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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Robust verification analysis

We introduce a new methodology for inferring the accuracy of computational simulations through the practice of solution verification. We demonstrate this methodology on examples from computational heat transfer, fluid dynamics and radiation transport. Our methodology is suited to both well- and ill-behaved sequences of simulations. Our approach to the analysis of these sequences of simulations incorporates expert judgment into the process directly via a flexible optimization framework, and the application of robust statistics. The expert judgment is systematically applied as constraints to the analysis, and together with the robust statistics guards against over-emphasis on anomalous analysis results. We have named our methodology Robust Verification. Our methodology is based on utilizing multiple constrained optimization problems to solve the verification model in a manner that varies the analysis' underlying assumptions. Constraints applied in the analysis can include expert judgment regarding convergence rates (bounds and expectations) as well as bounding values for physical quantities (e.g., positivity of energy or density). This approach then produces a number of error models, which are then analyzed through robust statistical techniques (median instead of mean statistics). This provides self-contained, data and expert informed error estimation including uncertainties for both the solution itself and order of convergence. Our method produces high quality results for the well-behaved cases relatively consistent with existing practice. The methodology can also produce reliable results for ill-behaved circumstances predicated on appropriate expert judgment. We demonstrate the method and compare the results with standard approaches used for both code and solution verification on well-behaved and ill-behaved simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Technical Issues in the Comprehensive Nuclear Test Ban Treaty (CTBT) Ratification Debate: A 20 Year Retrospective

Two decades after the U.S. Senate declined in 1999 to give its consent to ratification of the Comprehensive Nuclear Test Ban Treaty (CTBT), the treaty remains in legal and political limbo. Legally, the treaty cannot enter into force without U.S. ratification. However, the Senate’s rejection does not strip the treaty of its force as an element of customary international law or alter the will of other signatories to see it enter into force. Politically, the debate over the virtues and flaws of the treaty remains as strong as ever, with some CTBT advocates pushing energetically for U.S. re-review while some opponents seek ways to “un-sign” the treaty. Meanwhile, despite the Senate’s rejection of the treaty, the United States acts in a manner consistent with its main obligations by maintaining a moratorium on explosive nuclear testing and providing financial support (as well as technical expertise) to the CTBT Organization (CTBTO)—in particular the CTBTO’s International Monitoring System (IMS). The CTBT may well remain in such limbo for a long time to come, unless some catalytic event comes along to re-shape national perceptions and priorities, one way or the other. The treaty’s future, whatever it might be, will be determined in part by how much perspectives might have changed in light of interim developments. Our purpose is to shed light on some of those developments and to assess their relevance. The 1999 ratification debate addressed a large number of issues. Rejection was driven by various policy and technical judgments. The purpose of this paper is to re-examine those technical judgments in light of what has been learned over the following two decades. On some technical matters, there was explicit recognition of extant uncertainties, as well as a conviction and hope that time would dispel them. To be doubly clear, our purpose is not to recommend a way forward on CTBT ratification. The policy judgments of 1999 and 2020 are beyond the scope of this paper. This technical re-examination proceeds as follows. It begins with a short background section to introduce the key technical matters in discussion in the U.S. ratification process. Then it moves systematically through each of those topics with a review of relevant background information, a discussion of key points in debate, an analysis of subsequent experience, and a current assessment. The historical analysis draws on many sources including the primary documents of the Congressional debate, the official article-by-article interpretation by the Department of State, and the statements of key players in the process. We also relied on key technical reports and publications by subject matter experts that have addressed in more detail many of the issues in our focus. These sources include the 2002 and 2012 reports of the National Academy of Sciences as well as publications by senior technical staff of Lawrence Livermore National Laboratory (LLNL) who were actively involved in the ratification debate, including then-Laboratory Director Bruce Tarter. We also conducted several interviews with government officials from the 1990s, past laboratory directors, and other members of the scientific community. But, except where individuals are specifically cited by name, the judgments offered here are our own and should not be attributed to any other individual or to LLNL as such.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2018

Dose–volume histogram evaluation scheme for beam orientations in intensity-modulated radiation therapy

