Monte Carlo Simulation in Sampling Techniques of Traffic Data Collection

2002 ◽  
Vol 1804 (1) ◽  
pp. 91-97 ◽  
Author(s):  
Derek G. Williamson ◽  
Maosheng Yao ◽  
John McFadden
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Probability Function ◽  
Time Frame ◽  
Cumulative Probability ◽  
Sampling Techniques ◽  
Traffic Data ◽  
Traffic Data Collection ◽  
Traffic Volumes

Traffic volume counts are used in transportation planning, design, operation, and safety analyses. A new methodology establishes a statistical basis for comparing traffic volumes generated from different samples. Monte Carlo simulation was used to generate a cumulative probability function (CPF) of traffic volumes based on the fit-of-Weibull probability distribution to a particular traffic sample. A 90% confidence interval of the traffic volumes from a given traffic sample was obtained from the CPF and was used to compare different traffic samples. A case study was performed by using this methodology to determine if shorter time-frame data may be used to represent longer-time traffic. Results from the case study show that traffic at 20-min intervals may be used to represent 1-h traffic when moderate to high traffic volumes are considered. It was observed that subsamples failed to represent the 1-h traffic data for lower traffic volumes of selected vehicle types.

An Importance Sampling Approach for Time-Dependent Reliability

2011 ◽  
Author(s):  
Amandeep Singh ◽  
Zissimos P. Mourelatos ◽  
Efstratios Nikolaidis
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Random Process ◽  
Importance Sampling ◽  
Sampling Technique ◽  
Process Time ◽  
Cumulative Probability ◽  
Repairable Systems ◽  
Importance Sampling Method ◽  
True Value

Reliability is an important engineering requirement for consistently delivering acceptable product performance through time. The reliability usually degrades with time increasing the lifecycle cost due to potential warranty costs, repairs and loss of market share. Reliability is the probability that the system will perform its intended function successfully for a specified time. In this article, we consider the first-passage reliability which accounts for the first time failure of non-repairable systems. Methods are available which provide an upper bound to the true reliability which may overestimate the true value considerably. The traditional Monte-Carlo simulation is accurate but computationally expensive. A computationally efficient importance sampling technique is presented to calculate the cumulative probability of failure for random dynamic systems excited by a stationary input random process. Time series modeling is used to characterize the input random process. A detailed example demonstrates the accuracy and efficiency of the proposed importance sampling method over the traditional Monte Carlo simulation.

Application of life cycle assessment and Monte Carlo simulation for enabling sustainable product design

2014 ◽  
Vol 12 (3) ◽  
pp. 307-315 ◽  
Author(s):  
Sekar Vinodh ◽  
Gopinath Rathod
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Life Cycle Assessment ◽  
Life Cycle ◽  
Product Design ◽  
Sustainable Product Design ◽  
Content Type ◽  
Sustainable Product ◽  
Manufacturing Organization

Purpose – The purpose of this paper is to present an integrated technical and economic model to evaluate the reusability of products or components. Design/methodology/approach – Life cycle assessment (LCA) methodology is applied to obtain the product’s environmental performance. Monte Carlo simulation is utilized for enabling sustainable product design. Findings – The results show that the model is capable of assessing the potential reusability of used products, while the usage of simulation significantly increases the effectiveness of the model in addressing uncertainties. Research limitations/implications – The case study has been conducted in a single manufacturing organization. The implications derived from the study are found to be practical and useful to the organization. Practical implications – The paper reports a case study carried out for an Indian rotary switches manufacturing organization. Hence, the model is practically feasible. Originality/value – The article presents a study that investigates LCA and simulation as enablers of sustainable product design. Hence, the contributions of this article are original and valuable.

Uncertainty Analysis and Monitoring of Earth Dam

2014 ◽  
Vol 580-583 ◽  
pp. 954-957
Author(s):  
Ling Qiang Yang ◽  
Rui Gao ◽  
Yan Wang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Probabilistic Method ◽  
Finite Difference Methods ◽  
Earth Dam ◽  
Earth Dams ◽  
Program Code ◽  
Physical Behavior ◽  
Difference Methods

Monte Carlo simulation provides a probabilistic method to evaluate the physical behavior of earth dam. Therefore, the behavior could be got in a more realistic manner. Based on the theory, an innovative software program code is developed by combining the Monte Carlo and finite difference methods to predict the performance of earth dams after impounding. In order to assess the efficiency of the method, the case study of earth dam, located at Southeast of China, has been studied in detail. The performance of this dam is predicted and compared with the field monitoring by using the monitoring data. The results shows the robustness of the proposed method.

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