Thursday 27 November 2008

Mission to mars : How to Get People There and Back with Nuclear Energy




Mission to Mars: How to Get People There and Back with Nuclear Energy
By:
V. Dostal, K. Gezelius, J. Horng, J. Koser, J. Palaia IV, 
E. Shwageraus, P. Yarsky, and A.C. Kadak

Add and Edited By:

Arip Nurahman

Department of Physics, Faculty of Sciences and Mathematics
Indonesian University of Education


&


Follower Open Course Ware at MIT-Harvard University, Cambridge. USA.

Abstract

The goal of the design project was to develop supporting nuclear technologies for a near-term manned mission to Mars. Through the application of different nuclear technologies in a series of precursory missions, the reactor and propulsion technologies necessary for a manned mission to Mars are demonstrated before humans are committedto the trip.

As part of the project, the NASA design reference mission was adapted to make use of highly efficient, low mass, nuclear power systems and electric propulsion systems. A scalable space fission reactor and power conversion unit was developed for near-term deployment. A long-life, slow response surface fission reactor was also developed for use with in-situ resource utilization (ISRU) plants on the Martian surface.

The space power system is capable of producing up to 4 MW of DC electric power for a full- powcr lifetime of 570 days. For a VASIMR engine, 570 full power days (FPD) is equivalent to 3 round trips between Earth and Mars. The molten salt cooled fast reactor (MSFR) core is very compact, and the working fluid reaches very high temperature.

The surface powcr system produces an average of 200 kWe for more than 25 effective full powcr years (EFPY). This targeted full powcr lifetime was chosen to reduce the cost of future Mars missions by allowing for long-term infrastructure to be deployed on the surface. The surfacc system is a CO2 cooled epithermalconversion reactor (CECR) that is designedfor simple control mechanisms, long full powcr life, and ease of remote operation.

http://stuff.mit.edu/afs/athena/course/22/22.33/OldFiles/www/22.33.pdf

Thursday 20 November 2008

Aerospace Dynamics

Oleh:
Arip Nurahman
Department of Physics
Faculty of Sciences and Mathematics, Indonesia University of Education

and

Follower Open Course Ware at Massachusetts Institute of Technology
Cambridge, USA
Department of Physics
http://web.mit.edu/physics/
http://ocw.mit.edu/OcwWeb/Physics/index.htm
&
Aeronautics and Astronautics Engineering
http://web.mit.edu/aeroastro/www/
http://ocw.mit.edu/OcwWeb/Aeronautics-and-Astronautics/index.htm










 

 




Staff

Instructors:
Prof. Jonathan How
Prof. John Deyst

Course Meeting Times

Lectures:
Two sessions / week
1.5 hours / session

Level

Undergraduate


16.61 Aerospace Dynamics

Spring 2003

A gyroscope, adapted from Lecture 14. (Image courtesy of MIT OCW.)

Course Highlights

This course on Aerospace Dynamics includes a complete set of lecture notes and assignments, as well as an extensive reference reading list. Topics extend to analysis of both aircraft flight dynamics and spacecraft attitude dynamics, based upon presented principles and equations of motion.

Course Description

This undergraduate course builds upon the dynamics content of Unified Engineering, a sophomore course taught in the Department of Aeronautics and Astronautics at MIT. Vector kinematics are applied to translation and rotation of rigid bodies. Newtonian and Lagrangian methods are used to formulate and solve equations of motion. Additional numerical methods are presented for solving rigid body dynamics problems. Examples and problems describe applications to aircraft flight dynamics and spacecraft attitude dynamics.

Syllabus

Instructors
Prof. Jonathan P. How
Prof. John Deyst
Course Objectives



  1. Review of the basic Newtonian dynamics



    • Focus on 3D motion



    • Gyroscopic and rotational dynamics



    • Formal approaches for handling coordinate transformations




  2. Lagrangian formulation of the equations of motion



  3. Analysis of aircraft flight dynamics and stability



  4. Analysis of spacecraft attitude dynamics
Administrative
  1. Review of Newtonian dynamics ≈ 6 lectures
  2. Lagrangian dynamics ≈ 6 lectures
  3. Rigid body motions in 3D ≈ 6 lectures
  4. Aircraft/spacecraft dynamics ≈ 6 lectures


