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The process for integrating the NNSA knowledge base

Martinez, Elaine M.; Young, Christopher J.; Wilkening, Lisa K.

From 2002 through 2006, the Ground Based Nuclear Explosion Monitoring Research & Engineering (GNEMRE) program at Sandia National Laboratories defined and modified a process for merging different types of integrated research products (IRPs) from various researchers into a cohesive, well-organized collection know as the NNSA Knowledge Base, to support operational treaty monitoring. This process includes defining the KB structure, systematically and logically aggregating IRPs into a complete set, and verifying and validating that the integrated Knowledge Base works as expected.

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The 2004 knowledge base parametric grid data software suite

Ballard, Sanford B.; Chang, Marcus C.; Hipp, James R.; Jensen, Lee A.; Simons, Randall W.; Wilkening, Lisa K.

One of the most important types of data in the National Nuclear Security Administration (NNSA) Ground-Based Nuclear Explosion Monitoring Research and Engineering (GNEM R&E) Knowledge Base (KB) is parametric grid (PG) data. PG data can be used to improve signal detection, signal association, and event discrimination, but so far their greatest use has been for improving event location by providing ground-truth-based corrections to travel-time base models. In this presentation we discuss the latest versions of the complete suite of Knowledge Base PG tools developed by NNSA to create, access, manage, and view PG data. The primary PG population tool is the Knowledge Base calibration integration tool (KBCIT). KBCIT is an interactive computer application to produce interpolated calibration-based information that can be used to improve monitoring performance by improving precision of model predictions and by providing proper characterizations of uncertainty. It is used to analyze raw data and produce kriged correction surfaces that can be included in the Knowledge Base. KBCIT not only produces the surfaces but also records all steps in the analysis for later review and possible revision. New features in KBCIT include a new variogram autofit algorithm; the storage of database identifiers with a surface; the ability to merge surfaces; and improved surface-smoothing algorithms. The Parametric Grid Library (PGL) provides the interface to access the data and models stored in a PGL file database. The PGL represents the core software library used by all the GNEM R&E tools that read or write PGL data (e.g., KBCIT and LocOO). The library provides data representations and software models to support accurate and efficient seismic phase association and event location. Recent improvements include conversion of the flat-file database (FDB) to an Oracle database representation; automatic access of station/phase tagged models from the FDB during location; modification of the core geometric data representations; a new multimodel representation for combining separate seismic data models that partially overlap; and a port of PGL to the Microsoft Windows platform. The Data Manager (DM) tool provides access to PG data for purposes of managing the organization of the generated PGL file database, or for perusing the data for visualization and informational purposes. It is written as a graphical user interface (GUI) that can directly access objects stored in any PGL file database and display it in an easily interpreted textual or visual format. New features include enhanced station object processing; low-level conversion to a new core graphics visualization library, the visualization toolkit (VTK); additional visualization support for most of the PGL geometric objects; and support for the Environmental Systems Research Institute (ESRI) shape files (which are used to enhance the geographical context during visualization). The Location Object-Oriented (LocOO) tool computes seismic event locations and associated uncertainty based on travel time, azimuth, and slowness observations. It uses a linearized least-squares inversion algorithm (the Geiger method), enhanced with Levenberg-Marquardt damping to improve performance in highly nonlinear regions of model space. LocOO relies on PGL for all predicted quantities and is designed to fully exploit all the capabilities of PGL that are relevant to seismic event location. New features in LocOO include a redesigned internal architecture implemented to enhance flexibility and to support simultaneous multiple event location. Database communication has been rewritten using new object-relational features available in Oracle 9i.

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2 Results
2 Results