Carter M. Mast. Participants: Peter Mackenzie-Helnwein, Pedro Arduino, and Greg Miller. 6 th MPM Workshop Albuquerque, New Mexico August 9-10, 2010

Size: px
Start display at page:

Download "Carter M. Mast. Participants: Peter Mackenzie-Helnwein, Pedro Arduino, and Greg Miller. 6 th MPM Workshop Albuquerque, New Mexico August 9-10, 2010"

Transcription

1 Representing Arbitrary Bounding Surfaces in the Material Point Method Carter M. Mast 6 th MPM Workshop Albuquerque, New Mexico August 9-10, 2010 Participants: Peter Mackenzie-Helnwein, Pedro Arduino, and Greg Miller Department of Civil and Environmental Engineering University of Washington Seattle, WA

2 Outline Motivation and Overview Approach Implementation Outlook/Future Research 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 2

3 Motivation Loading on structures due to landslide/debris flows Landslide/Debris flow Appropriate numerical method (MPM) Material models Phase transition Etcetera Domain Topological l --- e.g. hll hillside Structural Both require general surfaces 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 3

4 Motivation Loading on structures due to landslide/debris flow Landslide/Debris flow Appropriate numerical method (MPM) Material models Phase transition Etcetera Domain Topological l --- e.g. hll hillside Structural Both require general surfaces 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 4

5 Overview Disadvantages of this surface representation: Surface is dependent on the computational nodes 8/9/2010 Unrealistic Carter Mast - University of Washington - 6th MPM Workshop 5

6 Overview Potential solutions/fix to the surface representation problem: Refine the mesh Represent esent the surface as a rigid body Irregular mesh over entire domain Computational tion expensive e Increase total number of particles Search algorithm Meshing algorithm 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 6

7 Overview Potential solutions to the surface representation problem: Refine the mesh Represent esent the surface as a rigid body Irregular mesh over entire domain Computational tion expensive e Increase total number of particles Search algorithm Meshing algorithm Introduce a second grid Dual-Grid Approach 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 7

8 Approach Ω A Ω α Dual-Grid methodology Introduce a separate (additional) grid that follows the geometry of the bounding surface Two grids, one body Effectively communicate dynamic information between the two grids 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 8

9 Approach Dual-Grid methodology The Blending Approach Each grid is used to create independent fields for velocity and acceleration Piecewise description: 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 9

10 Approach Ω A Ω α Φ The Blending Approach Enforce continuity along Φ Leads to the constraint of the form 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 10

11 Approach The Blending Approach Algorithmic implementation: 1. Use the traditional MPM algorithm to solve for nodal acceleration and velocity at time t n for those nodes in the boundary grid. 2. Solve for the nodal accelerations on the standard grid. 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 11

12 Approach The Blending Approach Algorithmic implementation: 3. Solve for the nodal velocities on the standard grid. 4. Update nodal values for both grids. 5. Update particles: a. For particles with p then the update comes from boundary grid nodes. b. For particles with then the update comes form p standard d grid nodes. 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 12

13 Implementation Evaluate algorithm using one- dimensional test case Uniaxial steel bar subjected to rigid boundary Standard d MPM: 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 13

14 Implementation 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 14

15 Implementation 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 15

16 Implementation Arbitrary boundary representation in 1-d: 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 16

17 Implementation 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 17

18 Implementation 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 18

19 Implementation 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 19

20 Implementation 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 20

21 Implementation From the 1-d results: Certain configurations (boundary location and boundary cell size) are problematic. Particularly for the Enhanced approach. The Blending approach provides more consistent results Boundary grid size should be similar to the standard grid size. 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 21

22 Implementation From the 1-d results: Certain configurations (boundary location and boundary cell size) are problematic. Boundary grid size should be similar to the standard grid size. 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 22

23 Implementation Moving into 2- and 3-d Increasing complexity Boundary orientation Evaluation of the integral linking the two grids Fully 3-d code restricted to planar boundaries with regular node spacing 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 23

24 Implementation A relatively straight forward problem 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 24

25 Implementation Single particle analysis 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 25

26 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 26

27 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 27

28 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 28

29 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 29

30 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 30

31 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 31

32 Implementation Single particle analysis Discretization A 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 32

33 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 33

34 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 34

35 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 35

36 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 36

37 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 37

38 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 38

39 Implementation Single particle analysis Discretization A Discretization B 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 39

40 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 40

41 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 41

42 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 42

43 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 43

44 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 44

45 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 45

46 Outlook Successfully models all boundary locations/orientations for the single particle The standard d MPM results are recovered Very little consistency from one boundary location to another Body or grid discretization error? Formulation error? Coding error? 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 46

47 Future Work Continue to try and find out why/what is causing the inconsistency. Implement the alternative dual-grid approach hin 2- and d3d 3-d. Explore alternative methods for incorporating an arbitrary boundary geometry into the Material Point Method. 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 47

48 Thank you! All workshop participants PI P.I. s Peter Mackenzie-Helnwein, i Pedro Arduino, and Greg Miller. The National Science Foundation grant CMMI /9/2010 Carter Mast - University of Washington - 6th MPM Workshop 48

49 QUESTIONS???? 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 49

50 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 50

51 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 51

52 Approach Dual-Grid methodology The Enhanced Velocity Field Approach The total velocity and acceleration field exists as a superposition from both grids.... With the conditions for 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 52

53 Approach Ω A Ω α Γ The Enhanced Velocity Field Approach Enforce essential condition along Γ Leads to a constraint of the form 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 53

