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  1. 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.

  2. 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

  3. 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.

  4. PSL DEM Lecture 06: Introduction to Soft-Particle 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 Soft-Particle DEM and Normal Contact Force Models - Part I.

  5. 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.

  6. 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.

  7. 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.

  8. 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...

  9. 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

  10. 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.