Effects of Coronal Density and Magnetic Field Distributions on a Global Solar EUV Wave

We investigate a global extreme-ultraviolet (EUV) wave associated with a coronal mass ejection (CME)-driven shock on 2017 September 10. The EUV wave is transmitted by north- and south-polar coronal holes (CHs), which is observed by the Solar Dynamics Observatory (SDO) and Solar Terrestrial Relations Observatory A (STEREO-A) from opposite sides of the Sun. We obtain key findings on how the EUV wave interacts with multiple coronal structures, and on its connection with the CME-driven shock: (1) the transmitted EUV wave is still connected with the shock that is incurvated to the Sun, after the shock has reached the opposite side of the eruption; (2) the south CH transmitted EUV wave is accelerated inside an on-disk, low-density region with closed magnetic fields, which implies that an EUV wave can be accelerated in both open and closed magnetic field regions; (3) part of the primary EUV wavefront turns around a bright point (BP) with a bipolar magnetic structure when it approaches a dim, low-density filament channel near the BP; (4) the primary EUV wave is diffused and apparently halted near the boundaries of remote active regions (ARs) that are far from the eruption, and no obvious AR related secondary waves are detected; (5) the EUV wave extends to an unprecedented scale of ~360{\deg} in latitudes, which is attributed to the polar CH transmission. These results provide insights into the effects of coronal density and magnetic field distributions on the evolution of an EUV wave, and into the connection between the EUV wave and the associated CME-driven shock.Comment: 16 pages, 8 figures, and 3 animations available at http://doi.org/10.13140/RG.2.2.12408.29442 , http://doi.org/10.13140/RG.2.2.25830.06723 , and http://doi.org/10.13140/RG.2.2.19119.18088 ; published in Ap

A simulation data-driven design approach for rapid product optimization

Traditional design optimization is an iterative process of design, simulation, and redesign, which requires extensive calculations and analysis. The designer needs to adjust and evaluate the design parameters manually and continually based on the simulation results until a satisfactory design is obtained. However, the expensive computational costs and large resource consumption of complex products hinder the wide application of simulation in industry. It is not an easy task to search the optimal design solution intelligently and efficiently. Therefore, a simulation data-driven design approach which combines dynamic simulation data mining and design optimization is proposed to achieve this purpose in this study. The dynamic simulation data mining algorithm—on-line sequential extreme learning machine with adaptive weights (WadaptiveOS-ELM)—is adopted to train the dynamic prediction model to effectively evaluate the merits of new design solutions in the optimization process. Meanwhile, the prediction model is updated incrementally by combining new “good” data set to reduce the modeling cost and improve the prediction accuracy. Furthermore, the improved heuristic optimization algorithm—adaptive and weighted center particle swarm optimization (AWCPSO)—is introduced to guide the design change direction intelligently to improve the search efficiency. In this way, the optimal design solution can be searched automatically with less actual simulation iterations and higher optimization efficiency, and thus supporting the rapid product optimization effectively. The experimental results demonstrate the feasibility and effectiveness of the proposed approach

The Distribution of Transcutaneous CO2 Emission and Correlation With the Points Along the Pericardium Meridian

AbstractThis study aimed to understand energy metabolism distribution along the pericardium meridian and verify the correlation between the body surface (points), and classic meridian theory. A highly sensitive CO2 instrument was used to measure the transcutaneous CO2 emission at 13 points along the pericardium meridian line (12 points on the line and one point beyond the line) and 13 control points beside them. Results showed that the distribution of transcutaneous CO2 emission is highly related to the position on the body. Transcutaneous CO2 emission is significantly higher at P7 and P3, than the control points beside them. The points along the meridian and the points beside them were clustered with relative distance by SAS statistics software. Two distance matrixes were then obtained. The correlation coefficients between the points along the line and between the control points were calculated. The results showed that the 13th point beyond the line was far from the 12 points on the line (distance, 0.24), while acupoints on the line clustered earlier when compared with the non-acupoints. The average correlation coefficients among the acu-points was 0.65 which was significantly higher than 0.56, among the non-acupoints. No such characteristics were found among the control points. It was concluded that there is a strong correlativity of energy metabolism activity between the body surfaces along the meridian, and an even stronger correlativity between the acupoints on the meridian