Experimental and Sampling Design for the INL-2 Sample Collection Operational Test

This report describes the experimental and sampling design developed to assess sampling approaches and methods for detecting contamination in a building and clearing the building for use after decontamination. An Idaho National Laboratory (INL) building will be contaminated with BG (Bacillus globigii, renamed Bacillus atrophaeus), a simulant for Bacillus anthracis (BA). The contamination, sampling, decontamination, and re-sampling will occur per the experimental and sampling design. This INL-2 Sample Collection Operational Test is being planned by the Validated Sampling Plan Working Group (VSPWG). The primary objectives are: 1) Evaluate judgmental and probabilistic sampling for characterization as well as probabilistic and combined (judgment and probabilistic) sampling approaches for clearance, 2) Conduct these evaluations for gradient contamination (from low or moderate down to absent or undetectable) for different initial concentrations of the contaminant, 3) Explore judgment composite sampling approaches to reduce sample numbers, 4) Collect baseline data to serve as an indication of the actual levels of contamination in the tests. A combined judgmental and random (CJR) approach uses Bayesian methodology to combine judgmental and probabilistic samples to make clearance statements of the form "X% confidence that at least Y% of an area does not contain detectable contamination” (X%/Y% clearance statements). The INL-2 experimental design has five test events, which 1) vary the floor of the INL building on which the contaminant will be released, 2) provide for varying the amount of contaminant released to obtain desired concentration gradients, and 3) investigate overt as well as covert release of contaminants. Desirable contaminant gradients would have moderate to low concentrations of contaminant in rooms near the release point, with concentrations down to zero in other rooms. Such gradients would provide a range of contamination levels to challenge the sampling, sample extraction, and analytical methods to be used in the INL-2 study. For each of the five test events, the specified floor of the INL building will be contaminated with BG using a point-release device located in the room specified in the experimental design. Then quality control (QC), reference material coupon (RMC), judgmental, and probabilistic samples will be collected according to the sampling plan for each test event. Judgmental samples will be selected based on professional judgment and prior information. Probabilistic samples were selected with a random aspect and in sufficient numbers to provide desired confidence for detecting contamination or clearing uncontaminated (or decontaminated) areas. Following sample collection for a given test event, the INL building will be decontaminated. For possibly contaminated areas, the numbers of probabilistic samples were chosen to provide 95% confidence of detecting contaminated areas of specified sizes. For rooms that may be uncontaminated following a contamination event, or for whole floors after decontamination, the numbers of judgmental and probabilistic samples were chosen using the CJR approach. The numbers of samples were chosen to support making X%/Y% clearance statements with X = 95% or 99% and Y = 96% or 97%. The experimental and sampling design also provides for making X%/Y% clearance statements using only probabilistic samples. For each test event, the numbers of characterization and clearance samples were selected within limits based on operational considerations while still maintaining high confidence for detection and clearance aspects. The sampling design for all five test events contains 2085 samples, with 1142 after contamination and 943 after decontamination. These numbers include QC, RMC, judgmental, and probabilistic samples. The experimental and sampling design specified in this report provides a good statistical foundation for achieving the objectives of the INL-2 study

Scaling Relationships Based on Scaled Tank Mixing and Transfer Test Results

This report documents the statistical analyses performed (by Pacific Northwest National Laboratory for Washington River Protection Solutions) on data from 26 tests conducted using two scaled tanks (43 and 120 inches) in the Small Scale Mixing Demonstration platform. The 26 tests varied several test parameters, including mixer-jet nozzle velocity, base simulant, supernatant viscosity, and capture velocity. For each test, samples were taken pre-transfer and during five batch transfers. The samples were analyzed for the concentrations (lbs/gal slurry) of four primary components in the base simulants (gibbsite, stainless steel, sand, and ZrO2). The statistical analyses including modeling the component concentrations as functions of test parameters using stepwise regression with two different model forms. The resulting models were used in an equivalent performance approach to calculate values of scaling exponents (for a simple geometric scaling relationship) as functions of the parameters in the component concentration models. The resulting models and scaling exponents are displayed in tables and graphically. The sensitivities of component concentrations and scaling exponents to the test parameters are presented graphically. These results will serve as inputs to subsequent work by other researchers to develop scaling relationships that are applicable to full-scale tanks

