In Situ Decommissioning Sensor Network, Meso-Scale Test Bed - Phase 3 Fluid Injection Test Summary Report

Serrato, M. G.

Savannah River Site (S.C.)

关键词: 46 Instrumentation Related To Nuclear Science And Technology In Situ Decommissioning;    12 Management Of Radioactive And Non-Radioactive Wastes From Nuclear Facilities;    In Situ Decommissioning;    Nuclear Facilities;    Sensor Network;   

DOI  :  10.2172/1098219
RP-ID  :  SRNL-STI--2013-00569
RP-ID  :  DE-AC09-08SR22470
RP-ID  :  1098219

美国|英语

来源: UNT Digital Library

【 摘 要 】

The DOE Office of Environmental management (DOE EM) faces the challenge of decommissioning thousands of excess nuclear facilities, many of which are highly contaminated. A number of these excess facilities are massive and robust concrete structures that are suitable for isolating the contained contamination for hundreds of years, and a permanent decommissioning end state option for these facilities is in situ decommissioning (ISD). The ISD option is feasible for a limited, but meaningfull number of DOE contaminated facilities for which there is substantial incremental environmental, safety, and cost benefits versus alternate actions to demolish and excavate the entire facility and transport the rubble to a radioactive waste landfill. A general description of an ISD project encompasses an entombed facility; in some cases limited to the blow-grade portion of a facility. However, monitoring of the ISD structures is needed to demonstrate that the building retains its structural integrity and the contaminants remain entombed within the grout stabilization matrix. The DOE EM Office of Deactivation and Decommissioning and Facility Engineering (EM-13) Program Goal is to develop a monitoring system to demonstrate long-term performance of closed nuclear facilities using the ISD approach. The Savannah River National Laboratory (SRNL) has designed and implemented the In Situ Decommissioning Sensor Network, Meso-Scale Test Bed (ISDSN-MSTB) to address the feasibility of deploying a long-term monitoring system into an ISD closed nuclear facility. The ISDSN-MSTB goal is to demonstrate the feasibility of installing and operating a remote sensor network to assess cementitious material durability, moisture-fluid flow through the cementitious material, and resulting transport potential for contaminate mobility in a decommissioned closed nuclear facility. The original ISDSN-MSTB installation and remote sensor network operation was demonstrated in FY 2011-12 at the ISDSN-MSTB test cube located at the Florida International University Applied Research Center, Miami, FL (FIU-ARC). A follow-on fluid injection test was developed to detect fluid and ion migration in a cementitious material/grouted test cube using a limited number of existing embedded sensor systems. This In Situ Decommissioning Sensor Network, Meso-Scale Test Bed (ISDSN-MSTB) - Phase 3 Fluid Injection Test Summary Report summarizes the test implementation, acquired and processed data, and results from the activated embedded sensor systems used during the fluid injection test. The ISDSN-MSTB Phase 3 Fluid Injection Test was conducted from August 27 through September 6, 2013 at the FIU-ARC ISDSN-MSTB test cube. The fluid injection test activated a portion of the existing embedded sensor systems in the ISDSN-MSTB test cube: Electrical Resistivity Tomography-Thermocouple Sensor Arrays, Advance Tensiometer Sensors, and Fiber Loop Ringdown Optical Sensors. These embedded sensor systems were activated 15 months after initial placement. All sensor systems were remotely operated and data acquisition was completed through the established Sensor Remote Access System (SRAS) hosted on the DOE D&D Knowledge Management Information Tool (D&D DKM-IT) server. The ISDN Phase 3 Fluid Injection Test successfully demonstrated the feasibility of embedding sensor systems to assess moisture-fluid flow and resulting transport potential for contaminate mobility through a cementitious material/grout monolith. The ISDSN embedded sensor systems activated for the fluid injection test highlighted the robustness of the sensor systems and the importance of configuring systems in-depth (i.e., complementary sensors and measurements) to alleviate data acquisition gaps.