Use of a genetic algorithm to solve fluid flow problems on an NCUBE/2 multiprocessor computer
This paper presents a method to solve partial differential equations governing two-phase fluid flow by using a genetic algorithm on the NCUBE/2 multiprocessor computer. Genetic algorithms represent a significant departure from traditional approaches of solving fluid flow problems. The inherent parallelism of genetic algorithms offers the prospect of obtaining solutions faster than ever possible. The paper discusses the two-phase flow equations, the genetic representation of the unknowns, the fitness function, the genetic operators, and the implementation of the genetic algorithm on the NCUBE/2 computer. The paper investigates the implementation efficiency using a pipe blowdown test and presents the effects of varying both the genetic parameters and the number of processors. The results show that genetic algorithms provide a major advancement in methods for solving two-phase flow problems. A desired goal of solving these equations for a specific simulation problem in real time or faster requires computers with an order of magnitude more processors or faster than the NCUBE/2's 1024.
- Research Organization:
- Sandia National Labs., Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE; USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC04-76DP00789
- OSTI ID:
- 5365046
- Report Number(s):
- SAND-91-2532; ON: DE92014044
- Country of Publication:
- United States
- Language:
- English
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Use of a genetic algorithm to solve two-fluid flow problems on an NCUBE multiprocessor computer
Use of a genetic algorithm to solve two-fluid flow problems on an NCUBE multiprocessor computer
Related Subjects
SUPERCONDUCTIVITY AND SUPERFLUIDITY
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
NAVIER-STOKES EQUATIONS
NUMERICAL SOLUTION
TWO-PHASE FLOW
PARALLEL PROCESSING
ALGORITHMS
ARRAY PROCESSORS
HYPERCUBE COMPUTERS
COMPUTERS
DIFFERENTIAL EQUATIONS
EQUATIONS
FLUID FLOW
MATHEMATICAL LOGIC
PARTIAL DIFFERENTIAL EQUATIONS
PROGRAMMING
665000* - Physics of Condensed Matter- (1992-)
990200 - Mathematics & Computers