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Distributed Big Data & Analytics University of Cincinnati – Modeling and Simulation

•Project/Research Title: Study of Active and Passive Flow Control Techniques over Turbine Blades

•Industry Sector: Consumer Products

•Science Sub-domain: Mechanical Engineering, Modeling and Simulation

•Short Description of Project & Relation to Big Data: The UC Simulation Center, in collaboration with Procter & Gamble, focuses on high-fidelity numerical simulation of complex flow phenomena with a wide range of length and time scales. The UC Simulation center is a partnership where students work on M&S of complex industrial problems associated with porous media, multiphase flows, etc. Predictive performance analysis of the multidisciplinary, multi-scale systems generate terabytes of data.

•Best Contact: Jane Combs, combsje@uc.edu

•Big Data Attributes: Simulation datasets and data visualization

•Aggregate Data Size: Now __2TB___, 2016 __4TB___, 2017 __6___, 2020 _____

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Distributed Big Data & Analytics Project Template

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Distributed Big Data & Analytics Project Template

•Project/Research Title: Machine Tool Ball Screw Health Monitoring

•Industry Sector: Manufacturing / Industrial Machinery

•Science Sub-domain: Data Analysis / Prognostics & Health Management

•Short Description of Project & Relation to Big Data: The goal of this project is to conduct multiple run-to-failure tests using commercially available machine tool ball screws and motors to collect data and design a data driven model for health monitoring and prediction of such ball screws. Data from these tests is transferred and stored on a central server. A mobile app will be developed for monitoring these tests.

•Best Contact: Professor Jay Lee

•Big Data Attributes: Sensor, Near Real-time

•Aggregate Data Size: Now __5TB___, 2016 __15TB___, 2017 __30TB___, 2020 _____