The Use of Data to Identify Systems for Reliability Assessment Using Monte-Carlo Simulation Techniques

1989 ◽  
pp. 694-704
Author(s):  
A M Featherstone ◽  
K Ghazvini
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Reliability Assessment ◽  
Simulation Techniques ◽  
Use Of Data

Reliability assessment of bioreactor landfills using Monte Carlo simulation and coupled hydro-bio-mechanical model

2018 ◽  
Vol 72 ◽  
pp. 329-338 ◽  
Author(s):  
Krishna R. Reddy ◽  
Girish Kumar ◽  
Rajiv K. Giri ◽  
B. Munwar Basha
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Mechanical Model ◽  
Reliability Assessment ◽  
Bioreactor Landfills

scholarly journals Practical Risk Assessment of Ground Vibrations Resulting from Blasting, Using Gene Expression Programming and Monte Carlo Simulation Techniques

2020 ◽  
Vol 10 (2) ◽  
pp. 472 ◽  
Author(s):  
Amir Mahdiyar ◽  
Danial Jahed Armaghani ◽  
Mohammadreza Koopialipoor ◽  
Ahmadreza Hedayat ◽  
Arham Abdullah ◽  
...  
Keyword(s):  
Gene Expression ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Gene Expression Programming ◽  
Sensitivity Analyses ◽  
Accurate Estimation ◽  
Blasting Operation ◽  
Simulation Techniques ◽  
Input Variables ◽  
The Impact

Peak particle velocity (PPV) is a critical parameter for the evaluation of the impact of blasting operations on nearby structures and buildings. Accurate estimation of the amount of PPV resulting from a blasting operation and its comparison with the allowable ranges is an integral part of blasting design. In this study, four quarry sites in Malaysia were considered, and the PPV was simulated using gene expression programming (GEP) and Monte Carlo simulation techniques. Data from 149 blasting operations were gathered, and as a result of this study, a PPV predictive model was developed using GEP to be used in the simulation. In order to ensure that all of the combinations of input variables were considered, 10,000 iterations were performed, considering the correlations among the input variables. The simulation results demonstrate that the minimum and maximum PPV amounts were 1.13 mm/s and 34.58 mm/s, respectively. Two types of sensitivity analyses were performed to determine the sensitivity of the PPV results based on the effective variables. In addition, this study proposes a method specific to the four case studies, and presents an approach which could be readily applied to similar applications with different conditions.

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