Transfer Path Research Articles

Modeling and Contribution Analysis of Vibration Transfer Paths for a Dual-Rotor Aeroengine

Modeling and Contribution Analysis of Vibration Transfer Paths for a Dual-Rotor Aeroengine

Experimental study on the low-temperature preheating performance of positive-temperature-coefficient heating film in the prismatic power battery module

The performance of a power battery directly affects the thermal safety performance of the vehicle. Aiming at the improvement of thermal safety of lithium-ion batteries under low temperature condition, this study focuses on the effect of the positive-temperature-coefficient (PTC) heating film on the heating performance of batteries through experimental testing. First, the side and bottom of the cell were heated, and the heat transfer path and mode of the single cell were analyzed. The effects of different power densities and geometric positions on the heating effect were studied by testing the heating time and temperature consistency. Second, for the battery module, a low-temperature heating thermal management heat transfer model was built to analyze the heating mechanism of the heating film under different heating power densities. Finally, the results of these studies were synthesized to obtain the optimal heating power density. The results show that for the cell, the optimum power density of side heating and bottom heating is 0.5 W /cm2 and 0.4 W /cm2, respectively. The time required for side heating from −20 °C to 10 °C is 730 s lower than that of bottom heating, and the maximum temperature difference is 1.885 °C lower. For battery modules, a power density of 0.5 W/cm2 was appropriate for both bottom and side heating methods. Due to the existence of heat conduction between battery packs, the battery modules will be quickly and evenly preheated. Under the optimal power density, the time length for side heating from –20 °C to 10 °C was 1459 s, and the maximum temperature difference was 6.32 °C; bottom heating time required slightly more time (1783 s), and the maximum temperature difference was 6.221 °C. Side heating can be beneficial for the rapid preheating of the battery module. This study will contribute to improving the performance and safety of batteries in cold environments.

Atomically Dispersed Cobalt Anchored on Hollow Tubular Carbon Nitride Mediates Direct Electron Transfer and Oxygen-Related Active Species Path for Activation of Permonosulfate.

Atomically dispersed catalysts anchored on nitrogen-rich substrates present promising application potential for the persulfate-based advanced oxidation process. Nevertheless, efficient activation efficiency and a clear activated mechanism of persulfate remain challenging in carbon nitride-based single-atom catalysts (SACs). To these, combined with the regulation strategy of metal-ligand section and carrier's architecture, an atomically dispersed Co single-atom catalyst anchored on regular hollow tubular carbon nitride (Co/TCN SAC) herein was devised and utilized to activate permonosulfate. As a result, Co/TCN SACs show excellent catalytic performance for the degradation of common antibiotics. Combined with X-ray absorption fine structure and theory calculation, it is confirmed that superficially anchored CoO3 sites of the Co2N2O2-CoO3 unit are the catalytic active center for peroxymonosulfate (PMS) activation. The electrochemical test and in situ electron paramagnetic resonance results demonstrate radical (SO4•- and •OH) and nonradical (electron transfer process and 1O2) paths contributing to the superior catalytic performance. In addition, the catalyst exhibits high reaction efficiency and structural stability considering water quality parameters. Finally, a continuous and efficient device was operated on a laboratory scale, which exhibited satisfactory efficiency in continuously removing electron-rich antibiotics such as tetracycline. This work reveals the atomic-level modulation of cobalt atomic sites on hollow tubular carbon nitride and their structure-activity relationship with persulfate activation.

Methods for separating the noise produced by the wheels and track during a train pass-by

AbstractRolling noise is produced by vibration of the wheels and track, induced by their combined surface roughness. It is important to know the relative contributions of the different sources, as this affects noise control strategies as well as acceptance testing of new rolling stock. Three different techniques are described that aim to use pass-by measurements to separate the wheel and track components of rolling noise. One is based on the TWINS model, which is tuned to measured track vibration. The second is based on the advanced transfer path analysis method, which provides an entirely experimental assessment. The third is based on the pass-by analysis method in combination with static vibroacoustic transfer functions which are obtained using a reciprocity method. The development of these methods is described and comparisons between them are presented using the results from three experimental measurement campaigns. These covered a metro train, a regional train and a high-speed train at a range of speeds. The various methods agree reasonably well in terms of overall trends, with moderate agreement in the mid-frequency region, and less consistent results at low and high frequency.

