Best Paper Honorable Mention Award in the IEEE Visualization Conference 2016
The paper "In Situ Distribution Guided Analysis and Visualization of Transonic Jet Engine Simulations" demonstrates an in situ distribution guided data summarization and visual analytics approach to help understand the rotating stall phenomenon in transonic jet engine compressors. The CFD simulation code TURBO, used in this work, is a state-of-the-art Navier-Stokes based, time-accurate computational fluid dynamics simulator. Despite the proven high modeling accuracy of TURBO, the excessive simulation data prohibits traditional post-processing based analysis in both storage and I/O time. This work addresses these big data issues and proposes an alternative in situ analysis pathway for the study of rotating stall. The proposed technique summarizes statistics of important properties of the simulation data directly while the simulation is running using a probabilistic data modeling scheme. This in situ data summarization enables flexible and scalable anomaly detection for flow instability in post analysis, which reveals the spatiotemporal trends of rotating stall. Furthermore, the verification of the hypotheses and exploratory visualization using the summarized data are realized using probabilistic visualization techniques such as uncertain isocontouring.