Heidi Elliott
El Campo High School
El Campo ISD
POWER SET Sponsor
Cable Kurwitz
Department of Nuclear Engineering
Nuclear Power Institute
Texas A&M University
University to Classroom Connection

Pre-Test
 How would you distinguish between discrete
and continuous data?
 What is the difference between
domain/range for a function and
domain/range for the problem situation?
University to Classroom Connection

Day 1:
 Introduction to Engineering
○ What is an Engineer?
○ Who is an Engineer?
○ What is a project?
○ What is Engineering Design?
Remember when?
TVs were in black & white
 Computers first came out

What could tomorrow bring?
Objectives for Today:

Introduce you to what is meant by
“Engineering”
More Specifically:






CHINN & RAO
What is Engineering?
Who are Engineers?
What is a Project?
Where do Projects
Originate?
What’s the difference between “Good”
Engineering and, ah, er, well…you know?!’
What is the design process?
E3 Program - Summer 2012
6
Evidence of Engineering is everywhere…
From: blog.lib.umn.edu/muwah005/architecture/
CHINN & RAO
From: www.educ.uvic.ca/.../438/CHINA/CHINA-WALL.HTML
E3 Program - Summer 2012
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Remember when?

Cell phones
Engineering Design then, is:
“… the process of applying various techniques
and scientific principles for the purpose of defining
a device, a process or a system in sufficient detail
to permit its realization.
…Design may be simple or enormously complex,
easy or difficult, mathematical or nonmathematical; it may involve a trivial problem or
one of great importance.”
(From “Design of Machinery” by R.L.Norton, 2004)
CHINN & RAO
E3 Program - Summer 2012
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What happens when the designs
don’t work ?
Titanic – an “unsinkable” ship
 New London, Texas School
 1971-1976 Ford Pinto
 Space Shuttles: Challenger & Columbia
 Union Carbide – Bhopal, India
 Chernobyl
 Milwaukee Water Treatment Plant
 British Petroleum
 Toyota Motor Company
 The
CHINN & RAO
E3 Program - Summer 2012
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Engineering Design Process
The Design
Process shown
Graphically
Courtesy Project Lead The Way
CHINN & RAO
E3 Program - Summer 2012
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University to Classroom Connection

Day 2:
 Nuclear Engineering Project: Liquid/Gas
Inventory and Location Determination
○ Purpose
○ Process
○ Plan
 Develop Prototype
○ Calculate prototype criteria/restrictions
 Materials
 Costs
Space Engineering Research Center

Mission:
 To raise the Technology Readiness Level (TRL) of
important Space Technologies by assisting
Business, Government, and Education with
Research and Development Projects
ic Hydrogen is that the density difference between the
liquid and vapor is small resulting in similar responses
to gauging methods. Photon sources and detectors
coupled with a new approach to interpreting the data
can be used to create a quick, accurate gauging system.
This report analyzes this gauging technique using
Monte Carlo N-Particle transport code (MCNP) and
compressed sensing decompression methods.
Model: The figure below shows the tank, sources,
and detectors configuration.
cross-section properties: 1.0 MeV has little relative
interaction, 0.1 MeV has peak scattering, 0.01 MeV is
close to equal scattering and absorption, and 0.001
MeV is almost purely absorption. Pair production
would unnecessarily complicate the analysis and thus
the photon source energy didn’t exceed 1.0 MeV. Scat-
Og Gas/Fluid Inventory Determination
The propellant tank was modeled as a regular cylinder with spherical end-caps, with dimensions of 5 m
inner diameter and 10 m inner height. The tank wall
was 1 cm thick aluminum. The hydrogen was modeled
with 0.0246 g/cm3 vapor density and 0.0380 g/cm3
liquid density, with varying fill level.
The detectors were all modeled as 5 cm radius
spheres, and the gamma sources were modeled as isen- 14
tering is generally preferred over absorption, as we
want a wide array of energies detected from the system
Photons emitted into the tank will have a probability of
interaction per unit path length resulting in a scattering
event where the photon loses some amount of energy
or an absorption event removing the photon from the
system. The detectors measure number and energy of
the photons passing though there volume.
MCNP: The system was modeled using the dimensions and properties from the Model section. Air was
assumed to surround the tank and detectors, out to a
6 m radius. The sources emitted photons with the pre-
Og Gas/Fluid Inventory Determination

Accurate inventory determination is
challenging due to a few factors:
 Substance orientation
 Substance properties
 Measurement technique

Several RFPs have been granted to
develop new technologies to provide
better accuracy in 1g and 0g conditions
Gas Stations Today
“Gas Stations” Tomorrow
What’s The Goal?