    • Midterm exam #1 in class (1 hour) after Lecture 6 (15%)
    • Midterm exam #2 in class (1 hour) after Lecture 14 (20%)
    • Final exam at the end of the semester (30%)
    • Homework - Out Thursdays, due following Thursday at beginning of class (35%)
      Hand-in in class or drop-off at my office. Collaboration: You can discuss problems
      with others, but you are expected to write up and hand in your own work.
    • You will definitely need access to MATLAB®
Textbooks
None required. Lecture notes will be handed out in class. But various books available for reference are:



  1. Meriam and Kraige. Engineering Mechanics - Dynamics. Wiley, 2001.



  2. Hibbeler. Engineering Mechanics - Statics and Dynamics. Prentice Hall.



  3. Beer and Johnston. Vector Mechanics for Engineers. McGraw-Hill.



  4. Greenwood. Principles of Dynamics. 2nd ed. Prentice Hall [RB dynamics].



  5. Williams, Jr. Fundamentals of Applied Dynamics. Wiley, 1996.



  6. Baruh. Analytical Dynamics. McGraw Hill [fairly advanced].



  7. Wells. Schaum's Outline of Lagrangian Dynamics. McGraw-Hill, 1967.



  8. Goldstein. Classical Mechanics. 2nd ed. Addison Wesley [very advanced].
Learning Objectives for Students Graduating from 16.61 will be Able to:



  1. Use methods of vector kinematics to analyze the translation and rotation of rigid bodies - and explain with appropriate visualizations.



  2. Identify appropriate coordinate frames and calculate the transformations between them.



  3. Formulate and solve for the equations of motion using both the Newtonian and Lagrangian formulations.



  4. Use the basic equations of motion to calculate the fundamental flight modes of an aircraft.



  5. Use the basic equations of motion to calculate the attitude motions of a low Earth orbit spacecraft.
Measurable Outcomes for Students Graduating from 16.61 will be Able to:



  1. Derive the equations of motion in accelerating and rotating frames.



  2. Solve for the equations of motion using both the Newtonian and Lagrangian formulations.



  3. Simulate and predict complex dynamic behavior of vehicles such as projectiles, aircraft, and spacecraft.



  4. Use MATLAB® as a tool for matrix manipulations and dynamic simulation.



  5. Linearize the 6DOF motions associated with most dynamic behavior to establish the basic modes of the motion.

MATLAB® is a trademark of The MathWorks, Inc.

Exams

This course included three exams. The first two exams were administered during the semester, and the final took place during the week immediately following the end of classes. The first two exams, and the solution to the first, are included here.
Midterm Exam #1 (PDF)
Midterm Exam #1 Solutions (PDF)
Midterm Exam #2 (PDF)

Assignments

This section includes a complete set of assignments for the course. Problem sets were assigned approximately once every week, and were typically due one week later. Graded problem sets were returned to students after another week. Performance on problem sets comprised 35% of a student's final grade.
Assignment #1 (PDF)
Assignment #2 (PDF)
Assignment #3 (PDF)
Assignment #4 (PDF)
Assignment #5 (PDF)
Assignment #6 (PDF)
Assignment #7 (PDF)
Assignment #8 (PDF)
Assignment #9 (PDF)
Assignment #10 (PDF)

Calendar

This calendar incorporates the lecture schedule and the assignment schedule. Some lecture topics may have required more than one class session to cover.










LEC #


TOPICS


ASSIGNMENTS











1


Aerospace Dynamics















2


Coriolis "Demystified"


HW1 Issued











3


Dynamics















4


Introduction to Multiple Intermediate Frames


HW1 Due
HW2 Issued












5


Momentum, Angular Momentum, and Dynamics of a System of Particles


HW2 Due
HW3 Issued












6


Numerical Solution of Nonlinear Differential Equations


HW3 Due















Midterm Exam #1















7


Lagrange's Equations















8


Examples Using Lagrange's Equations

Handout:
Examples (from Lagrangian and Hamiltonian Mechanics by M. G. Calkin. River Edge, NJ: World Scientific Publishing Co. Pte. Ltd., 1999.)



