Spot the Difference

Kiwon Um, Xiangyu Y. Hu, Bing Wang, N. Thuerey
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引用次数: 5

Abstract

Comparative evaluation lies at the heart of science, and determining the accuracy of a computational method is crucial for evaluating its potential as well as for guiding future efforts. However, metrics that are typically used have inherent shortcomings when faced with the under-resolved solutions of real-world simulation problems. We show how to leverage the human visual system in conjunction with crowd-sourced user studies to address the fundamental problems of widely used classical evaluation metrics. We demonstrate that such user studies driven by visual perception yield a very robust metric and consistent answers for complex phenomena without any requirements for proficiency regarding the physics at hand. This holds even for cases away from convergence where traditional metrics often end up with inconclusive results. More specifically, we evaluate results of different essentially non-oscillatory (ENO) schemes in different fluid flow settings. Our methodology represents a novel and practical approach for scientific evaluations that can give answers for previously unsolved problems.
发现差异
比较评估是科学的核心,确定计算方法的准确性对于评估其潜力以及指导未来的努力至关重要。然而,当面对现实世界模拟问题的未解决方案时,通常使用的度量具有固有的缺点。我们展示了如何利用人类视觉系统与众包用户研究相结合,以解决广泛使用的经典评估指标的基本问题。我们证明,这种由视觉感知驱动的用户研究可以为复杂现象提供非常稳健的度量和一致的答案,而无需对手头物理的熟练程度有任何要求。这一点甚至适用于那些传统指标往往以不确定的结果告终的情况。更具体地说,我们评估了不同基本非振荡(ENO)方案在不同流体流动设置下的结果。我们的方法代表了一种新颖而实用的科学评估方法,可以为以前未解决的问题提供答案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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