughty Benjamin
Published: October 2024

The direct air capture (DAC) of CO2 using aqueous solvents is plagued by slow kinetics and interfacial barriers that limit effectiveness in combating climate change. Functionalizing air/aqueous surfaces with charged amphiphiles shows promise in accelerating DAC; however, insight into these interfaces and how they evolve in time remains poorly understood. Specifically, competitive ion interactions between DAC reagents and reaction products feedback onto the interfacial structure, thereby modulating interfacial chemical composition and overall function. In this work, we probe the role of glycine amino acid anions (Gly−), an effective CO2 capture reagent, that promotes the organization of cationic oligomers at air/aqueous interfaces. These surfaces are probed with vibrational sum frequency generation spectroscopy and molecular dynamics simulations. Our findings demonstrate that the competition for surface sites between Gly− and captured carbonaceous anions (HCO3−, CO32−, carbamates) drives changes in surface hydration, which in turn tunes oligomer ordering. This phenomenon is related to a hierarchical ordering of anions at the surface that are electrostatically attracted to the surface and their ability to compete for interfacial water. These results point to new ways to tune interfaces for DAC via stratification of ions based on relative surface propensities and specific ion effects.
Mechanism of frequency-dependent gate breakdown in p-GaN/AlGaN/GaN HEMTs
Authors: Yin Yulian , Liu Xiaoyu , Tang Xi , Xie Xuan , Wang Huan , Zhao Changhui , Yang Shu
Published: October 2024

In this Letter, time-dependent gate breakdown (TDB) characteristics under dynamic switching conditions were investigated in p-GaN/AlGaN/GaN high-electron-mobility transistors (HEMTs) with either Schottky-type or Ohmic-type gates. The dynamic TDB of the Schottky-type devices increased with frequencies ranging from 100 Hz to 100 kHz, while that of the Ohmic-type devices remained frequency-independent. This was analyzed by the frequency-dependent electroluminescence (EL) characteristics on both types of devices with semi-transparent gate electrodes. The electroluminescence (EL) emission intensity of Schottky-type devices increased with elevated frequencies, notably for blue and ultraviolet emissions, which exhibited a pronounced positive correlation with frequency. In contrast, the EL emissions of Ohmic-type devices were frequency-independent. Energy band diagrams were drawn to explain the different TDB and EL behaviors between two types of devices. The frequency-enhanced EL emissions of the Schottky-type devices indicated the frequency-enhanced hole injection and radiative recombination, which then suppressed the hot-electron effects on the metal/p-GaN junction and enhanced the dynamic TDB in p-GaN/AlGaN/GaN HEMTs.
Weyl points in a twisted multilayer photonic system
Authors: Abrashuly Aivar , Guo Cheng , Papadakis Georgia T. , Catrysse Peter B. , Fan Shanhui
Published: October 2024

We numerically demonstrate the creation of Weyl points in a twisted multilayer photonic system. In our system, each layer is anisotropic with plasmonic response along a direction perpendicular to the layer and with anisotropic dielectric response within the layer. We show that Weyl points can be created by controlling the twist angles between the layers so that spatial-inversion symmetry is broken. Compared with existing approaches, our findings offer a potentially simpler structure for creating Weyl points and highlight the prospect of using twisted multilayer systems for achieving topological photonic effects.
Effects of canyon wind speed and angle on the aerodynamic performance of a high-speed train passing through canyon tunnel–bridge–tunnel infrastructure
Authors: Zhang Yao-Sheng , Zhou Dan , Feng Ji-Qi , Xue Ru-Dai , Chen Guang
Published: October 2024

A significant airflow acceleration effect generated by canyon terrain and the bridge poses a serious threat to the safety of train operation in the canyon wind zone. The scale-resolving hybrid turbulence model and overset mesh technology have been employed to investigate the aerodynamic performance of the train traversing a tunnel–bridge–tunnel infrastructure under the canyon wind. Meanwhile, the mechanism of aerodynamic load variation is explored in combination with the characteristics of wind field distribution. The results indicate that the wind speed reaching the windward track of the bridge is about twice the wind speed of far-field inflow. The air within both tunnels will be sucked toward the center of the canyon. The accelerated flow area outside the tunnel portal leads to sudden changes in the lateral force and overturning moment of the train, with the most significant occurring in the head car. The peak of the lateral force and overturning moment coefficients are the highest at wind angles of approximately 60° and 120°, while smaller at 90°, exhibiting an overall approximate “M-shaped” variation pattern. The peak of the sudden change in lift coefficient is later than that of the lateral force coefficient, indicating a lag phenomenon. The direction of vortex shedding is roughly the same as the direction of the composite velocity of train-induced wind and canyon wind, except at the tunnel portal. The research results can provide a reference for the safety of train operation and the design of wind barrier facilities in canyon areas.
Unsteady numerical study on the effects of inlet distortion parameters on the aerodynamic instability of the centrifugal compressor
Authors: Zhang Liangrui , Liu Yanming , Sun Shijun , Wang Jianhua
Published: October 2024

