| # |
Date |
Lesson |
Reading |
| 1 |
1/10/08 |
Part
I: Event based Monte Carlo Theory
Introduction
Statistical
formulae
|
pp.
296-298
313-321 |
| 2 |
1/17/08 |
"Random"
number generation
Quasi-random
|
Numerical
Recipes
(7.0,7.1) |
| 3 |
1/24/08 |
Choosing
variables from distributions
Metropolis method
|
|
| 4 |
1/31/08 |
Choosing
from common transport distributions |
|
| 5 |
2/7/08 |
Test#1:
Event-based Theory
Part
II: Event based Variance Reduction
1D slab
event-based transport
exercise
|
|
6
|
2/14/08 |
Traditional variance
reduction techniques
|
|
7
|
2/21/08 |
MCNP Variance
reduction techniques |
|
8
|
2/28/08 |
Use of adjoint
solutions
|
|
|
3/6/08 |
Test#2:
Variance Reduction Methods
|
Paper#1 |
9
|
3/27/08 |
Part
III: Function-based Monte Carlo Theory
Monte Carlo Approximation of functions
Basis of MC integration
Application to integral
equations
|
|
| 10 |
4/3/08 |
Application to
differential equations
Linked equations
Neumann analysis
|
|
| 11 |
4/10/08 |
Application to
Boltzmann Transport Equation
|
Paper#2 |
| 12 |
4/17/08 |
Test#3:
Function-based Monte Carlo
Part
IV: MCNP Analysis
MCNP input: Geometry and materials
|
KSU
tutorial |
| 13 |
4/24/08 |
MCNP input:
Sources and tallies
MCNP variance reduction
|
|
| |
5/1/08
Midnight
|
Project: MCNP
takehome project due
|
|
NE582 Monte Carlo