English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The cooling pipe network system of the power plant has the characteristics of multiple users, multiple working conditions, and complex topological structure. The division of water supply to the pipe network can simplify the topological structure of the pipe network, facilitate flow regulation, and adapt to the requirements of multiple working conditions. District water supply can be divided into districts according to flow, pressure and structure. The user allocation of pipe network water supply system is a typical combined optimization problem. When the system is relatively complex and the number of users is huge, conventional enumeration methods, dynamic programming and other methods are often unable to solve such problems. The combined algorithm of particle swarm algorithm and genetic algorithm can obtain approximate solutions to such problems. By using a combination of particle swarm algorithm and genetic algorithm to analyze and determine the distribution of pipe network user traffic, it is possible to avoid the waste of energy in the distribution of pipe network users based on experience. The combined algorithm proposed in this paper has high stability, can change the number of partitions to adjust user allocation according to actual needs, and has strong versatility. For the case described in this article, when the number of partitions is 2, compared to the cases where the number of partitions is 3 and 4, the flow rate and pressure drop of each partition are not much different, which can better meet the reliability and maintainability requirements

Optimization of Multi-zone Cooling System of Complex Pipe Network Based on Particle Swarm and Genetic Algorithm