cven302-501 computer applications in engineering and construction dr. jun zhang
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CVEN302-501CVEN302-501
Computer Applications in Computer Applications in
Engineering and ConstructionEngineering and Construction
Dr. Jun Zhang
TeachingTeaching AssistantsAssistantsMr. TBA
(Section 501 and computer lab)
Office: Room
Phone:
Email:
Office Hour:
Lab Hours: Mon & Thur 7:00-9:00pm
Course ObjectivesCourse Objectives To develop the ability to solve engineering problems
numerically
To evaluate numerical solution methods (knowing the
advantages and limitations of numerical methods)
To design, implement, and test computer programs
To improve the skills of writing MATLAB codes
Objective: “Numerical methods”Objective: “Numerical methods”
Numerical methods give solutions to math problems written as algebraic statements that computers can execute
We will learn to formulate the solutions and evaluate their applicability and performance.
Objective: “Design”Objective: “Design”
Writing the solutions as a series of steps a computer can execute flow chart and pseudo-code
Objective: “Implementation”Objective: “Implementation”
Converting the pseudo-code solution into a computer program.
Objective: “Testing”Objective: “Testing”
Checking that the computer program actually solves the equations you mean to solve
Evaluating the success of the numerical solution chosen
Numerical accuracy, stability, and efficiency
Objective: “Evaluation”Objective: “Evaluation”
Critical evaluation of the solution the program gives for the actual engineering problem.
This requires all your engineering and computer skills
Objective: “Presentation”Objective: “Presentation”
Communication of the results of a computer program to the people who need to know the answer
Clients Bosses Regulators Contractors
Chapter 1Chapter 1
Mathematical Modeling and Engineering Problem Solving
Engineering ProblemsEngineering ProblemsEmpiricalobservation and experimentcertain aspects of empirical studies occur repeatedly such general behavior can be expressed as
fundamental laws that essentially embody the cumulative wisdom of past experience
Theoretical / Numerical formulation of fundamental lawsAlgebraic
ODE
PDE qy
T
x
T
dt
xdm
dt
dvmF
E ;maF
2
2
2
2
2
2
Mathematical ModelsMathematical Models
Modeling is the development of a mathematical representation of a physical/biological/chemical/ economic/etc. system
Putting our understanding of a system into math
Problem Solving Tools: Analytic solutions, statistics, numerical methods,
graphics, etc.Numerical methods are one means by which
mathematical models are solved
Mathematical ModelingThe process of solving an engineering or physical problem.
C o m m o n fe a tu reso p era tion
A p p lica tio ns
S o lu tio ns
A n a lytica l & Num erical Methods
F o rm u la tion o r G o vern ingE q ua tio ns
M a th em a tica l M od e ling A p pro x im a tio n & A ssu m p tion
E n g ine e ring o r P h ys ica l p rob le m s(D e sc rip tio n )
Bungee JumperBungee Jumper
You are asked to predict the velocity of a bungee jumper as a function of time during the free-fall part of the jump
Use the information to determine the length and required strength of the bungee cord for jumpers of different mass
The same analysis can be applied to a falling parachutist or a rain drop
Newton’s Second Law
F = ma = Fdown - Fup
= mg - cdv2 (gravity minus air resistance)
Observations / Experiments
Where does mg come from?
Where does -cdv2 come from?
Bungee Jumper / Falling ParachutistBungee Jumper / Falling Parachutist
Now we have fundamental physical laws, so we combine those with observations to model the system
A lot of what you will do is “canned” but need to know how to make use of observations
How have computers changed problem solving in engineering?
Allow us to focus more on the correct description of the problem at hand, rather than worrying about how to solve it.
Newton’s Second Law
Exact (Analytic) SolutionExact (Analytic) Solution
2d
2d
vm
cg
dt
dv
vcmgdt
dvm
Exact Solution
t
m
gc
c
mgtv d
d
tanh)(
Numerical MethodNumerical Method
i1i
i1i
0t
tt
tvtv
t
v
t
v
dt
dv
)()(
lim
What if cd = cd (v) const? Solve the ODE numerically!Solve the ODE numerically!
Assume constant slope (i.e, constant drag force)
over t
Finite difference (Euler’s) method
Numerical (Approximate) SolutionNumerical (Approximate) Solution
2i
d
i1i
i1i
i1i
i1i
tvm
cg
tt
tvtv
tt
tvtv
t
v
dt
dv
)()()(
)()(
Numerical Solution
)()()()( i1i2
id
i1i tttvm
cgtvtv
Example 1.2 Hand CalculationsExample 1.2 Hand CalculationsA stationary bungee jumper with m = 68.1 kg leaps from a stationary hot air balloon. Use the Euler’s method with a time increment of 2 s to compute the velocity for the first 12 s of free fall. Assume a drag coefficient of 0.25 kg/m.
0tv0t
tttvm
cgtvtv
00
i1i2
id
i1i
)( ;
)()()()(
Explicit time-marching scheme
m = 68.1 kg, g = 9.81 m/s2, cd = 0.25 kg/m
sm6008511012312351168
250819312351vs12t
sm312351810180250168
250819180250vs10t
sm18025068298346168
250819298346vs8t
sm29834646413736168
250819413736vs6t
sm43173624620019168
250819620019vs4t
sm620019020168
2508190vs2t
2
2
2
2
2
2
/.)().(.
... ;
/.)().(.
... ;
/.)().(.
... ;
/.)().(.
... ;
/.)().(.
... ;
/.)()(.
.. ;
Euler’s MethodEuler’s Method
Step 1
Step 2
Step 3
Step 4
Step 5
Step 6
The solution accuracy depends on time increment
Use a constant time increment t = 2 s
Example: Bungee JumperExample: Bungee Jumper
Olympic 10-m Platform DivingOlympic 10-m Platform Diving
mgvvcmgdt
dvmWater
mgvcmgdt
dvmAir
wdw
a2da
:
:Buoyant Force
cda cdw
Example: Finite Elements and Example: Finite Elements and Structural AnalysisStructural Analysis
Simple truss - force balance Complex truss
Instead of limiting our analysis to simple cases, numerical method allows us to work on realistic cases.