Total pressure inlet distortion significantly impairs the aerodynamic performance and flow stability of centrifugal compressors. This paper presents a full annulus unsteady numerical simulation to investigate the flow mechanisms under varying inlet distortion parameters. First, the flow characteristics of a uniform inflow is studied as a baseline for comparison with distorted inlet conditions. Results indicate that the interaction between shock waves and tip leakage flow is a primary factor leading to aerodynamic instability. The instability signal in this region is detected through fast Fourier transform and frequency slice wavelet transform (FSWT). Under near stall condition, different distortion parameters are set to research the effects on aerodynamic performance, flow mechanisms, and instability characteristics. The results reveal that distortion intensity has the most significant impact, causing a maximum stall margin loss of 55.43%, followed by distortion angle with a maximum stall margin loss of 43.02%. Total pressure inlet distortion leads to a deterioration in aerodynamic performance, primarily due to premature occurrences of unstable flow phenomena such as leading-edge spillage and trailing-edge backflow. The onset key features triggering aerodynamic instability are identified as leading-edge spillage vortex, tip leakage vortex, and passage vortex. The continuous disintegration of the tip leakage vortex results in low-frequency fluctuating energy exhibiting multipeak characteristics, with pulsation peaks centered around 0.5 BPF, related to the spike stall of the compressor. The high-energy frequency band dissipates over time in the time–frequency spectrum, as shown by FSWT results, indicating the characteristics of instability in the flow.
Intrinsically disordered region amplifies membrane remodeling to augment selective ER-phagy
Authors: Poveda-Cuevas Sergio Alejandro , Lohachova Kateryna , Markusic Borna , Dikic Ivan , Hummer Gerhard , Bhaskara Ramachandra M.
Published: October 2024

Intrinsically disordered regions (IDRs) play a pivotal role in organellar remodeling. They transduce signals across membranes, scaffold signaling complexes, and mediate vesicular traffic. Their functions are regulated by constraining conformational ensembles through specific intra- and intermolecular interactions, physical tethering, and posttranslational modifications. The endoplasmic reticulum (ER)-phagy receptor FAM134B/RETREG1, known for its reticulon homology domain (RHD), includes a substantial C-terminal IDR housing the LC3 interacting motif. Beyond engaging the autophagic machinery, the function of the FAM134B-IDR is unclear. Here, we investigate the characteristics of the FAM134B-IDR by extensive modeling and molecular dynamics simulations. We present detailed structural models for the IDR, mapping its conformational landscape in solution and membrane-anchored configurations. Our analysis reveals that depending on the membrane anchor, the IDRs collapse onto the membrane and induce positive membrane curvature to varying degrees. The charge patterns underlying this Janus-like behavior are conserved across other ER-phagy receptors. We found that IDRs alone are sufficient to sense curvature. When combined with RHDs, they intensify membrane remodeling and drive efficient protein clustering, leading to faster budding, thereby amplifying RHD remodeling functions. Our simulations provide a perspective on IDRs of FAM134B, their Janus-like membrane interactions, and the resulting modulatory functions during large-scale ER remodeling.
The role of variable retrieval in effective learning
Authors: Butowska-Buczyńska Ewa , Kliś Paulina , Zawadzka Katarzyna , Hanczakowski Maciej
Published: October 2024

Current research on memory indicates that learning is most effective when it involves spaced retrieval practice of study materials. Here, we investigated whether the benefits of both retrieval practice and spacing can be further boosted when variability is introduced across practice sessions. Across six experiments, participants learned translations of foreign vocabulary, with foreign words embedded in contextual sentences hinting at the meaning of these words. These sentences were then either kept constant or varied from one learning cycle to another. Whenever repeated practice took the form of retrieval from long-term memory with contextual sentences serving as cues (with or without feedback after retrieval attempts), variable sentences led to better learning of the meanings of the embedded foreign words than constant sentences. The benefits of variable retrieval were observed both immediately after study and after a 24-h delay, and they were larger when retrieval practice was spaced rather than massed. However, these benefits were not appreciated by the learners who judged learning to be more effective with constant rather than variable cues. This metacognitive illusion, misaligning the effectiveness of learning and its appraisal by learners, was confirmed in the seventh experiment which focused on learning lecture content. Thus, while spaced retrieval practice employing variable cues clearly produces robust benefits for memory performance, such benefits may be severely underappreciated by the learners.
Bacterial defense and phage counterdefense lead to coexistence in a modeled ecosystem
Authors: Kimchi Ofer , Meir Yigal , Wingreen Ned S.
Published: October 2024

