dc.contributor.author |
Do, NNL |
en |
dc.contributor.author |
Taberner, Andrew |
en |
dc.contributor.author |
Ruddy, Bryan |
en |
dc.coverage.spatial |
Neuchatel, Switzerland |
en |
dc.date.accessioned |
2019-09-30T06:26:39Z |
en |
dc.date.issued |
2019-07-03 |
en |
dc.identifier.isbn |
978-1-5386-5805-5 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/48093 |
en |
dc.description.abstract |
This paper proposes the work of analyzing and optimizing three types of linear transverse flux motors in order to build a compact handheld device for needle-free jet injection. The use of finite-element analysis, deep neural network models, and convex non-linear optimization in the study will be explored. The high performance computing infrastructure allowed for rapid creation of 534435 motor design data points via parallel 3-D finite-element analysis jobs. With the available data, a deep regression neural network was trained to make highly accurate predictions (96% accuracy) about any motor with design factors within the given ranges. The optimization process found a number motor configurations which satisfy the given specification but not yet found a practical design for the application. Future effort will focus on widening the search range, and more importantly tuning the optimizer, prototyping and experimental validation. |
en |
dc.publisher |
IEEE |
en |
dc.relation.ispartof |
12th International Symposium on Linear Drives for Industry Applications (LDIA) |
en |
dc.relation.ispartofseries |
Proceedings 2019 12th International Symposium on Linear Drives for Industry Applications (LDIA) |
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dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
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dc.title |
Design of a Linear Permanent Magnet Transverse Flux Motor for Needle-free Jet Injection |
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dc.type |
Conference Item |
en |
dc.identifier.doi |
10.1109/LDIA.2019.8770975 |
en |
dc.rights.holder |
Copyright: The author |
en |
pubs.finish-date |
2019-07-03 |
en |
pubs.publication-status |
Published |
en |
pubs.start-date |
2019-07-01 |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/RestrictedAccess |
en |
pubs.subtype |
Proceedings |
en |
pubs.elements-id |
777361 |
en |
pubs.org-id |
Bioengineering Institute |
en |
pubs.org-id |
ABI Associates |
en |
pubs.org-id |
Engineering |
en |
pubs.org-id |
Engineering Science |
en |
pubs.record-created-at-source-date |
2019-07-29 |
en |
pubs.online-publication-date |
2019-07-25 |
en |