Experimental Design for a Sponge-Wipe Study to Relate the Recovery Efficiency and False Negative Rate to the Concentration of a Bacillus anthracis Surrogate for Six Surface Materials

Two concerns were raised by the Government Accountability Office following the 2001 building contaminations via letters containing Bacillus anthracis (BA). These included the: 1) lack of validated sampling methods, and 2) need to use statistical sampling to quantify the confidence of no contamination when all samples have negative results. Critical to addressing these concerns is quantifying the false negative rate (FNR). The FNR may depend on the 1) method of contaminant deposition, 2) surface concentration of the contaminant, 3) surface material being sampled, 4) sample collection method, 5) sample storage/transportation conditions, 6) sample processing method, and 7) sample analytical method. A review of the literature found 17 laboratory studies that focused on swab, wipe, or vacuum samples collected from a variety of surface materials contaminated by BA or a surrogate, and used culture methods to determine the surface contaminant concentration. These studies quantified performance of the sampling and analysis methods in terms of recovery efficiency (RE) and not FNR (which left a major gap in available information). Quantifying the FNR under a variety of conditions is a key aspect of validating sample and analysis methods, and also for calculating the confidence in characterization or clearance decisions based on a statistical sampling plan. A laboratory study was planned to partially fill the gap in FNR results. This report documents the experimental design developed by Pacific Northwest National Laboratory and Sandia National Laboratories (SNL) for a sponge-wipe method. The testing was performed by SNL and is now completed. The study investigated the effects on key response variables from six surface materials contaminated with eight surface concentrations of a BA surrogate (Bacillus atrophaeus). The key response variables include measures of the contamination on test coupons of surface materials tested, contamination recovered from coupons by sponge-wipe samples, RE, and FNR. The experimental design involves 16 test runs, performed in two blocks of eight runs. Three surface materials (stainless steel, vinyl tile, and ceramic tile) were tested in the first block, while three other surface materials (plastic, painted wood paneling, and faux leather) were tested in the second block. The eight surface concentrations of the surrogate were randomly assigned to test runs within each block. Some of the concentrations were very low and presented challenges for deposition, sampling, and analysis. However, such tests are needed to investigate RE and FNR over the full range of concentrations of interest. In each run, there were 10 test coupons of each of the three surface materials. A positive control sample was generated at the same time as each test sample. The positive control results will be used to 1) calculate RE values for the wipe sampling and analysis method, and 2) fit RE- and FNR-concentration equations, for each of the six surface materials. Data analyses will support 1) estimating the FNR for each combination of contaminant concentration and surface material, 2) estimating the surface concentrations and their uncertainties of the contaminant for each combination of concentration and surface material, 3) estimating RE (%) and their uncertainties for each combination of contaminant concentration and surface material, 4) fitting FNR-concentration and RE-concentration equations for each of the six surface materials, 5) assessing goodness-of-fit of the equations, and 6) quantifying the uncertainty in FNR and RE predictions made with the fitted equations

Calculating Confidence, Uncertainty, and Numbers of Samples When Using Statistical Sampling Approaches to Characterize and Clear Contaminated Areas