Beam orientations in intensity-modulated radiation therapy (IMRT) is an important, but difficult NP-hard optimization problem. A considerable part of this difficulty is due to the essential prerequisite of defining, appropriately, counter-intuitive criteria for a mathematical plan evaluation that coincides with the clinical judgment of the considered plan. Moreover, the quality of beam directions depends heavily on their intensities. Usually a stochastic selector is utilized for optimizing beam orientations, and the intensities are thus calculated many thousands of times, each time for a different selection of beam directions, resulting in excessive time complexity. Therefore, selecting an appropriate set of beam directions in IMRT is still a time-consuming manual trial-and-error search procedure that depends on intuition and empirical knowledge. To overcome these difficulties, this work utilizes the concept of dose–volume histogram (DVH), which is one of the main recognized quantitative measurement tools used for plan judgment, and presents a DVH evaluation scheme that parallelizes plan evaluation with clinical plan judgment. This scheme is then utilized to optimize the intensities of each individual beam, enabling it to be represented by its DVHs, produced for the different irradiated volumes. Finally, an evolutionary algorithm is employed to search for the best combination of those DVHs reflecting the clinical optimal. The presented methods have been applied to three real clinical examples. In comparison to the standard equally spaced beam plans, improvements were reported in all three cases. In comparison with the greedy algorithm, improvements were reported in those examples requiring more than five beam directions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Key Constructs for Reasonable Confidence in System Validation Programs

This paper presents four key constructs developed in preparing IEEE Std P2411TM, Human Factors Engineering Guide for the Validation of System Designs and Integrated Systems Operations at Nuclear Facilities for submission. These constructs reflect judgments that responsible parties make in order to bring validation to closure. Such judgments weigh competing concerns and cost-benefits for stakeholders. Improved processes and methods may support such judgments but cannot alone eliminate uncertainty. Stating and clarifying these constructs aims to reduce uncertainty in the validation process, to better prepare the implementers and reviewers of future validation programs, both in the nuclear industry and beyond. Reasonable Confidence – A proof standard, as used to reach conclusions in a legal case. Legal proof standards are bounded between “preponderance of evidence” and “beyond reasonable doubt”. Reasonable confidence is comparable to an intermediate legal proof standard of “clear and convincing evidence.” Representative Test Set – A collection of scenarios of sufficient variety to represent the anticipated range of operational conditions, events, evolutions, and activities for validating the system(s) under test. Dispositive vs. Diagnostic Criteria – Relevant performance criteria are placed in one of two categories. Dispositive criteria are assessed, without exception, to determine whether a validation test passes or fails overall. Diagnostic criteria are assessed, subject to justified exception, to evaluate the quality or degree of some particular aspect of performance. Repeatability – Consistency in achieving passing results is to be demonstrated for each scenario in the representative test set; thus, the minimum number of formal repetitions for each scenario is two.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Generation of Low Fidelity Experimental Covariance Matrices for ICSBEP Cases

In validation, statistical methods routinely incorporate information from integral experiments to improve estimations of code biases and uncertainties. One source of high quality integral experiments is the ICSBEP Handbook. While uncertainties for criticality benchmarks are well characterized in the Handbook, information pertaining to the shared uncertainty/covariance between the cases is sparse, yet required for the aforementioned methods; correlations can result from using the same fuel for example. To remedy the lack of available covariance data in the Handbook, recent efforts have been undertaken, notably, within the framework of the NEA Expert Group on Uncertainty Analysis in Criticality Safety Assessment (UACSA) under the Working Party on Nuclear Criticality Safety (WPNCS) . The UACSA activities have focused primarily on comparing methods used to generate high quality covariance matrices for a small number of evaluations. Despite these efforts, within the Database for ICSBEP DICE only about 2% of the nearly 5000 experiments in the ICSBEP Handbook have correlation coefficients, so the amount of work required to generate the missing data appears daunting. And so, to fill in the gaps where no correlations are available, it is proposed to generate low fidelity correlations by isolating the largest components of uncertainty and determining the fraction shared between cases within an evaluation. Uncertainties can be shared when they are not independently measured, or the source of uncertainty is unchanged between cases. The degree to which an uncertainty is shared is linked to the experimental procedure; an approximation is made that in the absence of additional information, similar experimental procedures will lead to a similar fraction of shared uncertainty. Between experimental procedures there is some commonality. One method, proposed here, to help elucidate similar procedures is to encode each procedure into a decision tree grouped by uncertainty type. End nodes of the tree require judgment to assign the fraction of shared uncertainty between cases associated with the node. This can also be thought of as a set of rules, such that if experimental procedures and conditions occurred, then assign the shared uncertainty as some number between 0.0 and 1.0. One advantage of such a procedure is the formation of a transparent logical link between the judgment applied and the amount of shared uncertainty. This makes the results both more reproducible and easy to update. Generating correlation coefficients is reduced to developing decision trees that categorize how the experiments were done, and apply judgment of the degree of shared uncertainty for the end node of the tree. Trees need to be constructed after reading section 1 and 2 of the evaluation and some evaluations certainly do not contain enough information to create informative decision trees nor to assign an amount of shared uncertainty. These evaluations will not be considered here. (authors)

