Intelligent Light and FieldView

Come See Us at AIAA SciTech 2019

Join us at AIAA SciTech in conference sessions and in our booth to learn how we are advancing CFD with innovations in Uncertainity Quantificaton (UQ), Analytics for CFD and large CFD results handling. We have an eye on your largest problems today with HPC FieldView and FieldView 18 and are looking toward 2030 to ensure we will meet the needs of the CFD community tomorrow.

Visit booth #207 for a one-on-one demo of the new FieldView 18.

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Conference Sessions

Application of a CFD Uncertainty Quantification Framework for Industrial-Scale Aerodynamic Analysis

Wed, Jan 09, 5:00pm - 5:30pm, Torrey Hills

John Schaefer and Andrew Cary of The Boeing Company and Earl Duque and Seth Lawrence of Intelligent Light

In a joint effort between the Applied Research Group (Intelligent Light) and Boeing Research and Technology (The Boeing Company), the application of the latest developments in Uncertainty Quantification (UQ) are demonstrated as case studies for industrial scale CFD problems. Starting with a 2D NACA 0012 airfoil at zero lift, then moving to a 3D full-scale aircraft in high lift configuration, the latest UQ frameworks are implemented to determine numerical and model input uncertainty. This effort provides a step towards standardizing the use of UQ as a design and engineering tool to build confidence and reliability in scientific computational engineering and design.

Assessment of Model Validation and Calibration Approaches in the Presence of Uncertainty

Thu, Jan 10, 4:00pm - 4:30pm, Harbor H

Nolan Whiting and Christopher Roy of Virginia Polytechnic Institute and State University, and Earl Duque and Seth Lawrence of Intelligent Light

This paper discusses the investigation and implementation of various methods for quantifying Model Form Uncertainty​ (MFU) in scientific computing. Metrics were obtained through rigorous implementation of several MFU methods to produce comparison studies that quantify the conservativeness of each method. The findings include which methods perform best under different circumstances and provide a guide to best practices when choosing a method for quantifying the model form uncertainty in a computational UQ study.

Summary of 2017 SciTech Computational Environments Special Session Toward the CFD Vision 2030

Fri, Jan 11, 9:30am - 10:00am, Vista B

Andrew Lofthouse, CREATE AV Team, Earl Duque, Intelligent Light, Roger Davis, University of California‚ Davis

Computational Environments can be defined as the hardware and software required to efficiently use high performance computing resources and to easily extract knowledge from that data. As such, they underlie nearly all large-scale simulations. The CFD Vision 2030 report published recommendations for advancements in all areas of computational fluid dynamics that are needed in order to take advantage of Exascale hardware that is expected to be in operation by the year 2030. This paper summarized a special session held at SciTech 2017 sponsored by the Meshing, Visualization and Computational Environments technical committee that looked in more detail at the current status of computational environments and where additional research is required in order to efficiently use Exascale machines.

The session consisted of technical presentations and a question and answer period with a panel of invited experts. Computational environments are vital for efficient use of heterogeneous hardware architectures, large-scale data management, interfaces between multidisciplinary domains, uncertainty quantification and error analysis, as well as automation of complex simulations.

Spectre: A Computational Environment for Managing Total Uncertainty Quantification of CFD Studies

Fri, Jan 11, 10:00am - 10:30am, Vista B

Earl Duque and Seth Lawrence of Intelligent Light

The future of uncertainty quantification as a tool for computational engineering and design hinges on the management, execution and visualization of complex data-driven workflows. Whether the data is historic experiments or modern computational simulations, UQ workflows require onerous dedication to the management and synchronization of all available data. To address the needs of complex UQ workflows, the Applied Research Group at Intelligent Light has developed Spectre: A Computational Environment for Managing Total Uncertainty Quantification of CFD Studies. By encompassing a database, server and user-interface into a RESTful web deployed platform, Spectre provides seamless integration of data management, solver execution and visualization.

Introducing FieldView 18