54 Approach The Enhanced Velocity Field Approach Algorithmic implementation: 1. Obtain the nodal acceleration at time t n for those nodes in the boundary grid as well as the standard grid by solving the system. 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 54

55 Approach The Enhanced Velocity Field Approach Algorithmic implementation: 2. Obtain the nodal velocity at time t n for those nodes in the boundary grid as well as the standard grid by solving the system. 3. Update nodal values for both grids. 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 55

56 Approach The Enhanced Velocity Field Approach Algorithmic implementation: 4. Update all particles using the nodes on the standard grid. 5. For those particles with p, perform an additional update using those nodes in the boundary grid. 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 56

57 Implementation 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 57

58 Implementation 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 58

59 Implementation 8/9/2010 Carter Mast - University of Washington - 6th MPM Workshop 59

Lecture 10: Reinforcement Learning

Lecture 10: Reinforcement Learning Lecture 1: Reinforcement Learning Cognitive Systems II - Machine Learning SS 25 Part III: Learning Programs and Strategies Q Learning, Dynamic Programming Lecture 1: Reinforcement Learning p. Motivation

More information

BMBF Project ROBUKOM: Robust Communication Networks

BMBF Project ROBUKOM: Robust Communication Networks BMBF Project ROBUKOM: Robust Communication Networks Arie M.C.A. Koster Christoph Helmberg Andreas Bley Martin Grötschel Thomas Bauschert supported by BMBF grant 03MS616A: ROBUKOM Robust Communication Networks,

More information

B.S/M.A in Mathematics

B.S/M.A in Mathematics B.S/M.A in Mathematics The dual Bachelor of Science/Master of Arts in Mathematics program provides an opportunity for individuals to pursue advanced study in mathematics and to develop skills that can

More information

ME 443/643 Design Techniques in Mechanical Engineering. Lecture 1: Introduction

ME 443/643 Design Techniques in Mechanical Engineering. Lecture 1: Introduction ME 443/643 Design Techniques in Mechanical Engineering Lecture 1: Introduction Instructor: Dr. Jagadeep Thota Instructor Introduction Born in Bangalore, India. B.S. in ME @ Bangalore University, India.

More information

Axiom 2013 Team Description Paper

Axiom 2013 Team Description Paper Axiom 2013 Team Description Paper Mohammad Ghazanfari, S Omid Shirkhorshidi, Farbod Samsamipour, Hossein Rahmatizadeh Zagheli, Mohammad Mahdavi, Payam Mohajeri, S Abbas Alamolhoda Robotics Scientific Association

More information

(Sub)Gradient Descent

(Sub)Gradient Descent (Sub)Gradient Descent CMSC 422 MARINE CARPUAT marine@cs.umd.edu Figures credit: Piyush Rai Logistics Midterm is on Thursday 3/24 during class time closed book/internet/etc, one page of notes. will include

More information

PELLISSIPPI STATE TECHNICAL COMMUNITY COLLEGE MASTER SYLLABUS APPLIED MECHANICS MET 2025

PELLISSIPPI STATE TECHNICAL COMMUNITY COLLEGE MASTER SYLLABUS APPLIED MECHANICS MET 2025 PELLISSIPPI STATE TECHNICAL COMMUNITY COLLEGE MASTER SYLLABUS APPLIED MECHANICS MET 2025 Class Hours: 3.0 Credit Hours: 4.0 Laboratory Hours: 3.0 Revised: Fall 06 Catalog Course Description: A study of

More information

Artificial Neural Networks written examination

Artificial Neural Networks written examination 1 (8) Institutionen för informationsteknologi Olle Gällmo Universitetsadjunkt Adress: Lägerhyddsvägen 2 Box 337 751 05 Uppsala Artificial Neural Networks written examination Monday, May 15, 2006 9 00-14

More information

Massachusetts Institute of Technology Tel: Massachusetts Avenue Room 32-D558 MA 02139

Massachusetts Institute of Technology Tel: Massachusetts Avenue  Room 32-D558 MA 02139 Hariharan Narayanan Massachusetts Institute of Technology Tel: 773.428.3115 LIDS har@mit.edu 77 Massachusetts Avenue http://www.mit.edu/~har Room 32-D558 MA 02139 EMPLOYMENT Massachusetts Institute of

More information

PRODUCT PLATFORM DESIGN: A GRAPH GRAMMAR APPROACH

PRODUCT PLATFORM DESIGN: A GRAPH GRAMMAR APPROACH Proceedings of DETC 99: 1999 ASME Design Engineering Technical Conferences September 12-16, 1999, Las Vegas, Nevada DETC99/DTM-8762 PRODUCT PLATFORM DESIGN: A GRAPH GRAMMAR APPROACH Zahed Siddique Graduate

More information

TEACHING HEAT TRANSFER AND FLUID FLOW BY MEANS OF COMPUTATIONAL FLUID DYNAMICS (CFD)

TEACHING HEAT TRANSFER AND FLUID FLOW BY MEANS OF COMPUTATIONAL FLUID DYNAMICS (CFD) HEFAT2012 9 th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics 16 18 July 2012 Malta TEACHING HEAT TRANSFER AND FLUID FLOW BY MEANS OF COMPUTATIONAL FLUID DYNAMICS (CFD) Spalding

More information

Reinforcement Learning by Comparing Immediate Reward

Reinforcement Learning by Comparing Immediate Reward Reinforcement Learning by Comparing Immediate Reward Punit Pandey DeepshikhaPandey Dr. Shishir Kumar Abstract This paper introduces an approach to Reinforcement Learning Algorithm by comparing their immediate

