scholarly journals Combining Monte Carlo simulations and experimental design for incorporating risk and uncertainty in investment decisions for cleantech: a fast pyrolysis case study

2018 ◽  
Vol 20 (6) ◽  
pp. 1195-1206 ◽  
Author(s):  
Tom Kuppens ◽  
Parisa Rafiaani ◽  
Kenny Vanreppelen ◽  
Jan Yperman ◽  
Robert Carleer ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Experimental Design ◽  
Monte Carlo Simulations ◽  
Fast Pyrolysis ◽  
Investment Decisions ◽  
Risk And Uncertainty

Risk Based Contingency in Project Cost Estimates

2017 ◽  
pp. 130-138
Author(s):  
Mohammed Shafique Malik
Keyword(s):  
Monte Carlo ◽  
Cost Estimation ◽  
Investment Decisions ◽  
Senior Management ◽  
Cost Estimate ◽  
Project Cost ◽  
Final Project ◽  
Calculation Methodology ◽  
Project Risks

Project Cost estimation is carried out for making investment decisions. Cost estimation is carried out during different phases of the project. Contingency in cost estimation is an important factor before releasing final cost estimate for formal approval of the project by senior management. Major Petrochemical companies use risk-based contingency calculation instead of following a standard practice of adding a certain fixed percentage to the final project cost estimate. In this chapter, cost contingency calculation methodology has been elaborated by conducting case study of a sample project. The methodology described here uses famous tool of Monte Carlo for simulation. It is pragmatic approach to calculate required cost contingency in the project cost estimate, based upon the particular project risks as compared to simply following rule of adding fixed percentage of the estimate as cost contingency in overall project cost estimate.

MONTE CARLO SIMULATIONS FOR THE RISK MANAGEMENT OF ENVIRONMENTAL POLLUTION

2010 ◽  
Vol 12 (01) ◽  
pp. 87-101
Author(s):  
OSAMA A. B. HASSAN
Keyword(s):  
Risk Management ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Monte Carlo Simulations ◽  
Environmental Pollution ◽  
Human Health ◽  
Stochastic Models ◽  
Chemical Pollution ◽  
The Monte Carlo Method

This article attempts to adapt the Monte Carlo method to the quantitative risk management of environmental pollution. In this context, the feasibility of stochastic models to quantitatively evaluate the risk of chemical pollution is first discussed and then linked to a case study in which Monte Carlo simulations are applied. The objective of the case study is to develop a Monte Carlo scheme for evaluating the pollution in a lake environment. It is shown that the results can be of interest as they define the risk margins that are important to the sustainability of the ecosystem in general, and human health in particular. Moreover, assessing the environmental pollution with the help of the Monte Carlo method can be feasible and serve the purpose of investigating and controlling the environmental pollution, in the long and short terms.

Multivariate Normal Data: A Tool for Instruction

1992 ◽  
Vol 19 (3) ◽  
pp. 188-189 ◽  
Author(s):  
John F. Walsh
Keyword(s):  
Monte Carlo ◽  
Experimental Design ◽  
Monte Carlo Simulations ◽  
Covariance Structure ◽  
Data Sets ◽  
Multivariate Normal ◽  
International Mathematical ◽  
Statistical Library ◽  
Scale Transformations

Courses in statistics and experimental design can be enhanced through use of crafted data sets. The use of examples highlights the interface between data and statistical routine. FORTRAN programs utilizing the International Mathematical and Statistical Library subroutines permit the user to control the variance—covariance structure of multivariate normal variables and build data sets that have instructional value. Scale transformations and Monte Carlo simulations of the data can be performed as well.

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