Charge transfer between layers of polymeric carbon nitride driven by surface grafting phosphotungstic polyanions toward efficient photocatalytic hydrogen evolution

It is a challenging issue to achieve efficient charge transfer between layers for the layered polymer photocatalysts, because the photogenerated carriers would prefer random migration within layers and thus have high reverse recombination rate due to their inherent anisotropy and high exciton binding energy. Herein, an innovative surface grafting strategy is developed to modify the layered polymeric carbon nitride (PCN) making use of phosphotungstic (PWO) polyanions. The surface coupling effect of PWO on PCN effectively improves reduction ability and utility rate of luminous energy through shifting the conduction band (CB) upward and broadening light absorption range to cover near infrared region up to 1000 nm, respectively. In especial, the strong electron-withdrawing effect of surface PWO moieties can reduce layer spacing to shorten electron transfer path and attract the photogenerated electrons transfer from PCN matrix to surface, thus conquering the charge transfer restriction between layers to improve the carrier separation efficiency. As a result, the photocatalytic hydrogen evolution (PHE) performance is dramatically enhanced. The optimal PWO-PCN-1% sample achieves an average PHE rate of 9.6 times that of PCN, stable operation for a total of 28 h on 7 cycles, and an AQY up to 22.3% at 400 nm. This contribution affords a viable modification avenue to overcome the limitation of charge transfer between layers for layered polymer photocatalysts.

Dynamic Temporal Denoise Neural Network with Multi-Head Attention for Fault Diagnosis Under Noise Background

Fault diagnosis plays a crucial role in maintaining the operational safety of mechanical systems. As intelligent data-driven approaches evolve, deep learning (DL) has emerged as a pivotal technique in fault diagnosis research. However, the collected vibrational signals from mechanical systems are usually corrupted by unrelated noises due to complicated transfer path modulations and component coupling. To solve the above problems, this paper proposed the dynamic temporal denoise neural network with multi-head attention (DTDNet). Firstly, this model transforms one-dimensional signals into two-dimensional tensors based on the periodic self-similarity of signals, employing multi-scale two-dimensional convolution kernels to extract signal features both within and across periods. Secondly, for the problem of lacking denoising structure in traditional convolutional neural networks, a temporal variable denoise (TVD) module with dynamic nonlinear processing is proposed to filter the noises. Lastly, a multi-head attention fusion (MAF) module is used to weight the denoted features of signals with different periods. Evaluation on two datasets, Case Western Reserve University bearing dataset (single sensor) and Real aircraft sensor dataset (multiple sensors), demonstrates that the DTDNet can reduce the useless noises in signals and achieve a remarkable improvement in classification performance compared with the state-of-the-art method. DTDNet provides a high-performance solution for potential noise that may occur in actual fault diagnosis tasks, which has important application value.

Boosted photothermal-assisted photocatalytic H2 production by dual heat source-based S-scheme heterojunction

With advances in catalytic research, improvement of catalytic efficiency by using photothermal synergies to strengthen the reaction mechanisms has been focused. In this work, a novel photothermal-assisted photocatalytic H2 production system was constructed by loading Co3O4 nanoparticles on surface of black carbon nitride (BCN) nanosheets, served as the dual thermal source to enhance photothermal effect for synergistically assisting in photocatalytic H2 evolution with optimal H2 production rate reached 3.7 mmol g−1 h−1, significantly higher than that of pure carbon nitride (CN) and BCN. Moreover, the S-scheme heterojunction is also formed between Co3O4 and BCN, leading to the optimization of the charge transfer path, which further promotes the improvement of photothermal-assisted photocatalytic H2 production activity. This study provides the design idea of coupling the multi-heat source effect with the heterojunction electron transport for constructing an efficient photothermal-assisted hydrogen production system.

In-Situ Structure and Topography of AMPA Receptor Scaffolding Complexes Visualized by CryoET.

Most synapses in the brain transmit information by the presynaptic release of vesicular glutamate, driving postsynaptic depolarization through AMPA-type glutamate receptors (AMPARs). The nanometer-scale topography of synaptic AMPARs regulates response amplitude by controlling the number of receptors activated by synaptic vesicle fusion. The mechanisms controlling AMPAR topography and their interactions with postsynaptic scaffolding proteins are unclear, as is the spatial relationship between AMPARs and synaptic vesicles. Here, we used cryo-electron tomography to map the molecular topography of AMPARs and visualize their in-situ structure. Clustered AMPARs form structured complexes with postsynaptic scaffolding proteins resolved by sub-tomogram averaging. Sub-synaptic topography mapping reveals the presence of AMPAR nanoclusters with exclusion zones beneath synaptic vesicles. Our molecular-resolution maps visualize the predominant information transfer path in the nervous system.

Construction of Ag-modified ZnO/g-C3N4 heterostructure for enhanced photocatalysis performance.

