A Hybrid Level Set Method for the Topology Optimization of Functionally Graded Structures

This paper presents a hybrid level set method (HLSM) to design novelty functionally graded structures (FGSs) with complex macroscopic graded patterns. The hybrid level set function (HLSF) is constructed to parametrically model the macro unit cells by introducing the affine concept of convex optimization theory. The global weight coefficients on macro unit cell nodes and the local weight coefficients within the macro unit cell are defined as master and slave design variables, respectively. The local design variables are interpolated by the global design variables to guarantee the C0 continuity of neighboring unit cells. A HLSM-based topology optimization model for the FGSs is established to maximize structural stiffness. The optimization model is solved by the optimality criteria (OC) algorithm. Two typical FGSs design problems are investigated, including thin-walled stiffened structures (TWSSs) and functionally graded cellular structures (FGCSs). In addition, additively manufactured FGCSs with different core layers are tested for bending performance. Numerical examples show that the HLSM is effective for designing FGSs like TWSSs and FGCSs. The bending tests prove that FGSs designed using HLSM are have a high performance

SlowFast Action Recognition Algorithm Based on Faster and More Accurate Detectors

Object detection algorithms play a crucial role in other vision tasks. This paper finds that the action recognition algorithm SlowFast’s detection algorithm FasterRCNN (Region Convolutional Neural Network) has disadvantages in terms of both detection accuracy and speed and the traditional IOU (Intersection over Union) localization loss is difficult to make the detection model converge to the minimum stability point. To solve the above problems, the article uses YOLOv3 (You Only Look Once), YOLOX, and CascadeRCNN to improve the detection accuracy and speed of the SlowFast. This paper proposes a new localization loss function that adopts the Lance and Williams distance as a new penalty term. The new loss function is more sensitive when the distance difference is smaller, and this property is very suitable for the late convergence of the detection model. The experiments were conducted on the VOC (Visual Object Classes) dataset and the COCO dataset. In the final videos test, YOLOv3 improved the detection speed by 10.5 s. CascadeRCNN improved by 3.1%AP compared to FasterRCNN in the COCO dataset. YOLOX’s performance on the COCO dataset is also mostly better than that of FasterRCNN. The new LIOU (Lance and Williams Distance Intersection over Union) localization loss function performs better than other loss functions in the VOC dataset. It can be seen that improving the detection algorithm of the SlowFast seems to be crucial and the proposed loss function is indeed effective

Heteroatoms (O, N)-Doped Porous Carbon Derived From Bamboo Shoots Shells For High Performance Supercapacitors

Activated carbon derived from plant wastes is attractive for the fabrication of low cost and high performance electrochemical energy storage devices. The heteroatoms (O, N)-doped porous carbon (KAC-700) is fabricated from bamboo shoots shells via KOH activation. The symmetric supercapacitor based on KAC-700 has gravimetric and volumetric capacitance of 223.21 F g−1 and 167.63 F cm−3, respectively, at current density of 1 A g−1 in 1 M H2SO4 electrolyte. This supercapacitor also delivers a high energy density of 13.15 Wh kg−1 at power density of 546.60 W kg−1 in 1 M Na2SO4 electrolyte, as well as high capacitance retention rate of 93.62% after 4000 cycles at 5 A g−1. Compared with graphene, carbon nanotubes and other expensive carbon material, this activated carbon has a bright future due to its low cost and easy fabrication process as electrode material for supercapacitors

Driver Identification Methods in Electric Vehicles, a Review

Driver identification is very important to realizing customized service for drivers and road traffic safety for electric vehicles and has become a research hotspot in the field of modern automobile development and intelligent transportation. This paper presents a comprehensive review of driver identification methods. The basic process of driver identification task is proposed as four steps, the advantages and disadvantages of different data sources for driver identification are analyzed, driver identification models are divided into three categories, and the characteristics and research progress of driver identification models are summarized, which can provide a reference for further research on driver identification. It is concluded that on-board sensor data in the natural driving state is objective and accurate and could be the main data source for driver identification. Emerging technologies such as big data, artificial intelligence, and the internet of things have contributed to building a deep learning hybrid model with high accuracy and robustness and representing an important gradual development trend of driver identification methods. Developing a driver identification method with high accuracy, real-time performance, and robustness is an important development goal in the future

A Review of Lithium-Ion Battery State of Health Estimation and Prediction Methods

Lithium-ion power batteries have been widely used in transportation due to their advantages of long life, high specific power, and energy. However, the safety problems caused by the inaccurate estimation and prediction of battery health state have attracted wide attention in academic circles. In this paper, the degradation mechanism and main definitions of state of health (SOH) were described by summarizing domestic and foreign literatures. The estimation and prediction methods of lithium-ion power battery SOH were discussed from three aspects: model-based methods, data-driven methods, and fusion technology methods. This review summarizes the advantages and disadvantages of the current mainstream SOH estimation and prediction methods. This paper believes that more innovative feature parameter extraction methods, multi-algorithm coupling, combined with cloud platform and other technologies will be the development trend of SOH estimation and prediction in the future, which provides a reference for health state estimation and prediction of lithium-ion power battery

