Course Name: Surrogates and Approximations in Engineering Design

Course abstract

In the context of engineering design, often the functional objective and the design constraints are approximated by connecting the design variables and the responses of interest at few points on the design space. Since these are approximation of the original functions, they are called surrogates and are widely used in design studies. This course will focus on introducing such surrogates – on how to build, evaluate and use them in design. Surrogates discussed will include polynomial regression, kriging and radial basis function while Desgin of Experiments discussions will include latin hypercube sampling and hammersley sequence.


Course Instructor

Media Object

Palaniappan Ramu

Prof. Palaniappan Ramu’s research interest revolves around optimization and treating uncertainties in product and process design to obtain reliable, robust and quality designs. Most of his work is focused on reduction of computer or physical experiments, building better metamodels, intelligently explore design space and enable better predictions and optimal designs under uncertainties.
More info

Teaching Assistant(s)

Sivakumar

BE - Mechanical Engineering

IITM

Deepan jayaraman

ME

IITM

 Course Duration : Aug-Sep 2018

  View Course

 Enrollment : 18-Apr-2018 to 27-Aug-2018

 Exam registration : 25-Jun-2018 to 28-Aug-2018

 Exam Date : 07-Oct-2018

Enrolled

409

Registered

19

Certificate Eligible

13

Certified Category Count

Gold

1

Silver

0

Elite

7

Successfully completed

5

Participation

0

Success

Elite

Gold





Legend

>=90 - Elite + Gold
60-89 - Elite
40-59 - Successfully Completed
<40 - No Certificate

Final Score Calculation Logic

  • Assignment Score = Average of best 3 out of 4 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score.
Surrogates and Approximations in Engineering Design - Toppers list

SASHIDHAR PALANI 90%

INDIAN INSTITUTE OF TECHNOLOGY MADRAS

VENKATESAN G 81%

SIEMENS

Enrollment Statistics

Total Enrollment: 409

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Assignment Statistics




Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.