Defining And Characterizing Sample Representativeness For DWPF Melter Feed Samples

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Representative sampling is important throughout the Defense Waste Processing Facility (DWPF) process, and the demonstrated success of the DWPF process to achieve glass product quality over the past two decades is a direct result of the quality of information obtained from the process. The objective of this report was to present sampling methods that the Savannah River Site (SRS) used to qualify waste being dispositioned at the DWPF. The goal was to emphasize the methodology, not a list of outcomes from those studies. This methodology includes proven methods for taking representative samples, the use of controlled analytical methods, and data ... continued below

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48 p.

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Shine, E. P. & Poirier, M. R. October 29, 2013.

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This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this report can be viewed below.

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  • Savannah River Site (S.C.)
    Publisher Info: Savannah River Site (SRS), Aiken, SC (United States)
    Place of Publication: Aiken, South Carolina

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Description

Representative sampling is important throughout the Defense Waste Processing Facility (DWPF) process, and the demonstrated success of the DWPF process to achieve glass product quality over the past two decades is a direct result of the quality of information obtained from the process. The objective of this report was to present sampling methods that the Savannah River Site (SRS) used to qualify waste being dispositioned at the DWPF. The goal was to emphasize the methodology, not a list of outcomes from those studies. This methodology includes proven methods for taking representative samples, the use of controlled analytical methods, and data interpretation and reporting that considers the uncertainty of all error sources. Numerous sampling studies were conducted during the development of the DWPF process and still continue to be performed in order to evaluate options for process improvement. Study designs were based on use of statistical tools applicable to the determination of uncertainties associated with the data needs. Successful designs are apt to be repeated, so this report chose only to include prototypic case studies that typify the characteristics of frequently used designs. Case studies have been presented for studying in-tank homogeneity, evaluating the suitability of sampler systems, determining factors that affect mixing and sampling, comparing the final waste glass product chemical composition and durability to that of the glass pour stream sample and other samples from process vessels, and assessing the uniformity of the chemical composition in the waste glass product. Many of these studies efficiently addressed more than one of these areas of concern associated with demonstrating sample representativeness and provide examples of statistical tools in use for DWPF. The time when many of these designs were implemented was in an age when the sampling ideas of Pierre Gy were not as widespread as they are today. Nonetheless, the engineers and statisticians used carefully thought out designs that systematically and economically provided plans for data collection from the DWPF process. Key shared features of the sampling designs used at DWPF and the Gy sampling methodology were the specification of a standard for sample representativeness, an investigation that produced data from the process to study the sampling function, and a decision framework used to assess whether the specification was met based on the data. Without going into detail with regard to the seven errors identified by Pierre Gy, as excellent summaries are readily available such as Pitard [1989] and Smith [2001], SRS engineers understood, for example, that samplers can be biased (Gy�s extraction error), and developed plans to mitigate those biases. Experiments that compared installed samplers with more representative samples obtained directly from the tank may not have resulted in systematically partitioning sampling errors into the now well-known error categories of Gy, but did provide overall information on the suitability of sampling systems. Most of the designs in this report are related to the DWPF vessels, not the large SRS Tank Farm tanks. Samples from the DWPF Slurry Mix Evaporator (SME), which contains the feed to the DWPF melter, are characterized using standardized analytical methods with known uncertainty. The analytical error is combined with the established error from sampling and processing in DWPF to determine the melter feed composition. This composition is used with the known uncertainty of the models in the Product Composition Control System (PCCS) to ensure that the wasteform that is produced is comfortably within the acceptable processing and product performance region. Having the advantage of many years of processing that meets the waste glass product acceptance criteria, the DWPF process has provided a considerable amount of data about itself in addition to the data from many special studies. Demonstrating representative sampling directly from the large Tank Farm tanks is a difficult, if not unsolvable enterprise due to limited accessibility. However, the consistency and the adequacy of sampling and mixing at SRS could at least be studied under the controlled process conditions based on samples discussed by Ray and others [2012a] in Waste Form Qualification Report (WQR) Volume 2 and the transfers from Tanks 40H and 51H to the Sludge Receipt and Adjustment Tank (SRAT) within DWPF. It is important to realize that the need for sample representativeness becomes more stringent as the material gets closer to the melter, and the tanks within DWPF have been studied extensively to meet those needs.

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48 p.

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  • Report No.: SRNL-STI--2013-00544
  • Grant Number: DE-AC09-08SR22470
  • DOI: 10.2172/1098943 | External Link
  • Office of Scientific & Technical Information Report Number: 1098943
  • Archival Resource Key: ark:/67531/metadc869334

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  • October 29, 2013

Added to The UNT Digital Library

  • Sept. 16, 2016, 12:32 a.m.

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  • Dec. 6, 2016, 6:18 p.m.

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Shine, E. P. & Poirier, M. R. Defining And Characterizing Sample Representativeness For DWPF Melter Feed Samples, report, October 29, 2013; Aiken, South Carolina. (digital.library.unt.edu/ark:/67531/metadc869334/: accessed September 20, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.