Supercomputing and Computation

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Knowledge Discovery


The national level grand challenge in Computer Science is the ability to acquire, reduce, analyze and extract meaning from massive amounts of data. ORNL is studying methods for the discovery of "hidden laws and processes" underlying observable behaviors in complex systems. ORNL researchers are developing software frameworks that provide a significant advancement in automating the knowledge discovery process.  We research and apply methods to efficiently provide comprehensive, accurate, verified, validated, and easily understood information to support situational awareness and informed decision-making, going past traditional approaches to develop new methods for meeting user needs across a wide range of domains. These systems are able to develop actionable insights from massive, dynamic, disparate data while enabling the user to ask more complex questions and detect more complex answers.

Related Projects

1-3 of 3 Results
 

Fallout Planning Tool
— Implement a standalone and Web-deployable tool which accurately depicts the location of nuclear debris concentrations suitable for forensics analysis and the dose to the collector tasked to retrieve forensic samples. Automate the planning of forensic collection missions.

SCIPUFF Server
— Provide on-demand hazard prediction and consequence assessment for chemical, biological, and radiological events and releases.

Chemical Security Assessment Tool
— The Chemical Security Assessment Tool (CSAT) collects directly from chemical facilities, refineries, and LNG facilities information in support of chemical security regulation.

 
 
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