2010
Ahrens, James; Heitmann, Katrin; Petersen, Mark; Woodring, Jonathan; Williams, Sean; Fasel, Patricia; Ahrens, Christine; Hsu, Chung-Hsing; Geveci, Berk
Verification of Scientific Simulations via Hypothesis-Driven Comparative and Quantitative Visualization Journal Article
In: IEEE Computer Graphics and Applications Magazine, vol. 30, no. 6, 2010, (LA-UR-10-07017).
Abstract | Links | BibTeX | Tags: hypothesis testing, Space, Visual Evidence; Feature Detection and Tracking, Visualization in Earth
@article{ahrens2010verification,
title = {Verification of Scientific Simulations via Hypothesis-Driven Comparative and Quantitative Visualization},
author = {James Ahrens and Katrin Heitmann and Mark Petersen and Jonathan Woodring and Sean Williams and Patricia Fasel and Christine Ahrens and Chung-Hsing Hsu and Berk Geveci},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/06/VerificationOfTheScientificSimulationsViaHypothesis-DrivenComparativeAndQuantitativeVisualization.pdf},
year = {2010},
date = {2010-01-01},
journal = {IEEE Computer Graphics and Applications Magazine},
volume = {30},
number = {6},
publisher = {Oak Ridge National Laboratory (ORNL)},
abstract = {We describe a visualization-assisted process for the verification of scientific simulation codes. The need for code verification stems from the requirement for very accurate predictions to interpret data confidently. We compare different cosmological and oceanographic simulations to reliably predict differences in simulation results. Our verification consists of the integration of an iterative hypothesis-verification process with comparative, feature, and quantitative visualization. We validate this process by verifying the results of different cosmology and oceanographic simulation codes.},
note = {LA-UR-10-07017},
keywords = {hypothesis testing, Space, Visual Evidence; Feature Detection and Tracking, Visualization in Earth},
pubstate = {published},
tppubtype = {article}
}
We describe a visualization-assisted process for the verification of scientific simulation codes. The need for code verification stems from the requirement for very accurate predictions to interpret data confidently. We compare different cosmological and oceanographic simulations to reliably predict differences in simulation results. Our verification consists of the integration of an iterative hypothesis-verification process with comparative, feature, and quantitative visualization. We validate this process by verifying the results of different cosmology and oceanographic simulation codes.
Hsu, Chung-Hsing; Ahrens, James; Heitmann, Katrin
Verification of the time evolution of cosmological simulations via hypothesis-driven comparative and quantitative visualization Proceedings Article
In: Pacific Visualization Symposium (PacificVis), 2010 IEEE, pp. 81–88, IEEE 2010, (LA-UR-09-08278).
Abstract | Links | BibTeX | Tags: environmental sciences, Space, Visual Evidence; Feature Detection and Tracking, Visualization in Earth
@inproceedings{hsu2010verification,
title = {Verification of the time evolution of cosmological simulations via hypothesis-driven comparative and quantitative visualization},
author = {Chung-Hsing Hsu and James Ahrens and Katrin Heitmann},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/06/VerificationOfTheTimeEvolutionOfCosmologicalSimulationsViaHyphothesis-DrivenComparativeAndQuantitativeVisualization.pdf},
year = {2010},
date = {2010-01-01},
booktitle = {Pacific Visualization Symposium (PacificVis), 2010 IEEE},
pages = {81--88},
organization = {IEEE},
abstract = {We describe a visualization-assisted process for the verification of cosmological simulation codes. The need for code verification stems from the requirement for very accurate predictions in order to interpret observational data confidently. We compare different simulation algorithms in order to reliably predict differences in simulation results and understand their dependence on input parameter settings. Our verification process consists of the integration of iterative hypothesis-verification with comparative, feature and quantitative visualization. We validate this process by verifying the time evolution results of three different cosmology simulation codes. The purpose of this verification is to study the accuracy of AMR methods versus other N-body simulation methods for cosmological simulations.},
note = {LA-UR-09-08278},
keywords = {environmental sciences, Space, Visual Evidence; Feature Detection and Tracking, Visualization in Earth},
pubstate = {published},
tppubtype = {inproceedings}
}
We describe a visualization-assisted process for the verification of cosmological simulation codes. The need for code verification stems from the requirement for very accurate predictions in order to interpret observational data confidently. We compare different simulation algorithms in order to reliably predict differences in simulation results and understand their dependence on input parameter settings. Our verification process consists of the integration of iterative hypothesis-verification with comparative, feature and quantitative visualization. We validate this process by verifying the time evolution results of three different cosmology simulation codes. The purpose of this verification is to study the accuracy of AMR methods versus other N-body simulation methods for cosmological simulations.