Bacteria have evolved many defenses against invading viruses (phage). Despite the many bacterial defenses and phage counterdefenses, in most environments, bacteria and phage coexist, with neither driving the other to extinction. How is coexistence realized in the context of the bacteria/phage arms race, and how are immune repertoire sizes determined in conditions of coexistence? Here we develop a simple mathematical model to consider the evolutionary and ecological dynamics of competing bacteria and phage with different immune/counterimmune repertoires. We find an ecologically stable fixed point exhibiting coexistence, in agreement with the experimental observation that each individual bacterium typically carries multiple defense systems, though fewer than the maximum number possible. However, in simulations, the populations typically remain dynamic, exhibiting chaotic fluctuations around this fixed point. These dynamics enable coexistence even when phage (predator) strains outnumber bacteria (prey) strains. We obtain quantitative predictions for the mean, amplitude, and timescale of these dynamics. Our results provide a framework for understanding the evolutionary and ecological dynamics of the bacteria/phage arms race and demonstrate how bacteria/phage coexistence can stably arise from the coevolution of bacterial defense systems and phage counterdefense systems.
Multi-head attention-based variational autoencoders ensemble for remaining useful life prediction of aero-engines
Authors: Wang Yuxiao , Suo Chao , Zhao Yuyu
Published: October 2024

Accurate remaining useful life (RUL) prediction of aero-engines through condition monitoring (CM) data is of great significance for flight reliability and safety. Although deep learning (DL)-based approaches have been widely considered, individual DL models suffer from significant stochasticity and limited generalizability when predicting the RUL. To solve this issue, a novel multi-head attention-based variational autoencoders (MHAT-VAEs) ensemble model is proposed. Two distinct MHAT-VAEs are designed, employing linear and convolutional operations to capture global and temporal compressed representations of the CM data. Additionally, a dual-level ensemble strategy is introduced to adaptively fuse the outputs of the two base learners. A hyperparameter optimization method is also implemented to further enhance the efficiency and performance of the base learners. The effectiveness of the proposed method is validated using the C-MAPSS and N-CMAPSS datasets, with experimental results showing that it outperforms state-of-the-art approaches.
Performance enhancement of a magnetoactive elastomer actuator through a coupled magnetoelastic topology optimization scheme
Authors: Bergen Christian , Ounaies Zoubeida , von Lockette Paris
Published: October 2024

We have found that considering local magnetic fields, large deformations, and magnetoelastic coupling simultaneously significantly affect the resulting shape in magnetoelastic topology optimization in a uniaxial actuator case. In contrast to the work presented here, other works incorporate magnetoelastic formulations that include simplifying assumptions on the local field, and subsequent effects on the magnetization response of the material, or the absence of large deformation mechanics, or both. These assumptions were shown to produce solutions that differ substantively from cases where local fields and large deformations are addressed concurrently. Magnetoelastic topology optimization schemes are needed to optimize magnetoactive elastomer (MAE) devices. MAE devices are magnetic particle-filled polymer matrices designed for specific actuations and controlled remotely by an external magnetic field. They garner considerable research interest as an emerging technology for actuators in soft robots or in applications requiring untethered actuation. The material properties of MAEs are dependent on the volume fraction of particles in the elastomer matrix, where a high-volume fraction increases relative permeability (for soft magnetic particles) but also increases elastic modulus. For optimal actuation, a tradeoff between low stiffness and high magnetic response must be made by adjusting volume fraction and controlling material placement. Using a topology optimization scheme that considers both the magnetic and mechanical properties of the material, the shape and material composition of the device can be tuned to best achieve the desired actuation displacement. In this work, a two-dimensional density-based magnetoelastic multimaterial topology optimization scheme for soft magnetic material is implemented in COMSOL Multiphysics. The optimization scheme uses multiphysics coupling that considers local magnetic fields and large deformations at each iteration through a Maxwell stress tensor formulation. A simulated example is then considered to demonstrate the effectiveness and necessity of a coupled optimization. The effect of considering large deformations during optimization is also investigated. It was found that a coupled topology optimization scheme with large deformations produced shapes with modes of actuation not captured by schemes with simplifying assumptions, leading to better performance at lower material cost. Considering large deformations in the coupled scheme offered significantly better performance, with an increase of 81.3% in a side-by-side performance simulation when compared to uncoupled cases.
Combining underground and on-surface third-generation gravitational-wave interferometers
Authors: Iacovelli Francesco , Belgacem Enis , Maggiore Michele , Mancarella Michele , Muttoni Niccolò
Published: October 2024

Recently, detailed studies have been made to compare the performance of the European next generation GW observatory Einstein Telescope (ET) in a single-site triangular configuration with the performance of a configuration featuring two L-shaped detectors in different sites, still taken to have all other ET characteristics except for the geometry, in particular, underground and composed of a low-frequency interferometer working at cryogenic temperatures and a high-frequency interferometer working at room temperature.
Here we study a further possibility for a European network, made by a single L-shaped underground detector, like one of the detectors considered for the 2L version of ET, and a single third-generation 20-km L-shaped interferometer on the surface.
We compare the performances of such a network to those of the triangle and of the 2L-underground ET configurations. We then examine the performance of an intercontinental network made by a 40-km CE in the U.S., together with any of these European networks.
Survival of gas in subhalos and its impact on the 21 cm forest signals: insights from hydrodynamic simulations
Authors: Naruse Genki , Hasegawa Kenji , Kadota Kenji , Tashiro Hiroyuki , Ichiki Kiyotomo
Published: October 2024

