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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Influence of sampling frequency and estimation method on phosphorus load uncertainty in the Western Lake Erie Basin, Ohio, USA

Accurate estimates of nutrient loads are necessary to identify critical source areas and quantify the impact of management practices on pollutant export. Previous studies have investigated nutrient load estimate uncertainty, but they often focus on nutrient loads estimated using an interpolation method for large-scale watersheds with short-term datasets. The study objective was to quantify uncertainty in soluble reactive phosphorus (SRP), total phosphorus (TP), and suspended solids (SS) load estimates from two small (<10 3 km 2 ) agricultural watersheds in the western Lake Erie Basin resulting from different sampling frequencies. Each watershed had high temporal resolution datasets of discharge (15 min) and nutrient concentration (1 to 3 samples per day) collected over a 30-year period (1990–2020). Firstly, SRP, TP, and SS loads were calculated using the high temporal resolution datasets, which was assumed as “true loads”. Secondly, the high temporal concentration data were decomposed to semiweekly, weekly, biweekly, and monthly sampling and annual loads were estimated using four common load estimation methods to assess the effect of sampling frequency and load estimation method on load estimate error. Across the four different methods, the composite method had the lowest relative root mean square and absolute bias, but the rectangular interpolation method was the most precise. Furthermore, even with semiweekly sampling, the composite method resulted in an unacceptable level of precision (average imprecision = 39 %), while the interpolation method resulted in an unacceptable bias (average absolute bias = 16 %). Because neither method could provide acceptable accuracy and precision at the lowest decrease in sampling (e.t. semiweekly sampling), continued daily sampling is recommended in these watersheds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Automated “Cells-To-Peptides” Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes

Mass spectrometry-based quantitative proteomic analysis has proven valuable for clinical and biotechnology-related research and development. Improvements in sensitivity, resolution, and robustness of mass analyzers have also added value. However, manual sample preparation protocols are often a bottleneck for sample throughput and can lead to poor reproducibility, especially for applications where thousands of samples per month must be analyzed. To alleviate these issues, we developed a “cells-to-peptides” automated workflow for Gram-negative bacteria and fungi that includes cell lysis, protein precipitation, resuspension, quantification, normalization, and tryptic digestion. The workflow takes 2 h to process 96 samples from cell pellets to the initiation of the tryptic digestion step and can process 384 samples in parallel. We measured the efficiency of protein extraction from various amounts of cell biomass and optimized the process for standard liquid chromatography–mass spectrometry systems. The automated workflow was tested by preparing 96 Escherichia coli samples and quantifying over 600 peptides that resulted in a median coefficient of variation of 15.8%. Similar technical variance was observed for three other organisms as measured by highly multiplexed LC-MRM–MS acquisition methods. These results show that this automated sample preparation workflow provides robust, reproducible proteomic samples for high-throughput applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Sample registration software for process automation in the Neutron Activation Analysis (NAA) Facility in Malaysia nuclear agency

Neutron Activation Analysis (NAA) had been established in Nuclear Malaysia since 1980s. Most of the procedures established were done manually including sample registration. The samples were recorded manually in a logbook and given ID number. Then all samples, standards, SRM and blank were recorded on the irradiation vial and several forms prior to irradiation. These manual procedures carried out by the NAA laboratory personnel were time consuming and not efficient. Sample registration software is developed as part of IAEA/CRP project on ‘Development of Process Automation in the Neutron Activation Analysis (NAA) Facility in Malaysia Nuclear Agency (RC17399)’. The objective of the project is to create a pc-based data entry software during sample preparation stage. This is an effective method to replace redundant manual data entries that needs to be completed by laboratory personnel. The software developed will automatically generate sample code for each sample in one batch, create printable registration forms for administration purpose, and store selected parameters that will be passed to sample analysis program. The software is developed by using National Instruments Labview 8.6.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Note: Design and development of wireless controlled aerosol sampling network for large scale aerosol dispersion experiments

Wireless based custom built aerosol sampling network is designed, developed, and implemented for environmental aerosol sampling. These aerosol sampling systems are used in field measurement campaign, in which sodium aerosol dispersion experiments have been conducted as a part of environmental impact studies related to sodium cooled fast reactor. The sampling network contains 40 aerosol sampling units and each contains custom built sampling head and the wireless control networking designed with Programmable System on Chip (PSoC™) and Xbee Pro RF modules. The base station control is designed using graphical programming language LabView. The sampling network is programmed to operate in a preset time and the running status of the samplers in the network is visualized from the base station. The system is developed in such a way that it can be used for any other environment sampling system deployed in wide area and uneven terrain where manual operation is difficult due to the requirement of simultaneous operation and status logging.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

