The joint optimal operation of cascade reservoir system can greatly improve the utilization of water resources. However, the complex high-dimensional and non-linear features and calculated costs often hinder the refined operation and management of reservoirs. Recently, the local parallel computing has become an effective way to alleviate the "curse of dimensionality". Current local parallel computing has hardware limitations, which is difficult to adapt to large-scale computing. This study proposes a novel parallel dynamic programming algorithm based on Spark (PDPoS) via cloud computing. The simulation experiments are carried out for a comparative analysis of the solution efficiency, influence factors and stability of cloud computing. The results are as follows: (1) The efficiency of the cloud-based PDPoS is related to some factors; the number of CPU cores is the main influencing factor, followed by the operator, and the architecture has the least influence. (2) The runtime variance of cloud computing is 2.03, indicating cloud computing has high stability. (3) Under the same configuration (i.e., CPU and memory), the runtime of cloud computing is 41.5%?~?110.3% longer than that of physical machines. However, cloud computing has rich resources, good scalability, and good portability of online operations, which is an attractive alternative for optimal operation of large-scale reservoir system.
To shed light on the effect of pulse flow on shear force and membrane fouling, the pulse frequency and flow velocity based on fiber Bragg grating (FBG) sensing technology were studied. The results show that there is a threshold for this synergy between the pulse frequency and flow velocity, which forms more easily at a high pulse frequency and low flow velocity. Moreover, the transition from pulse flow to continuous flow affects the shear force distribution with the membrane module height. Besides, at the same volumetric flow, Re gradually reaches a plateau as the pulse frequency increases from 1 to 5 Hz, and the membrane fouling control has a better flux recovery, which can reach a maximum of 28.89%. Finally, the results also show that the combined effect of high pulse frequency and low flow velocity would be higher than that of low pulse frequency and high flow velocity. 相似文献