This report discusses the methodology, formulas, and inputs needed to make characterization and clearance decisions for Bacillus anthracis-contaminated and uncontaminated (or decontaminated) areas using a statistical sampling approach. Specifically, the report includes the methods and formulas for calculating the • number of samples required to achieve a specified confidence in characterization and clearance decisions • confidence in making characterization and clearance decisions for a specified number of samples for two common statistically based environmental sampling approaches. In particular, the report addresses an issue raised by the Government Accountability Office by providing methods and formulas to calculate the confidence that a decision area is uncontaminated (or successfully decontaminated) if all samples collected according to a statistical sampling approach have negative results. Key to addressing this topic is the probability that an individual sample result is a false negative, which is commonly referred to as the false negative rate (FNR). The two statistical sampling approaches currently discussed in this report are 1) hotspot sampling to detect small isolated contaminated locations during the characterization phase, and 2) combined judgment and random (CJR) sampling during the clearance phase. Typically if contamination is widely distributed in a decision area, it will be detectable via judgment sampling during the characterization phrase. Hotspot sampling is appropriate for characterization situations where contamination is not widely distributed and may not be detected by judgment sampling. CJR sampling is appropriate during the clearance phase when it is desired to augment judgment samples with statistical (random) samples. The hotspot and CJR statistical sampling approaches are discussed in the report for four situations: 1. qualitative data (detect and non-detect) when the FNR = 0 or when using statistical sampling methods that account for FNR > 0 2. qualitative data when the FNR > 0 but statistical sampling methods are used that assume the FNR = 0 3. quantitative data (e.g., contaminant concentrations expressed as CFU/cm2) when the FNR = 0 or when using statistical sampling methods that account for FNR > 0 4. quantitative data when the FNR > 0 but statistical sampling methods are used that assume the FNR = 0. For Situation 2, the hotspot sampling approach provides for stating with Z% confidence that a hotspot of specified shape and size with detectable contamination will be found. Also for Situation 2, the CJR approach provides for stating with X% confidence that at least Y% of the decision area does not contain detectable contamination. Forms of these statements for the other three situations are discussed in Section 2.2. Statistical methods that account for FNR > 0 currently only exist for the hotspot sampling approach with qualitative data (or quantitative data converted to qualitative data). This report documents the current status of methods and formulas for the hotspot and CJR sampling approaches. Limitations of these methods are identified. Extensions of the methods that are applicable when FNR = 0 to account for FNR > 0, or to address other limitations, will be documented in future revisions of this report if future funding supports the development of such extensions. For quantitative data, this report also presents statistical methods and formulas for 1. quantifying the uncertainty in measured sample results 2. estimating the true surface concentration corresponding to a surface sample 3. quantifying the uncertainty of the estimate of the true surface concentration. All of the methods and formulas discussed in the report were applied to example situations to illustrate application of the methods and interpretation of the results

Scaling Relationships Based on Scaled Tank Mixing and Transfer Test Results

This report documents the statistical analyses performed (by Pacific Northwest National Laboratory for Washington River Protection Solutions) on data from 26 tests conducted using two scaled tanks (43 and 120 inches) in the Small Scale Mixing Demonstration platform. The 26 tests varied several test parameters, including mixer-jet nozzle velocity, base simulant, supernatant viscosity, and capture velocity. For each test, samples were taken pre-transfer and during five batch transfers. The samples were analyzed for the concentrations (lbs/gal slurry) of four primary components in the base simulants (gibbsite, stainless steel, sand, and ZrO2). The statistical analyses including modeling the component concentrations as functions of test parameters using stepwise regression with two different model forms. The resulting models were used in an equivalent performance approach to calculate values of scaling exponents (for a simple geometric scaling relationship) as functions of the parameters in the component concentration models. The resulting models and scaling exponents are displayed in tables and graphically. The sensitivities of component concentrations and scaling exponents to the test parameters are presented graphically. These results will serve as inputs to subsequent work by other researchers to develop scaling relationships that are applicable to full-scale tanks