A multi-probe thermophoretic soot sampling system for high-pressure diffusion flames

Optical diagnostics and physical probing of the soot processes in high pressure combustion pose challenges that are not faced in atmospheric flames. One of the preferred methods of studying soot in atmospheric flames is in situ thermophoretic sampling followed by transmission electron microscopy imaging and analysis for soot sizing and morphology. The application of this method of sampling to high pressures has been held back by various operational and mechanical problems. In this work, we describe a rotating disk multi-probe thermophoretic soot sampling system, driven by a microstepping stepper motor, fitted into a high-pressure chamber capable of producing sooting laminar diffusion flames up to 100 atm. Innovative aspects of the sampling system design include an easy and precise control of the sampling time down to 2.6 ms, avoidance of the drawbacks of the pneumatic drivers used in conventional thermophoretic sampling systems, and the capability to collect ten consecutive samples in a single experimental run. Proof of principle experiments were performed using this system in a laminar diffusion flame of methane, and primary soot diameter distributions at various pressures up to 10 atm were determined. High-speed images of the flame during thermophoretic sampling were recorded to assess the influence of probe intrusion on the flow field of the flame.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Adjoint Klein-Nishina Sampling Methods: Efficiency, Speed and Applications

Three new rejection sampling methods for generating samples from the adjoint Klein-Nishina cross section are discussed: the two-branch rejection sampling procedure, the three-branch linear rejection sampling procedure and the three-branch inverse rejection sampling procedure. These methods have all been implemented in the Framework for REsearch in Nuclear ScIence and Engineering (FRENSIE). The efficiency and sample generation rate of each of these methods are evaluated to characterize the methods and to make recommendations regarding their use. The use of these methods in realistic transport simulations is also evaluated by incorporating a scattering function into the sampling process. Furthermore, the results of an infinite medium problem are presented to verify that the sampling procedure can be used in an adjoint Monte Carlo simulation to generate results that are in agreement with an equivalent forward simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Improving the sampling efficiency of the Grand Canonical Simulated Quenching approach

Most common atomistic simulation techniques, like molecular dynamics or Metropolis Monte Carlo, operate under a constant interatomic Hamiltonian with a fixed number of atoms. Internal (atom positions or velocities) or external (simulation cell size or geometry) variables are then evolved dynamically or stochastically to yield sampling in different ensembles, such as microcanonical (NVE), canonical (NVT), isothermal-isobaric (NPT), etc. Averages are then taken to compute relevant physical properties. At least two limitations of these standard approaches can seriously hamper their application to many important systems: (1) they do not allow for the exchange of particles with a reservoir, and (2) the sampling efficiency is insufficient to allow the obtention of converged results because of the very long intrinsic timescales associated with these quantities. To fix ideas, one might want to identify low (free) energy configurations of grain boundaries (GB). In reality, grain boundaries are in contact the grains which act as reservoirs of defects (e.g., vacancies and interstitials). Since the GB can exchange particles with its environment, the most stable configuration cannot provably be found by sampling from NVE or NVT ensembles alone: one needs to allow the number of atoms in the sample to fluctuate. The first limitation can be circumvented by working in the grand canonical ensemble (TV ) or its derivatives (such as the semi-grand-canonical ensemble useful for the study of substitutional alloys). Monte Carlo methods have been the first to adapt to this kind of system where the number of atoms is allowed to fluctuate. Many of these methods are based on the Widom insertion method [Widom63] where the chemical potential of a given chemical species can be inferred from the potential energy changes upon random insertion of a new particle within the simulation cell. Other techniques, such as the Gibbs ensemble Monte Carlo [Panagiotopoulos87] where exchanges of particles are attempted to equilibrate the chemical potential between two cells and hence allow for the calculation of coexistence curves, exploit the same idea: particle insertion (or exchange) is attempted and accepted with a Metropolis-like rule that depends exponentially on the energy change upon insertion. A well known limitation of this kind of approach is that the probability of accepting such a move decreases extremely rapidly with increasing density, due to the extremely large short-range repulsion between atoms. In response to these difficulties it became apparent that a solution to the problem might be to avoid abrupt insertions but instead to proceed gradually, so as to allow the system to react and make way for the incoming particle. In this view of things, the 'occupation' of a certain atomic site can be viewed as a continuous variable, ranging between 0 and 1, representing 'how much' of the particle is present at any given time. These ideas proved ideal in Molecular Dynamics (MD) settings because equations of motions for these occupation variables can sometimes be obtained. For example, in the case of Grand Canonical Molecular Dynamics [Cagin91], one special particle is allowed to have a fractional occupation. This can lead to either its destruction (occupation = 0) or its complex creation (occupation = 1) so as to enforce a given chemical potential. These approaches proved useful, but mostly in the liquid state where the probability of successfully inserting a new particle is sufficiently high. At higher densities, convergence proved to be hampered by very inefficient sampling. In this work, we explore the use of a related MD-based grand canonical technique, the Grand Canonical Simulated Quenching (GCSQ) of Phillpot and Rickman [Phillpot92,Phillpot94], and explore its application to the grand canonical sampling of solid state systems. We show that, in conjunction with advanced sampling techniques, GCSQ can be a useful tool to sample conformations of complex systems, such as GBs, and assist in the identification of their most stable states and/or most likely defective states.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Nevada National Security Site Integrated Groundwater Sampling Plan, Revision 0

