Giter Site home page Giter Site logo

mathworks / sensitivity-analysis-with-matlab-for-student-competition-scores Goto Github PK

View Code? Open in Web Editor NEW
2.0 4.0 1.0 569 KB

This repository presents the MATLAB code for sensitivity analysis to identify the most sensitive design variable for aircraft design.

License: Other

aeromodelling aerospace aircraft design matlab sensitivity-analysis

sensitivity-analysis-with-matlab-for-student-competition-scores's Introduction

Sensitivity Analysis with MATLAB for Student Competition Scores

View Sensitivity-Analysis-with-MATLAB-for-Student-Competition-Sco on File Exchange

Open in MATLAB Online

Introduction

Sensitivity Analysis (SA) is a technique used to measure the impact of uncertainties in input variables on output variables in a model. SA aims to determine which input variables impact the output most and identify the range of values in which the model is most sensitive. This information helps to design a robust model with reduced uncertainties.

SA is practiced in a range of fields, including but not limited to finance, engineering, and economics. Specifically, in the field of engineering design, it helps engineers optimize their designs and to improve the quality, reliability, and performance of the system. Model aircraft design competitions, such as the AIAA DBF and SAE Aero Design, are no exception. SA is used here specifically to evaluate score sensitivity. It helps teams identify the most sensitive design variables and optimize their vehicle designs to maximize their score.

For the current demo, our attention will be on the student competition score function. Especially competitions focused on model aircraft design, i.e., AIAA Design Build Fly, SAE AeroDesign, etc., as a case study to investigate how distinctive design variables affect the mission score. To demonstrate this, we will use the scoring function, from the AIAA Design Build Fly Competition 2021 Rule Book, with MATLAB plotting approach. By the end of this demo, you will better understand how to make informed design choices to optimize the competition score.

Course Layout Total Mission Score Analysis
Mission-2 Score Analysis Mission 3: Sensor Length vs Sensor Weight

Setup

To run:

  1. Download the repository and extract it to your local directory.
  2. In the MATLAB environment make this directory as current folder.
  3. Open the file either by double clicking on the 'Sensivity_Analysis_with_MATLAB_for_Student_Competition_Score.mlx' in the Current Folder Window or by running the command, open('Sensivity_Analysis_with_MATLAB_for_Student_Competition_Score') in MATLAB Command Window.
  4. Run the file by clicking on the Run Button available in the Live Editor menu bar.

MathWorks Products (https://www.mathworks.com)

  1. MATLAB release R2022a or higher

Additional resources

Learn MATLAB with following resources

  1. MATLAB Onramp
  2. Explore MATLAB Examples and Documentation
  3. Get Started with Introductory MATLAB Videos

License

The license for Sensitivity Analysis with MATLAB for Student Competition Scores is available in the License.txt file in this GitHub repository.

For any queries, contact the authors at [email protected]

Copyright 2023 The MathWorks, Inc.

sensitivity-analysis-with-matlab-for-student-competition-scores's People

Contributors

khush1008 avatar

Stargazers

 avatar  avatar

Watchers

 avatar  avatar  avatar  avatar

Forkers

hiraertin

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.