Experimental Design for the INL Sample Collection Operational Test

This document describes the test events and numbers of samples comprising the experimental design that was developed for the contamination, decontamination, and sampling of a building at the Idaho National Laboratory (INL). This study is referred to as the INL Sample Collection Operational Test. Specific objectives were developed to guide the construction of the experimental design. The main objective is to assess the relative abilities of judgmental and probabilistic sampling strategies to detect contamination in individual rooms or on a whole floor of the INL building. A second objective is to assess the use of probabilistic and Bayesian (judgmental + probabilistic) sampling strategies to make clearance statements of the form “X% confidence that at least Y% of a room (or floor of the building) is not contaminated. The experimental design described in this report includes five test events. The test events (i) vary the floor of the building on which the contaminant will be released, (ii) provide for varying or adjusting the concentration of contaminant released to obtain the ideal concentration gradient across a floor of the building, and (iii) investigate overt as well as covert release of contaminants. The ideal contaminant gradient would have high concentrations of contaminant in rooms near the release point, with concentrations decreasing to zero in rooms at the opposite end of the building floor. For each of the five test events, the specified floor of the INL building will be contaminated with BG, a stand-in for Bacillus anthracis. The BG contaminant will be disseminated from a point-release device located in the room specified in the experimental design for each test event. Then judgmental and probabilistic samples will be collected according to the pre-specified sampling plan. Judgmental samples will be selected based on professional judgment and prior information. Probabilistic samples will be selected in sufficient numbers to provide desired confidence for detecting contamination or clearing uncontaminated (or decontaminated) areas. Following sample collection for a given test event, the INL building will be decontaminated using Cl2O gas. For possibly contaminated areas (individual rooms or the whole floor of a building), the numbers of probabilistic samples were chosen to provide 95% confidence of detecting contaminated areas of specified sizes. The numbers of judgmental samples were chosen based on guidance from experts in judgmental sampling. For rooms that may be uncontaminated following a contamination event, or for whole floors after decontamination, the numbers of judgmental and probabilistic samples were chosen using a Bayesian approach that provides for combining judgmental and probabilistic samples to make a clearance statement of the form “95% confidence that at least 99% of the room (or floor) is not contaminated”. The experimental design also provides for making 95%/Y% clearance statements using only probabilistic samples, where Y < 99. For each test event, the numbers of samples were selected for a minimal plan (containing fewer samples) and a preferred plan (containing more samples). The preferred plan is recommended over the minimal plan. The preferred plan specifies a total of 1452 samples, 912 after contamination and 540 after decontamination. The minimal plan specifies a total of 1119 samples, 744 after contamination and 375 after decontamination. If the advantages of the “after decontamination” portion of the preferred plan are judged to be small compared to the “after decontamination” portion of the minimal plan, it is an option to combine the “after contamination” portion of the preferred plan (912 samples) with the “after decontamination” portion of the minimal plan (375 samples). This hybrid plan would involve a total of 1287 samples

Database and Interim Glass Property Models for Hanford HLW Glasses

The purpose of this report is to provide a methodology for an increase in the efficiency and a decrease in the cost of vitrifying high-level waste (HLW) by optimizing HLW glass formulation. This methodology consists in collecting and generating a database of glass properties that determine HLW glass processability and acceptability and relating these properties to glass composition. The report explains how the property-composition models are developed, fitted to data, used for glass formulation optimization, and continuously updated in response to changes in HLW composition estimates and changes in glass processing technology. Further, the report reviews the glass property-composition literature data and presents their preliminary critical evaluation and screening. Finally the report provides interim property-composition models for melt viscosity, for liquidus temperature (with spinel and zircon primary crystalline phases), and for the product consistency test normalized releases of B, Na, and Li. Models were fitted to a subset of the screened database deemed most relevant for the current HLW composition region