HW4 Issued











9


Virtual Work and the Derivation of Lagrange's Equations



















Virtual Work and the Derivation of Lagrange's Equations (Continued)


HW4 Due
HW5 Issued












10


Friction in Lagrange's Equations



















Friction in Lagrange's Equations (Continued)


HW5 Due
HW6 Issued












11


Kinematics of Rigid Bodies















12


Rigid Body Dynamics


HW6 Due
HW7 Issued












13


Axisymmetric Rotations















14


Gyroscopes


HW7 Due
HW8 Issued
















Gyroscopes (Continued)


HW8 Due















Midterm Exam #2


HW9 Issued











15


Spacecraft Attitude Dynamics



















Spacecraft Attitude Dynamics (Continued)


HW9 Due
HW10 Issued












16


Aircraft Dynamics















17


Aircraft Longitudinal Dynamics


HW10 Due











18


Aircraft Lateral Dynamics



















Final Exam


Lecture Notes

These lecture notes were made available to students in the class electronically. Some of these lectures may have required more than one class session to cover.





LEC #


TOPICS







1


Aerospace Dynamics (PDF - 1.1 MB)







2


Coriolis "Demystified" (PDF - 2.4 MB)







3


Dynamics (PDF - 1.3 MB)







4


Introduction to Multiple Intermediate Frames (PDF)







5


Momentum, Angular Momentum, and Dynamics of a System of Particles (PDF)







6


Numerical Solution of Nonlinear Differential Equations (PDF - 1.4 MB)







7


Lagrange's Equations (PDF)







8


Examples Using Lagrange's Equations (PDF)







9


Virtual Work and the Derivation of Lagrange's Equations (PDF)







10


Friction in Lagrange's Equations (PDF)







11


Kinematics of Rigid Bodies (PDF - 1.6 MB)







12


Rigid Body Dynamics (PDF - 2.8 MB)







13


Axisymmetric Rotations (PDF - 2.4 MB)







14


Gyroscopes (PDF - 1.2 MB)







15


Spacecraft Attitude Dynamics (PDF - 1.4 MB)







16


Aircraft Dynamics (PDF)







17


Aircraft Longitudinal Dynamics (PDF)







18


Aircraft Lateral Dynamics (PDF - 1.5 MB)

Sumber: MIT Open Course Ware






MATLAB® is a trademark of The MathWorks, Inc.



Semoga Bermanfaat dan Terima Kasih

Tuesday 18 November 2008

Indonesian Space Sciences & Technology School

Thermal Energy


Added & Edited

By: Arip Nurahman
Department of Physics Education, Faculty of Sciences and Mathematics
Indonesia University of Education

and

Follower Open Course Ware at Massachusetts Institute of Technology
Cambridge, USA
Department of Physics 
http://web.mit.edu/physics/
http://ocw.mit.edu/OcwWeb/Physics/index.htm
&
Aeronautics and Astronautics Engineering
http://web.mit.edu/aeroastro/www/
http://ocw.mit.edu/OcwWeb/Aeronautics-and-Astronautics/index.htm


















Level:

Undergraduate

Instructors:

Prof. Zoltan Spakovszky
Prof. Edward Greitzer

An h-s diagram of a non-ideal Brayton cycle and a simplified gas turbine schematic, from the "Gas Power and Propulsion Cycles" section of the lecture notes. (Image courtesy of MIT OCW.)

Course Features

Course Highlights

The already-extensive lecture notes for this course have developed markedly in recent years, and now include, in addition to concepts and examples, a set of "muddy points". Through student feedback, the instructors have compiled a list of frequently misunderstood ideas, or "muddy points", and identified and addressed these pitfalls right in the notes.

Course Description

This course is taught in four main parts. The first is a review of fundamental thermodynamic concepts (e.g. energy exchange in propulsion and power processes), and is followed by the second law (e.g. reversibility and irreversibility, lost work). Next are applications of thermodynamics to engineering systems (e.g. propulsion and power cycles, thermo chemistry), and the course concludes with fundamentals of heat transfer (e.g. heat exchange in aerospace devices). 

Lecture Notes

When combined, the lecture notes below form a continuous document. They are divided here for accessibility and ease of use. The sections are numbered independently. The table of contents and index below apply to the complete set of lecture notes. These materials were made available to students online, and formed the basis for class sessions.