The purpose of the Nevada National Security Site (NNSS) Integrated Sampling Plan (referred to herein as the Plan) is to provide a comprehensive, integrated approach for collecting and analyzing groundwater samples to meet the needs and objectives of the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office (NNSA/NFO) Underground Test Area (UGTA) Activity. Implementation of this Plan will provide high-quality data required by the UGTA Activity for ensuring public protection in an efficient and cost-effective manner. The Plan is designed to ensure compliance with the UGTA Quality Assurance Plan (QAP). The Plan’s scope comprises sample collection and analysis requirements relevant to assessing the extent of groundwater contamination from underground nuclear testing. This Plan identifies locations to be sampled by corrective action unit (CAU) and location type, sampling frequencies, sample collection methodologies, and the constituents to be analyzed. In addition, the Plan defines data collection criteria such as well-purging requirements, detection levels, and accuracy requirements; identifies reporting and data management requirements; and provides a process to ensure coordination between NNSS groundwater sampling programs for sampling of interest to UGTA. This Plan does not address compliance with requirements for wells that supply the NNSS public water system or wells involved in a permitted activity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Data Validation Package, June 2016 Groundwater Sampling at the Hallam, Nebraska, Decommissioned Reactor Site, August 2016

The 2008 Long-Term Surveillance Plan [LTSP] for the Decommissioned Hallam Nuclear Power Facility, Hallam, Nebraska (http://www.lm.doe.gov/Hallam/Documents.aspx) requires groundwater monitoring once every 2 years. Seventeen monitoring wells at the Hallam site were sampled during this event as specified in the plan. Planned monitoring locations are shown in Attachment 1, Sampling and Analysis Work Order. Water levels were measured at all sampled wells and at two additional wells (6A and 6B) prior to the start of sampling. Additionally, water levels of each sampled well were measured at the beginning of sampling. See Attachment 2, Trip Report, for additional details. Sampling and analysis were conducted as specified in Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated, http://energy.gov/lm/downloads/sampling-and-analysis-plan-us-department- energy-office-legacy-management-sites). Gross alpha and gross beta are the only parameters that were detected at statistically significant concentrations. Time/concentration graphs of the gross alpha and gross beta data are included in Attachment 3, Data Presentation. The gross alpha and gross beta activity concentrations observed are consistent with values previously observed and are attributed to naturally occurring radionuclides (e.g., uranium and uranium decay chain products) in the groundwater.

2016 Groundwater Sampling↗
DOE OSTI2016

Data Validation Package - April and July 2015 Groundwater and Surface Water Sampling at the Gunnison, Colorado, Processing Site

This event included annual sampling of groundwater and surface water locations at the Gunnison, Colorado, Processing Site. Sampling and analyses were conducted as specified in Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites. Samples were collected from 28 monitoring wells, three domestic wells, and six surface locations in April at the processing site as specified in the 2010 Ground Water Compliance Action Plan for the Gunnison, Colorado, Processing Site. Domestic wells 0476 and 0477 were sampled in July because the homes were unoccupied in April, and the wells were not in use. Duplicate samples were collected from locations 0113, 0248, and 0477. One equipment blank was collected during this sampling event. Water levels were measured at all monitoring wells that were sampled. No issues were identified during the data validation process that requires additional action or follow-up.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Data Validation Package May 2016 Groundwater Sampling at the Lakeview, Oregon, Processing Site August 2016

