
PSL DEM Lecture 01: Motivation
26 Jan 2008  Teaching Materials  Contributor(s): Carl Wassgren, Avik Sarkar
The Particulate Systems Laboratory at Purdue University presents the Discrete Element Modeling (DEM) Short Course Series. This is Lecture 01: Motivation.

PSL DEM Lecture 02: Hard Particle Collision Modeling
26 Jan 2008  Teaching Materials  Contributor(s): Carl Wassgren, Avik Sarkar
The Particulate Systems Laboratory at Purdue University presents the Discrete Element Modeling (DEM) Short Course Series. This is Lecture 02: Hard Particle Collision Modeling

PSL DEM Lecture 03: Hard Particle Contact Detection
26 Jan 2008  Teaching Materials  Contributor(s): Carl Wassgren, Avik Sarkar
The Particulate Systems Laboratory at Purdue University presents the Discrete Element Modeling (DEM) Short Course Series. This is Lecture 03: Hard Particle Contact Detection.

PSL DEM Lecture 06: Introduction to SoftParticle DEM and Normal Contact Force Models  Part I
26 Jan 2008  Teaching Materials  Contributor(s): Carl Wassgren, Avik Sarkar
The Particulate Systems Laboratory at Purdue University presents the Discrete Element Modeling (DEM) Short Course Series. This is Lecture 06: Introduction to SoftParticle DEM and Normal Contact Force Models  Part I.

PSL DEM Lecture 07: Normal Contact Force Models  Part II
26 Jan 2008  Teaching Materials  Contributor(s): Carl Wassgren, Avik Sarkar
The Particulate Systems Laboratory at Purdue University presents the Discrete Element Modeling (DEM) Short Course Series. This is Lecture 07: Normal Contact Force Models  Part II.

PSL DEM Lecture 13: 3D Rotations
26 Jan 2008  Teaching Materials  Contributor(s): Carl Wassgren, Avik Sarkar
The Particulate Systems Laboratory at Purdue University presents the Discrete Element Modeling (DEM) Short Course Series. This is Lecture 13: 3D Rotations.

Probability Theory Review
05 May 2008  Teaching Materials  Contributor(s): Gary Blau
For any real system or phenomenon, there will be a certain amount of variability associated with data generated by the system.Probability is the language used to characterize and interpret the variability of this data.Probability is the most widely used formalism for quantifying uncertainty.

Review of Statistics
05 May 2008  Teaching Materials  Contributor(s): Gary Blau
This lecture covers the following topicsDifference between statistics and probabilityStatistical InferenceSamples and populationsIntro to JMP software packageCentral limit theoremConfidence intervalsHypothesis testingRegression and modeling fundamentalsIntroduction to Model BuildingSimple linear...

Single Factor Experiments
05 May 2008  Teaching Materials  Contributor(s): Gary Blau
The purpose of single factor experiments is to:Quantify relationship between a single factor and a single measured or response variableCompare the relative effectiveness of two or more treatments (levels of the factor).Estimate the level of the factor that optimizes the response variable

Factorial Experimentation
05 May 2008  Teaching Materials  Contributor(s): Gary Blau
A full factorial experiment is a set of experimental runs such that all levels of a given factor are combined with all levels of every other factor.