The grinding hardening is an integrated manufacturing technology which combines the surface hardening theory and the grinding technology. However, the grinding chatter accompanies with the whole grinding hardening process. It is the existence of the grinding chatter that makes the transformation unsteady. To this end, the paper presents a three-hybrid model to investigate the relationship between the grinding chatter and the grinding hardening layers distribution. The dynamic grinding force with the analytic and numerical method is calculated firstly. Then the finite difference method (FDM) is used to obtain the dynamic temperature distribution accordingly. Thirdly, the cellular automata (CA) method is applied to calculate the transformed microstructure distribution under different chatter strengths. The study shows that the thickness of the grinding hardening layers goes up with the increase of the grinding chatter. However, the quality of the grinding hardening layers reduces with the increase of the chatter strength. In addition, the martensite content varies with different hardening layers since each layer has its own unique temperature distribution. Moreover, metallurgical experiments are conducted to validate the proposed model. The model is anticipated to be meaningful for the improvements of workpiece's mechanical properties by controlling the chatter strength in the industry manufacturing.
In this study, a polarization selective beam splitter constructed by only a single layer subwavelength multisubpart profile grating is presented. Rigorous coupled-wave analysis is adopted to investigate the properties of the structure. It is shown that for a transverse electric polarized wave, the device demonstrates very high reflectivity (>97%) from 1.46 to 1.58 μm; and for a transverse magnetic polarized wave, at the wavelength of 1.55 μm, it exhibits about 50/50 beam ratio under normal incidence. To evaluate the response of the polarizing beam splitters under variation in structure parameters, we also investigated the fabrication tolerances of the device.
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An efficient and robust method for analyzing constituents of a well-known traditional Chinese medicine (TCM) formula SiWu decoction (SWD) contains AngelicaeSinensis Radix (ASR), Chuanxiong Rhizoma (CR), Paeoniae Radix Alba (PRA), and RehmanniaeRadix Praeparata (RRP) by ultra high-performance liquid chromatography (UHPLC)/time-of-flight mass spectrometry (TOF-MS) was established. The method efficiently applied to the separation of 75 compounds, including organic acids, phthalides, phenylpropanoid glycosides, iridoid glycosides, monoterpene glycosides, and galloyl glycosides in the complex prescription, 52 compounds in this study can be unambiguously identified or tentatively characterized. The separation was achieved within 20 min at the optimized chromatographic conditions. Our study provided a reliable and high-efficient method for the understanding of the chemical basis of SWD.
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As more and more distributed generation resources are integrated into the grid through smart micro-grid, achieving a more economic and better responsive distributed generation dispatch is of great importance. Economic and environmental characteristics of distributed generation are synthetically combined in a dispatch model with objective function of minimum generation cost and emission cost in this paper, and also a novel algorithm Shuffled Frog Leap Algorithm (SFLA) optimized by random Nelder Mead (RNM) model was proposed to solve the economic and environmental problem. At last, the differences in generation cost and Computation time of RNM-SFLA, Genetic Algorithm (GA), Evolutionary Programming (EP) and Shuffled Frog Leap Algorithm (SFLA) are compared with a numerical example, verifying the feasibility and advancement of environmental and economic dispatch model based on RNM-SFLA.
PL
W artykule przedstawiono model przesyłu energii elektrycznej w systemie elektroenergetycznym, mający na celu minimalizację kosztów wytwarzania i przesyłu energii. Zaproponowano także nowy algorytm SFL (ang. Shuffled Frog Leap), który został zoptymalizowany metodą Nelder’aa-Mead’a. Algorytm ma zastosowanie w rozwiązywaniu zagadnień ekonomicznych i środowiskowych. Przeprowadzona została analiza porównawcza opisanego modelu.
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