Understanding the survival of gas within subhalos under various astrophysical processes is crucial for elucidating cosmic structure formation and evolution. We study the resilience of gas in subhalos, focusing on the impact of tidal and ram pressure stripping through hydrodynamic simulations. Our results uncover significant gas stripping primarily driven by ram pressure effects, which also profoundly influence the gas distribution within these subhalos. Notably, despite their vulnerability to ram pressure effects, the low-mass subhalos can play a pivotal role in influencing the observable characteristics of cosmic structures due to their large abundance.

Specifically, we explore the application of our findings to the 21 cm forest, showing how the survival dynamics of gas in subhalos can modulate the 21 cm optical depth, a key probe for detecting minihalos in the pre-reionization era.
Our previous study demonstrated that the 21 cm optical depth can be enhanced by the subhalos, but the effects of tidal and ram pressure stripping on the subhalo abundance have not been fully considered.
In this work, we further investigate the contribution of subhalos to the 21 cm optical depth with hydrodynamic simulations, particularly highlighting the trajectories and fates of subhalos within mass ranges of 104-6
M
⊙
h
-1 in a host halo of 107
M
⊙h-1, and subhalos within mass range of 104-5
M
⊙h-1 in a host halo of 106
M
⊙h-1.
Despite their susceptibility to ram pressure stripping, the contribution of abundant low-mass subhalos to the 21 cm optical depth is more significant than that of their massive counterparts primarily due to their greater abundance. We find that the 21 cm optical depth can be increased by a factor of approximately two due to the abundant low-mass subhalos. However, this enhancement is about twice as low as previously estimated in our earlier study, a discrepancy attributed to the effects of ram pressure stripping. Our work provides critical insights into the gas dynamics within subhalos in the early universe, highlighting their resilience against environmental stripping effects, and their impact on observable 21 cm signals.
Study on the characteristics of fluid exciting force on impeller of high-speed centrifugal pump under the condition of poiseuille inflow
Authors: Wang Hao , Li Yibin , Lei Mengxiang , Ren Haowei
Published: October 2024

The paper adopted the turbulence model of Wall-Model Large Eddy Simulation with improved algebraic form (WMLES S-Omega) to carry out the study on the fluid exciting force on impeller of high-speed centrifugal pump under the conditions of Poiseuille inflow and uniform inflow. The external characteristics and the vibration displacement of the shaft of high-speed centrifugal pump are tested. The results indicated that it is the high matching that the test and numerical external data of high-speed centrifugal pump under the condition of Poiseuille inflow. The test results of vibration displacement of shaft match the fluid exciting force better in terms of waveform and phase difference under the condition of Poiseuille inflow. The contribution degree of force and torque from the shroud inner surface in the X and Y direction is 76.3%, 80.7%, 79.5% and 85% of the resultant force and torque, and its force from the inner and outer surfaces of shroud and hub in the Z direction is 94.3%, and its torque from blades’ surfaces in the Z direction is 98.3%. The study results can provide some theoretical support for the research of fluid exciting force and hydraulic optimization design of centrifugal pump.
Construction of data base containing flow field information under different blade placement of pumping station in digital twin
Authors: Xu Wentao , Cheng Li , Jiang Hongying , Yan Hongqin , Pan Weifeng
Published: October 2024

The data base in digital twin technology includes various data such as the structure, performance, and operating status of the physical object. And the data base is the key point for the construction of the digital twin system. However, the data bases of different digital twin systems usually contain different information. In this paper, the flow state of the pumping station under different angles of four blades is selected as the research object. The research methods in this paper mainly include Latin hypercube sampling, numerical simulation and neural network prediction. The Latin hypercube sampling is used to select the typical Angle difference model. The numerical simulation is used to obtain flow field information. The neural network prediction method is used to construct a complete data base. The study incorporates an actual large-scale mixed-flow pump station to head, efficiency, and shaft power as the prediction targets. It utilizes the different angle difference data of ten sets of four blades as the training set, forty sets of remaining samples as the experiment set, and employs the backpropagation neural network method for constructing the prediction network. By changing the experiment set and test set, the method can efficiently complete the construction of data base including actual test and numerical simulation, which provides a solid foundation for the construction of digital twin platform.
Prediction of Pressure Fluctuation of Double-Suction Centrifugal Pump in Different Cavitation Conditions based on EMD-GRU
Authors: Du Yuxin , Lu Hongzhong , Yao Zhifeng , Tao Ran , Xiao Ruofu , Wang Fujun
Published: October 2024

