Lecture |
Date |
Lesson |
Class notes section |
1 |
1/14/19 |
SECTION 1: BASIC MONTE CARLO CONCEPTS
Introduction
Statistical concepts
|
1.1-1.5 |
|
1/21/19 |
(No class - MLK holiday) |
|
2 |
1/28/19 |
Pseudo-random numbers
Quasi-random numbers
Direct inversion of PDFs
|
1.6-2.1
|
3 |
2/4/19 |
Other techniques for choosing from PDFs
Stratified sampling
Solving event-based problems
|
2.2-2.5
|
4 |
2/11/19 |
SECTION 2: EVENT-BASED MONTE CARLO TRANSPORT
Decisions during life of a neutron
Governing PDFS
Choosing from the PDFs
Flux estimation techniques
|
3.1-3.6
|
|
2/18/19 |
Test#1 (covering Lectures
1-3)
|
|
5 |
2/25/19 |
Volume, surface, and point tallies
K-effective calculations
Coding a 1D slab code
|
3.7-3-10
|
6 |
3/4/19 |
Basis of PDF-modifying variance reduction
Typical PDF-modifying variance reduction techniques
Figure of merit
|
4.1-4.5
|
7 |
3/11/19 |
Basis of variance-controlling
variance reduction
Cell weighting and weight windows |
4.6-4.10
|
|
3/18/19 |
(No class - Spring Break) |
|
8 |
3/25/19 |
SECTION 3: FUNCTION-BASED MONTE CARLO TRANSPORT
Estimation of integrals
Dirac delta function estimation
Solution of an integral equation
|
5.1-5.5
|
|
4/1/19 |
Test#2 (covering Lectures 4 through 7) |
|
9 |
4/8/19 |
Solution of linked integral equations
Neumann breakdown of recursive equations
Vector applications
|
5.6-5.9
|
10 |
4/15/19 |
Application of Dirac delta to forward IBE to form general algorithm
Application of PDFs to form specific algorithm
Tallies as integrals and/or point function values
Handout of takehome final
|
6.1-6-5
|
11 |
4/22/19 |
Advanced topics
|
|
|
5/1/19
|
Takehome Final Due
(midnight)
|
|