Call for Papers: Special Issue on Artificial Intelligence and Engineering Design
JMD Welcomes Conrad Tucker, Richard Malak, Julian Norato, Michel-Alexandre Cardin, Babak Heydari, and Sheng Li to the Editorial Board
2019 Editors' Choice Paper Award and Honorable Mentions
JMD Announces a New Double Blind Review Option for JMD Authors
COVID-19 Response and Call for Papers
Although the journal is committing to reviewing and processing papers as expeditiously as possible, we understand that members of our community including editors, authors, and reviewers may be impacted severely by the pandemic. If you are experiencing any difficulties with journal related workflow we encourage you to communicate with the journal Editor or Associate Editor(s) so that accommodations and/or time extensions can be arranged.
To assist researchers and those working to bring this health crisis to an end, ASME has made all COVID-19 relevant journal and conference content available at no charge. We encourage JMD authors to contribute articles to COVID-19 related subjects. Such papers will still be submitted to JMD, going through an expedited review process, and published with a link to the ASME COVID-19 Resource virtual issue at https://asmedigitalcollection.asme.org/journals/pages/covid19resource
ASME Reports JMD's Top 10 Downloads in 2019
ASME Announces 2019 Reviewer Awards
Featured Articles Editor: Scott Ferguson
Microstructural Stress Shape Optimization Using the Level Set Method
Renato Picelli, Scott Townsend, H. Alicia Kim
The shape optimization of microstructural cells is investigated in this paper. Microstructure optimization yields the design of an architected material with a desired material property. Material usage and cost can be reduced by inserting holes into the microstructure. However, depending on the hole shape, the macroscale structure can fail because of the mechanical stress observed in the microstructural cell. Read more...
Efficient Spot Welding Sequence Optimization in a Geometry Assurance Digital Twin
Roham Sadeghi Tabar, Kristina Wärmefjord, Rikard Söderberg, Lars Lindkvist
The availability of big data has made the role of digital twins in manufacturing more prominent. This paper introduces a geometry assurance digital twin - created from the scanned data of individual components - to define and improve an assembly’s geometrical quality. The joining sequence in a sheet metal assembly impacts geometrical quality and determining the optimal joining sequence is computationally expensive. Meta-heuristic optimization techniques like genetic algorithms often require many simulations, which can increase computational cost. This work improves the optimization process by combining a model-based heuristic algorithm...read more
Conceptualizing Stable States in Origami-Based Devices Using an Energy Visualization Approach
Jacob Greenwood, Alex Avila, Larry Howell, Spencer Magleby
Origami can provide unique inspiration when designing engineered systems because it promotes multiple configurations, compact storage, and quick deployablility. However, origami-based products can be challenging to design because they often are mechanically unstable - folding when not desired or when under load. While there are some existing techniques for achieving stability in origami-based designs, determining which combination of techniques will achieve the desired results for a given application can be difficult. For example, how can you design an origami-based ballistic barrier to stay upright when you need it for protection, but also stay collapsed for storage? Read more...
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