The double-suction centrifugal pumps play a crucial role in various applications such as in irrigation-drainage projects, water diversion projects, and urban water supply and drainage projects. The pressure fluctuation is one of the crucial parameters for assessing the operational stability of pump. The pressure fluctuation exhibits distinct characteristics in various cavitation conditions. A pressure fluctuation prediction method based on Empirical Mode Decomposition (EMD) and Gated Recurrent Unit (GRU) is proposed in this paper. The model enables accurate forecasting of pressure fluctuation signals when pump operates at different cavitation conditions. The data were obtained from experimental measurements of a double-suction centrifugal pump. The original signal was decomposed into multiple sub-signals with varying energy levels using the EMD method. The neural network of GRU was employed for training and data prediction on individual sub-signals. The predicted results of each sub-signal were combined to form the final pressure fluctuation signals. The method based on EMD-GRU proves effective in predicting pressure fluctuation in three different cavitation conditions. The mean absolute error (MAE) in time-domain characteristics is below 6%, and the prediction error for the main frequency is below 1%. The prediction of low-frequency characteristics still requires improvement.
Observation of Superposition of Cavitation Instability in Liquid Rocket Inducer by Multi-point Pressure Measurement
Authors: Harada Sota , Nakura Yuto , Tamura Koki , Kawasaki Satoshi , Iga Yuka
Published: October 2024

The purpose of this study is to investigate the relationship between the growth and contraction processes of each blade cavity and cavitation instability, and to conduct multi-point pressure measurement tests. The experiments will be conducted using cavitation water flow tunnels installed at the Kakuda Space Center of the Japan Aerospace Exploration Agency (JAXA). In the multi-point pressure measurement experiment, a number of pressure sensors are installed in the inducer casing, and the cavity area can be estimated and the cavity length can be obtained by creating a pressure distribution between the blades during the depressurization experiments. This method makes it possible to continuously determine cavity length variation during inducer experiments and to investigate the cavity growth process. In addition, cavity length variation can be obtained with higher time resolution than in visualization experiment, allowing more detailed investigation of the unsteady cavity behaviour during cavitation instability. And two types of superposition cavitation instability were found in this study: one is Super-S R.C. and C.S., the other is Sync R.C. and C.S..
Prediction of cavitation using machine learning techniques on centrifugal pump
Authors: Stephen Christopher , Guguloth Vivek , Sivasailam Kumaraswamy , Gu Yandong , Parmar Richa , Banerjee Chandan
Published: October 2024

When the local static pressure drops below the fluid’s vapour pressure at that particular temperature, a dynamic process known as cavitation takes place in the liquid. Due to cavitation, the performance (total head and flow rate) of the pump will deteriorate, and hence the vibration and noise will develop. Both the performance and cavitation investigations are carried out for a low-specific-speed pump as per the testing standards. The results obtained during cavitation studies are extracted to train the machine learning algorithms. The flow rate, speed, torque, suction head, and delivery head are considered as input variables for machine learning, with total head, Net Positive Suction Head (NPSH), efficiency, and noise magnitude being output variables. The current studies employ four machine learning techniques: random forest, support vector machines, extreme gradient boosting, and linear regression. In the analysis, notable performance was observed for the random forest and extreme gradient boosting algorithms among others consistently demonstrated superior predictive capabilities for the output parameters of the pumps. For linear regression, random forest, and extreme gradient boosting, the coefficient correlation values are around one for all output parameters except for noise. Similar observation is depicted for coefficient of determination and normalized root mean squared error. These ensure the level of noise during cavitation is very dynamic. These findings will enable the pump user to incorporate AI techniques for the diagnosis of centrifugal pump operation with reference to the nominal flow rate (best efficiency flow). Through this technology, preventive and predictive maintenance of pumps can be adapted with less downtime in process industries, power plants, chemical industries, oil and gas refineries, and so on.
Analysis of Internal Leakage in Multistage Centrifugal Pumps under Conditions of Impeller Oscillation and Non-oscillation
Authors: Yang Zhengyin , Gu Yandong , Bian Junjie
Published: October 2024

Centrifugal pumps with multiple stages and floating impellers provide a convenient option for easy adjustment, boasting advantages such as easy head adjustment and efficient transfer of axial thrust from the impeller to the casing. These pumps utilize sealing gaskets to reduce leakage and control the axial movement of the impeller. Nonetheless, the influence of impeller oscillation and non-oscillation conditions on leakage losses and internal flow characteristics remains uncertain. To explore these phenomena, numerical simulation methods were employed, enabling the impeller to undergo both axial movement and rotation, with validation achieved through experimental verification of the numerical simulation results. Leakage in the front pump chamber exceeded that of the rear pump chamber significantly, whether oscillation was present or not. Consequently, the impeller’s immediate position during oscillation had a more pronounced impact on leakage in the front pump chamber than in the rear pump chamber. The overall leakage trend in the front pump chamber exhibited a negative correlation with the impeller’s instantaneous position, whereas it displayed a positive correlation with the overall leakage trend in the rear pump chamber. Impeller oscillation notably impacted the flow velocity and pressure in the front pump chamber, while exerting minimal effects on those parameters in the rear pump chamber. This research offers valuable insights on improving the efficiency and stability of multistage pumps.
Application of finite element analysis in wound sealing negative pressure drainage in the treatment of swelling
Authors: Han Jinying , Yin Zhimin , Luo Yi
Published: October 2024