SEC #


TOPICS











Table of Contents and Acknowledgement (PDF)







0


Prelude: Introduction and Review of Unified Engineering Thermodynamics (PDF)







1


The Second Law of Thermodynamics







1a


Background to the Second Law of Thermodynamics (PDF)







1b


The Second Law of Thermodynamics (PDF)







1c


Applications of the Second Law (PDF)







1d


Interpretation of Entropy on the Microscopic Scale — The Connection between Randomness and Entropy (PDF)







2


Applications of Thermodynamics to Engineering Systems







2a


Gas Power and Propulsion Cycles (PDF)







2b


Power Cycles with Two-Phase Media (Vapor Power Cycles) (PDF)







2c


Introduction to Thermochemistry (PDF)







3


Fundamentals of Heat Transfer (PDF)







3a


Introduction to Conduction Heat Transfer







3b


Introduction to Convection Heat Transfer







3c


Applications of the Concepts: Heat Exchangers







3d


Introduction to Thermal Radiation and Radiation Heat Transfer











Index (PDF)



 

 




Sumber:

MIT Open Course Ware

Monday 10 November 2008

Wednesday 5 November 2008

Lightning

Lightning is a massive electrostatic discharge caused by unbalanced electric charge in the atmosphere, either inside clouds, cloud to cloud or cloud to ground, accompanied by the loud sound of thunder.

A typical cloud to ground lightning strike can be over 5 km (3 mi) long. A typical thunderstorm may have three or more strikes per minute at its peak. Lightning is usually produced by cumulonimbus clouds up to 15 km high (10 mi) high, based 5–6 km (3-4 mi) above the ground. Lightning is caused by the circulation of warm moisture-filled air through electric fields. Ice or water particles then accumulate charge as in a Van de Graaf generator. Lightning may occur during snow storms (thundersnow), volcanic eruptions, dust storms, forest fires or tornadoes. Hurricanes typically generate some lightning, mainly in the rainbands as much as 160 km (100 mi) from the center.
When the local electric field exceeds the dielectric strength of damp air (about 3 million Volts/m), electrical discharge results, often followed by more discharges along the same path. Mechanisms that cause lightning are still a matter of scientific investigation.
Fear of lightning is called astraphobia. The study or science of lightning is called fulminology.

Wikipedia

Saturday 1 November 2008

Indonesian Space Sciences Technology School,

Computational Methods

in Aerospace Engineering 


Staff

Instructor:
Prof. David Darmofal

Course Meeting Times

Lectures:
Three sessions / week
1 hour / session

Level

Undergraduate



Added & Edited

By: Arip Nurahman
Department of Physics Education, Faculty of Sciences and Mathematics
Indonesia University of Education

and

Follower Open Course Ware at Massachusetts Institute of Technology
Cambridge, USA
Department of Physics
http://web.mit.edu/physics/
http://ocw.mit.edu/OcwWeb/Physics/index.htm
&
Aeronautics and Astronautics Engineering
http://web.mit.edu/aeroastro/www/
http://ocw.mit.edu/OcwWeb/Aeronautics-and-Astronautics/index.htm























Mach 2 inviscid flow simulation over a cylinder, from Project #1. (Image courtesy of Professor Darmofal.)

Course Highlights

This course features a complete set of lecture notes and assignments, and also a variety of study materials.

Course Description

This course serves as an introduction to computational techniques arising in aerospace engineering. Applications are drawn from aerospace structures, aerodynamics, dynamics and control, and aerospace systems. Techniques include: numerical integration of systems of ordinary differential equations; finite-difference, finite-volume, and finite-element discretization of partial differential equations; numerical linear algebra; eigenvalue problems; and optimization with constraints.

Technical Requirements

Special software is required to use some of the files in this course: .m, .mat.

Study Materials

The following materials are provided for preparation for the problem sets and final exam.

Sample Problems Sets

Problem Set 1 (PDF)
Solution Set 1 (PDF)
Problem Set 2 (PDF)
Solution Set 2 (PDF)

Final Exam Preparation

Preparation Materials (PDF)

Syllabus

Course Objectives

Students successfully completing 16.901 should have:
  1. A conceptual understanding of computational methods commonly used for analysis and design of aerospace systems.
  2. A working knowledge of computational methods including experience implementing them for model problems drawn from aerospace engineering applications.
  3. A basic foundation in theoretical techniques to analyze the behavior of computational methods.

