Algorithmic design of wind instrument shape via 3D FDTD and deep learning
Name
1128185621-MIT.pdf
Size
7.82 MB
Format
Adobe PDF
Checksum (MD5)
5c619e2063639effe71f919172a45d69
Author(s)
Wang, Larry(Larry Z.)
Advisor(s)
Justin Solomon.
Alternative Title
Algorithmic design of wind instrument shape via three-dimensional Finite Difference Time Domain and deep learning
Date Issued
2019
Publisher
Massachusetts Institute of Technology
Abstract
Traditional design of wind instruments centers around simple shapes such as tubes and cones, whose acoustic properties are well understood and are easily fabricated with traditional manufacturing methods. The advent of additive manufacturing enables the realization of highly complex geometries and new wind instruments with unique sound qualities. While simulation software exists to predict the sound of wind instruments given their shape, the inverse problem of generating a shape that creates a desired sound is challenging given the computational cost of 3D acoustic simulations. In this work we create a fast 3D acoustic wind instrument simulator using GPU acceleration. In addition, we use deep learning to solve the inverse problem of generating a 3D shape that roughly approximates a desired sound when played as a single-reed instrument. Finally we develop an automatic method for determining pitch hole locations for a given shape to generate playable instruments.
Description
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 59-60).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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