Local vibration characteristics of rotating blades induced by moving rub-impact loads

Considering spin softening and centrifugal stiffening effect of blades, the parameterized finite element model of rotating blades with moving rub-impact loads is established. Time domain response and frequency domain response are analyzed along with the change of speed and local vibration characteristic of the blade is studied under the different harmonic components. With investigation of the rotating blades, some conclusions have been found: The displacement caused by centrifugal effect has a maximum amplitude at blade tip and appears a smaller amplitude at blade root. And the stress change is just the opposite, which is basically a linear relation with location, and stress value caused by the centrifugal effect is basically in direct proportion to square of rotation speed within a certain range. Rub-impact can induced a variety of frequency multiplication components of the rotating blades, which cause different levels vibration response of the blade. The corresponding high-frequency components of the local stress mostly appear at angular position and root position of blade, which is easy to cause local fatigue damage of blade. Therefore, it need pay more attention to avoid frequency multiplication omponents caused by rub-impact approaching the natural frequency of the blade in order to prevent from local vibration. The results of the study in this paper will provide theoretical reference for the characteristic analysis and fault diagnosis of similar rotating blades

Multi-functional anodes boost the transient power and durability of proton exchange membrane fuel cells.

Proton exchange membrane fuel cells have been regarded as the most promising candidate for fuel cell vehicles and tools. Their broader adaption, however, has been impeded by cost and lifetime. By integrating a thin layer of tungsten oxide within the anode, which serves as a rapid-response hydrogen reservoir, oxygen scavenger, sensor for power demand, and regulator for hydrogen-disassociation reaction, we herein report proton exchange membrane fuel cells with significantly enhanced power performance for transient operation and low humidified conditions, as well as improved durability against adverse operating conditions. Meanwhile, the enhanced power performance minimizes the use of auxiliary energy-storage systems and reduces costs. Scale fabrication of such devices can be readily achieved based on the current fabrication techniques with negligible extra expense. This work provides proton exchange membrane fuel cells with enhanced power performance, improved durability, prolonged lifetime, and reduced cost for automotive and other applications

Experimental studies on the complex oscillatory behaviour in gallic acid – BrO₃^{-  }Mn²⁺- H₂SO₄

823-828The title system has been studied in the batch reactor and its state followed by the bromide electrode potentials and UV spectroscopy. The system exhibits complex oscillatory behaviour including sequential oscillations. aperiodic oscillations and even the more complex oscillating states. On the basis of the analysis of the reaction products. the oscillations involving the following systems have been distinguished: (a) uncatalvzcd oscillations in gallic acid (GA)-BrO3 –H2SO4, system. (b) Mn2+ -catalyzcd oscillations in gallic acid (GA)-BrO3 –H2SO4 system. (c) Mn2+-catalyzed oscillations in monobromogallic acid(BrGA)-BrO3 –H2SO4 system. The inhibition and combination between these oscillations result in the complex oscillatory pattern observedm the present system. The oscillating mechanism has been discussed on the basis of FKN mechanism and OKN mechanism

Machine Learning and Swarm Optimization Algorithm in Temperature Compensation of Pressure Sensors

The main temperature compensation method for MEMS piezoresistive pressure sensors is software compensation, which processes the sensor data using various algorithms to improve the output accuracy. However, there are few algorithms designed for sensors with specific ranges, most of which ignore the operating characteristics of the sensors themselves. In this paper, we propose three temperature compensation methods based on swarm optimization algorithms fused with machine learning for three different ranges of sensors and explore the partitioning ratio of the calibration dataset on Sensor A. The results show that different algorithms are suitable for pressure sensors of different ranges. An optimal compensation effect was achieved on Sensor A when the splitting ratio was 33.3%, where the zero-drift coefficient was 2.88 × 10−7/°C and the sensitivity temperature coefficient was 4.52 × 10−6/°C. The algorithms were compared with other algorithms in the literature to verify their superiority. The optimal segmentation ratio obtained from the experimental investigation is consistent with the sensor operating temperature interval and exhibits a strong innovation

Research progress on the application of rare earth materials in electrochemical energy storage

The exploration of energy storage materials has been accompanied by the development of rare earth materials and their applications.Rare earth materials are widely used in various fields of electrochemical energy storage.In this paper,we review the latest applications of rare earth materials in lead-acid batteries,nickel-metal hydride batteries,solid oxide fuel cells,lithium-ion batteries,super capacitors,and lithium-sulfur batteries.Also,the important role of rare earth materials in electrochemical energy storage is introduced here.Hopefully,rare earth materials will have a wider application prospect and brighter future in energy storage

Ag/Bi₂WO₆ prepared by photo-reduction method and its visible-light photocatalytic activity

In this paper,an ionic liquid assisted solvothermal process has been developed to synthesize the Bi2WO6 photocatalyst.Furthermore,Ag/Bi2WO6 was prepared by aphoto-reduction method.The relationships between catalyst structure and catalysis performance were discussed in detail.Ag nanoparticles deposited on the surface of Bi2WO6 enhanced the absorption of visible light and improved the separation efficiency of the carrier via plasma resonance effect.Ag/Bi2WO6 catalyst with 0.75% (mole fraction) Ag/Bi and photo-reduction time of 20 min has been confirmed to have the best photocatalytic activity

Breast Cancer Histopathological Image Recognition Based on Pyramid Gray Level Co-Occurrence Matrix and Incremental Broad Learning

In order to recognize breast cancer histopathological images, this article proposed a combined model consisting of a pyramid gray level co-occurrence matrix (PGLCM) feature extraction model and an incremental broad learning (IBL) classification model. The PGLCM model is designed to extract the fusion features of breast cancer histopathological images, which can reflect the multiresolution useful information of the images and facilitate the improvement of the classification effect in the later stage. The IBL model is used to improve the classification accuracy by increasing the number of network enhancement nodes horizontally. Unlike deep neural networks, the IBL model compresses the training and testing time cost greatly by making full use of its single-hidden-layer structure. To our knowledge, it is the first attempt for the IBL model to be introduced into the breast cancer histopathological image recognition task. The experimental results in four magnifications of the BreaKHis dataset show that the accuracy of binary classification and eight-class classification outperforms the existing algorithms. The accuracy of binary classification reaches 91.45%, 90.17%, 90.90% and 90.73%, indicating the effectiveness of the established combined model and demonstrating the advantages in breast cancer histopathological image recognition

Microwave-Assisted Photocatalytic Degradation of Organic Pollutants via CNTs/TiO₂

Introducing microwave fields into photocatalytic technology is a promising strategy to suppress the recombination of photogenerated charge carriers. Here, a series of microwave-absorbing photocatalysts, xCNTs/TiO2, were prepared by combining titanium dioxide (TiO2) with carbon nanotubes (CNTs) using a typical alcoholic thermal method to study the promotion of microwave-generated thermal and athermal effects on the photocatalytic oxidation process. As good carriers that are capable of absorbing microwaves and conducting electrons, CNTs can form hot spots and defects under the action of the thermal effect from microwaves to capture electrons generated on the surface of TiO2 and enhance the separation efficiency of photogenerated electrons (e−) and holes (h+). Excluding the influence of the reaction temperature, the athermal effect of the microwave field had a polarizing effect on the catalyst, which improved the light absorption rate of the catalyst. Moreover, microwave radiation also promoted the activation of oxygen molecules and hydroxyl groups on the catalyst surface to generate more reactive oxygen radicals. According to the mechanism analysis, the microwave effect significantly improved the photocatalytic advanced oxidation process, which lays a solid theoretical foundation for practical application