More information

Introduction to Simulation

Introduction to Simulation Introduction to Simulation Spring 2010 Dr. Louis Luangkesorn University of Pittsburgh January 19, 2010 Dr. Louis Luangkesorn ( University of Pittsburgh ) Introduction to Simulation January 19, 2010 1 /

More information

Continual Curiosity-Driven Skill Acquisition from High-Dimensional Video Inputs for Humanoid Robots

Continual Curiosity-Driven Skill Acquisition from High-Dimensional Video Inputs for Humanoid Robots Continual Curiosity-Driven Skill Acquisition from High-Dimensional Video Inputs for Humanoid Robots Varun Raj Kompella, Marijn Stollenga, Matthew Luciw, Juergen Schmidhuber The Swiss AI Lab IDSIA, USI

More information

Radius STEM Readiness TM

Radius STEM Readiness TM Curriculum Guide Radius STEM Readiness TM While today s teens are surrounded by technology, we face a stark and imminent shortage of graduates pursuing careers in Science, Technology, Engineering, and

More information

A Neural Network GUI Tested on Text-To-Phoneme Mapping

A Neural Network GUI Tested on Text-To-Phoneme Mapping A Neural Network GUI Tested on Text-To-Phoneme Mapping MAARTEN TROMPPER Universiteit Utrecht m.f.a.trompper@students.uu.nl Abstract Text-to-phoneme (T2P) mapping is a necessary step in any speech synthesis

More information

Improving Action Selection in MDP s via Knowledge Transfer

Improving Action Selection in MDP s via Knowledge Transfer In Proc. 20th National Conference on Artificial Intelligence (AAAI-05), July 9 13, 2005, Pittsburgh, USA. Improving Action Selection in MDP s via Knowledge Transfer Alexander A. Sherstov and Peter Stone

More information

Given a directed graph G =(N A), where N is a set of m nodes and A. destination node, implying a direction for ow to follow. Arcs have limitations

Given a directed graph G =(N A), where N is a set of m nodes and A. destination node, implying a direction for ow to follow. Arcs have limitations 4 Interior point algorithms for network ow problems Mauricio G.C. Resende AT&T Bell Laboratories, Murray Hill, NJ 07974-2070 USA Panos M. Pardalos The University of Florida, Gainesville, FL 32611-6595

More information

Performance. In the Fall semester of 2005, one of the sections of the advanced architectural design studio in the Department of. Explorations.

Performance. In the Fall semester of 2005, one of the sections of the advanced architectural design studio in the Department of. Explorations. Forms of Performance Explorations in a BY GANAPATHY MAHALINGAM, ASSOCIATE PROFESSOR AND DIRECTOR Department of Architecture and Landscape Architecture NORTH DAKOTA STATE UNIVERSITY Fargo, North Dakota

More information

3D DIGITAL ANIMATION TECHNIQUES (3DAT)

3D DIGITAL ANIMATION TECHNIQUES (3DAT) 3D DIGITAL ANIMATION TECHNIQUES (3DAT) COURSE NUMBER: DIG3305C CREDIT HOURS: 3.0 SEMESTER/YEAR: FALL 2017 CLASS LOCATION: OORC, NORMAN (NRG) 0120 CLASS MEETING TIME(S): M 3:00 4:55 / W 4:05 4:55 INSTRUCTOR:

More information

BODY LANGUAGE ANIMATION SYNTHESIS FROM PROSODY AN HONORS THESIS SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE OF STANFORD UNIVERSITY

BODY LANGUAGE ANIMATION SYNTHESIS FROM PROSODY AN HONORS THESIS SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE OF STANFORD UNIVERSITY BODY LANGUAGE ANIMATION SYNTHESIS FROM PROSODY AN HONORS THESIS SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE OF STANFORD UNIVERSITY Sergey Levine Principal Adviser: Vladlen Koltun Secondary Adviser:

More information

Aviation English Solutions

Aviation English Solutions Aviation English Solutions DynEd's Aviation English solutions develop a level of oral English proficiency that can be relied on in times of stress and unpredictability so that concerns for accurate communication

More information

THE ROLE OF TOOL AND TEACHER MEDIATIONS IN THE CONSTRUCTION OF MEANINGS FOR REFLECTION

THE ROLE OF TOOL AND TEACHER MEDIATIONS IN THE CONSTRUCTION OF MEANINGS FOR REFLECTION THE ROLE OF TOOL AND TEACHER MEDIATIONS IN THE CONSTRUCTION OF MEANINGS FOR REFLECTION Lulu Healy Programa de Estudos Pós-Graduados em Educação Matemática, PUC, São Paulo ABSTRACT This article reports

More information

Missouri GLE FIRST GRADE. Communication Arts Grade Level Expectations and Glossary

Missouri GLE FIRST GRADE. Communication Arts Grade Level Expectations and Glossary Missouri GLE FIRST GRADE Communication Arts Grade Level Expectations and Glossary 1 Missouri GLE This document contains grade level expectations and glossary terms specific to first grade. It is simply

More information

AP Calculus AB. Nevada Academic Standards that are assessable at the local level only.