ZnO/g-C3N4 heterojunction modified with Ag nanoparticles (ZnO/CN/Ag) was synthesized by depositing ZnO nanorods/Ag nanoparticles onto g-C3N4 nanosheets. Under xenon lamp irradiation, 99% of Rhodamine B (RhB) was degraded by ZnO/CN/Ag-5% composite within 30min, which was much higher than the degradation efficiency of ZnO and ZnO/CN. The synergistic effect of g-C3N4 and ZnO, along with the localized surface plasmon resonance effect of Ag NPs, contributes to the improvement of photocatalytic performance. Ag nanoparticle provides another charge transfer path from g-C3N4 to ZnO, which speeds up the separation of electron-hole pairs. Meanwhile, the catalyst had good stability and recyclability. Finite-difference time-domain method and the density functional theory were used to obtain the charge transfer process. The photodegradation process has been studied in depth.

Fault tracing in multistage gearbox systems based on an improved transfer path analysis method

This study, has developed a novel structural dynamics decoupling method based on TPA. This approach effectively facilitates fault diagnosis and tracing in multistage gearbox systems. Initially, the research explores the relationship between the transfer function of systems with rigid link decoupling and the coupled system’s frequency response function. Compared with Huangfu et al. (2023) , the signal measurement points are reduced. The MWI (Yu et al., 2023) is employed to solve the inverse problem of bearing force identification. Subsequently, the decoupled frequency response and bearing forces are multiplied to calculate the path contribution, determining the dominant fault transfer path and thereby facilitating fault tracing in gearboxes. The effectiveness of this method is validated through numerical simulations and experimental studies, with fault characteristic enhancement exceeding 200%. To evaluate the method’s universality and robustness, experiments on diverse gearbox systems under varying conditions show enhanced fault characteristics across three fault types, confirming its generalizability.

Insights into the pore structure effect on the mass transfer of fuel cell catalyst layer via combining machine learning and multiphysics simulation

Analysis of the catalytic layer (CL) pore structure and three-phase (electron phase, proton phase, and reactant phase) mass transfer in high-temperature polymer electrolyte membrane fuel cell (HT-PEMFC) is critical for improving concentration polarization and optimizing performance. However, there is a lack of studies on the pore structure’s impact on the catalytic layer three-phase mass transfer. In this work, the influence of pore structure on catalytic layer three-phase mass transfer and multiphysics distribution was investigated by combining machine learning and multiphysics simulation. Among many key factors investigated by machine learning that impact the performance of catalytic layer, porosity emerges as the primary influencing factor. Porosity accounts for 32.7 % of the electric potential drop, with macro/micro porosity contributing 27.6 % and 5.1 %, and 32.8 % of the current density, with macro/micro porosity contributing 15.6 % and 17.2 %. Furthermore, the macropore structure has a much greater influence on the performance of the catalytic layer compared to the micropore structure. Moreover, the simulation results demonstrated that porosity has a great influence on three-phase mass transfer, the oxygen molarity increases with increasing porosity. The electric potential difference increases exponentially as porosity increases. The relationship between current density and porosity is a volcanic relationship, which can be expressed as a quadratic polynomial function. The mesoscopic pore-scale model (PSM) with an εeff of 0.502 (εmic of 0.2 and εmac of 0.378) exhibits the highest mean current density at 619.526 mA/cm2@0.5 V, attributed to a more uniform and efficient three-phase transfer path. The accuracy of the mesoscopic pore-scale model and the polynomial equation is further confirmed through corresponding experiments. The experiment results show that the current density decreased as the εeff increased from 0.682 to 0.702, which aligns with the theoretical predictions of the PSM model and polynomial equation. These studies are valuable for comprehending the internal three-phase mass transfer behavior and optimizing the catalytic layer pore structure to enhance HT-PEMFC performance.

A nickel porphyrin-based covalent organic framework modified electrode for the electrochemical detection of acetaminophen.

Covalent organic frameworks (COFs) can be rationally designed with functional organic ligands to improve the electrochemical responsiveness of the electrode toward certain medicinal compounds. In this study, we synthesized a COF-Ni electrocatalyst material, which is formed by covalent coupling of electron-rich 2,3,6,7-tetrakis (4-formylphenyl) tetrakis (4-imidazolyl) (TTF-4CHO) and hole-rich 5,10,15,20-tetrakis (4-aminophenyl) porphyrin nickel(II) (TAPP-Ni). The reasonable electron transfer path design, the large specific surface area of the COF and the physical properties of ordered nanopores, as well as the Ni-N4 bond as a highly active catalytic center, allow the COF-Ni material modified electrode to exhibit excellent sensing performance for acetaminophen (ACOP). The detection limit for ACOP is as low as 47.6 nM, with a linear range of 1-1500 μM, which is better than for most of the reported sensors. With superior interference resistance and good stability performance, COF-Ni is a highly suited electrode modification material for real-world sample detection, which provided a new perspective for application of COF materials in drug analysis.

