Engineering Talk - DCS's Blog on Quality and Engineering

Dimensional Analysis: How Many Monte Carlo Simulations Should I Run? Part 2

How Many Simulations Should I Run to Know That I've Run Enough?

Say that five times fast. Seriously, though, how many simulations are enough to be confident that your results are accurate?

 Edited 2-11-2015 for clarity

DCS recommends running 5000 to 20,000 simulations when analyzing a model.

Here is why:

Statistics are estimates of the parameters of a population. 3DCS results are statistics based on a sample (the number of simulations run) of an infinite population (the number of simulations that could be run). Because a statistic is an estimate, the confidence interval is used to determine how good an estimate it is. The confidence interval is calculated from the sample's size and standard deviation and the chosen confidence level (typically 90%, 95%, or 99%).

Topics: 3DCS

What Is a Confidence Interval and Why Is It Important? Part 1

Why Does the Confidence Interval for My Dimensional Analysis Matter?

Confidence intervals provide information about the relationship between the actual statistic for a given simulation and the expected value of the parameter if a simulation had an infinite number of runs.

Topics: 3DCS

Best Practices: Working with Large Models

Best Practices to Working with Large Models in CATIA and 3DCS

Large models keeping you down? Taking you an hour to save your work? 

Try some of these Tips to make your life easier. 


Topics: 3DCS T&T