Modeling of Hydraulic Pipeline Transients Accompanied With Cavitation and Gas Bubbles Using Parallel Genetic Algorithms

2008 ◽  
Vol 75 (4) ◽  
Author(s):  
Songjing Li ◽  
Chifu Yang ◽  
Dan Jiang
Keyword(s):  
Experimental Data ◽  
Genetic Algorithms ◽  
Mathematical Models ◽  
Gas Bubbles ◽  
Computation Time ◽  
Unknown Parameters ◽  
Pressure Transients ◽  
Parallel Genetic Algorithms ◽  
Simulation Results ◽  
Transient Models

Mathematical models of pressure transients accompanied with cavitation and gas bubbles are studied in this paper to describe the flow behavior in a hydraulic pipeline. The reasonable prediction for pressure transients in a low pressure hydraulic pipeline largely depends on several unknown parameters involved in the mathematical models, including the initial gas bubble volumes in hydraulic oils, gas releasing and resolving time constants. In order to identify the parameters in the mathematical models and to shorten the computation time of the identification, a new method—parallel genetic algorithm (PGA)—is applied in this paper. Based on the least-square errors between the experimental data and simulation results, the fitness function of parallel genetic algorithms is programed and implemented. The global optimal parameters for hydraulic pipeline pressure transient models are obtained. The computation time of parallel genetic algorithms is much shorter than that of serial genetic algorithms. By using PGAs, the executing time is 20h. However, it takes about 204h by using GAs. Simulation results with identified parameters obtained by parallel genetic algorithms agree well with the experimental data. The comparison between simulation results and the experimental data indicates that parallel genetic algorithms are feasible and efficient to estimate the unknown parameters in hydraulic pipeline transient models accompanied with cavitation and gas bubbles.

Industrial Robot Kinematics Parameter Identification

2014 ◽  
Vol 889-890 ◽  
pp. 1136-1143
Author(s):  
Yong Gui Zhang ◽  
Chen Rong Liu ◽  
Peng Liu
Keyword(s):  
Experimental Data ◽  
Genetic Algorithms ◽  
Parameter Identification ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Robot Kinematics ◽  
Kinematic Parameters ◽  
Unknown Parameters ◽  
Preliminary Measurement ◽  
Kinematics Modeling

For an industrial robots with unknown parameters, on the basis of preliminary measurement and data of the Cartesian and joints coordinates which are shown on the FlexPendant, the kinematic parameters is identified by using genetic algorithms and accurate kinematics modeling of the robot is established. Experimental data could prove the validity of this method.

scholarly journals Numerical analysis of momentum transfer processes in a mechanically agitated air – biophase – liquid system

2017 ◽  
Vol 38 (3) ◽  
pp. 465-475 ◽  
Author(s):  
Monika Musiał ◽  
Magdalena Cudak ◽  
Joanna Karcz
Keyword(s):  
Experimental Data ◽  
Numerical Analysis ◽  
Momentum Transfer ◽  
Sucrose Concentration ◽  
Gas Bubbles ◽  
Continuous Phase ◽  
Liquid System ◽  
Numerical Computations ◽  
Transfer Processes ◽  
Simulation Results

AbstractThe results of numerical computations concerning momentum transfer processes in an air – biophase – liquid system agitated in a bioreactor equipped with baffles and a Smith turbine (CD 6 impeller) are presented in this paper. The effect of sucrose concentration on the distributions of the velocity of the continuous phase, gas hold-up and the size of gas bubbles in the system was analysed. Simulation results were presented in the form of the contours of the analysed magnitudes. The effect of sucrose concentration on the averaged values (i.e. determined on the basis of local values) of gas hold-up and gas bubbles size was evaluated. The results of the numerical computations of gas hold-up were compared with our own experimental data.

Modeling and Simulation of a Co-current Rotary Dryer

2016 ◽  
Vol 12 (2) ◽  
pp. 189-194 ◽  
Author(s):  
Zhi-gang Huang ◽  
Yun-xuan Weng ◽  
Nan Fu ◽  
Zong-qiang Fu ◽  
Dong Li ◽  
...  
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Moisture Content ◽  
Mathematical Models ◽  
Modeling And Simulation ◽  
Air Temperature ◽  
Good Accuracy ◽  
Rotary Dryer ◽  
Simulation Results ◽  
The Mathematical Model

Abstract Mathematical models including mass and energy conservation were developed in order to predict the outlet particles temperature and moisture. As the inlet air temperature increased, the outlet particles temperature increased as well and the outlet particles moisture decreased quickly. The outlet particles temperature and moisture changed a little as a function of the speed of rotation at the low inlet air temperature, while the outlet particles temperature and moisture increased very apparently with the speed of rotation increased at the high inlet air temperature. The error of the simulation results compared to the experimental data showed good accuracy for particles temperature and moisture content. The mathematical model performs well to predict the outlet particles temperature and moisture content.