AP Calculus AB. Nevada Academic Standards that are assessable at the local level only. Calculus AB Priority Keys Aligned with Nevada Standards MA I MI L S MA represents a Major content area. Any concept labeled MA is something of central importance to the entire class/curriculum; it is a

More information

Arizona s College and Career Ready Standards Mathematics

Arizona s College and Career Ready Standards Mathematics Arizona s College and Career Ready Mathematics Mathematical Practices Explanations and Examples First Grade ARIZONA DEPARTMENT OF EDUCATION HIGH ACADEMIC STANDARDS FOR STUDENTS State Board Approved June

More information

INPE São José dos Campos

INPE São José dos Campos INPE-5479 PRE/1778 MONLINEAR ASPECTS OF DATA INTEGRATION FOR LAND COVER CLASSIFICATION IN A NEDRAL NETWORK ENVIRONNENT Maria Suelena S. Barros Valter Rodrigues INPE São José dos Campos 1993 SECRETARIA

More information

Learning Prospective Robot Behavior

Learning Prospective Robot Behavior Learning Prospective Robot Behavior Shichao Ou and Rod Grupen Laboratory for Perceptual Robotics Computer Science Department University of Massachusetts Amherst {chao,grupen}@cs.umass.edu Abstract This

More information

Mathematics subject curriculum

Mathematics subject curriculum Mathematics subject curriculum Dette er ei omsetjing av den fastsette læreplanteksten. Læreplanen er fastsett på Nynorsk Established as a Regulation by the Ministry of Education and Research on 24 June

More information

Interpreting Graphs Middle School Science

Interpreting Graphs Middle School Science Middle School Free PDF ebook Download: Download or Read Online ebook interpreting graphs middle school science in PDF Format From The Best User Guide Database. Rain, Rain, Go Away When the student council

More information

EECS 700: Computer Modeling, Simulation, and Visualization Fall 2014

EECS 700: Computer Modeling, Simulation, and Visualization Fall 2014 EECS 700: Computer Modeling, Simulation, and Visualization Fall 2014 Course Description The goals of this course are to: (1) formulate a mathematical model describing a physical phenomenon; (2) to discretize

More information

Dublin City Schools Mathematics Graded Course of Study GRADE 4

Dublin City Schools Mathematics Graded Course of Study GRADE 4 I. Content Standard: Number, Number Sense and Operations Standard Students demonstrate number sense, including an understanding of number systems and reasonable estimates using paper and pencil, technology-supported

More information

Measurement. When Smaller Is Better. Activity:

Measurement. When Smaller Is Better. Activity: Measurement Activity: TEKS: When Smaller Is Better (6.8) Measurement. The student solves application problems involving estimation and measurement of length, area, time, temperature, volume, weight, and

More information

Faculty of Engineering

Faculty of Engineering Jordan University of Science and Technology Faculty of Engineering Department of Industrial Engineering Undergraduate Curriculum for the B.Sc. Degree in Industrial Engineering Date: 16/08/2007 Vision To

More information

Hands-On CFD Educational Interface for Engineering Courses and Laboratories

Hands-On CFD Educational Interface for Engineering Courses and Laboratories Hands-On CFD Educational Interface for Engineering Courses and Laboratories FREDERICK STERN IIHR-Hydroscience & Engineering The University of Iowa TAO XING IIHR-Hydroscience & Engineering The University

More information

Hands-On CFD Educational Interface for. Engineering Courses and Laboratories

Hands-On CFD Educational Interface for. Engineering Courses and Laboratories Hands-On CFD Educational Interface for Engineering Courses and Laboratories Frederick Stern IIHR-Hydroscience & Engineering The University of Iowa Tao Xing IIHR-Hydroscience & Engineering The University

More information

Major Milestones, Team Activities, and Individual Deliverables

Major Milestones, Team Activities, and Individual Deliverables Major Milestones, Team Activities, and Individual Deliverables Milestone #1: Team Semester Proposal Your team should write a proposal that describes project objectives, existing relevant technology, engineering

More information

A Context-Driven Use Case Creation Process for Specifying Automotive Driver Assistance Systems

A Context-Driven Use Case Creation Process for Specifying Automotive Driver Assistance Systems A Context-Driven Use Case Creation Process for Specifying Automotive Driver Assistance Systems Hannes Omasreiter, Eduard Metzker DaimlerChrysler AG Research Information and Communication Postfach 23 60

More information

EGRHS Course Fair. Science & Math AP & IB Courses

EGRHS Course Fair. Science & Math AP & IB Courses EGRHS Course Fair Science & Math AP & IB Courses Science Courses: AP Physics IB Physics SL IB Physics HL AP Biology IB Biology HL AP Physics Course Description Course Description AP Physics C (Mechanics)

More information

KSBA Staff Review of HB 520 Charter Schools Rep. Carney - (as introduced )

KSBA Staff Review of HB 520 Charter Schools Rep. Carney - (as introduced ) KSBA Staff Review of HB 520 Charter Schools Rep. Carney - (as introduced 2-17-17) Section Statute Summary Comments 1 pg. 1 DEFINITIONS FOR SECTIONS 1 TO 10 Definition of achievement gap conflicts with

More information

PELLISSIPPI STATE TECHNICAL COMMUNITY COLLEGE MASTER SYLLABUS APPLIED STATICS MET 1040

PELLISSIPPI STATE TECHNICAL COMMUNITY COLLEGE MASTER SYLLABUS APPLIED STATICS MET 1040 PELLISSIPPI STATE TECHNICAL COMMUNITY COLLEGE MASTER SYLLABUS APPLIED STATICS MET 1040 Class Hours: 3.0 Credit Hours: 3.0 Laboratory Hours: 0.0 Revised: Fall 06 Catalog Course Description: A study of the

