The simulation of a natural gas pipeline network allows us to predict the behavior of a gas network system under different conditions. Such predictions can be effectively used to guide decisions regarding the design and operation of the real system. The simulation is generally associated with a high computational cost since the pipeline network is becoming more and more complex, as well as large-scale. In our previous study, the Decoupled Implicit Method for Efficient Network Simulation (DIMENS) method was proposed based on the ‘Divide-and-Conquer Approach’ ideal, and its computational speed was obviously high. However, only continuity/momentum Equations of the simple pipeline network composed of pipelines were studied in our previous work. In this paper, the DIMENS method is extended to the continuity/momentum and energy Equations coupled with the complex pipeline network, which includes pipelines and non-pipeline components. The extended DIMENS method can be used to solve more complex engineering problems than before. To extend the DIMENS method, two key issues are addressed in this paper. One is that the non-pipeline components are appropriately solved as the multi-component interconnection nodes; the other is that the procedures of solving the energy Equation are designed based on the gas flow direction in the pipeline. To validate the accuracy and efficiency of the present method, an example of a complex pipeline network is provided. From the result, it can be concluded that the accuracy of the proposed method is equivalent to that of the Stoner Pipeline Simulator (SPS), which includes commercially available simulation core codes, while the efficiency of the present method is over two times higher than that of the SPS.
Cymbaria daurica L. is widely used in traditional Mongolian medicine for the treatment of impetigo, psoriasis, pruritus, fetotoxicity, and diabetes. Therefore, the anti-inflammatory and a-glucosidase-inhibitory activities of four polar C. daurica extracts (water, n-butanol, ethyl acetate, and petroleum ether extract) were preliminarily evaluated to identify the active extracts. We also investigated the chemical composition of the active extracts by phytochemical analysis. The n-butanol and ethyl acetate extracts exhibited significant (p < 0.05) anti-inflammatory activities by inhibiting lipopolysaccharide-induced nitric oxide (NO) production in RAW 264.7 cells. None of the tested extracts exhibited cytotoxic effects at the effective concentrations. The ethyl acetate extract significantly inhibited a-glucosidase activity, and the inhibition potency was equivalent to that of acarbose (p > 0.05). The n-Butanol extract presented the second highest inhibitory activity. As the n-butanol and ethyl acetate extracts were found to have potent antiinflammatory and a-glucosidase-inhibitory activities, we separated and identified 10 compounds from the extracts. Among them, vanillic acid, cistanoside F, echinacoside, arenarioside, verbascoside, isoacteoside, and tricin were isolated from C. daurica for the first time. Further, 30 compounds from the n-butanol and ethyl acetate extracts of C. daurica were identified using UHPLC-Q-Exactive. The present study demonstrates for the first time that C. daurica contains phenylethanoid glycosides. In addition, this novel HPLC method was subsequently used for simultaneous identification of five compounds in the n-butanol and ethyl acetate extracts of C. daurica. This study provides a chemical basis for further characterization and utilization of C. daurica, which could be a potential source of novel anti-diabetic and anti-inflammatory agents.
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