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Pumped hydro energy storage (PHES) is currently the only proven large-scale energy storage technology. Frequent changes between pump and turbine operations pose significant challenges in the design of a pump-turbine runner with high efficiency and stability, especially for ultrahigh-head reversible pump-turbine runners. In the present paper, a multiobjective optimization design system is used to develop an ultrahigh-head runner with good overall performance. An optimum configuration was selected from the optimization results. The effects of key design parameters-namely blade loading and blade lean-were then investigated in order to determine their effects on runner efficiency and cavitation characteristics. The paper highlights the guidelines for application of inverse design method to high-head reversible pump-turbine runners. Middle-loaded blade loading distribution on the hub, back-loaded distribution on the shroud, and large positive blade lean angle on the high pressure side are good for the improvement of runner power performance. The cavitation characteristic is mainly influenced by the blade loading distribution near the low pressure side, and large blade lean angles have a negative impact on runner cavitation characteristics.

Ultrasound-assisted dispersive liquid-liquid microextraction (UDLLME) and simultaneous derivatization followed by GC-MS was developed for the analysis of four aldehydes including acetaldehyde (ACE), propionaldehyde (PRO), butyraldehyde (BUT) and valeraldehyde (VAL) in water samples. In the proposed method, the aldehydes were derivatized with O-2,3,4,5,6-(pentafluorobenzyl)hydroxylamine (PFBHA) and extracted by UDLLME in aqueous solution simultaneously; finally, the derivatives were analyzed by GC-MS. The experimental parameters were investigated and the method validations were studied. The optimal conditions were: aqueous sample of 5 mL, PFBHA of 50 μL, 1.0 mL ethanol (disperser solvent) containing 20 μL chlorobenzene (extraction solvent), ultrasound time of 2 min and centrifuging time of 3 min at 6000 rpm. The proposed method provided satisfactory precision (RSD 1.8-10.2%), wide linear range (0.8-160 μg/L), good linearity (R(2) 0.9983-0.9993), good relative recovery (85-105%) and low limit of detection (0.16-0.23 μg/L). The proposed method was successfully applied for the analysis of aldehydes in water samples. The experimental results showed that the proposed method was a very simple, rapid, low-cost, sensitive and efficient analytical method for the determination of trace amount of aldehydes in water samples.

In this work, polydopamine-coated magnetic graphene nanocomposites were synthesized by a simple solvothermal reaction and self-polymerization of dopamine, and the as-made nanocomposites were successfully applied as an effective adsorbent for the preconcentration of the four chlorophenols in environmental water samples before high-performance liquid chromatography. The polydopamine-coated magnetic graphene nanocomposites have several advantages such as a high surface area, fast separation ability, super-hydrophilicity, and high peak intensities for aromatic analytes. Various parameters, including eluting solvent and volume, the amounts of absorbents, extraction time and elution time were optimized. Validation experiments showed that the optimized method had good linearity (r(2) > 0.9990), satisfactory precision (RSD < 6.7%) and high recovery (90-105%). The limits of detection were 0.013-0.020 μg/L and the limits of quantification ranged from 0.043 to 0.070 μg/L. The results indicated that the proposed method had advantages of convenience, good sensitivity, and high efficiency. The method has been applied successfully to analyze chlorophenols in real water samples.