Print

2018　Basics of Stochastic Process for Earthquake Engineering

Font size  SML

Register update notification mail Add to favorite lecture list
Academic unit or major
Graduate major in Urban Design and Built Environment
Instructor(s)
Morikawa Hitoshi 
Class Format
Lecture     
Media-enhanced courses
Day/Period(Room No.)
Tue3-4(G323)  
Group
-
Course number
UDE.S431
Credits
1
Academic year
2018
Offered quarter
1Q
Syllabus updated
2018/3/20
Lecture notes updated
-
Language used
English
Access Index

Course description and aims

This course deals with mathematical basics of stochastic process. After the introduction of probability theory, concept of stochastic processes are introduced. It includes definition, mathematical representation, and spectral representation. To understand the theoretical background, a project is developed. The project requests that students generate numerically a stochastic process with a certain shape of power spectrum and confirm the stochastic properties of the power spectrum. The results of project will be presented and discussed at the final class. Furthermore, students submit a resume, which includes the summary of the results.

Student learning outcomes

To consider the uncertainties of the natural phenomena, stochastic techniques are very important in the field of civil engineering and disaster mitigation. This course deals with time-varying phenomena such as earthquake ground motions and discuss their stochastic model. The mathematical basics of stochastic process is introduced: (1) understanding probabilistic space, (2) understanding calculation of probability, (3) understanding the definition of stochastic process, (4) understanding representation of stochastic process in frequency domain using Fourier transform, (5) understanding physical meaning of power spectrum, (6) students can generate numerically stochastic process with any shapes of power spectrum using random number.

Keywords

stochastic process, Fourier transform, Fourier Stieltjes integral, auto-correlation function, power spectrum, cross-correlation function, cross spectrum, Rice's representation, numerical calculation, random number

Competencies that will be developed

✔ Specialist skills Intercultural skills Communication skills ✔ Critical thinking skills ✔ Practical and/or problem-solving skills

Class flow

Important points will be written on blackboard. Details will be understood through the project.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Introduction and about Project introduction and about Project
Class 2 Basics of probability theory (probability space) definitions of set theory, probability space, and probability
Class 3 Basics of probability theory (probability density function) definition of probability variable and probability density function, calculation of probability
Class 4 Basics of stochastic process definition of stochastic process
Class 5 Spectral representation of stochastic process spectral representation, Fourier Stieltjes integral
Class 6 Power and phase spectra definition of power and phase spectra
Class 7 Rice's representation and numerical generation of stochastic process Rice's representation and numerical method to generate stochastic process
Class 8 Presentation and discussion on results of the project Presentation and discussion on results of the project

Textbook(s)

No textbook is assigned.

Reference books, course materials, etc.

Leon Cohen, "Time Frequency Analysis: Theory and Applications," Prentice Hall, 1994.

Assessment criteria and methods

Students' knowledge of the topics on this course will be assessed through presentation and resume of the project.

Related courses

  • UDE.S531 ： Microtremor Survey Techniques using Theory of Stochastic Process

Prerequisites (i.e., required knowledge, skills, courses, etc.)

Programming skills and environment for numerical calculation are required.

Page Top