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A JAVA/Processing sketch that implements a geometric solution to the generation of optimum Mitchell trusses. Structural design and optimization of frames (trusses). Massachusetts Institute of Technology (MIT). 2015/2017.

Java 100.00%
optimization java architecture design-space-exploration gui-application mit mit-license processing processing-library processing-sketch

mitchelltrussapi's Introduction

Exploring Mitchell Structures

Mitchell Structure API This is a standalone application for exploring optimum Mitchell trusses written in Java. It uses the Processing API for graphic elements, rendering, and GUI objects. This implementation builds on a geometric solution of discrete Mitchell trusses in their basic symmetric form: a discrete optimum truss supported by two fixed points (positioned along the same vertical line) and a vertical point load positioned in between the supports at a fixed distance.

The geometric solution is described in detail in A. Mazurek, W.F. Baker, C. Tort (2011) "Geometrical aspects of optimum truss like structures", Structural and Multidisciplinary Optimization, 43 (2). Custom computational abstractions were developed along with appropriate algorithms to provide a parametric framework for generating the geometry of optimum trusses. More specifically, according to the selected parameters and values 21 trusses in total can be calculated. The parameters considered are: h, the vertical distance between the supports, L the horizontal distance between the supports and the point load applied at the tip of the structure, and n the total number of bars in the system. The forces on each member are computed with a routine that implements the method of joints.

For more information on this geometric solution and its computational implementation, please read the uploaded PDF writeup called MitchellStructureWriteup.pdf.

Dependencies: JAMA matrix package, ControlP5, toxiclibs.

Acknowledgements

This application was developed as part of an assignment in the course 4.s48 Computational Structural Design and Optimization (now 4.450J/1.575J) taught by Prof. Caitlin Mueller at MIT in the Spring semester of 2015.

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