Measurable Outcomes

The subject is divided into four sections:
  • Integration of Systems of Ordinary Differential Equations (ODE's)
  • Finite Volume and Finite Difference Methods for Partial Differential Equations (PDE's)
  • Finite Element Methods for Partial Differential Equations
  • Probabilistic Simulation Techniques
For each of these sections, the measurable outcomes are described below. Specifically, a student successfully completing 16.901 will be able to:

Integration Methods for ODE's

  1. (a) Describe the Adams-Bashforth, Adams-Moulton, and Backwards Differentiation families of multi-step methods;
    (b) Describe the form of the Runge-Kutta family of multi-stage methods; and
    (c) Explain the relative computational costs of multi-step versus multi-stage methods.
  2. (a) Explain the concept of stiffness of a system of equations, and
    (b) Describe how it impacts the choice of numerical method for solving the equations.
  3. (a) Explain the differences and relative advantages between explicit and implicit methods to integrate systems of ordinary differential equations; and
    (b) For nonlinear systems of equations, explain how a Newton-Raphson can be used in the solution of an implicit method.
  4. (a) Define a convergent method;
    (b) Define a consistent method;
    (c) Explain what (zero) stability is; and
    (d) Demonstrate an understanding of the Dahlquist Equivalence Theorem by describing the relationship between a convergent method, consistency, and stability.
  5. Determine if a multi-step method is stable and consistent.
  6. (a) Define global and local order of accuracy for an ODE integration method,
    (b) Describe the relationship between global and local order of accuracy, and
    (c) Calculate the local order of accuracy for a given method using a Taylor series analysis.
  7. (a) Define eigenvalue stability, and
    (b) Determine the stability boundary for a multi-step or multi-stage method applied to a linear system of ODE's.
  8. Recommend an appropriate ODE integration method based on the features of the problem being solved.
  9. Implement multi-step and multi-stage methods to solve a representative system of ODE's from an engineering application.

Finite Difference and Finite Volume Methods for PDE's

  1. (a) Define the physical domain of dependence for a problem,
    (b) Define and determine the numerical domain of dependence for a discretization, and
    (c) Explain the CFL condition and determine the timestep constraints resulting from the CFL conditions.
  2. Determine the local truncation error for a finite difference approximation of a PDE using a Taylor series analysis.
  3. Explain the difference between a centered and a one-sided (e.g. upwind) discretization.
  4. Describe the Godunov finite volume discretization of two-dimensional convection on an unstructured mesh.
  5. Perform an eigenvalue stability analysis of a finite difference approximation of a PDE using either Von Neumann analysis or a semi-discrete (method of lines) analysis.
  6. Implement a finite difference or finite volume discretization to solve a representative PDE (or set of PDE's) from an engineering application.

Finite Element Methods for PDE's

  1. (a) Describe how the Method of Weighted Residuals (MWR) can be used to calculate an approximate solution to a PDE,
    (b) Describe the differences between MWR, the collocation method, and the least-squares method for approximating a PDE, and
    (c) Describe what a Galerkin MWR is.
  2. (a) Describe the choice of approximate solutions (i.e. the test functions or interpolants) used in the Finite Element Method, and
    (b) Give examples of a basis for the approximate solutions in particular including a nodal basis for at least linear and quadratic solutions.
  3. (a) Describe how integrals are performed using a reference element,
    (b) Explain how Gaussian quadrature rules are derived, and
    (c) Describe how Gaussian quadrature is used to approximate an integral in the reference element.
  4. Explain how Dirichlet and Neumann boundary conditions are implemented for Laplace's equation discretized by FEM.
  5. (a) Describe how the FEM discretization results in a system of discrete equations and, for linear problems, gives rises to the stiffness matrix; and
    (b) Describe the meaning of the entries (rows and columns) of the stiffness matrix and of the right-hand side vector for linear problems.