Pulse Jet Mixing Tests With Noncohesive Solids

This report summarizes results from pulse jet mixing (PJM) tests with noncohesive solids in Newtonian liquid conducted during FY 2007 and 2008 to support the design of mixing systems for the Hanford Waste Treatment and Immobilization Plant (WTP). Tests were conducted at three geometric scales using noncohesive simulants. The test data were used to independently develop mixing models that can be used to predict full-scale WTP vessel performance and to rate current WTP mixing system designs against two specific performance requirements. One requirement is to ensure that all solids have been disturbed during the mixing action, which is important to release gas from the solids. The second requirement is to maintain a suspended solids concentration below 20 weight percent at the pump inlet. The models predict the height to which solids will be lifted by the PJM action, and the minimum velocity needed to ensure all solids have been lifted from the floor. From the cloud height estimate we can calculate the concentration of solids at the pump inlet. The velocity needed to lift the solids is slightly more demanding than "disturbing" the solids, and is used as a surrogate for this metric. We applied the models to assess WTP mixing vessel performance with respect to the two perform¬ance requirements. Each mixing vessel was evaluated against these two criteria for two defined waste conditions. One of the wastes was defined by design limits and one was derived from Hanford waste characterization reports. The assessment predicts that three vessel types will satisfy the design criteria for all conditions evaluated. Seven vessel types will not satisfy the performance criteria used for any of the conditions evaluated. The remaining three vessel types provide varying assessments when the different particle characteristics are evaluated. The assessment predicts that three vessel types will satisfy the design criteria for all conditions evaluated. Seven vessel types will not satisfy the performance criteria used for any of the conditions evaluated. The remaining three vessel types provide varying assessments when the different particle characteristics are evaluated. The HLP-022 vessel was also evaluated using 12 m/s pulse jet velocity with 6-in. nozzles, and this design also did not satisfy the criteria for all of the conditions evaluated

Summary of Previous Chamber or Controlled Anthrax Studies and Recommendations for Possible Additional Studies

This report and an associated Excel file(a) summarizes the investigations and results of previous chamber and controlled studies(b) to characterize the performance of methods for collecting, storing and/or transporting, extracting, and analyzing samples from surfaces contaminated by Bacillus anthracis (BA) or related simulants. This report and the Excel are the joint work of the Pacific Northwest National Laboratory (PNNL) and the National Institute of Standards and Technology (NIST) for the Department of Homeland Security, Science and Technology Directorate. The report was originally released as PNNL-SA-69338, Rev. 0 in November 2009 with limited distribution, but was subsequently cleared for release with unlimited distribution in this Rev. 1. Only minor changes were made to Rev. 0 to yield Rev. 1. A more substantial update (including summarizing data from other studies and more condensed summary tables of data) is underwa

Assessment of the Group 5-6 (LB C2, LB S2, LV S1) Stack Sampling Probe Locations for Compliance with ANSI/HPS N13.1 1999

This document reports on a series of tests to assess the proposed air sampling locations for the Hanford Tank Waste Treatment and Immobilization Plant (WTP) Group 5-6 exhaust stacks with respect to the applicable criteria regarding the placement of an air sampling probe. The LB-C2, LV-S1, and LB S2 exhaust stacks were tested together as a group (Test Group 5-6) because the common factor in their design is that the last significant flow disturbance upstream of the air sampling probe is a reduction in duct diameter. Federal regulations( ) require that a sampling probe be located in the exhaust stack according to the criteria of the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-1999, Sampling and Monitoring Releases of Airborne Radioactive Substances from the Stack and Ducts of Nuclear Facilities. These criteria address the capability of the sampling probe to extract a sample that represents the effluent stream. The testing on scale models of the stacks conducted for this project was part of the River Protection Project—Waste Treatment Plant Support Program under Contract No. DE-AC05-76RL01830 according to the statement of work issued by Bechtel National Inc. (BNI, 24590-QL-SRA-W000-00101, N13.1-1999 Stack Monitor Scale Model Testing and Qualification, Revision 1, 9/12/2007) and Work Authorization 09 of Memorandum of Agreement 24590-QL-HC9-WA49-00001. The internal Pacific Northwest National Laboratory (PNNL) project for this task is 53024, Work for Hanford Contractors Stack Monitoring. The testing described in this document was further guided by the Test Plan Scale Model Testing the Waste Treatment Plant LB-C2, LB-S2, and LV-S1 (Test Group 5-6) Stack Air Sampling Positions (TP-RPP-WTP-594). The tests conducted by PNNL during 2009 and 2010 on the Group 5-6 scale model systems are described in this report. The series of tests consists of various measurements taken over a grid of points in the duct cross-section at the designed sampling probe locations and at five duct diameters up and downstream from the design location to accommodate potential construction variability. The tests were done only at the design sampling probe location on the scale model of LB-S2 because that ductwork was already constructed. The ANSI/HPS N13.1-1999 criteria and the corresponding results of the test series on the scale models are summarized in this report