Extraction of structure-based geoelectric models by hybrid genetic algorithms

Geophysics ◽  
2010 ◽  
Vol 75 (1) ◽  
pp. F15-F22 ◽  
Author(s):  
Irfan Akça ◽  
Ahmet Tuğrul Basokur
Keyword(s):  
Genetic Algorithms ◽  
Subsurface Layer ◽  
Computation Time ◽  
Physical Property ◽  
Unknown Parameters ◽  
Delaunay Triangulations ◽  
Hybrid Genetic Algorithms ◽  
Sedimentary Environments ◽  
Lithologic Unit ◽  
Inversion Techniques

A major difficulty in electrical resistivity imaging is the identification of the lithologic units, especially in the sedimentary environments. The geologic interpretation generally is realized by visual inspection of the final resistivity section. Although sharp boundary inversion techniques based on a local linearization could allow the delineation of interfaces between geologic units, these techniques will succeed only if an initial model already close to the best solution is available. Stochastic algorithms might localize a point around the global minimum of the misfit function; however, they are not efficient at finding the precise solution. For this reason, our previously published hybrid genetic algorithms, derived from evolution theories, are used to verify structure-based models. The geometric parameters are defined by thickness values of the lithologic units at control points distributed along the horizontal axis. A zero thickness value indicates the nonexistence of a certain unit at the corresponding con-trol point. An unstructured grid composed of irregular triangles is constructed by the application of Delaunay triangulations to represent complicated structural boundaries. In addition, the computation time for the calculation of model response is reduced greatly by this strategy. Because the suggested parameterization reduces the number of unknown parameters to a few tens and the computation time for the model responses is reduced by the Delaunay triangulation, the implementation of hybrid genetic algorithms for 2D problems becomes possible. A huge number of models are generated randomly in the first generation (a population of parameters) and then updated in subsequent generations by the simulation of biological processes. The suggested algorithms consist of two computational phases. In the first stage, the physical property of each subsurface layer is represented by a distinct resistivity value. After some succeeding genera-tions, laterally varying resistivities within the same lithologic unit are permitted to simulate lateral changes in geologic conditions.

Research on Parallel Genetic Algorithms Related Logistics Transportation Scheduling Problem

2013 ◽  
Vol 411-414 ◽  
pp. 2704-2709
Author(s):  
Yu Qiang Chen ◽  
Wei Jun Yang
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Scheduling Problem ◽  
Parallel Genetic Algorithm ◽  
Parallel Genetic Algorithms ◽  
Transportation Scheduling ◽  
Simulation Results

The research based on complex RVRP. On the basis of deep analysis, a parallel genetic algorithm was designed. Simulation results proved that the parallel genetic algorithm is more excellent than conventional serial genetic algorithm.

scholarly journals Dynamic Model Parameter Identification and Simulation of SCR Based on Genetic Algorithm§

2015 ◽  
Vol 9 (1) ◽  
pp. 62-66
Author(s):  
Ren Hongjuan ◽  
Lou Diming ◽  
Zhu Jian ◽  
Luo Yiping
Keyword(s):  
Experimental Data ◽  
Genetic Algorithm ◽  
Kinetic Model ◽  
Parameter Identification ◽  
Dynamic Model ◽  
Unknown Parameters ◽  
Exhaust Temperature ◽  
Allowable Error ◽  
Simulation Results ◽  
Model Equations

The Selective Catalytic Reduce (SCR) is studied. The unknown parameters of the SCR kinetic model equations are fitted based on the Genetic Algorithm (GA), which is in the range of the allowable error, compared to the experimental data. Then in AVL Boost software, the simulation results of SCR reaction are obtained. Compared to the test data, the simulation results prove that the parameter identification is effective. At last, the SCR reaction is simulated in AVL Boost, and at the same exhaust temperature, the effect of GHSV and NSR on the SCR reaction is studied.

Integrating experimental data and mathematical models in simulation of physical systems

AIAA Journal ◽  
1997 ◽  
Vol 35 ◽  
pp. 1787-1790
Author(s):  
Boris A. Zeldin ◽  
Andrew J. Meade
Keyword(s):  
Experimental Data ◽  
Mathematical Models ◽  
Physical Systems

BEHAVIORAL MODEL OF A LINEAR VOLTAGE STABILIZER IN THE SPICE LANGUAGE

2019 ◽  
Author(s):  
Aleksey Malahanov
Keyword(s):  
Experimental Data ◽  
Behavioral Model ◽  
Voltage Stabilizer ◽  
Static Mode ◽  
Technical Description ◽  
Simulation Results ◽  
Chip Manufacturer ◽  
Linear Voltage

A variant of the implementation of the behavioral model of a linear voltage stabilizer in the Spice language is presented. The results of modeling in static mode are presented. The simulation results are compared with experimental data and technical description of the chip manufacturer.

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