Cloud computing technology and its application in simulation and analysis of large-scale LNG storage tanks
LNG storage tank is one of the most core equipments of liquefied natural gas (LNG) receiving station, and with the increase of natural gas demand, the development trend of LNG storage tank is large-scale and super-large-scale. Due to the complex structure, high cost, harsh working conditions and high safety requirements of large-scale LNG storage tanks, a large number of finite element analysis calculations must be carried out during the design process, and the feasibility of the design scheme is verified based on the results of the simulation calculations. The finite element simulation technology of large-scale LNG storage tanks involves a series of complex modeling, load solving, normalization and other technologies, which is a great challenge to the tool software and the engineer's personal technical ability and experience, and it is difficult to meet the requirements of rapid program design and optimization and improvement of the traditional single person - single tool work mode, so my team in the large-scale LNG storage tanks for many years, on the basis of the accumulation of experience in the simulation technology combined with Therefore, based on years of experience in large-scale LNG storage tank simulation technology, my team combines cloud computing technology with the bottom software and hardware resources, technical experience, industry specifications and other unified planning and construction to form a simulation cloud platform for LNG storage tanks, and releases the simulation function to the application engineers in the form of professional APP service to realize the rapid promotion and application of technical experience, and this paper makes a systematic elaboration on the key technology and application effect.
Authors
- Ningning Ji
- Tuanhai Chen (ORCID: https://orcid.org/0009-0002-5235-3943)
- Xingshu Wang
- Bendong Wang
- Hailin Xiang
- Cong Zhen
Institutions
- Beijing Institute of Technology (CN)
Publication Details
- Published
- 2024-08-30
- DOI
- https://doi.org/10.1145/3708282.3708313
- Primary Topic
- Advanced Data Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00