42 ENGINEERING↗
DOE OSTI2025

Identifying preferential flow from soil moisture time series: Review of methodologies

Abstract Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods to highlight important information for readers who want to identify PF from soil moisture data and to inform those who aim to develop new methods or improve existing ones. Core Ideas Soil moisture data can be used to identify the occurrence of preferential flow (PF) and its initiating conditions. Various data‐analysis methods to identify PF differ in susceptibility to error, bias, and subjectivity. These methods can utilize vast amounts of data from soil moisture monitoring networks to develop understanding of when, where, and under what conditions PF occurs. Newly developed methods may lead to better accuracy and reliability, and reduce the need for subjective judgments. Plain Language Summary Preferential flow through soil occurs when a large amount of water is suddenly available, as during an intense storm. This type of flow moves rapidly through the soil in distinct narrow pathways rather than moving evenly throughout the body of soil, with major consequences for groundwater resources, ecosystems, spreading of contaminants, and other vital concerns. Methods of detecting preferential flow have been developed that utilize measurements of soil water content made by sensors installed at various depths. This measurement technology has been widely implemented, many locations now having datasets years in length, and various methods have been developed for using these to identify preferential flow. The various methods are based on different features in the soil moisture records and vary in their advantages and shortcomings. In this review, we explain and evaluate these methods, highlighting important information for their implementation to identify preferential flow from soil moisture data and for efforts to develop new methods or improve existing ones.

Nimmo, John R↗
DOE OSTI2016

A Bayesian Machine Learning Model for Estimating Building Occupancy from Open Source Data

Understanding building occupancy is critical to a wide array of applications including natural hazards loss analysis, green building technologies, and population distribution modeling. Due to the expense of directly monitoring buildings, scientists rely in addition on a wide and disparate array of ancillary and open source information including subject matter expertise, survey data, and remote sensing information. These data are fused using data harmonization methods which refer to a loose collection of formal and informal techniques for fusing data together to create viable content for building occupancy estimation. In this paper, we add to the current state of the art by introducing the Population Data Tables (PDT), a Bayesian based informatics system for systematically arranging data and harmonization techniques into a consistent, transparent, knowledge learning framework that retains in the final estimation uncertainty emerging from data, expert judgment, and model parameterization. PDT probabilistically estimates ambient occupancy in units of people/1000ft2 for over 50 building types at the national and sub-national level with the goal of providing global coverage. The challenge of global coverage led to the development of an interdisciplinary geospatial informatics system tool that provides the framework for capturing, storing, and managing open source data, handling subject matter expertise, carrying out Bayesian analytics as well as visualizing and exporting occupancy estimation results. We present the PDT project, situate the work within the larger community, and report on the progress of this multi-year project.Understanding building occupancy is critical to a wide array of applications including natural hazards loss analysis, green building technologies, and population distribution modeling. Due to the expense of directly monitoring buildings, scientists rely in addition on a wide and disparate array of ancillary and open source information including subject matter expertise, survey data, and remote sensing information. These data are fused using data harmonization methods which refer to a loose collection of formal and informal techniques for fusing data together to create viable content for building occupancy estimation. In this paper, we add to the current state of the art by introducing the Population Data Tables (PDT), a Bayesian model and informatics system for systematically arranging data and harmonization techniques into a consistent, transparent, knowledge learning framework that retains in the final estimation uncertainty emerging from data, expert judgment, and model parameterization. PDT probabilistically estimates ambient occupancy in units of people/1000 ft 2 for over 50 building types at the national and sub-national level with the goal of providing global coverage. The challenge of global coverage led to the development of an interdisciplinary geospatial informatics system tool that provides the framework for capturing, storing, and managing open source data, handling subject matter expertise, carrying out Bayesian analytics as well as visualizing and exporting occupancy estimation results. We present the PDT project, situate the work within the larger community, and report on the progress of this multi-year project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

