Sensor Scoring Methodology for Subterranean Structure Confirmation,

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Principal Investigators
Darrell S. Dunn
Mark R. Lesher
Theodore A. Kramer
Stephen L. Wiedmann
Jeremy K. Zoss

Inclusive Dates:  09/15/2003 - Current

Background - One of the Center for Nuclear Waste Regulatory Analyses (CNWRA) primary goals is to evaluate the subterranean monitoring methods for the Yucca Mountain hazardous waste site during the 100-year preclosure period. The site is characterized as having extreme environmental challenges that include high temperature (>180 °F), high radiation (>1,400 rem/hr), elevated humidity (nearly 90 percent), and remote access. As part of the requirements for this site, a number of remote sensors will be deployed to measure the factors deemed necessary to monitor the integrity of the hazardous waste emplacement drifts. Monitoring the performance of sensors that are remotely deployed in hazardous locations is not a Yucca-specific problem. Instead, hazardous waste facilities would benefit from being able to assess the performance of a particular sensor before it is deployed, potentially reducing the costs associated with sensor extraction and waste disposal.

Approach - The objective of this project is to develop a sensor-scoring methodology for long-term deployment of sensors in hazardous environments. To accomplish this task, the research team will establish a set of sensor performance and environmental requirements, develop a methodology and sensor technology classification, and provide an interface to allow the user to assess a particular sensor. This methodology would estimate (score) the performance of a specific sensor in the environment during the anticipated monitoring period, by de-rating the sensor attributes (i.e., sensitivity, accuracy) when subjected to the aforementioned environmental and performance requirements.

Accomplishments - After defining the sensor classes to be investigated and the sensor requirements in terms of environmental and performance requirements, a sensor technology classification study was initiated to provide the data necessary to incorporate into the scoring methodology. The sensor classification study has been under investigation with the aid of a sensor classification form that standardized the parameters that may be used in the methodology. In addition, the team put together a sensor materials template for two of the sensor classes. Both the materials template and the sensor technology and classification study for the various sensor classes are being used to develop the sensor scoring methodology. In conjunction with the technology classification, the team developed two iterations of the sensor scoring methodology. The second iteration incorporates a rules-based scoring technique and a reliability model that de-rates sensor attributes when subjected to the user-supplied environmental and performance specifications. Lastly, the team established a rough draft of a user interface that will be used when porting the methodology to a software platform.

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