Develop a non-intrusive, reliable, simple
instrument to accurately determine the
inventory level
 Use ‘dumb’ sensors
 Utilize simple physics
 Take advantage of ‘random’ nature of fluid
Classroom Application

Students will research prototype design
possibilities
University to Classroom Connection

Day 3-4:
 Designing experiment prototype
○ Generate prototype concepts
○ Perform design calculations
 Time Permitting:
○ Assemble prototype
 Need: green laser, sensor, container, liquid
○ Test and Evaluate
○ Refine
Classroom Application

Students will discuss research prototype
design possibilities
Classroom Application

Use equations to perform calculations
involving materials for prototype design
Classroom Application
Classroom Application
University to Classroom Connection

Day 5:
 Evaluate
 Analyze
○ Trends/Correlation
○ Predictions
 Post-Test
○ How would you distinguish between discrete
and continuous data?
○ What is the difference between domain/range
for a function and domain/range for the
problem situation?
University to Classroom Connection
Review: Engineering Design Process
Courtesy of Project Lead The Way
Future Implications

Systems involving fluids and the
need for inventory sensing and
location determination
STAAR Algebra II
Classroom Application

Introduction to Functions
 Students will collect data by
experimentation, analyze collected data and
given data, interpret the scatterplots to make
predictions, and fit the graph to the most
reasonable parent function. Students will
make predictions using representations of
the data.
Classroom Application

Relations and Functions
 Students will collect data by experimentation
and analyze the data to determine if it
represents a function. Students will
determine characteristics of the relationship
and model the data using various
representations. Students will interpret the
representations to make predictions and fit
the graph to the most reasonable parent
function
Classroom Application

Changing Parents
 Students apply geometric transformations to
relations. Students determine rules to
predict effects on changing parameters on
parent functions. Students determine graphs
and equations from the predictions.
Classroom Application

Linear programming
 Students will be expected to formulate
systems of equations and inequalities from
this particular situation, use a variety of
methods to solve, and then analyze the
solution in terms of the situation.
TEKS

2A1. Foundation for functions. The student uses
properties and attributes of functions and applies
functions to problem situations. The student is
expected to
 1A: Identify the mathematical domains and
ranges of functions and determine reasonable
domain and range values for continuous and
discrete situations.
 1B: Collect and organize data, make and
interpret scatter plots, fit the graph of a function
to the data, interpret the results, and proceed to
model, predict, and make decisions and critical
judgments.
TEKS

2A.3: Foundations for functions. The student
formulates systems of equations and inequalities
from problem situations, uses a variety of methods
to solve them, and analyzes the solutions in terms
of the situations. The student is expected to
 3A: Analyze situations and formulate systems of
equations in two or more unknowns or
inequalities in two unknowns to solve problems.
 3B: Use algebraic methods, graphs, tables, or
matrices, to solve systems of equations or
inequalities.
 3C: Interpret and determine the reasonableness
of solutions to systems of equations or
inequalities for given contexts.
TEKS

2A.4: Algebra and geometry. The student
connects algebraic and geometric representations
of functions. The student is expected to:
 4A: Identify and sketch graphs of parent
functions, including linear, quadratic,
exponential, and logarithmic functions, absolute
value of x, square root of x, and reciprocal of x.
 4B: Extend parent functions with parameters
and describe the effects of the parameter
changes on the graph of parent functions.
TEKS

2A.7: Quadratic and square root functions. The
student interprets and describes the effects of
changes in the parameters of quadratic functions
in applied and mathematical situations. The
student is expected to:
 7B: Use the parent function to investigate,
describe, and predict the effects of changes in a,
h, and k on the graphs of form of a functions in
applied and purely mathematical situations.
TEKS

2A.9: Quadratic and square root functions. The
student formulates equations and inequalities
based on square root functions, uses a variety of
methods to solve them, and analyzes the solutions
in terms of the situation. The student is expected
to:
 9A: Use the parent function to investigate,
describe, and predict the effects of parameter
changes on the graphs of square root functions
and describe limitations on the domains and
ranges.
TEKS

2A.11: Exponential and logarithmic functions. The
student formulates equations and inequalities
based on exponential and logarithmic functions,
uses a variety of methods to solve them, and
analyzes the solutions in terms of the situation.
The student is expected to:
 11B: Use the parent functions to investigate,
describe, and predict the effects of parameter
changes on the graphs of exponential and
logarithmic functions, describe limitations on the
domains and ranges, and examine asymptote
behavior.
Summary
Introduce engineering design process
 A new approach to inventory fill
determination has been demonstrated
utilizing a unique, simple, non-intrusive
detector arrangement
 Approach may potentially be capable of
accurately determining zero-g liquid
inventory and liquid location

Acknowledgements
TAMU E3 Program
 Nuclear Power Institute
 National Science Foundation

Dr. Cable Kurwitz – PI
 Jake Peterson – MS Student
 Dr. Igor Carron – Collaborator from France