Rod-shaped Cd0.8Mn0.2S and Co3O4 quantum dots construct S-scheme heterojunction for photocatalytic hydrogen evolution

Photocatalytic water splitting for hydrogen production is one of the key pathways to achieving a zero-carbon economy. Cd0.8Mn0.2S has significant potential for photocatalytic hydrogen evolution, but it faces serious challenges due to the recombination of photogenerated charge carriers. To address this issue, we successfully coupled Co3O4 QDs onto Cd0.8Mn0.2S nanorods via ultrasonic self-assembly, constructing a S-scheme heterojunction to reduce charge carrier recombination rates. In this configuration, Co3O4 QDs serves as the electron donor, while Cd0.8Mn0.2S act as the electron acceptor. The Cd0.8Mn0.2S/Co3O4 QDs structure creates a closely spaced interface, providing the shortest possible path for electron transfer. Under 10 W white light irradiation, the Cd0.8Mn0.2S/Co3O4 QDs composite photocatalyst exhibited remarkable hydrogen evolution activity, achieving a hydrogen production rate of 33.39 mmol⋅g⁻¹⋅h⁻¹. This S-scheme heterojunction strategy lays the foundation for the structural design of highly active visible-light photocatalysts.

Elaborate construction of a MOF-derived novel morphology Z-scheme ZnO/ZnCdS heterojunction for enhancing photocatalytic H2 evolution and tetracycline degradation

Elaborate construction of novel Z-scheme heterojunction with exceptional morphology derived from metal-organic framework (MOF) have been attracted greatly interest for improving the photocatalytic ability. Herein, a Z-scheme ZnO/ZnCdS heterojunction of rare morphology with ultrathin-nanosheet assembled hierarchical morphology ZnCdS supporting on rich gap ZnO nanospheres were constructed from Zn-based MOF (namely PZH-139) for the first time. This unique feature increased specific surface area, offered abundant mass transport channels and accessible catalytic active sites, accelerated electron migration, which highly elevated photocatalytic property. Furthermore, electron paramagnetic resonance (EPR) measurements and density functional theory (DFT) calculations confirmed the reservation of strong redox capability owing to Z-scheme electron transfer path and the ΔGH* closer to zero of Z-scheme ZnO/ZnCdS system were another two key factors for boosting the photocatalytic activity. As a result, 3-ZnO-700/ZnCdS-160 with optimal morphology showed the best H2 generation performance of 15.43 mmol h−1 g−1 and degradation tetracycline (TC) efficiency of 98.14 %. This work offered a novel and feasible idea for elaborate synthesis of the high-efficiency Z-scheme ZnO/ZnCdS heterojunction with special morphology derived from Zn-MOF.

Failure mechanism and crashworthiness optimization of variable stiffness nested origami crash box

In recent years, the study of the crashworthiness of lightweight and efficient thin-walled energy-absorbing structures has received increasing attention. In this work, 3D printing technology was adopted to create a nested origami crash box with stiffness variation, which was made of short carbon fiber reinforced nylon material. The structure effectively inhibits the development of failure behavior of short carbon fiber-reinforced nylon origami crash box due to material brittleness. The quasi-static compression experiment results indicate that compared to origami crash box, nested origami crash box improves by 40% in specific energy absorption and 50% in crash force efficiency, while the initial peak crushing force remains unchanged. The effects of three key geometrical parameters, namely dihedral angle, distance between tubes, and height difference on the damage mechanism of the nested origami crash box are discussed in detail using the finite element method, and the response surface model combined with the non-dominated sorting genetic algorithm II is used for multi-objective optimization. In this work, the concepts of origami theory and nested systems are integrated for the first time, aiming to achieve a stable and efficient energy-absorbing deformation mode by precisely modulating the stress transfer path of the structure and its stiffness. This work provides new ideas for the design and fabrication of novel lightweight energy-absorption boxes.