Wound closure combined with negative pressure pump drainage technique is an emerging medical technology. This technique is widely used in various clinical fields and plays an important role in the treatment of various acute and chronic wounds. The fluid solid coupling porous elastic structure model is used to study the pressure distribution of negative pressure drainage wound when different negative pressure is applied. By using Abaqus software to construct the corresponding finite element model, the deformation of various types of negative pressure kits under different pressures, whether the pressure distribution is uniform, whether the drainage is smooth and so on are studied by computer calculation and analysis. The effects of different negative pressure on the internal pressure of the dressing are analyzed and compared, so as to find a way to drive and suck out an appropriate amount of residue. The improved finite element model provides theoretical basis and guidance for the design of negative pressure drainage device and an improved direction for the clinical application of this technology.
Analysis of static stress and vibration characteristics of the impeller in a tubular pump
Authors: Li Jian , Jin Yan , Song Xijie , Zhang Ye , Chen Hongcheng , Ni Debin
Published: October 2024

The tubular pump blade vibrates due to water flow excitation force and centrifugal force, which is susceptible to damage. This will lead to the abnormal operation of pump unit. To acquire the static stress and vibration characteristics of the impeller, a unidirectional fluid-structure coupling (FSC) method is adopted for static stress analysis and modal analysis. The results indicate that under different conditions, the static stress and displacement deformation law of the impeller are the same. The static stress increases as the radius decreases, with the maximum value occurring at the intersection of pressure surface and hub. The displacement deformation increases continuously with the expanding radius, and the highest value of deformation occurs near the shroud. The values of the maximum equivalent stress (MES) and maximum total deformation (MTD) of the impeller gradually decrease as the flow rate increases from 260L/s to 380 L/s. The natural frequency of the impeller is lower in wet mode compared to dry mode, and the additional mass of the water medium has different effects on each order. The research can be used as a reference for designing tubular pumps optimally and improving their stability.
Analysis of diversion ratio and study of sediment transport in the first canal station of an irrigation area based on Mike21 hydrodynamic model
Authors: Cui Yuna , Sun Yufeng , Wu Jinxin , Cheng Li
Published: October 2024

Based on MIKE21 hydrodynamic model, the change of diversion ratio and sediment transport at the first canal station in an irrigation area are analyzed. Two-dimensional numerical simulation is carried out by using MIKE21 FM hydrodynamic module, and the split ratio is studied. In the aspect of sediment transport, the transport path and deposition distribution of different sediment particle sizes are simulated by simulating sediment transport. The results show that under the lowest daily average water level, the diversion canal flow can meet the irrigation demand; The particle size of sediment has a great influence on the deposition distribution and thickness of the approach channel at the first station of the canal, and then affects the water diversion capacity of the pumping station.
Numerical investigation of the effect of the non-uniform intake flow on the unsteady flow and the excitation of the pump in a water-jet propulsion
Authors: Sun C , Dai Y X , Cai Y L , Wang Z L , Zhang H
Published: October 2024

Water-jet propulsions are widely used in high-performance ships. This study conducts numerical study on the unsteady flow of a complete water-jet propulsion. The internal flow field of the propulsion pump under the conditions of no installation of the shaft sleeve (and installation of the shaft sleeve. Spectrum analysis is used to compare the time-varying external characteristic and excitation characteristic under different conditions. Then, Dynamic Mode Decomposition technique is used to extract the high energy flow structures and corresponding frequencies. The results indicated that a large-scale vortex roll up above the driving shaft under the condition of rotational shaft, a pair of anti-rotation vortices appear behind the driving shaft under the condition of stationary shaft. These shaft induced vortices develop into unstable flow structures in the impeller region which moves relative to the impeller blades at rotational frequency. They further affect the unsteady flow in the guide vane region. The shedding vortices induced by the rotor-stator interaction are strengthened, while the passage vortices are weakened. Moreover, the dominant frequency of the passage vortex has decreased from 1.68 times the rotational frequency to 1.50 times the rotational frequency.
Optimum geometry of the Hydraulic Machinery impeller based on the response surface approximation surrogate model
Authors: Nguyen Duc-Anh , Kim Jin-Hyuk
Published: October 2024

