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In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose a shallow neural network-based learning methodology for such fluid flow reconstruction. Our approach learns an end-to-end mapping between the sensor measurements and the high-dimensional fluid flow field, without any heavy preprocessing on the raw data. No prior knowledge is assumed to be available, and the estimation method is purely data-driven. We demonstrate the performance on three examples in fluid mechanics and oceanography, showing that this modern data-driven approach outperforms traditional modal approximation techniques which are commonly used for flow reconstruction. Not only does the proposed method show superior performance characteristics, it can also produce a comparable level of performance to traditional methods in the area, using significantly fewer sensors. Thus, the mathematical architecture is ideal for emerging global monitoring technologies where measurement data are often limited.

The fuel cell with a ten-channel serpentine flow field has a low operating pressure drop, which is conducive to extended test operations and stable use. According to numerical results of the ten-channel serpentine flow field fuel cell, the multi-channel flow field usually has poor mass transmission under the ribs, and the lower pressure drop is not favorable for drainage from the outlet. In this paper, an optimized flow field is developed to address these two disadvantages of the ten-channel fuel cell. As per numerical simulation, the optimized flow field improves the gas distribution in the reaction area, increases the gas flow between the adjacent ribs, improves the performance of PEMFC, and enhances the drainage effect. The optimized flow field can enhance water pipe performance, increase fuel cell durability, and decelerate aging rates. According to further experimental tests, the performance of the optimized flow field fuel cell was better than that of the ten-channel serpentine flow field at high current density, and the reflux design requires sufficient gas flow to ensure the full play of the superior performance.

Extracellular vesicles (EVs) have a great potential in clinical applications. However, their isolation from different bodily fluids and their characterisation are currently not optimal or standardised. Here, we report the results of examining the performance of ultrafiltration combined with size exclusion chromatography (UF-SEC) to isolate EVs from urine. The results reveal that UF-SEC is an efficient method and provides high purity. Furthermore, we introduce asymmetrical-flow field-flow fractionation coupled with a UV detector and multi-angle light-scattering detector (AF4/UV-MALS) as a characterisation method and compare it with current methods. We demonstrate that AF4/UV-MALS is a straightforward and reproducible method for determining size, amount and purity of isolated urinary EVs.

Large-Slim (L-S) boreholes are characterized by having two or more annular sections with significantly different equivalent diameters within the same open hole interval. This wellbore configuration is commonly found in deep and super-deep wells. Because of the disparity in annular clearance diameters, L-S borehole structures often encounter issues such as inadequate cuttings removal in the upper portion and high frictional losses in the lower part. It is challenging to strike a balance between wellbore cleaning and the workload of surface equipment, necessitating optimization. Considering the High-Pressure High-Temperature (HPHT) performance of drilling fluid, a flow model for L-S boreholes was established, and a flow field adjustment tool was developed. The flow rate distribution and flow resistance models of this tool were also constructed, thereby forming the flow field optimization technology for L-S boreholes. Taking the PS-6 well as an instance, an optimization analysis was carried out. The results indicate that, while ensuring cuttings removal throughout the annulus, the bottom hole pressure has been decreased to an extent of 15 MPa, and the standpipe pressure has been reduced by 27 MPa. This has great importance for efficient and rapid drilling in complex wellbore structures.

Flow field plays an important role in the performance of proton exchange membrane (PEM) fuel cells, such as transporting reactants and removing water products. Therefore, the performance of a PEM fuel cell can be improved by optimizing the flow field dimensions and designs. In this work, single serpentine flow fields with four different land widths are used in PEM fuel cells to study the effects of the land width. The gas diffusion layers are made of carbon cloth. Since different land widths may be most suitable for different reactant flow rates, three different inlet flow rates are studied for all the flow fields with four different land widths. The effects of land width and inlet flow rate on fuel cell performance are studied based on the polarization curves and power densities. Without considering the pumping power, the cell performance always increases with the decrease in the land width and the increase in the inlet flow rates. However, when taking into consideration the pumping power, the net power density reaches the maximum at different combinations of land widths and reactant flow rates at different cell potentials.

High temperatures and non-uniform temperatures both have a negative bearing on the performance of proton exchange membrane fuel cells. The temperature of proton exchange membrane fuel cells can be lowered by reasonably distributed cooling channels. The flow field distribution of five different cooling plates is designed, and the temperature uniformity, pressure drop and velocity of each cooling flow field are analyzed by computational fluid dynamics technology. The results show that while the pressure drop is high, the flow channel distribution of a multi-spiral flow field and honeycomb structure flow field contribute more to improving the temperature uniformity. As the coolant is blocked by the uniform plate, it is found that although the flow field channel with a uniform plate has poor performance in terms of temperature uniformity, its heat dissipation capacity is still better than that of the traditional serpentine flow field. The multi-spiral flow field has the strongest ability to maintain the temperature stability in the cooling plate when the heat flux increases. The increase in Reynolds number, although increasing the pressure drop, can reduce the maximum temperature and temperature difference of the flow field, ameliorate the temperature uniformity and improve the heat transfer capacity of the cooling plate.