This biennial event includes sampling five groundwater locations (four monitoring wells and one domestic well) at the Lakeview, Oregon, Processing Site. For this event, the domestic well (location 0543) could not be sampled because no one was in residence during the sampling event (Note: notification was provided to the resident prior to the event). Per Appendix A of the Groundwater Compliance Action Plan, sampling is conducted to monitor groundwater quality on a voluntary basis. Sampling and analyses were conducted as specified in the Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated). One duplicate sample was collected from location 0505. Water levels were measured at each sampled monitoring well. The constituents monitored at the Lakeview site are manganese and sulfate. Monitoring locations that exceeded the U.S. Environmental Protection Agency (EPA) Secondary Maximum Contaminant Levels for these constituents are listed in Table 1. Review of time-concentration graphs included in this report indicate that manganese and sulfate concentrations are consistent with historical measurements.

2016 Groundwater Sampling Lakeview, Oregon↗
DOE OSTI2016

Data Validation Package December 2015 Groundwater Sampling at the Ambrosia Lake, New Mexico, Disposal Site March 2016

The Long-Term Surveillance Plan for the Ambrosia Lake, New Mexico, Disposal Site does not require groundwater monitoring because groundwater in the uppermost aquifer is of limited use, and supplemental standards have been applied to the aquifer. However, at the request of the New Mexico Environment Department, the U.S. Department of Energy conducts annual monitoring at three locations: monitoring wells 0409, 0675, and 0678. Sampling and analyses were conducted as specified in the Sampling and Analysis Plan for US. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated). Monitoring Well 0409 was not sampled during this event because it was dry. Water levels were measured at each sampled well. One duplicate sample was collected from location 0675. Groundwater samples from the two sampled wells were analyzed for the constituents listed in Table 1. Time-concentration graphs for selected analytes are included in this report. At well 0675, the duplicate results for total dissolved solids and for most metals (magnesium, molybdenum, potassium, selenium, sodium, and uranium) were outside acceptance criteria, which may indicate non-homogeneous conditions at this location. November 2014 results for molybdenum and uranium at well 0675 also were outside acceptance criteria. The well condition will be evaluated prior to the next sampling event.

2015 Sampling Ambrosia Lake West, New Mexico↗
DOE OSTI2017

Graph Sampling for Visual Analytics

Effectively visualizing large graphs and capturing the statistical properties are two challenging tasks. To aid in these two tasks, many sampling approaches for graph simplification have been proposed, falling into three categories: node sampling, edge sampling, and traversal-based sampling. It is still unknown which approach is the best. We evaluate commonly used graph sampling methods through a combined visual and statistical comparison of graphs sampled at various rates. We conduct our evaluation on three graph models: random graphs, small-world graphs, and scale-free graphs. Initial results indicate that the effectiveness of a sampling method is dependent on the graph model, the size of the graph, and the desired statistical property. This benchmark study can be used as a guideline in choosing the appropriate method for a particular graph sampling task, and the results presented can be incorporated into graph visualization and analysis tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Microfluidic-Based Robotic Sampling System for Radioactive Solutions

A novel microfluidic based robotic sampling system has been developed for sampling and analysis of liquid solutions in nuclear processes. This system couples the use of a microfluidic sample chip with a robotic system designed to allow remote, automated sampling of process solutions in-cell and facilitates direct coupling of the microfluidic sample chip with analytical instrumentation. This system provides the capability for near real time analysis, reduces analytical waste, and minimizes the potential for personnel exposure associated with traditional sampling methods. A prototype sampling system was designed, built and tested. System testing demonstrated operability of the microfluidic based sample system and identified system modifications to optimize performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Towards a Robust Sampling Approach: A Computational Review and Design

