Engineering at TAMU

1
Engineering at TAMU

• Its the M of TAMU!

2
University Structure

• College of Agriculture and Life Science
• College of Architecture
• College of Education and Human Development
• College of Geosciences
• College of Liberal Arts

• College of Science
• College of Veterinary Medicine
• Dwight Look College of Engineering
• George Bush School of Government and Public
  Service
• Mays Business School

3
Dwight Look College of Engineering(http//enginee
ring.tamu.edu/academics/depts.html)

• Aerospace
• Biological and Agricultural
• Biomedical
• Chemical
• Civil
• Computer Science

• Electrical and Computer
• Engineering Technology and Industrial
  Distribution
• Industrial and Systems
• Mechanical
• Nuclear
• Petroleum

4
COE Greatness!

• http//engineering.tamu.edu/about/look_college.htm
  l
• http//engineering.tamu.edu/about/facts.html

5
Curriculum for Engineering Students

• Degree Plans
• http//engineering.tamu.edu/academics/degrees.html
  
• Difference in freshman and sophomore years are
  minimal
• All take math through differential equations
• Introductory chemistry and physics
• In transition on freshman and sophomore
  engineering classes (http//engineering.tamu.edu/a
  cademics/engr-courses.html)

6
Stats on Students

• http//eapo.tamu.edu/stats.htm
• Student retention
• Lose about 20-25 of freshman
• Minority kids
• Females
• Regents Scholars are not doing well
• Supply more than half of the engineers in Texas

7
Understanding Research

• Research begins with a question The hypothesis
• Objectives are defined to test the hypothesis
• Experiments are designed to generate results to
  meet the objectives
• Can be theoretical simulations
• Can be field studies
• Can be laboratory (bench) studies
• Others

8
Experimental Design

• Experiments are typically designed to generate
  model parameters
• What is a model?
• Can be a mathematical formulation
• Can be a theoretical construct
• Models in engineering usually mean an equation or
  series of equations to be solved

9
CONTROLS!!!

• Experimental design should include controls
• Negative ones
• Positive ones
• Baselines/zero values
• Replication is essential
• Know the assumptions
• Rarely can we include all the complexities
• Engineering is a lot about the assumptions

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Assumptions

• One of the great strengths of engineering is
  learning how to make simplifying assumptions
• Take complex problems or situations and reduce
  them to the essentials
• What is most important
• What can be neglected
• Of course, there is always the potential for poor
  assumptions which lead to wrong answers!

11
Models

• Can be a way to organize information
• Can be used to describe a chemical reaction,
  physical phenomenon, biological sequence, etc.
• Usually developed first
• Then design the experiments
• So results are fed into the model for
  interpretation
• Often an iterative process

12
Results

• Experimental design should anticipate the kind of
  results to be generated
• Should know how these results will be analyzed
  before experiments are performed
• Can design experiments with a publication in mind
• Sometimes just exploring

13
Data Interpretation

• Perhaps data fed into a model
• Statistical analysis?
• Curve fitting exercises
• Something is measured, but what does it mean?
• Compare to existing literature
• Refute or support the literature?

14
Presentations

• Use your BEST data!
• The data is what the data is.
• Experiments often fail
• Edison failed more than 3,000 times before he got
  the light bulb to work!
• There can be valuable information from failed
  experiments

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Good research leads to more questions!

• We never run out of things to study.
• Which may explain why professors are accused of
  being experts in minutia?!