Comparison of Multiple Large Fluid-Structure Interaction Simulations in Virtual Reality

Daniel Orban, Seth Johnson, Hakizumwami Birali Runesha, Lingyu Meng, Bethany Juhnke, Arthur G Erdman, Francesca Samsel, Daniel F Keefe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Scientific visualization tools are rapidly embracing the necessary challenge of simultaneously visualizing multiple parameterized simulation data sets [8]. In the new paradigm, scientists hope to understand parameter relationships and stochastic trends that exist in a parameter space [6], [7]. At the same time, virtual reality (VR) environments have enabled exciting possible opportunities for exploring and comparing time varying spatial data sets [3]. Although VR offers a unique perspective to view 3D and 4D data, it requires high framerates for interactivity and optimized use of precious GPU memory. Accurate simulations, on the other hand, are often very large due to dynamic unstructured mesh resolutions and small timesteps, making it difficult to simply render even one data set. To solve this, large data visualization frameworks often use data sampling and efficient rendering techniques to engage the GPU [1], [8]. Even then, VR is mostly used to add a stereoscopic view, and is rarely an integral part of interactive data instance comparison [3].

Original languageEnglish (US)
Title of host publication2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages110-111
Number of pages2
ISBN (Electronic)9781538668733
DOIs
StatePublished - Oct 1 2018
Event8th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2018 - Berlin, Germany
Duration: Oct 21 2018 → …

Publication series

Name2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018

Conference

Conference8th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2018
CountryGermany
CityBerlin
Period10/21/18 → …

Fingerprint

Fluid structure interaction
Virtual Reality
Virtual reality
Data visualization
Fluid
Interaction
Simulation
Stochastic Trend
Scientific Visualization
Dynamic Mesh
Interactivity
Data Visualization
Sampling
Unstructured Mesh
Large Data
Data storage equipment
Spatial Data
Rendering
Parameter Space
Time-varying

Cite this

Orban, D., Johnson, S., Runesha, H. B., Meng, L., Juhnke, B., Erdman, A. G., ... Keefe, D. F. (2018). Comparison of Multiple Large Fluid-Structure Interaction Simulations in Virtual Reality. In 2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018 (pp. 110-111). [8739222] (2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/LDAV.2018.8739222

Comparison of Multiple Large Fluid-Structure Interaction Simulations in Virtual Reality. / Orban, Daniel; Johnson, Seth; Runesha, Hakizumwami Birali; Meng, Lingyu; Juhnke, Bethany; Erdman, Arthur G; Samsel, Francesca; Keefe, Daniel F.

2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 110-111 8739222 (2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Orban, D, Johnson, S, Runesha, HB, Meng, L, Juhnke, B, Erdman, AG, Samsel, F & Keefe, DF 2018, Comparison of Multiple Large Fluid-Structure Interaction Simulations in Virtual Reality. in 2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018., 8739222, 2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018, Institute of Electrical and Electronics Engineers Inc., pp. 110-111, 8th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2018, Berlin, Germany, 10/21/18. https://doi.org/10.1109/LDAV.2018.8739222
Orban D, Johnson S, Runesha HB, Meng L, Juhnke B, Erdman AG et al. Comparison of Multiple Large Fluid-Structure Interaction Simulations in Virtual Reality. In 2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 110-111. 8739222. (2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018). https://doi.org/10.1109/LDAV.2018.8739222
Orban, Daniel ; Johnson, Seth ; Runesha, Hakizumwami Birali ; Meng, Lingyu ; Juhnke, Bethany ; Erdman, Arthur G ; Samsel, Francesca ; Keefe, Daniel F. / Comparison of Multiple Large Fluid-Structure Interaction Simulations in Virtual Reality. 2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 110-111 (2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018).
@inproceedings{eb21eb1794e0409a801307b370eccdfc,
title = "Comparison of Multiple Large Fluid-Structure Interaction Simulations in Virtual Reality",
abstract = "Scientific visualization tools are rapidly embracing the necessary challenge of simultaneously visualizing multiple parameterized simulation data sets [8]. In the new paradigm, scientists hope to understand parameter relationships and stochastic trends that exist in a parameter space [6], [7]. At the same time, virtual reality (VR) environments have enabled exciting possible opportunities for exploring and comparing time varying spatial data sets [3]. Although VR offers a unique perspective to view 3D and 4D data, it requires high framerates for interactivity and optimized use of precious GPU memory. Accurate simulations, on the other hand, are often very large due to dynamic unstructured mesh resolutions and small timesteps, making it difficult to simply render even one data set. To solve this, large data visualization frameworks often use data sampling and efficient rendering techniques to engage the GPU [1], [8]. Even then, VR is mostly used to add a stereoscopic view, and is rarely an integral part of interactive data instance comparison [3].",
author = "Daniel Orban and Seth Johnson and Runesha, {Hakizumwami Birali} and Lingyu Meng and Bethany Juhnke and Erdman, {Arthur G} and Francesca Samsel and Keefe, {Daniel F}",
year = "2018",
month = "10",
day = "1",
doi = "10.1109/LDAV.2018.8739222",
language = "English (US)",
series = "2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "110--111",
booktitle = "2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018",

}

TY - GEN

T1 - Comparison of Multiple Large Fluid-Structure Interaction Simulations in Virtual Reality

AU - Orban, Daniel

AU - Johnson, Seth

AU - Runesha, Hakizumwami Birali

AU - Meng, Lingyu

AU - Juhnke, Bethany

AU - Erdman, Arthur G

AU - Samsel, Francesca

AU - Keefe, Daniel F

PY - 2018/10/1

Y1 - 2018/10/1

N2 - Scientific visualization tools are rapidly embracing the necessary challenge of simultaneously visualizing multiple parameterized simulation data sets [8]. In the new paradigm, scientists hope to understand parameter relationships and stochastic trends that exist in a parameter space [6], [7]. At the same time, virtual reality (VR) environments have enabled exciting possible opportunities for exploring and comparing time varying spatial data sets [3]. Although VR offers a unique perspective to view 3D and 4D data, it requires high framerates for interactivity and optimized use of precious GPU memory. Accurate simulations, on the other hand, are often very large due to dynamic unstructured mesh resolutions and small timesteps, making it difficult to simply render even one data set. To solve this, large data visualization frameworks often use data sampling and efficient rendering techniques to engage the GPU [1], [8]. Even then, VR is mostly used to add a stereoscopic view, and is rarely an integral part of interactive data instance comparison [3].

AB - Scientific visualization tools are rapidly embracing the necessary challenge of simultaneously visualizing multiple parameterized simulation data sets [8]. In the new paradigm, scientists hope to understand parameter relationships and stochastic trends that exist in a parameter space [6], [7]. At the same time, virtual reality (VR) environments have enabled exciting possible opportunities for exploring and comparing time varying spatial data sets [3]. Although VR offers a unique perspective to view 3D and 4D data, it requires high framerates for interactivity and optimized use of precious GPU memory. Accurate simulations, on the other hand, are often very large due to dynamic unstructured mesh resolutions and small timesteps, making it difficult to simply render even one data set. To solve this, large data visualization frameworks often use data sampling and efficient rendering techniques to engage the GPU [1], [8]. Even then, VR is mostly used to add a stereoscopic view, and is rarely an integral part of interactive data instance comparison [3].

UR - http://www.scopus.com/inward/record.url?scp=85068883046&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85068883046&partnerID=8YFLogxK

U2 - 10.1109/LDAV.2018.8739222

DO - 10.1109/LDAV.2018.8739222

M3 - Conference contribution

T3 - 2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018

SP - 110

EP - 111

BT - 2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -