scholarly journals Calibrating the Micromechanical Parameters of the PFC2D(3D) Models Using the Improved Simulated Annealing Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Min Wang ◽  
Ping Cao
Keyword(s):  
Numerical Simulation ◽  
Simulated Annealing ◽  
3D Model ◽  
Simulated Annealing Algorithm ◽  
3D Models ◽  
Calibration Process ◽  
Bond Model ◽  
Physical Experiments ◽  
Annealing Algorithm ◽  
The Relationship

PFC2D(3D) is commercial software, which is commonly used to model the crack initiation of rock and rock-like materials. For the PFC2D(3D) numerical simulation, a proper set of microparameters need to be determined before the numerical simulation. To obtain a proper set of microparameters for PFC2D(3D) model based on the macroparameters obtained from physical experiments, a novel technique has been carried out in this paper. The improved simulated annealing algorithm was employed to calibrate the microparameters of the numerical simulation model of PFC2D(3D). A Python script completely controls the calibration process, which can terminate automatically based on a termination criterion. The microparameter calibration process is not based on establishing the relationship between microparameters and macroparameters; instead, the microparameters are calibrated according to the improved simulated annealing algorithm. By using the proposed approach, the microparameters of both the contact-bond model and parallel-bond model in PFC2D(3D) can be determined. To verify the validity of calibrating the microparameters of PFC2D(3D) via the improved simulated annealing algorithm, some examples were selected from the literature. The corresponding numerical simulations were performed, and the numerical simulation results indicated that the proposed method is reliable for calibrating the microparameters of PFC2D(3D) model.

ESTIMATING AND ENHANCING THE FEEDBACKABILITY OF COMPLEX NETWORKS

2018 ◽  
Vol 21 (02) ◽  
pp. 1850005
Author(s):  
CHENGYI TU ◽  
RUIYANG YAN
Keyword(s):  
Simulated Annealing ◽  
Complex Networks ◽  
Structural Properties ◽  
Real World ◽  
Simulated Annealing Algorithm ◽  
Random Perturbation ◽  
Optimal Perturbation ◽  
Topological Features ◽  
Annealing Algorithm ◽  
The Relationship

In this paper, we explore the relationship between Minimum Feedbackability Set (MFS) and Feedbackability Set (FS) of complex networks and use simulated annealing algorithm to obtain a relatively fast and reliable estimation of the MFS. Then, we implement this method to estimate the MFS of some real-world networks and explore whether the topological features influence the size of MFS. Additionally, we propose an optimal perturbation strategy to enhance the feedbackability of complex networks. Finally, we also research the intricate relationship between the structural properties and the feedbackability of various networks perturbed by optimal and random perturbation strategies.

A New Solution for Maxterm Problem in Trigonometric Functions by Simulated Annealing Algorithm

2013 ◽  
Vol 4 (2) ◽  
pp. 20-28
Author(s):  
Farhad Soleimanian Gharehchopogh ◽  
Hadi Najafi ◽  
Kourosh Farahkhah
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Trigonometric Functions ◽  
Matlab Software ◽  
Annealing Algorithm ◽  
Do So

The present paper is an attempt to get total minimum of trigonometric Functions by Simulated Annealing. To do so the researchers ran Simulated Annealing. Sample trigonometric functions and showed the results through Matlab software. According the Simulated Annealing Solves the problem of getting stuck in a local Maxterm and one can always get the best result through the Algorithm.

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