CE 59700 – Computational Methods in Civil Engineering

Credits and contact hours:

  • 3 credits
  • Lecture meets for 150 minutes per week for 15 weeks

Specific course information:

  • Catalog description: The objective of the course is to introduce students to numerical methods for solving problems in civil engineering (both for modeling and experimental work). The course provides students with the necessary background to enable them to use basic computational tools and gain a fundamental understanding of numerical methods. It also introduces them to basic computer programming and inculcates a systematic logical thought process towards problem solving.
  • Prerequisites: Linear algebra, index and matrix notation. In particular the student should be comfortable with matrix and index notation.
  • Course status: 

Specific Goals for the course:

  • Student learning outcomes - Upon successful completion of this course the student shall be able to:
    • Introduce students to classical numerical methods available for engineering problem- solving
    • Expose students to concepts such as precision, errors and tolerances and their effect on the quality of the solutions produced by scientific computing
    • Develop and practice systematic, logical thought processes towards problem solving
    • Introduce students to a computer language for scientific computing
    • Improve programming skills and familiarize students with the computer as an engineering and simulation tool
    • Enhance fundamental understanding of concepts acquired in algebra, calculus and differential equations
  •  Relationship of course to program outcomes
    • Outcome 1: An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science and mathematics.

Topics:

  • Introduction to scientific computing (basics, loops, if statements, machine precision, double precision, etc). Introduction to Linux/Unix environment, Tutorial on C and Fortran, Systems of linear equations, Solution to non-linear equations, Interpolation and polynomial approximation, Optimization, Numerical differentiation, Numerical integration, Partial differential equations, Ordinary differential equations.