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Modelling the effect of computation sampling on insight error in computational fluid dynamics scientific simulation

Moeti Masiane (Department of Computer Science, Virginia Tech, Blacksburg, Virginia, USA)
Eric Jacques (Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA)
Wuchun Feng (Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA)
Chris North (Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA)

Journal of Engineering, Design and Technology

ISSN: 1726-0531

Article publication date: 5 August 2020

Issue publication date: 3 March 2021

Abstract

Purpose

The purpose of this paper is to collect data from humans as they generate insights from the visualised results of computational fluid dynamics (CFD) scientific simulation. The authors hypothesise the behaviour of their insight errors (IEs) and proceed to quantify the IEs provided by the crowd participants. They then use the insight framework to model the behaviours of the errors. Using the crowd responses and models from the framework, they test the hypotheses and use the results to validate the framework for the speedup of CFD applications.

Design/methodology/approach

The authors use a randomised between-subjects experiment with blocking. CFD grid resolution is the independent variable while IE is the dependent variable. The experiment has one treatment factor with five levels. In case varying timestamps has an effect on insight variance levels, the authors block the responses by timestep. In total, 150 participants are randomly assigned to one of five groups and also randomly assigned to one of five blocks within a treatment. Participants are asked to complete a benchmark and open-ended task.

Findings

The authors find that the variances of insight and perception errors have a U-shaped relationship with grid resolution, that similar to the previously studied visualisation applications, the IE framework is valid for insights generated from CFD results and grid resolution can be used to predict the variance of IE resulting from observing CFD post-processing results.

Originality/value

To the best of the authors’ knowledge, no other work has measured IE variance to present it to simulation users so that they can use it as a feedback metric for selecting the ideal grid resolution when using grid resolution to speedup CFD simulation.

Keywords

Citation

Masiane, M., Jacques, E., Feng, W. and North, C. (2021), "Modelling the effect of computation sampling on insight error in computational fluid dynamics scientific simulation", Journal of Engineering, Design and Technology, Vol. 19 No. 1, pp. 263-290. https://doi.org/10.1108/JEDT-05-2020-0161

Publisher

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Emerald Publishing Limited

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