As pointed out in several other works, the estimation of the reliability of the electrical grid can not be conducted without the estimation of the stochastic phenomena of electicity demand and electricity production by variable renewable sources. Therefore, sampling procedures have become integral in the design of engineering structures and analysis. Commonly referred to as Monte Carlo uncertainty analysis or integration, the general objective of these procedures is to establish specifics about the uncertainty of an output characteristic of such an engineering system, given uncertainty about its input characteristics. These sampling procedures are applied in a context in which establishing such specifics cannot be performed through other means. Variance-reduction techniques are designed to lessen the variability among estimators to estimate statistics of those output uncertainties. Importance-sampling techniques, on the other hand, are designed to reduce the number of samples needed to estimate a particular statistic—e.g., a tail probability. The combination of these approaches can reduce the computational burden considerably for a particular estimator and statistic. Importance sampling—geared and designed as it is toward improving a particular estimator—suffers, unfortunately, from the unintended consequence of reducing the performance of other estimators in terms of their variance. The objective of this paper is to offer an alternative sampling procedure where this variance does not grow unacceptably large for a suite of estimators. Moreover, it is anticipated that, with additional knowledge of how an engineering output characteristic responds to its input characteristics, tuning parameters of the input’s sampling procedure can be set to improve the output characteristic’s estimation. This work proves the effectiveness of the suggested alternative approach. Such positive outcome will lead to a decrease of the computational burden of performing stochastic optimization of integrated energy systems (e.g., components dispatch, and portfolio composition). In particular, capturing the contribution to the overall system cost of rare and unlikely events and patterns of the electricity demand and production will become less computationally expensive. This is due to the fact that the approach demonstrated here will allow the sampling of those rare occurrences more frequently without misrepresenting their probabilistic impacts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Expediting Groundwater Sampling at Hanford and Making It Safer - 13158

The CH2M HILL Plateau Remediation Company (CHPRC) manages the groundwater monitoring programs at the Department of Energy's 586-square-mile Hanford site in southeastern Washington state. These programs are regulated by the Resource Conservation and Recovery Act (RCRA), the Comprehensive Environmental Response Compensation and Liability Act (CERCLA), and the Atomic Energy Act (AEA). The purpose of monitoring is to track existing groundwater contamination from past practices, as well as other potential contamination that might originate from RCRA treatment, storage, and disposal (TSD) facilities. An integral part of the groundwater-monitoring program involves taking samples of the groundwater and measuring the water levels in wells scattered across the site. Each year, more than 1,500 wells are accessed for a variety of reasons. Historically, the monitoring activities have been very 'people intensive'. Field personnel or 'samplers' have been issued pre-printed forms showing information about the well(s) for a particular sampling evolution. This information is taken from two official electronic databases: the Hanford Well Information System (HWIS) and the Hanford Environmental Information System (HEIS). The samplers traditionally used these hardcopy forms to document the groundwater samples and well water-levels. After recording the entries in the field, the samplers turned the forms in at the end of the day and other personnel posted the collected information. In Automating Groundwater Sampling at Hanford (HNF-38542-FP Revision 0, Presented at Waste Management 2009 Conference, March 1 - March 5, 2009, Phoenix, AZ), we described the methods, tools, and techniques that would be used in automating the activities associated with measuring water levels. The Field Logging and Electronic Data Gathering (FLEDG) application/database that automates collecting the water-level measurement data has now been implemented at Hanford. In addition to eliminating the need to print out documents, the system saves three-to-four man days each month for the field personnel taking the measurements and the scientists and administrators managing the data and the documentation. After the information has received technical review, FLEDG automatically updates the database for water-level measurements and loads the document management system with the completed sampling report. Due to safety considerations, access to wells is conditional. A spreadsheet with appropriate data not only lists the wells that are cleared for work, but also the safety personnel who must be present before work can start. This spreadsheet is used in planning daily activities. Daily plans are structured to ensure that the wells to be sampled are cleared for work and the appropriate safety personnel have been assigned and are present before the work starts. Historically, the spreadsheets have been prepared manually, and as a result, are potentially subject to human error. However, a companion database application has been developed to work with FLEDG - making the entire sampling process more efficient and safer for personnel. The Well Access List - Electronic, WAL-E, is a database that contains much the same information that was previously manually loaded into the spread sheet. In addition, WAL-E contains a managed work-flow application that shows the access requirements and allows for appropriate reviews of the compiled well. Various CHPRC organizations, including Industrial Hygiene, RADCON, and Well Maintenance and Sample Administration are able to enter and review the wells added or deleted from the WAL-E database. The FLEDG system then accesses this database information to identify appropriate support personnel and provide safety requirements to field personnel. In addition, WAL-E offers the assurance that wells have appropriate locks and are correctly labeled and electrically grounded as required, before well activities begin. This feature is an extremely important aspect of the FLEDG/WAL-E system because it adds another safety check to the work evolution and reduces the potential for unsafe conditions to exist that would lead to a stop-work situation. This paper will further describe the technical aspects of both electronic programs/databases and their successful application at Hanford. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Small Scale Mixing Demonstration Batch Transfer and Sampling Performance of Simulated HLW - 12307

