AddLat2D the 2D Lattice Generator[Formula presented]

Martha Baldwin; Nicholas A. Meisel; Christopher McComb

doi:10.1016/j.simpa.2023.100567

AddLat2D the 2D Lattice Generator[Formula presented]

Martha Baldwin
, Nicholas A. Meisel
, Christopher McComb

School of Engineering Design and Innovation

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

This work addresses the challenges of acquiring additive manufacturing data, given the complexities and design possibilities of such structures. Researchers in additive manufacturing struggle with scarcity and unsuitability of 2D datasets which pose further difficulties. To overcome these concerns, this research presents an application, AddLat2D, for generating 2D lattice structure datasets tailored to user specifications. Building upon a previous version of the application (Baldwin et al., 2023, 2022), this work highlights our development and usage of AddLat2D to generate datasets that have custom image size and pixel intensity values.

Original language	English (US)
Article number	100567
Journal	Software Impacts
Volume	17
DOIs	https://doi.org/10.1016/j.simpa.2023.100567
State	Published - Sep 2023

All Science Journal Classification (ASJC) codes

Software

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10.1016/j.simpa.2023.100567

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title = "AddLat2D the 2D Lattice Generator[Formula presented]",

abstract = "This work addresses the challenges of acquiring additive manufacturing data, given the complexities and design possibilities of such structures. Researchers in additive manufacturing struggle with scarcity and unsuitability of 2D datasets which pose further difficulties. To overcome these concerns, this research presents an application, AddLat2D, for generating 2D lattice structure datasets tailored to user specifications. Building upon a previous version of the application (Baldwin et al., 2023, 2022), this work highlights our development and usage of AddLat2D to generate datasets that have custom image size and pixel intensity values.",

author = "Martha Baldwin and Meisel, \{Nicholas A.\} and Christopher McComb",

note = "Publisher Copyright: {\textcopyright} 2023 The Author(s)",

year = "2023",

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AU - Baldwin, Martha

AU - Meisel, Nicholas A.

AU - McComb, Christopher

PY - 2023/9

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N2 - This work addresses the challenges of acquiring additive manufacturing data, given the complexities and design possibilities of such structures. Researchers in additive manufacturing struggle with scarcity and unsuitability of 2D datasets which pose further difficulties. To overcome these concerns, this research presents an application, AddLat2D, for generating 2D lattice structure datasets tailored to user specifications. Building upon a previous version of the application (Baldwin et al., 2023, 2022), this work highlights our development and usage of AddLat2D to generate datasets that have custom image size and pixel intensity values.

AB - This work addresses the challenges of acquiring additive manufacturing data, given the complexities and design possibilities of such structures. Researchers in additive manufacturing struggle with scarcity and unsuitability of 2D datasets which pose further difficulties. To overcome these concerns, this research presents an application, AddLat2D, for generating 2D lattice structure datasets tailored to user specifications. Building upon a previous version of the application (Baldwin et al., 2023, 2022), this work highlights our development and usage of AddLat2D to generate datasets that have custom image size and pixel intensity values.

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UR - https://www.scopus.com/pages/publications/85169467062#tab=citedBy

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DO - 10.1016/j.simpa.2023.100567

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VL - 17

JO - Software Impacts

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ER -

AddLat2D the 2D Lattice Generator[Formula presented]

Abstract

All Science Journal Classification (ASJC) codes

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