Probabilistic Methods

Note: all students are expected to have a thorough understanding of probability, random variables, PDF's, CDF's, mean (expectation), variance, standard deviation, percentiles, uniform distributions, normal distributions, and x2-distributions from the prerequisite coursework.
  1. Describe how Monte Carlo sampling from multivariable, uniform distributions works.
  2. Describe how to modify Monte Carlo sampling from uniform distributions to general distributions.
  3. (a) Describe what an unbiased estimator is;
    (b) State unbiased estimators for mean, variance, and probability; and
    (c) State the distributions of these unbiased estimators.
  4. (a) Define standard error;
    (b) Give standard errors for mean, variance and probability;
    (c) Place confidence intervals for estimates of the mean, variance, and probability; and
    (d) Demonstrate the dependence of Monte Carlo convergence on the number of random inputs and the number of samples using the above error estimates.
  5. (a) Describe stratified sampling for single input and multiple inputs,
    (b) Describe Latin Hypercube Sampling (LHS), and
    (c) Describe the benefits of LHS for nearly linear outputs in terms of the standard error convergence of the mean with the number of samples.
  6. (a) Describe the Response Surface Method (RSM);
    (b) Describe the construction of a response surface through Taylor series, Design of Experiments with the least-square regression, and random sampling with least-squares regression; and
    (c) Describe the R2 -metric, its use in measuring the quality of a response surface, and its potential problems.

Homework Problems

A homework problem will be given at the end of most regular lectures and will be due at the beginning of the next class. These homework problems are intended to take 1-2 hours to complete. The individual homework sets will be graded on the following scale:
3: A complete solution demonstrating an excellent understanding of the concepts.
2: A complete solution demonstrating an adequate understanding of the concepts, though some minor mistakes may have been made.
1: A complete or nearly-complete solution demonstrating some understanding of the concepts, though major mistakes may have been made.
0: A largely incomplete solution or no solution at all.
Note: the individual homework grades will only be integer values. At the end of the semester, the highest 2/3's of the grades received in the homeworks will be averaged to determine an overall homework letter grade. Roughly, the following ranges will be used. A: 2.5-3; B: 2-2.5; C: 1.5-2; D: 1-1.5; F: 0-1.

Projects

Currently, three programming projects are planned for this semester (one for each section of the course except the ODE section). The projects will focus on applying numerical algorithms to aerospace applications. The programming is highly recommended to be done in Matlab®. The expected due dates for the projects are as follows.


PROJECTS DUE DATES
Project 1 Lecture 16
Project 2 Lecture 30
Project 3 Lecture 38

The project assignments will be distributed at least one week prior to the due dates. No homeworks will be given during the week the projects are due. Each project will be assigned a letter grade based on the standard MIT letter grade descriptions (see Course Grade).

Homework and Project Collaboration

While discussion of the homework and projects is encouraged among students, the work submitted for grading must represent your understanding of the subject matter. Significant help from other sources should be noted.

Oral Exams

There will be a mid-term and final oral exam. The mid-term oral exam will be held between Lecture 20 and Lecture 21. The final oral exam will be held during Final Exam Week. I will schedule the mid-term oral exam by the end of February based on preferences from each student. I will schedule the final oral exam once the final exam schedule for the institute has been published. Each oral exam will be assigned a letter grade based on the standard MIT letter grade descriptions (see Course Grade).

Course Grade

The subject total grade will be based on the letter grades from the homework, projects, and oral exams. Roughly, the weighting of the individual letters grade is as follows:


ACTIVITIES BREAKDOWN
Homework Letter Grades 1/8 of the Subject Total Grade
Project Letter Grades Each Project is 1/8 of the Total Grade
Oral Exam Letter Grades Each Exam is 1/4 of the Total Grade

For the subject letter grade, I adhere to the MIT grading guidelines which give the following description of the letter grades:
A: Exceptionally good performance demonstrating a superior understanding of the subject matter, a foundation of extensive knowledge, and a skillful use of concepts and/or materials.
B: Good performance demonstrating capacity to use the appropriate concepts, a good understanding of the subject matter, and an ability to handle the problems and materials encountered in the subject.
C: Adequate performance demonstrating an adequate understanding of the subject matter, an ability to handle relatively simple problems, and adequate preparation for moving on to more advanced work in the field.
D: Minimally acceptable performance demonstrating at least partial familiarity with the subject matter and some capacity to deal with relatively simple problems, but also demonstrating deficiencies serious enough to make it inadvisable to proceed further in the field without additional work.

Textbooks

Notes will be distributed. Reference texts will be recommended for specific topics as needed.


Citable URI: http://hdl.handle.net/1721.1/36877

Projects

Special software is required to use some of the files in this section: .m, .mat.
There are three programming projects for the class, one for each section of the course except the ODE section. They focus on applying numerical algorithms to aerospace applications.

