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1 Distributed Big Data & Analytics University of Cincinnati –- Computational Fluid Dynamics Research - Aerospace Project/Research Title: Study of Active.

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Presentation on theme: "1 Distributed Big Data & Analytics University of Cincinnati –- Computational Fluid Dynamics Research - Aerospace Project/Research Title: Study of Active."— Presentation transcript:

1 1 Distributed Big Data & Analytics University of Cincinnati –- Computational Fluid Dynamics Research - Aerospace Project/Research Title: Study of Active and Passive Flow Control Techniques over Turbine Blades Industry Sector: Aerospace Science Sub-domain: Mechanical Engineering, Comp Fluid Dynamics Short Description of Project & Relation to Big Data: Collaborative immersive visualization of large datasets and simulation trajectories to support the study of active and passive flow control techniques and turbine-blade cooling. The goal of such simulations is to provide predictive performance analysis of physical systems that may contain many integrated components and which are described by multiple, interacting, physical processes. 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 _____

2 2 Distributed Big Data & Analytics Project Template

3 3 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 _____


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