More information

COUNSELLING PROCESS. Definition

COUNSELLING PROCESS. Definition Definition COUNSELLING PROCESS The word process means an identifiable sequence of events taking place over time usually there is the implication of progressive stages in the process, Counselling has a

More information

Math Grade 3 Assessment Anchors and Eligible Content

Math Grade 3 Assessment Anchors and Eligible Content Math Grade 3 Assessment Anchors and Eligible Content www.pde.state.pa.us 2007 M3.A Numbers and Operations M3.A.1 Demonstrate an understanding of numbers, ways of representing numbers, relationships among

More information

Transfer Learning Action Models by Measuring the Similarity of Different Domains

Transfer Learning Action Models by Measuring the Similarity of Different Domains Transfer Learning Action Models by Measuring the Similarity of Different Domains Hankui Zhuo 1, Qiang Yang 2, and Lei Li 1 1 Software Research Institute, Sun Yat-sen University, Guangzhou, China. zhuohank@gmail.com,lnslilei@mail.sysu.edu.cn

More information

Maximizing Learning Through Course Alignment and Experience with Different Types of Knowledge

Maximizing Learning Through Course Alignment and Experience with Different Types of Knowledge Innov High Educ (2009) 34:93 103 DOI 10.1007/s10755-009-9095-2 Maximizing Learning Through Course Alignment and Experience with Different Types of Knowledge Phyllis Blumberg Published online: 3 February

More information

THE REFLECTIVE SUPERVISION TOOLKIT

THE REFLECTIVE SUPERVISION TOOLKIT Sample of THE REFLECTIVE SUPERVISION TOOLKIT Daphne Hewson and Michael Carroll 2016 Companion volume to Reflective Practice in Supervision D. Hewson and M. Carroll The Reflective Supervision Toolkit 1

More information

arxiv: v1 [math.at] 10 Jan 2016

arxiv: v1 [math.at] 10 Jan 2016 THE ALGEBRAIC ATIYAH-HIRZEBRUCH SPECTRAL SEQUENCE OF REAL PROJECTIVE SPECTRA arxiv:1601.02185v1 [math.at] 10 Jan 2016 GUOZHEN WANG AND ZHOULI XU Abstract. In this note, we use Curtis s algorithm and the

More information

Seminar - Organic Computing

Seminar - Organic Computing Seminar - Organic Computing Self-Organisation of OC-Systems Markus Franke 25.01.2006 Typeset by FoilTEX Timetable 1. Overview 2. Characteristics of SO-Systems 3. Concern with Nature 4. Design-Concepts

More information

AGS THE GREAT REVIEW GAME FOR PRE-ALGEBRA (CD) CORRELATED TO CALIFORNIA CONTENT STANDARDS

AGS THE GREAT REVIEW GAME FOR PRE-ALGEBRA (CD) CORRELATED TO CALIFORNIA CONTENT STANDARDS AGS THE GREAT REVIEW GAME FOR PRE-ALGEBRA (CD) CORRELATED TO CALIFORNIA CONTENT STANDARDS 1 CALIFORNIA CONTENT STANDARDS: Chapter 1 ALGEBRA AND WHOLE NUMBERS Algebra and Functions 1.4 Students use algebraic

More information

Georgetown University at TREC 2017 Dynamic Domain Track

Georgetown University at TREC 2017 Dynamic Domain Track Georgetown University at TREC 2017 Dynamic Domain Track Zhiwen Tang Georgetown University zt79@georgetown.edu Grace Hui Yang Georgetown University huiyang@cs.georgetown.edu Abstract TREC Dynamic Domain

More information

Inside the mind of a learner

Inside the mind of a learner Inside the mind of a learner - Sampling experiences to enhance learning process INTRODUCTION Optimal experiences feed optimal performance. Research has demonstrated that engaging students in the learning

More information

Circuit Simulators: A Revolutionary E-Learning Platform

Circuit Simulators: A Revolutionary E-Learning Platform Circuit Simulators: A Revolutionary E-Learning Platform Mahi Itagi Padre Conceicao College of Engineering, Verna, Goa, India. itagimahi@gmail.com Akhil Deshpande Gogte Institute of Technology, Udyambag,

More information

Introduction. Research Questions

Introduction. Research Questions Community of prospective primary teachers facing the relative motion and PCK analysis Marisa Michelini, Lorenzo Santi, Alberto Stefanel, Stefano Vercellati michelini@fisica.uniud.it, lorenzo.santi@uniud.it,

More information

Education: Integrating Parallel and Distributed Computing in Computer Science Curricula

Education: Integrating Parallel and Distributed Computing in Computer Science Curricula IEEE DISTRIBUTED SYSTEMS ONLINE 1541-4922 2006 Published by the IEEE Computer Society Vol. 7, No. 2; February 2006 Education: Integrating Parallel and Distributed Computing in Computer Science Curricula

More information

Students Understanding of Graphical Vector Addition in One and Two Dimensions

Students Understanding of Graphical Vector Addition in One and Two Dimensions Eurasian J. Phys. Chem. Educ., 3(2):102-111, 2011 journal homepage: http://www.eurasianjournals.com/index.php/ejpce Students Understanding of Graphical Vector Addition in One and Two Dimensions Umporn

More information

Questions On Spur Objectives Answers

Questions On Spur Objectives Answers On Spur Objectives Answers Free PDF ebook Download: On Spur Objectives Answers Download or Read Online ebook questions on spur objectives answers in PDF Format From The Best User Guide Database Answers