Projects Supporting Files Solutions
Project 1 (PDF) CalcForces.m (M)

cyl_adaptmesh.m (M)

cyl_initmesh.m (M)

cylgeom.mat (MAT)

eulerflux.m (M)

FVM.m (M)

SetRefineList.m (M)

SetupEdgeList.m (M)

SetupMesh.m (M)

wallflux.m (M)
(PDF - 1.4 MB)
Project 2 (PDF) bladeheat.m (M)

bladeplot.m (M)

hpblade_coarse.mat (MAT)

hpblade_fine.mat (MAT)

hpblade_medium.mat (MAT)

findloc.m (M)

Thgas.m (M)
(PDF)

p2_matlabsol.txt (TXT)
Project 3 (PDF) calcblade.m (M)

DesignIntent.m (M)

hpblade_coarse.mat (MAT)

loadblade.m (M)

MCdriver.m (M)

Screen.m (M)

Thgas.m (M)

trirnd.m (M)
(PDF)

See also


References

  1. ^ “IEEE Standard Glossary of Software Engineering Terminology,” IEEE std 610.12-1990, 1990, quoted at the beginning of Chapter 1: Introduction to the guide "Guide to the Software Engineering Body of Knowledge" (February 6, 2004). Retrieved on 2008-02-21.
  2. ^ Pecht, Michael (1995). Product Reliability, Maintainability, and Supportability Handbook. CRC Press. ISBN 0-8493-9457-0.
  3. ^ Pehrson, Ronald J. (January 1996). "Software Development for the Boeing 777". CrossTalk: the Journal of Defense Software Engineering. http://www.stsc.hill.af.mil/crosstalk/1996/01/Boein777.asp. , "The 2.5 million lines of newly developed software were approximately six times more than any previous Boeing commercial airplane development program. Including commercial-off-the-shelf (COTS) and optional software, the total size is more than 4 million lines of code."
  4. ^ Randell, Brian (10 Aug 2001). "The 1968/69 NATO Software Engineering Reports". Brian Randell's University Homepage. The School of Computer Sciences, Newcastle University. Retrieved on 2008-10-11. "The idea for the first NATO Software Engineering Conference, and in particular that of adopting the then practically unknown term "software engineering" as its (deliberately provocative) title, I believe came originally from Professor Fritz Bauer."
  5. ^ Table 1 in Chapter 1,"Guide to the Software Engineering Body of Knowledge" (February 6, 2004). Retrieved on 2008-02-21.
  6. ^ Ian Sommerville (2004). Software Engineering. 7th edition. Chapter 1. Bezien 20 Okt 2008.
  7. ^ Table 2 in Chapter 1,"Guide to the Software Engineering Body of Knowledge" (February 6, 2004). Retrieved on 2008-02-21.
  8. ^ Bureau of Labor Statistics, U.S. Department of Labor, USDL 05-2145: Occupational Employment and Wages, November 2004, Table 1.
  9. ^ "Software Engineering". Retrieved on 2008-02-01.
  10. ^ Cowling, A. J. 1999. The first decade of an undergraduate degree programme in software engineering. Ann. Softw. Eng. 6, 1-4 (Apr. 1999), 61-90.
  11. ^ "ABET Accredited Engineering Programs" (April 3, 2007). Retrieved on 2007-04-03.
  12. ^ McConnell, Steve (July 10, 2003. Professional Software Development: Shorter Schedules, Higher Quality Products, More Successful Projects, Enhanced Careers. ISBN 978-0321193674.
  13. ^ Actually the ACM made an explicit decision not to continue with certification. 1
  14. ^ IEEE Computer Society. "2006 IEEE computer societe report to the IFIP General Assembly". Retrieved on 2007-04-10.
  15. ^ Canadian Information Processing Society. "I.S.P. Designation". Retrieved on 2007-03-15.
  16. ^ As outsourcing gathers steam, computer science interest wanes
  17. ^ Computer Programmers
  18. ^ Software developer growth slows in North America | InfoWorld | News | 2007-03-13 | By Robert Mullins, IDG News Service
  19. ^ Hot Skills, Cold Skills
  20. ^ Dual Roles: The Changing Face of IT

Further reading


External links