Numerical thermal analysis and structural optimization of cascaded PCM heat sinks for thermal management of electronics

In the present study, an innovative cascaded phase change material (PCM) heat sink using organic PCMs was proposed for electronic thermal management. The design arranges multiple PCMs with progressively lower melting points along the heat transfer path, allowing active control of the melt front. A numerical model with 5 % accuracy was developed to evaluate thermal performance. Based on the validated model, the effects of PCM stage numbers, PCM volume fractions, fin types, and fin volume fractions were analyzed. The fin volume fractions were further optimized using a support vector machine (SVM) and genetic algorithm (GA) methods. Results showed that a three-stage PCM heat sink with pin fins and increasing configurations outperformed single-stage PCM heat sinks, enhancing heat transfer by up to 36.7 %. Additionally, the innovative cascaded PCM heat sink with a uniform 20 % fin volume fraction across the three stages achieved a 38.8 % improvement compared to single-stage configurations. When the fin volume fractions were set to 24.1 %, 17.6 %, and 13.0 % for the three stages, thermal performance of the innovative cascaded PCM heat sink was enhanced by up to 39.8 % compared to single-stage configurations. The findings provide valuable insights for the design and application of PCM-based thermal management systems, potentially leading to more efficient solutions for various engineering fields.

Investigation on in-situ thermal behavior of tunnel surrounding rock based on the thermal probe test

Heat-transfer mechanism of energy tunnel is different from that of conventional borehole heat exchanger, where the thermal flux flows along perpendicular to the tunnel circumferential direction. However, the existing measurement methods cannot directly detect the in-situ thermal behavior and thermal conductivity of surrounding rock of tunnel circumferential direction. Hence, a thermal probe test (TPT) equipment was developed and the TPT was performed to investigate the in-situ thermal behavior of surrounding rock, the thermal conductivity measurement methods of tunnel surrounding rock was proposed and compared with laboratory measurement methods. The results showed that the developed TPT equipment achieved to directly detect the in-situ thermal behavior and thermal conductivity of circumferential surrounding rock. There was a significant variation in thermal response curves of different test areas due to the fact that joint development affected the transfer paths of the thermal flux, the temperature difference between test point 1 and test point 2 could reach up to 11.4 °C. The thermal conductivity tested by TPT was reliable and reflected the in-situ thermal behavior, the deviation was 6.99 % and 1.08 %, respectively, compared with laboratory measurement results. The joint development of the surrounding rock had a major impact on the thermal conductivity, where the thermal conductivity ranged from 0.66 to 2.91 W/m K in the 1# borehole and 1.96 to 3.66 W/m K in the 2# borehole. The local thermal conductivities were difficult to apply to an energy tunnel design, hence, the comprehensive thermal conductivity model of surrounding rock with joints was proposed based on series–parallel theory and was simplified according to the heat-transfer mechanism of energy tunnel. The comprehensive thermal conductivity model provided a new idea for obtaining the heterogeneity of thermal-physical properties of tunnel surrounding rock, which improved performance predictions and optimized design strategies for energy tunnel projects, enhancing their efficiency and reliability in various applications.

Operational transfer path analysis with crosstalk cancellation based on least variance spectrum estimation

Operational transfer path analysis with crosstalk cancellation based on least variance spectrum estimation

Exploring the application of a Bayesian framework in transfer path analysis

Transfer path analysis (TPA) is a methodology widely used in transmission identification of vibration and noise. Among the TPA families, the two prevailing approaches are classical TPA with the matrix inversion method and operational transfer path analysis (OTPA). Both methods rely on measurements within costly and complicated overdetermined systems. These experiment-based methods are also limited by sufficient space for the sensor mounting, which can result in difficulty when analyzing the transfer path in small objects. In this paper, we use an experimental setup that mimics an engine mounted on a suspension with resilient connections. The severity of errors stemming from the application of underdetermined measurement systems is assessed, alongside an exploration of how the Bayesian framework can be integrated into the analysis to mitigate errors and enhance the performance of TPA.

A development on the interior noise prediction technology using active noise control algorithm

When developing NVH of a vehicle, identifying a noise transmission vulnerable path is a very important task. The traditional TPA(Transfer Path Analysis) is based on a physical theoretical equation and calculates the contribution of each path by multiplying the ATF(Acoustic Transfer Function) of each path by the driving load. In this case, it is often difficult to calculate the driving load, and M/H consumption is also high. OTPA(Operational Transfer Path Analysis) performs transfer path analysis only with driving signals for each route, but has a disadvantage of insufficient physical causality. In this study, we proposed an efficient indoor noise TPA method that modifies the ANC algorithm by combining the reference signals while driving with the secondary path of Filtered-X LMS. The proposed method uses the secondary transfer function of Fx-LMS as the ATF for each path. It is not necessary to obtain physical load by predicting target noise with the Ref signal for each route. Therefore, it is possible to predict indoor noise with low M/H. In this study, it can be confirmed that the proposed method shows similar results compared to the existing methods and efficiently identifies main noise path for interior noise.