More information

What is Research? A Reconstruction from 15 Snapshots. Charlie Van Loan

What is Research? A Reconstruction from 15 Snapshots. Charlie Van Loan What is Research? A Reconstruction from 15 Snapshots Charlie Van Loan Warm-Up Question How do you evaluate the quality of a PhD Dissertation? The Skyline Factor It depends on the eye of the beholder. The

More information

CROSS-LANGUAGE INFORMATION RETRIEVAL USING PARAFAC2

CROSS-LANGUAGE INFORMATION RETRIEVAL USING PARAFAC2 1 CROSS-LANGUAGE INFORMATION RETRIEVAL USING PARAFAC2 Peter A. Chew, Brett W. Bader, Ahmed Abdelali Proceedings of the 13 th SIGKDD, 2007 Tiago Luís Outline 2 Cross-Language IR (CLIR) Latent Semantic Analysis

More information

Visualizing Architecture

Visualizing Architecture ARCH 5610: Architecture Representation 1 Visualizing Architecture Digital Techniques in Representation Instructor: Karen Lewis Office: KSA 232 Office Hours: Tuesdays, 11:30 1:30 and Wednesdays, 12:00 1:30

More information

Software Maintenance

Software Maintenance 1 What is Software Maintenance? Software Maintenance is a very broad activity that includes error corrections, enhancements of capabilities, deletion of obsolete capabilities, and optimization. 2 Categories

More information

Grade 6: Correlated to AGS Basic Math Skills

Grade 6: Correlated to AGS Basic Math Skills Grade 6: Correlated to AGS Basic Math Skills Grade 6: Standard 1 Number Sense Students compare and order positive and negative integers, decimals, fractions, and mixed numbers. They find multiples and

More information

Creating Your Term Schedule

Creating Your Term Schedule Creating Your Term Schedule MAY 2017 Agenda - Academic Scheduling Cycle - What is course roll? How does course roll work? - Running a Class Schedule Report - Pulling a Schedule query - How do I make changes

More information

ME 4495 Computational Heat Transfer and Fluid Flow M,W 4:00 5:15 (Eng 177)

ME 4495 Computational Heat Transfer and Fluid Flow M,W 4:00 5:15 (Eng 177) ME 4495 Computational Heat Transfer and Fluid Flow M,W 4:00 5:15 (Eng 177) Professor: Daniel N. Pope, Ph.D. E-mail: dpope@d.umn.edu Office: VKH 113 Phone: 726-6685 Office Hours:, Tues,, Fri 2:00-3:00 (or

More information

Montana Content Standards for Mathematics Grade 3. Montana Content Standards for Mathematical Practices and Mathematics Content Adopted November 2011

Montana Content Standards for Mathematics Grade 3. Montana Content Standards for Mathematical Practices and Mathematics Content Adopted November 2011 Montana Content Standards for Mathematics Grade 3 Montana Content Standards for Mathematical Practices and Mathematics Content Adopted November 2011 Contents Standards for Mathematical Practice: Grade

More information

Engineering Analysis with Finite Elements LS-DYNA for Undergraduate Students

Engineering Analysis with Finite Elements LS-DYNA for Undergraduate Students 12 th International LS-DYNA Users Conference Computing Technologies(4) Engineering Analysis with Finite Elements LS-DYNA for Undergraduate Students John D. Reid Department of Mechanical & Materials Engineering

More information

A Model to Detect Problems on Scrum-based Software Development Projects

A Model to Detect Problems on Scrum-based Software Development Projects A Model to Detect Problems on Scrum-based Software Development Projects ABSTRACT There is a high rate of software development projects that fails. Whenever problems can be detected ahead of time, software

More information

Moderator: Gary Weckman Ohio University USA

Moderator: Gary Weckman Ohio University USA Moderator: Gary Weckman Ohio University USA Robustness in Real-time Complex Systems What is complexity? Interactions? Defy understanding? What is robustness? Predictable performance? Ability to absorb

More information

The use of mathematical programming with artificial intelligence and expert systems

The use of mathematical programming with artificial intelligence and expert systems European Journal of Operational Research 70 (1993) 1-15 North-Holland Invited Review The use of mathematical programming with artificial intelligence and expert systems Richard D. McBride and Daniel E.

More information

9.85 Cognition in Infancy and Early Childhood. Lecture 7: Number

9.85 Cognition in Infancy and Early Childhood. Lecture 7: Number 9.85 Cognition in Infancy and Early Childhood Lecture 7: Number What else might you know about objects? Spelke Objects i. Continuity. Objects exist continuously and move on paths that are connected over

More information

Linking the Ohio State Assessments to NWEA MAP Growth Tests *

Linking the Ohio State Assessments to NWEA MAP Growth Tests * Linking the Ohio State Assessments to NWEA MAP Growth Tests * *As of June 2017 Measures of Academic Progress (MAP ) is known as MAP Growth. August 2016 Introduction Northwest Evaluation Association (NWEA

More information

MEE 6501, Advanced Air Quality Control Course Syllabus. Course Description. Course Textbook. Course Learning Outcomes. Credits.