Cellulose nanocrystals (CNCs) are bio-based building blocks for sustainable advanced materials with prospective applications in polymer composites, emulsions, electronics, sensors, and biomedical devices. However, their high surface area-to-volume ratio promotes agglomeration, which restrains their performance in size-driven applications, thereby hindering commercial CNC utilization. In this regard, ultrasonication is commonly applied to disperse CNCs in colloidal suspensions; however, ultrasonication methodology is not yet standardized and knowledge of the effects of ultrasound treatments on CNC size distribution is scarce. The major goals of this study were attributed to targeted breakage of CNC agglomerates and clusters by ultrasound. The evolution of particle size distribution and potential de-sulfation by ultrasonication as well as the long-term stability of ultrasonicated CNC suspensions were investigated. Colloidal suspensions of sulfated CNCs were isolated from cotton α-cellulose. Effects of ultrasonication on particle size distribution were determined by asymmetrical flow field-flow fractionation (AF4) coupled with on-line multi-angle light scattering and ultraviolet spectroscopy. These results were complemented with off-line dynamic light scattering. High ultrasound energy densities facilitated cumulative dispersion of CNC clusters. Consequently, the mean rod length decreased logarithmically from 178.1 nm at an ultrasound energy input of 2 kJ g−1 CNC to 141.7 nm (− 20%) at 40 kJ g−1 CNC. Likewise, the hydrodynamic diameter of the particle collective decreased logarithmically from 94.5 to 73.5 nm (− 22%) in the same processing window. While the rod length, below which 95 wt% of the CNCs were found, decreased from 306.5 to 231.8 nm (− 24%) from 2 to 40 kJ g−1 CNC, the shape factor of the main particle fraction ranged from 1.0 to 1.1, which indicated a decreasing number of dimers and clusters in the particle collective. In summary, progressing ultrasonication caused a shift of the particle length distribution to shorter particle lengths and simultaneously induced narrowing of the distribution. The suspension’s electrical conductivity concurrently increased, which has been attributed to faster diffusion of smaller particles and exposure of previously obscured surface charges. Colloidal stability, investigated through electrical AF4 and electrophoretic light scattering, was not affected by ultrasonication and, therefore, indicates no de-sulfation by the applied ultrasound treatment. Occurrence of minor CNC agglomeration at low ultrasound energy densities over the course of 6 months suggest the effect was not unmitigatedly permanent.

To address the difficulty of obtaining high fidelity flow field information for unmanned underwater vehicle pump-jet propulsor, the accuracy of super-resolution flow field reconstruction by using a hybrid down-sampling skip connection/multi-scale reconstruction model of data-driven methods is investigated. This model can use the nonlinear distribution of bias and weight to establish a complex relationship between the low resolution and the super-resolution flow fields. Comparing with the experimental and numerical simulation methods, which has the advantages of high efficiency, low cost, and high accuracy. Meanwhile, the uncertainty distribution of super-resolution reconstruction of pump-jet propulsor was analyzed by using the variational Bayesian theory. The results indicate that the hybrid data-driven model with variational Bayesian theory has higher accuracy in reconstructing the flow field of pump-jet propulsor, and high reconstruction errors are mainly distributed in the hub area and rotor blade rotation area. The present method can increase the low resolution flow field of the unmanned underwater vehicles pump-jet propulsor by 256 times, high uncertainty area is mainly distributed at the peak of the reconstructed curve. 针对水下无人航行器泵喷推进器难以获取高保真流场信息的缺陷, 利用数据驱动方法中的混合下采样跳跃连接/多尺度重构模型研究了后置定子泵喷推进器超分辨流场重构的准确性。该模型可利用偏置、权重的非线性分布建立低分辨率流场与超分辨率流场之间的复杂关系。相比实验方法, 所提方法存在成本低的优势, 而相比数值仿真方法, 存在效率高、精度高的优势。同时, 结合变分贝叶斯理论分析了泵喷推进器超分辨重构的不确定性分布。研究结果表明: 含有变分贝叶斯理论的混合数据驱动模型重构泵喷推进器准确性更高, 较高的重构误差主要分布在轮毂区域及叶片旋转区域。该方法可将水下无人航行器泵喷推进器的低分辨流场提高256倍, 较高不确定性区域主要分布在重构曲线的波峰处。

X rudder is particularly important for submarine maneuverability, but its influence on wake flow field remains largely unknown. In this study, the X rudder was scaled down three-dimensionally to 80%, 85%, 90%, 95% and 100% of the original rudder area with unchanged aspect ratio and installation position of rudder shaft. Next, the effects of X rudder area on the horizontal mechanical properties and wake flow field of the submarine with a tail control plane were analyzed using the CFD method. The results showed that when the X rudder area was reduced by 20%, the resistance was not significantly affected, and the yaw torque was still larger than that of cross-shaped rudder submarine. At the rudder angles of 0°, 2° and 5°, the velocity non-uniformity coefficients of S1 were reduced by about 9%, 25% and 71%, respectively, when compared to those of S5.

A 3D computational fluid dynamics (CFD) model is developed to examine the impact of flow field design on the performance of direct methanol fuel cells (DMFCs). Effect of three various type flow fields is investigated in this study: single, double serpentine and honeycomb models. The distribution of velocity and temperature are simulated in 3D models. According to simulation studies, the honeycomb flow field has made uniform flow velocity distribution and minimum temperature change on plate surface. This could result better on DMFC performance. The experimental studies emphasize the performance of a single cell DMFC with different flow field channel designs as well as exhibit maximum power density and open circuit voltage. In subsequent study, electrodeposited Ni-Co alloy on stainless steel mesh surface is utilized to oxidize methanol and the electrode performance has been tested using cyclic voltammetry in alkaline conditions to replace expensive and sensitive platinum and platinum alloy catalysts