: . .
1.
Ahrens, James; Heitmann, Katrin; Petersen, Mark; Woodring, Jonathan; Williams, Sean; Fasel, Patricia; Ahrens, Christine; Hsu, Chung-Hsing; Geveci, Berk
Verification of Scientific Simulations via Hypothesis-Driven Comparative and Quantitative Visualization Journal Article
In: IEEE Computer Graphics and Applications Magazine, vol. 30, no. 6, 2010, (LA-UR-10-07017).
@article{ahrens2010verification,
title = {Verification of Scientific Simulations via Hypothesis-Driven Comparative and Quantitative Visualization},
author = {James Ahrens and Katrin Heitmann and Mark Petersen and Jonathan Woodring and Sean Williams and Patricia Fasel and Christine Ahrens and Chung-Hsing Hsu and Berk Geveci},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/06/VerificationOfTheScientificSimulationsViaHypothesis-DrivenComparativeAndQuantitativeVisualization.pdf},
year = {2010},
date = {2010-01-01},
journal = {IEEE Computer Graphics and Applications Magazine},
volume = {30},
number = {6},
publisher = {Oak Ridge National Laboratory (ORNL)},
abstract = {We describe a visualization-assisted process for the verification of scientific simulation codes. The need for code verification stems from the requirement for very accurate predictions to interpret data confidently. We compare different cosmological and oceanographic simulations to reliably predict differences in simulation results. Our verification consists of the integration of an iterative hypothesis-verification process with comparative, feature, and quantitative visualization. We validate this process by verifying the results of different cosmology and oceanographic simulation codes.},
note = {LA-UR-10-07017},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We describe a visualization-assisted process for the verification of scientific simulation codes. The need for code verification stems from the requirement for very accurate predictions to interpret data confidently. We compare different cosmological and oceanographic simulations to reliably predict differences in simulation results. Our verification consists of the integration of an iterative hypothesis-verification process with comparative, feature, and quantitative visualization. We validate this process by verifying the results of different cosmology and oceanographic simulation codes.
2.
Hsu, Chung-Hsing; Ahrens, James; Heitmann, Katrin
Verification of the time evolution of cosmological simulations via hypothesis-driven comparative and quantitative visualization Proceedings Article
In: Pacific Visualization Symposium (PacificVis), 2010 IEEE, pp. 81–88, IEEE 2010, (LA-UR-09-08278).
@inproceedings{hsu2010verification,
title = {Verification of the time evolution of cosmological simulations via hypothesis-driven comparative and quantitative visualization},
author = {Chung-Hsing Hsu and James Ahrens and Katrin Heitmann},
url = {http://datascience.dsscale.org/wp-content/uploads/2016/06/VerificationOfTheTimeEvolutionOfCosmologicalSimulationsViaHyphothesis-DrivenComparativeAndQuantitativeVisualization.pdf},
year = {2010},
date = {2010-01-01},
booktitle = {Pacific Visualization Symposium (PacificVis), 2010 IEEE},
pages = {81--88},
organization = {IEEE},
abstract = {We describe a visualization-assisted process for the verification of cosmological simulation codes. The need for code verification stems from the requirement for very accurate predictions in order to interpret observational data confidently. We compare different simulation algorithms in order to reliably predict differences in simulation results and understand their dependence on input parameter settings. Our verification process consists of the integration of iterative hypothesis-verification with comparative, feature and quantitative visualization. We validate this process by verifying the time evolution results of three different cosmology simulation codes. The purpose of this verification is to study the accuracy of AMR methods versus other N-body simulation methods for cosmological simulations.},
note = {LA-UR-09-08278},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We describe a visualization-assisted process for the verification of cosmological simulation codes. The need for code verification stems from the requirement for very accurate predictions in order to interpret observational data confidently. We compare different simulation algorithms in order to reliably predict differences in simulation results and understand their dependence on input parameter settings. Our verification process consists of the integration of iterative hypothesis-verification with comparative, feature and quantitative visualization. We validate this process by verifying the time evolution results of three different cosmology simulation codes. The purpose of this verification is to study the accuracy of AMR methods versus other N-body simulation methods for cosmological simulations.