MEE 6501, Advanced Air Quality Control Course Syllabus. Course Description. Course Textbook. Course Learning Outcomes. Credits. MEE 6501, Advanced Air Quality Control Course Syllabus Course Description An in-depth study of advanced air quality control science and management practices. Addresses health effects, environmental impacts,

More information

LEARNING THROUGH INTERACTION AND CREATIVITY IN ONLINE LABORATORIES

LEARNING THROUGH INTERACTION AND CREATIVITY IN ONLINE LABORATORIES xi LEARNING THROUGH INTERACTION AND CREATIVITY IN ONLINE LABORATORIES Michael E. Auer Professor of Electrical Engineering Carinthia University of Applied Sciences Villach, Austria My Thoughts about the

More information

Elite schools or Normal schools: Secondary Schools and Student Achievement: Regression Discontinuity Evidence from Kenya

Elite schools or Normal schools: Secondary Schools and Student Achievement: Regression Discontinuity Evidence from Kenya Elite schools or Normal schools: Secondary Schools and Student Achievement: Regression Discontinuity Evidence from Kenya Isaac M. Mbiti University of Virginia and J-PAL Introduction: Motivation Many Developing

More information

ISFA2008U_120 A SCHEDULING REINFORCEMENT LEARNING ALGORITHM

ISFA2008U_120 A SCHEDULING REINFORCEMENT LEARNING ALGORITHM Proceedings of 28 ISFA 28 International Symposium on Flexible Automation Atlanta, GA, USA June 23-26, 28 ISFA28U_12 A SCHEDULING REINFORCEMENT LEARNING ALGORITHM Amit Gil, Helman Stern, Yael Edan, and

More information

Executive Guide to Simulation for Health

Executive Guide to Simulation for Health Executive Guide to Simulation for Health Simulation is used by Healthcare and Human Service organizations across the World to improve their systems of care and reduce costs. Simulation offers evidence

More information

Penn State University - University Park MATH 140 Instructor Syllabus, Calculus with Analytic Geometry I Fall 2010

Penn State University - University Park MATH 140 Instructor Syllabus, Calculus with Analytic Geometry I Fall 2010 Penn State University - University Park MATH 140 Instructor Syllabus, Calculus with Analytic Geometry I Fall 2010 There are two ways to live: you can live as if nothing is a miracle; you can live as if

More information

Innovating Toward a Vibrant Learning Ecosystem:

Innovating Toward a Vibrant Learning Ecosystem: KnowledgeWorks Forecast 3.0 Innovating Toward a Vibrant Learning Ecosystem: Ten Pathways for Transforming Learning Katherine Prince Senior Director, Strategic Foresight, KnowledgeWorks KnowledgeWorks Forecast

More information

Designing a Rubric to Assess the Modelling Phase of Student Design Projects in Upper Year Engineering Courses

Designing a Rubric to Assess the Modelling Phase of Student Design Projects in Upper Year Engineering Courses Designing a Rubric to Assess the Modelling Phase of Student Design Projects in Upper Year Engineering Courses Thomas F.C. Woodhall Masters Candidate in Civil Engineering Queen s University at Kingston,

More information

Faculty Schedule Preference Survey Results

Faculty Schedule Preference Survey Results Faculty Schedule Preference Survey Results Surveys were distributed to all 199 faculty mailboxes with information about moving to a 16 week calendar followed by asking their calendar schedule. Objective

More information

UNIV 101E The Student in the University

UNIV 101E The Student in the University UNIV 101E The Student in the University Catalog Course Description UNIV 101E-The Student in the University (Engineering Section). (3) The purpose of higher education and potential roles of the student

More information

OPTIMIZATINON OF TRAINING SETS FOR HEBBIAN-LEARNING- BASED CLASSIFIERS

OPTIMIZATINON OF TRAINING SETS FOR HEBBIAN-LEARNING- BASED CLASSIFIERS OPTIMIZATINON OF TRAINING SETS FOR HEBBIAN-LEARNING- BASED CLASSIFIERS Václav Kocian, Eva Volná, Michal Janošek, Martin Kotyrba University of Ostrava Department of Informatics and Computers Dvořákova 7,

More information

The IDN Variant Issues Project: A Study of Issues Related to the Delegation of IDN Variant TLDs. 20 April 2011

The IDN Variant Issues Project: A Study of Issues Related to the Delegation of IDN Variant TLDs. 20 April 2011 The IDN Variant Issues Project: A Study of Issues Related to the Delegation of IDN Variant TLDs 20 April 2011 Project Proposal updated based on comments received during the Public Comment period held from

More information

Juris Doctor (J.D.) Program

Juris Doctor (J.D.) Program Stetson Law Part-Time Juris Doctor (J.D.) Program full-time Quality Stetson offers a welcoming, supportive and inclusive environment in which students can develop the knowledge and skills needed to succeed

More information

Computer Graphics and Human-Computer Interaction at the University of Zaragoza, Spain

Computer Graphics and Human-Computer Interaction at the University of Zaragoza, Spain Computer Graphics and Human-Computer Interaction at the University of Zaragoza, Spain Abstract Francisco José Serón, Sandra Baldassarri, Juan Antonio Magallón, Pedro Latorre Grupo de Informática Gráfica

More information

PROGRAM AND EXAMINATION REGULATIONS FOR THE MASTER S PROGRAM IN INDUSTRIAL AND APPLIED MATHEMATICS

PROGRAM AND EXAMINATION REGULATIONS FOR THE MASTER S PROGRAM IN INDUSTRIAL AND APPLIED MATHEMATICS PROGRAM AND EXAMINATION REGULATIONS FOR THE MASTER S PROGRAM IN INDUSTRIAL AND APPLIED MATHEMATICS The official Onderwijs- en Examenregeling (OER) for IAM is a document in Dutch. This introduction provides