The ability to effectively mix, sample, certify, and deliver consistent batches of High Level Waste (HLW) feed from the Hanford Double Shell Tanks (DST) to the Waste treatment Plant (WTP) has been recognized as a significant mission risk with potential to impact mission length and the quantity of HLW glass produced. At the end of 2009 DOE's Tank Operations Contractor, Washington River Protection Solutions (WRPS), awarded a contract to EnergySolutions to design, fabricate and operate a demonstration platform called the Small Scale Mixing Demonstration (SSMD) to establish pre-transfer sampling capacity, and batch transfer performance data at two different scales. This data will be used to examine the baseline capacity for a tank mixed via rotational jet mixers to transfer consistent or bounding batches, and provide scale up information to predict full scale operational performance. This information will then in turn be used to define the baseline capacity of such a system to transfer and sample batches sent to WTP. The Small Scale Mixing Demonstration (SSMD) platform consists of 43'' and 120'' diameter clear acrylic test vessels, each equipped with two scaled jet mixer pump assemblies, and all supporting vessels, controls, services, and simulant make up facilities. All tank internals have been modeled including the air lift circulators (ALCs), the steam heating coil, and the radius between the wall and floor. The test vessels are set up to simulate the transfer of HLW out of a mixed tank, and collect a pre-transfer sample in a manner similar to the proposed baseline configuration. The collected material is submitted to an NQA-1 laboratory for chemical analysis. Previous work has been done to assess tank mixing performance at both scales. This work involved a combination of unique instruments to understand the three dimensional distribution of solids using a combination of Coriolis meter measurements, in situ chord length distribution measurements, and electro-resistive tomography. This current work utilized the same instruments to monitor simulated waste transfers. This paper will discuss some of the scaling compromises when it came to the scaled sampling system design, handling of large quantities of material for sampling, and present data for the discuss of likely behavior of the full scale DST based on scaling correlations using a scale ratio exponent (SRE) from 0.25 to 0.45 and the behavior observed in the SSMD platform. This does not establish a scaling factor for DST mixing using paired jet mixers but is an attempt to envelope the likely performance ranges in terms of certification sampling bias, certification sample root-mean-square-deviation, and bath to batch relative standard deviation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Delayed-Gamma Energy Biasing with Exact Energy Sampling in MCNP 6.2.0

Characterization of delayed-particle signatures is of the utmost importance for detecting, identifying, and quantifying special nuclear material (SNM). Various non-destructive assay (NDA) techniques used in nuclear material safeguards rely on characteristic gamma-ray or neutron emissions to infer properties of a material. The all-particle, all-energy Monte-Carlo radiation transport code MCNP6 is capable of simulating delayed-particle signatures from SNM in addition to modeling the transport of emitted particles to a detector or other instrument. In some cases, NDA techniques require the measurement of low probability emissions from a given material. In physical scenarios, this problem can be bypassed by longer count-times or may be simply irrelevant due to the mass, and therefore the total activity, of the material being measured. However, when applying the Monte-Carlo method to such scenarios, sampling of low probability emissions requires a large number of histories to converge to a statistically acceptable solution. To address this issue, the delayed-neutron and gamma energy biasing feature was introduced in MCNP6 by H. Armstrong et al. in 2013 which allows the user to set up energy windows in which delayed-particle emission sampling can be adjusted. For delayed-gamma sampling, this biasing method was based on the bin-wise structure of gamma emission data for both the multi-bin gamma and line-emission sampling modes. Recent improvements have been made to the line-emission sampling algorithm which upgrade the previous mini-bin sampling treatment to an exact energy-line treatment. This upgrade was not compatible with the biasing method implemented by H. Armstrong et al. due to the sampled data no longer having a bin-wise structure in line-emission mode. For this reason the delayed-gamma energy biasing feature has been rewritten to support the exact line-sampling treatment. This paper provides a description of the delayed-gamma energy biasing (DGEB) feature in MCNP6 as well as results and discussion for a gamma-ray spectroscopy example used to demonstrate the biasing utility. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