Qualification of Innovative High Level Waste Pipeline Unplugging Technologies

摘要

In the past, some of the pipelines have plugged during high level waste (HLW) transfers resulting in schedule delays and increased costs. Furthermore, pipeline plugging has been cited by the "best and brightest" technical review as one of the major issues that can result in unplanned outages at the Waste Treatment Plant causing inconsistent operation. As the DOE moves toward a more active high level waste retrieval, the site engineers will be faced with increasing cross-site pipeline waste slurry transfers that will result in increased probability of a pipeline getting plugged. Hence, availability of a pipeline unplugging tool/technology is crucial to ensure smooth operation of the waste transfers and in ensuring tank farm cleanup milestones are met. FIU had earlier tested and evaluated various unplugging technologies through an industry call. Based on mockup testing, two technologies were identified that could withstand the rigors of operation in a radioactive environment and with the ability to handle sharp 90 elbows. We present results of the second phase of detailed testing and evaluation of pipeline unplugging technologies and the objective is to qualify these pipeline unplugging technologies for subsequent deployment at a DOE facility. The current phase of testing and qualification comprises of a heavily instrumented 3-inch diameter (full-scale) pipeline facilitating extensive data acquisition for design optimization and performance evaluation, as it applies to three types of plugs atypical of the DOE HLW waste. Furthermore, the data from testing at three different lengths of pipe in conjunction with the physics of the process will assist in modeling the unplugging phenomenon that will then be used to scale-up process parameters and system variables for longer and site typical pipe lengths, which can extend as much as up to 19,000 ft. Detailed information resulting from the testing will provide the DOE end-user with sufficient data and understanding of the technology, and its limitations to aid in the benefit-cost analysis for management decision whether to deploy the technology or to abandon the pipeline as has been done in the past.