More information

University of Illinois

University of Illinois Overview At The Frederick Seitz Materials Research Laboratory NSF-supported FRG P.I. R. Martin (Physics) and D.D. Johnson(MatSE, Physics) Develop infrastructure to support and foster advances in multidisciplinary

More information

Rolando Cardenas 8100 Turquoise St. El Paso, Texas (915) University of Texas at El Paso (UTEP)

Rolando Cardenas 8100 Turquoise St. El Paso, Texas (915) University of Texas at El Paso (UTEP) Rolando Cardenas 8100 Turquoise St. El Paso, Texas 79904 (915) 497-6558 roncardenas3@gmail.com University of Texas at El Paso (UTEP) Education: PhD in Computational Science, UTEP, Expected Grad. 2013 Master

More information

Generating Test Cases From Use Cases

Generating Test Cases From Use Cases 1 of 13 1/10/2007 10:41 AM Generating Test Cases From Use Cases by Jim Heumann Requirements Management Evangelist Rational Software pdf (155 K) In many organizations, software testing accounts for 30 to

More information

Paul E. Slaboch. University of Notre Dame, Notre Dame, IN. Master of Science, January 2008 Aerospace Engineering

Paul E. Slaboch. University of Notre Dame, Notre Dame, IN. Master of Science, January 2008 Aerospace Engineering Paul E. Slaboch 103D Cebula Hall, St. Martin s University, Lacey, WA 98513 (360) 688-2742 pslaboch@stmartin.edu EDUCATION Ph.D. in Aerospace Engineering, May 2009 Dissertation: Fluid Mechanics and Passive

More information

A Lesson Study Project: Connecting Theory and Practice Through the Development of an Exemplar Video for Algebra I Teachers and Students

A Lesson Study Project: Connecting Theory and Practice Through the Development of an Exemplar Video for Algebra I Teachers and Students A Lesson Study Project: Connecting Theory and Practice Through the Development of an Exemplar Video for Algebra I Teachers and Students 2010 NCSM Annual Conference San Diego, CA April 19-21, 2010 Dr. Anne

More information

Commanding Officer Decision Superiority: The Role of Technology and the Decision Maker

Commanding Officer Decision Superiority: The Role of Technology and the Decision Maker Commanding Officer Decision Superiority: The Role of Technology and the Decision Maker Presenter: Dr. Stephanie Hszieh Authors: Lieutenant Commander Kate Shobe & Dr. Wally Wulfeck 14 th International Command

More information

SARDNET: A Self-Organizing Feature Map for Sequences

SARDNET: A Self-Organizing Feature Map for Sequences SARDNET: A Self-Organizing Feature Map for Sequences Daniel L. James and Risto Miikkulainen Department of Computer Sciences The University of Texas at Austin Austin, TX 78712 dljames,risto~cs.utexas.edu

More information

Myers-Briggs Type Indicator Team Report

Myers-Briggs Type Indicator Team Report Myers-Briggs Type Indicator Team Report Developed by Allen L. Hammer Sample Team 9112 Report prepared for JOHN SAMPLE October 9, 212 CPP, Inc. 8-624-1765 www.cpp.com Myers-Briggs Type Indicator Team Report

More information

UTILITY POLE ATTACHMENTS Understanding New FCC Regulations and Industry Trends

UTILITY POLE ATTACHMENTS Understanding New FCC Regulations and Industry Trends COURSE UTILITY POLE ATTACHMENTS Understanding New FCC Regulations and Industry Trends May 1-2, 2017 Atlanta Marriott Suites Midtown Atlanta, GA EUCI is authorized by IACET to offer 1.0 CEUs for this course

More information

Learning Semantic Maps Through Dialog for a Voice-Commandable Wheelchair

Learning Semantic Maps Through Dialog for a Voice-Commandable Wheelchair Learning Semantic Maps Through Dialog for a Voice-Commandable Wheelchair Sachithra Hemachandra and Matthew R. Walter Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology

More information

Curriculum Guide 7 th Grade

Curriculum Guide 7 th Grade Curriculum Guide 7 th Grade Kesling Middle School LaPorte Community School Corporation Mr. G. William Wilmsen, Principal Telephone (219) 362-7507 Mr. Mark Fridenmaker, Assistant Principal Fax (219) 324-5712

More information

Integrating simulation into the engineering curriculum: a case study

Integrating simulation into the engineering curriculum: a case study Integrating simulation into the engineering curriculum: a case study Baidurja Ray and Rajesh Bhaskaran Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York, USA E-mail:

More information

Constraining X-Bar: Theta Theory

Constraining X-Bar: Theta Theory Constraining X-Bar: Theta Theory Carnie, 2013, chapter 8 Kofi K. Saah 1 Learning objectives Distinguish between thematic relation and theta role. Identify the thematic relations agent, theme, goal, source,

More information

College and Career Ready Performance Index, High School, Grades 9-12

College and Career Ready Performance Index, High School, Grades 9-12 Dr. John D. Barge, State School Superintendent Making Education Work for All of Georgia s Students College and Career Ready Performance Index, High School, Grades 9-12 CONTENT MASTERY (END of COURSE TESTS

More information

AGENDA LEARNING THEORIES LEARNING THEORIES. Advanced Learning Theories 2/22/2016

AGENDA LEARNING THEORIES LEARNING THEORIES. Advanced Learning Theories 2/22/2016 AGENDA Advanced Learning Theories Alejandra J. Magana, Ph.D. admagana@purdue.edu Introduction to Learning Theories Role of Learning Theories and Frameworks Learning Design Research Design Dual Coding Theory

More information