Centrifugal pumps are known for their simplicity, reliability, and versatility, making them a preferred choice for a wide range of fluid transfer applications. Improving pump performance has an important meaning in saving energy and protecting the environment. Therefore, the impeller of the centrifugal pump in this study was optimized to improve efficiency at the best efficiency point based on the Response Surface Approximate surrogate model and Genetic Algorithm. To be able to capture the separation flow, numerical simulations are carried out using the Reynolds-averaged Navier-Stokes (RANS) equation and a Shear Stress Transport (SST k − ω) reattachment modification turbulence model with small y+ values at all wall surfaces. Experiments based on the base prototype are performed to confirm the reliability of the numerical simulation results. Two crucial parameters at the hub of the impeller are selected as design variables. The design points of these two design variables are initialized in the design space by Latin Hypercube Sampling method. Using a Genetic Algorithm, the optimum impeller model is identified with an efficiency increase of 1.445% and a power consumption decrease of 7.37% compared to the base model at the best efficiency point. After optimization, the elimination of separation flow at the leading edge of the impeller, arising from a mismatch between the impeller blade angle and flow angle, is obtained successfully resulting in the noteworthy reduction of the energy loss inside the impeller passage.
Study on the Internal Flow Characteristics of High Flowrate Emergency Drainage Series-parallel Pump
Authors: Tian Ding , Si Qiaorui , Liang Kang , Zhang Yong , Ju Yuanzhe , Yuan Jianping
Published: October 2024

Floods have become the main natural disaster threatening the safety of peoples lives and property. It is of great significance to develop high flow emergency drainage equipment. An innovative structure of pumps with high flow rate and multiple operating conditions is proposed in this paper to achieve series and parallel operation. It established an automatic optimization platform that integrates functions such as 3D modeling, mesh generation, computational fluid dynamics, and scheme optimization, and developed an efficient hydraulic model for a volute mixed flow pump combining flow field diagnostic techniques. The research results indicate that the inlet distortion of the secondary stage pump is the main cause of pump performance loss for both series and parallel operation condition. The third-generation vortex identification method was used to diagnose the internal flow of the pump under two operating conditions and control strategies were proposed. The final optimization scheme show that the pump can reach 1800 m3/h with a head of 9.6m and efficiency of 80% in parallel operation condition. In series operation condition, the pump can reach 900 m3/h with a head of 18.3m and an efficiency of 75.3%.
Optimization of Dual-Turbine Hydraulic Torque Converter Based on Meta-model of Optimal Prognosis
Authors: Zhou He-Jun , Zhu Geng-Hui , Yang Yi-Ming , Liu Quan-Zhong
Published: October 2024

The internal flow field of a specific model of hydraulic torque converter exhibits turbulence, resulting in suboptimal efficiency under the designed operating condition. This study aimed to improve the peak efficiency of the hydraulic torque converter by optimizing its design parameters. Computational fluid dynamics (CFD) analysis identified turbulence predominantly within the pump impeller region. Parameterized modeling of the pump blades was conducted, and an automatic optimization process was implemented. A Meta-model of Optimal Prognosis (MOP) was developed based on 250 sample points, and was then utilized to continuously optimize the blade parameters through evolutionary algorithm (EA). The results indicate an increase in the efficiency of the optimized torque converter from 82.2% to 84.34%, accompanied by a widening of the high-efficiency range (η≥75%) from 2.26 to 2.44. Furthermore, the torque coefficient of the impeller was enhanced.
Blade Airfoil Optimization and Its Impact on Vertical Axis Wind Turbine Performance
Authors: Zhang R Y , Li D Y , Wei X T , Chang H , Wang H J
Published: October 2024

Amidst the emergence of crises in petroleum prices and supply, the imperative for the development of clean energy has become increasingly apparent. Vertical axis wind turbines (VAWT), as a type of wind turbine, still grapple with challenges such as low wind energy utilization and sensitivity to dynamic wind speeds. This study focuses on optimizing the airfoil of a two-dimensional vertical axis wind turbine and analyzes the performance variations in a three-dimensional model. Following the optimization, the average power coefficients of the dual-blade two-dimensional VAWT increased by 7.9% and 4%, respectively, while those of the dual-blade three-dimensional model rose by 7.9% and 1.2%. However, the performance of the three-dimensional model was compromised due to the influence of tip vortices, resulting in inferior performance compared to the two-dimensional model. Both three-dimensional optimized blade designs exhibited a substantial reduction in the flow separation region downstream and improved pressure distribution fluctuations caused by the shedding of tip vortices, leading to decreased pressure differentials. Along the spanwise section, the power coefficient gradually decreased from the central segment to the tip segment. Notably, the power coefficient of the optimized blades at the tip segment increased significantly, accompanied by an augmented pressure differential between the upper and lower surfaces. This augmentation contributed to a significant enhancement in lift, thereby facilitating the rotation of the vertical axis wind turbine.
Failure analysis and treatment of sealing gland bolts for bulb turbine expansion joints
Authors: Liu Bo , Li Le , Zeng Zuopeng , Guan Peng , Liu Zhong , Yin Xinyuan
Published: October 2024

