{"680274":{"#nid":"680274","#data":{"type":"news","title":"Computer Graphics Team Makes Breakthrough in Simulating Ink Diffusion","body":[{"value":"\u003Cp\u003ECalculating and visualizing a realistic trajectory of ink spreading through water has been a longstanding and enormous challenge for computer graphics and physics researchers.\u003C\/p\u003E\u003Cp\u003EWhen a drop of ink hits the water, it typically sinks forward, creating a tail before various ink streams branch off in different directions. The motion of the ink\u2019s molecules upon mixing with water is seemingly random. This is because the motion is determined by the interaction of the water\u2019s viscosity (thickness) and vorticity (how much it rotates at a given point).\u003C\/p\u003E\u003Cp\u003E\u201cIf the water is more viscous, there will be fewer branches. If the water is less viscous, it will have more branches,\u201d said \u003Cstrong\u003EZhiqi\u003C\/strong\u003E \u003Cstrong\u003ELi\u003C\/strong\u003E, a graduate computer science student.\u003C\/p\u003E\u003Cp\u003ELi is the lead author of \u003Cem\u003EParticle-Laden Fluid on Flow Maps\u003C\/em\u003E, a best paper winner at the December 2024 ACM SIGGRAPH Asia conference. Assistant Professor \u003Cstrong\u003EBo\u003C\/strong\u003E \u003Cstrong\u003EZhu\u003C\/strong\u003E advises Li and is the co-author of six papers accepted to the conference.\u003C\/p\u003E\u003Cp\u003EZhu said they must correctly calculate and simulate the interaction between viscosity and vorticity before they can accurately predict the ink trajectory.\u003C\/p\u003E\u003Cp\u003E\u201cThe ink branches generate based on the intricate interaction between the vorticities and the viscosity over time, which we simulated,\u201d Zhu said. \u201cUsing a standard method to simulate the physics will cause most of the structures to fade quickly without being able to see any detailed hierarchies.\u201d\u003C\/p\u003E\u003Cp\u003EZhu added that researchers had yet to develop a method for this until he and his co-authors proposed a new way to solve the equation. Their breakthrough has unlocked the most accurate simulations of ink diffusion to date.\u003C\/p\u003E\u003Cp\u003E\u201cInk diffusion is one of the most visually striking examples of particle-laden flow,\u201d Zhu said.\u003C\/p\u003E\u003Cp\u003E\u201cWe introduce a new viscosity model that solves for the interaction between vorticity and viscosity from a particle flow map perspective. This new simulation lets you map physical quantities from a certain time frame, allowing us to see particle trajectory.\u201d\u003C\/p\u003E\u003Cp\u003EIn computer simulations, flow is the digital visualization of a gas or liquid through a system. Users can simulate these liquids and gases through different scenarios and study pressure, velocity, and temperature.\u003C\/p\u003E\u003Cp\u003EA particle-laden flow depicts solid particles mixing within a continuous fluid phase, such as dust or water sediment. A flow map traces particle motion from the start point to the endpoint.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDuowen\u003C\/strong\u003E \u003Cstrong\u003EChen\u003C\/strong\u003E, a computer science Ph.D. student also advised by Zhu and co-author of the paper, said previous efforts by researchers to simulate ink diffusion depended on guesswork. They either used limited traditional methods of calculations or artificial designs.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cThey add in a noise model or an artificial model to create vortical motions, but our method does not require adding any artificial vortical components,\u201d Chen said. \u201cWe have a better viscosity force calculation and vortical preservation, and the two give a better ink simulation.\u201d\u003C\/p\u003E\u003Cp\u003EZhu also won a best paper award at the 2023 SIGGRAPH Asia conference for his work explaining how neural network maps created through artificial intelligence (AI) could close the gaps of difficult-to-solve equations. In his new paper, he said it was essential to find a way to simulate ink diffusion accurately independent of AI.\u003C\/p\u003E\u003Cp\u003E\u201cIf we don\u2019t have to train a large-scale neural network, then the computation time will be much faster, and we can reduce the computation and memory costs,\u201d Zhu said. \u201cThe particle flow map representation can preserve those particle structures better than the neural network version, and they are a widely used data structure in traditional physics-based simulation.\u201d\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EInteractive computing researchers earned best-paper recognition for their breakthrough work to model interactions between viscosity and vorticity.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Interactive Computing researchers earned best-paper recognition for their breakthrough work to model interactions between viscosity and vorticity. "}],"uid":"32045","created_gmt":"2025-02-06 14:32:05","changed_gmt":"2025-03-26 01:20:48","author":"Ben Snedeker","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2025-02-06T00:00:00-05:00","iso_date":"2025-02-06T00:00:00-05:00","tz":"America\/New_York"},"extras":[],"hg_media":{"676228":{"id":"676228","type":"image","title":"An ink diffusion model developed at Georgia Tech","body":null,"created":"1738852349","gmt_created":"2025-02-06 14:32:29","changed":"1738852349","gmt_changed":"2025-02-06 14:32:29","alt":"An ink diffusion model developed at Georgia Tech","file":{"fid":"259964","name":"teaser.jpg","image_path":"\/sites\/default\/files\/2025\/02\/06\/teaser.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2025\/02\/06\/teaser.jpg","mime":"image\/jpeg","size":120007,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2025\/02\/06\/teaser.jpg?itok=DJ844Cl5"}}},"media_ids":["676228"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"1188","name":"Research Horizons"}],"categories":[],"keywords":[{"id":"10199","name":"Daily Digest"},{"id":"181991","name":"Georgia Tech News Center"},{"id":"187915","name":"go-researchnews"}],"core_research_areas":[{"id":"193652","name":"Matter and Systems"}],"news_room_topics":[{"id":"71881","name":"Science and Technology"}],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EBen Snedeker, Communications Manager\u003C\/p\u003E\u003Cp\u003EGeorgia Tech College of Computing\u003C\/p\u003E\u003Cp\u003Ealbert.snedeker@cc.gtaech.edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}