Roozbeh Salajeghe , Berin Šeta , Nicole Pellizzon , Carl Gustav Sander Kruse , Deepak Marla , Aminul Islam , Jon Spangenberg
{"title":"基于能量阈值法的层析体积增材制造数值建模","authors":"Roozbeh Salajeghe , Berin Šeta , Nicole Pellizzon , Carl Gustav Sander Kruse , Deepak Marla , Aminul Islam , Jon Spangenberg","doi":"10.1016/j.addma.2024.104552","DOIUrl":null,"url":null,"abstract":"<div><div>Tomographic Volumetric Additive Manufacturing (TVAM) has emerged as a rapid and efficient additive manufacturing method, overcoming many limitations of traditional approaches. While the technology is still advancing toward industrial adoption, there is a need to enhance the geometric fidelity especially for small features. This study introduces a new, computationally efficient numerical model for TVAM based on exposure thresholds, designed to optimize material and process parameters. The model requires only two parameters: the energy threshold and penetration depth. Using the Jaccard Similarity Index (JSI), the study demonstrates that an optimal range for penetration depth exists, dependent on the process parameters. Lower penetration depths negatively impact print quality, while higher values increase curing time, making the part vulnerable to sedimentation and oxygen diffusion. The study also finds that projection intensity primarily influences print time and does not affect the JSI. Additionally, it is shown that temporal sampling and rotation rate are interlinked; higher rotation rates necessitate shorter temporal sampling intervals to maintain quality. Scaling up the size of the vial and the print requires adjustments in both the penetration depth and light source intensity to preserve optimal quality. Finally, it is shown that the relative size of the print to the vial influences print quality, with smaller ratios yielding slightly lower quality.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"96 ","pages":"Article 104552"},"PeriodicalIF":10.3000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Numerical modeling of tomographic volumetric additive manufacturing based on energy threshold method\",\"authors\":\"Roozbeh Salajeghe , Berin Šeta , Nicole Pellizzon , Carl Gustav Sander Kruse , Deepak Marla , Aminul Islam , Jon Spangenberg\",\"doi\":\"10.1016/j.addma.2024.104552\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Tomographic Volumetric Additive Manufacturing (TVAM) has emerged as a rapid and efficient additive manufacturing method, overcoming many limitations of traditional approaches. While the technology is still advancing toward industrial adoption, there is a need to enhance the geometric fidelity especially for small features. This study introduces a new, computationally efficient numerical model for TVAM based on exposure thresholds, designed to optimize material and process parameters. The model requires only two parameters: the energy threshold and penetration depth. Using the Jaccard Similarity Index (JSI), the study demonstrates that an optimal range for penetration depth exists, dependent on the process parameters. Lower penetration depths negatively impact print quality, while higher values increase curing time, making the part vulnerable to sedimentation and oxygen diffusion. The study also finds that projection intensity primarily influences print time and does not affect the JSI. Additionally, it is shown that temporal sampling and rotation rate are interlinked; higher rotation rates necessitate shorter temporal sampling intervals to maintain quality. Scaling up the size of the vial and the print requires adjustments in both the penetration depth and light source intensity to preserve optimal quality. Finally, it is shown that the relative size of the print to the vial influences print quality, with smaller ratios yielding slightly lower quality.</div></div>\",\"PeriodicalId\":7172,\"journal\":{\"name\":\"Additive manufacturing\",\"volume\":\"96 \",\"pages\":\"Article 104552\"},\"PeriodicalIF\":10.3000,\"publicationDate\":\"2024-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Additive manufacturing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2214860424005980\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Additive manufacturing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214860424005980","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
Numerical modeling of tomographic volumetric additive manufacturing based on energy threshold method
Tomographic Volumetric Additive Manufacturing (TVAM) has emerged as a rapid and efficient additive manufacturing method, overcoming many limitations of traditional approaches. While the technology is still advancing toward industrial adoption, there is a need to enhance the geometric fidelity especially for small features. This study introduces a new, computationally efficient numerical model for TVAM based on exposure thresholds, designed to optimize material and process parameters. The model requires only two parameters: the energy threshold and penetration depth. Using the Jaccard Similarity Index (JSI), the study demonstrates that an optimal range for penetration depth exists, dependent on the process parameters. Lower penetration depths negatively impact print quality, while higher values increase curing time, making the part vulnerable to sedimentation and oxygen diffusion. The study also finds that projection intensity primarily influences print time and does not affect the JSI. Additionally, it is shown that temporal sampling and rotation rate are interlinked; higher rotation rates necessitate shorter temporal sampling intervals to maintain quality. Scaling up the size of the vial and the print requires adjustments in both the penetration depth and light source intensity to preserve optimal quality. Finally, it is shown that the relative size of the print to the vial influences print quality, with smaller ratios yielding slightly lower quality.
期刊介绍:
Additive Manufacturing stands as a peer-reviewed journal dedicated to delivering high-quality research papers and reviews in the field of additive manufacturing, serving both academia and industry leaders. The journal's objective is to recognize the innovative essence of additive manufacturing and its diverse applications, providing a comprehensive overview of current developments and future prospects.
The transformative potential of additive manufacturing technologies in product design and manufacturing is poised to disrupt traditional approaches. In response to this paradigm shift, a distinctive and comprehensive publication outlet was essential. Additive Manufacturing fulfills this need, offering a platform for engineers, materials scientists, and practitioners across academia and various industries to document and share innovations in these evolving technologies.