The sealing gland and sealing strip are the main means of waterproofing the expansion joint of the bulb turbine. Fracture Failure of the sealing gland bolts will lead to sealing failure, causing water leakage and even flooding of the plant accident. Aiming at the fracture failure of sealing gland bolts for bulb turbine expansion joints, samples were taken from the fracture A2-70 stainless steel bolts and 8.8 grade high-strength carbon steel bolts. Combined with physical and chemical inspection, vibration testing and finite element simulation analysis, the reasons for the fracture of sealing gland bolts were studied, and corresponding preventive measures were proposed. Research results show that bolt fracture failure is not caused by quality problems of the bolt itself, but by alternating unidirectional plane bending fatigue loads with low stress levels. The fracture failure of the gland bolts can be prevented by increasing the fatigue strength of the gland bolts, adjusting the on-cam relationship to reduce unit vibration, installing spherical washers, and adding sealing gland jack screw to reduce the impact of unit vibration on the sealing gland bolts. The research methods and results can provide scientific basis and reference for the operation and maintenance of connecting bolts of important components of hydroelectric projects, including expansion joint gland bolts.
Effects of temperature on Two-point statistical characteristics in turbulent jets
Authors: Li Hongru , Lai Huanxin
Published: October 2024

large eddy simulations are carried out for jets at Mach number 0.9, temperature ratio 2.0 and 3.4. Simulations are validated by comparing with experiments from literature. Two-point correlation- and coherence- functions are analyzed. Results show that the increment of jet temperature affects the decay rate of correlation functions. The correlation functions are analyzed both in space and time by employed a normalization method. The normalization coefficient is found changing with the temperature. Compared to spatial normalization coefficients, the time normalization coefficient is found more sensitive to the temperature. The coherence function is found asymmetric in the upstream and downstream of the reference point. The present attempt to construct an empirical model to normalize the coherence function, so as to provide reference for the study of acoustic field.
Investigation of cavitation with air injection using Eulerian-Lagrangian method
Authors: Li Linmin , Shen Bohan , Cheng Xiang , Zhu Zuchao
Published: October 2024

Air injection can be used to reduce the cavitation erosion in fluid machinery. However the inverse result that the injected air indeed increases the size of cavitation may be obtained. To find out the interaction between air injection and cavitation, the present work proposes a Eulerian-Lagrangian method to investigate the effect of air injection on the characteristics of cavitating flow. The Eulerian method is used to describe the liquid and vapor distribution, and the morphology of large cavities are tracked by the Volume of Fluid (VOF) method in the Eulerian frame. On the other side, the Lagrangian method is used to track both air and vapor bubbles in small scale. With the Eulerian-Lagrangian coupling, discrete micro bubbles in sub-grid scale as well as the large cavities can be well captured and simulated. This work takes two cavitation situations in different cavitation numbers of σ = 0.81 and 0.70 into account. The cavitation features in σ = 0.81 are mainly characterized by the intermittent shedding of small-scale cavities under re-entrant flow mechanism. For σ =0.70, the injected air flow plays an important part which enhances the scale of cavity. For both cases, simulated results of the cavity shapes and distribution of discrete bubbles anastomoses well with experimental results, which verifies the accuracy of the algorithm. The interaction between injected air and vapor is also analysed.
Study of Load-based Energy Saving for Multi-layer Networks on Base Station
Authors: Zhang Lili , Zhu Wenxin , Zhang Lichi
Published: October 2024

With the rapid deployment and widespread popularization of 5G technology, mobile networks have achieved wider frequency spectrum, more efficient data transmission, and larger capacity, providing users with unprecedented experiences. However, the multi-band technology applied by large urban base stations to meet the demand for high-speed internet experience has also led to a significant increase in energy consumption. It also receives a growing number of attentions from engineers and researchers, due to the increasing awareness of energy consumption issues. This paper proposes load-based energy-saving algorithm for multi-layer network on base stations. Through dividing cell into group based on the same coverage area and dynamically switch off and reactive cells strategies, the aim is to achieve a significant reduction in power consumption while ensuring network transmission efficiency.
Heart Failure Prediction Based on Broad Learning System
Authors: Ao Licheng , Cai Junyan , Lin Yifeng , Yang Yuer
Published: October 2024

Heart failure is a prevalent and serious cardiovascular condition characterized by the heart’s inability to pump blood to meet the body’s demands adequately. Current research on heart failure prediction primarily relies on conventional clinical assessment methods, traditional machine learning techniques, and traditional deep learning methods. Efficient and accurate heart failure prediction is a significant challenge due to its complex and multifactorial nature. In this study, we propose a heart failure prediction approach utilizing a broad learning system (BLS) that has the potential to capture intricate patterns in the data and enhance prediction accuracy. To evaluate our approach, we utilize an extensive dataset compiled from five previous independent datasets from the Cleveland, Hungary, Switzerland, Long Beach VA Hospital, and Stalog (heart) datasets. Experimental results demonstrate the effectiveness and efficiency of the BLS model, with a training time of 0.36 seconds and testing accuracy of 90%, precision of 88%, recall of 96%, and specificity of 82%, showcasing its potential performance for accurate heart failure prediction.