Effect of Gd on microstructure and corrosion behavior of Mg-xGd-1Er-1Zn-0.6Zr alloys

The Mg-xGd-1Er-1Zn-0.6Zr alloys with Gd contents of 7%(mass fraction), 9% and 11% were prepared by gravity casting method.The microstructure of the alloys was studied by means of optical microscope, scanning electron microscope and X-ray diffractometer.The corrosion behavior of the alloys were evaluated by means of open circuit potential, potentiodynamic polarization and electrochemical impedance spectroscopy measurements in 3.5%NaCl solution.The results show that when Gd content increases from 7% to 11%, the peak time of open circuit potential decreases from 1609 s to 851 s, the charge transfer resistance decreases from 588.50 Ω to 31.9 Ω, the corrosion current density increases from 2.21×10-5 A/cm2 to 3.97×10-5 A/cm2, indicating that the corrosion resistance of the alloys decreases with the increase of Gd content.It is attributed to the combined operation of the micro-galvanic corrosion effect as well as corrosion barrier effect of second phase.When the Gd content increases from 7% to 11%, the volume fraction of (Mg, Zn)3(Gd, Er) phase increases from 1.9% to 5.2%, and changes from discontinuous distribution to semi-continuous distribution along grain boundaries, the volume fraction of the lamellar-shape LPSO phase increases from 11.7% to 26.7% and penetrates into grains.The increase in the volume fraction of the (Mg, Zn)3(Gd, Er) phase and the lamellar-shape LPSO phase results in the decrease of corrosion resistance, however, a large number of fine lamellar-shape LPSO phases is able to prevent the corrosion from spreading and slow down the growth of corrosion rate of the alloy with 11%Gd content in 8-24 h

A review on magnesium alloys for application of degradable fracturing tools

The vulnerable corrosion resistance of Mg alloys is regarded as one of the main disadvantages restricting their application, while it can be used as an extraordinary specialty in some particular fields, such as petroleum exploitation and medicine. In recent years, many Mg alloys with high corrosion rate and high strength have been developed for fracturing temporary plugging tools in the oil exploitation. This review briefly introduces the performance requirements of the degradable fracturing tools classified into mechanical and corrosion properties. Recent progress on corrosion behavior of degradable Mg-Al, Mg-Zn, Mg-RE alloys and Mg matrix composites is then summarized and discussed. Finally, the factors influencing the degradation rate of Mg alloys are analyzed and divided into secondary phase, texture, dislocation, grain size and surface film. From the summary, it can be found that addition of Ni or Cu to the degradable Mg alloys is a common and effective method to enhance the degradation rate due to increasing the amount of secondary phases and deteriorating the corrosion product layers. For the as-extruded degradable Mg alloys, grain size, texture and dislocation are the key factors affecting the corrosion rate under different processing conditions. We expect this review is helpful for those who are working on developing Mg-based functional materials with superior degradation rate

Influencing factors of inequity in health services utilization among the elderly in China

Abstract Background With the rise of the aging population, it is particularly important for health services to be used fairly and reasonably in the elderly. This study aimed to assess the present inequality and horizontal inequity for health service use among the elderly in China and to identify the main determinants associated with the disparity. Methods This cross-sectional study was based on the sample of the survey of the China Health and Retirement Longitudinal Study (CHARLS) for 2015. The elderly was defined as individuals aged 60 and above, with a total of 7836 participants. We used the concentration index (CI) and the horizontal inequity (HI) to measure the inequity of the utilization of health services. The method of concentration index decomposition was utilized to measure the contribution of various influential factors to the overall unfairness. Results The CI for the probability and the frequency of outpatient use were 0.1102 and 0.1015, respectively, and the corresponding values of inpatient use were 0.2777 and 0.2980, respectively. The household consumption expenditure disparity was the greatest inequality factor favoring the better-off. The Urban Employee Basic Medical Insurance made a pro-wealth contribution to inequality in frequency of health services utilization (17.58% for outpatient and 13.40% for inpatient). The contributions of New Rural Cooperative Medical Scheme on reducing unfairness in inpatient use were limited (− 2.23% for probability of inpatient use and − 5.89% for frequency of inpatient use). Conclusions There was a strong pro-rich inequality in both the probability and the frequency of use for health services among the elderly in China. The medical insurance was not enough to address this inequity, and different medical insurance schemes had different effects on the unfairness of health service utilization

Measuring high pressure equation of state of polystyrene using laser driven shock wave

High precision polystyrene equation of state data were measured using laser-driven shock waves with pressures from 180 GPa to 700 GPa. α quartz was used as standard material, the shock wave trajectory in quartz and polystyrene was measured using the Velocity Interferometer for Any Reflector (VISAR). Instantaneous shock velocity in quartz and polystyrene was obtained when the shock wave pass the interface. This provided ~1% precision in shock velocity measurements