A mathematical approach to using the forgetting curve to evaluate experience and training factors in human reliability analysis

Traditional human reliability analysis (HRA) methods have difficulty dealing with the dynamic nature of factors such as time and rely on static and expert-judgment-based assessments of performance-shaping factors (PSFs) across limited levels. In this study, we introduce a mathematical approach for dynamically evaluating the experience and training PSF. Our proposed method integrates the psychological concept of the “forgetting curve” to evaluate how PSFs are impacted by the number of trainings and the time elapsed since training. To confirm the validity of the model, we provide experimental data fitted by identifying the quantitative relationship between training and human performance. This research enables dynamic and objective assessments, thus reducing reliance on subjective expert judgment and improving the accuracy of HRA.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Distinct non-invasive evaluation values of tumor-derived cell-free microRNAs, circulating microvesicles and exosomal microRNAs after renal carcinoma cryoablation

Highlights: • Circulating components could be used for the non-invasive evaluation of renal tumor cryoablation therapeutic effects. • Different circulating components have distinct roles in the evaluation of renal tumor cryoablation. • Exosomal microRNAs may be more suitable for the early postoperative judgment of tumor elimination effects. The detection of peripheral circulating tumor-derived components, such as cell-free microRNAs, circulating microvesicles, and exosomal microRNAs, has been shown as a promising noninvasive strategy. However, the different roles of these components in tumor therapy evaluations have remained largely undefined. In this paper, we employed an in vivo model of the human clear cell renal cell carcinoma line Caki-1-bearing mice to evaluate the therapeutic effects of cryoablation, which is a new minimally invasive treatment for renal cell carcinoma. At different times after cryoablation, we found that the levels of the cell-free microRNAs miR-122, miR-155 and miR-210 were first increased and then decreased. Additionally, the number of large-sized microvesicles was increased after cryoablation, but the number of small-sized circulating microvesicles did not change. Furthermore, the exosomal microRNAs miR-126–3p, miR-17–5p, and miR-21–3p rapidly decreased one day after cryoablation, an effect that was well correlated with the treatment degree. Therefore, we suggest that these circulating components may have different levels of importance in the evaluation of the efficacy of renal cell cryoablation, furthermore, exosomal microRNAs may be more suitable for the early postoperative judgment of tumor elimination effects, which are worth further exploration in clinical practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Benefits of utilizing CellProfiler as a characterization tool for U–10Mo nuclear fuel

Automated image processing techniques have the potential to aid in the performance evaluation of nuclear fuels by eliminating judgment calls that may vary from person-to-person or sample-to-sample. Analysis of in-core fuel performance is required for design and safety evaluations related to almost every aspect of the nuclear fuel cycle. This study presents a methodology for assessing the quality of uranium–molybdenum fuel images and describes image analysis routines designed for the characterization of several important microstructural properties. The analyses are performed in CellProfiler, an open-source program designed to enable biologists without training in computer vision or programming to automatically extract cellular measurements from large image sets. The quality metric scores an image based on three parameters: the illumination gradient across the image, the overall focus of the image, and the fraction of the image that contains scratches. The metric presents the user with the ability to ‘pass’ or ‘fail’ an image based on a reproducible quality score. Passable images may then be characterized through a separate CellProfiler pipeline, which enlists a variety of common image analysis techniques. The results demonstrate the ability to reliably pass or fail images based on the illumination, focus, and scratch fraction of the image, followed by automatic extraction of morphological data with respect to fission gas voids, interaction layers, and grain boundaries. - Graphical abstract: Display Omitted - Highlights: • A technique is developed to score U–10Mo FIB-SEM image quality using CellProfiler. • The pass/fail metric is based on image illumination, focus, and area scratched. • Automated image analysis is performed in pipeline fashion to characterize images. • Fission gas void, interaction layer, and grain boundary coverage data is extracted. • Preliminary characterization results demonstrate consistency of the algorithm.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Fission gas bubble identification using MATLAB's image processing toolbox

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Effects of Gain/Loss Framing in Cyber Defense Decision-Making

Cyber defense requires decision making under uncertainty. Yet this critical area has not been a strong focus of research in judgment and decision-making. Future defense systems, which will rely on software-defined networks and may employ ‘moving target’ defenses, will increasingly automate lower level detection and analysis, but will still require humans in the loop for higher level judgment. We studied the decision making process and outcomes of 17 experienced network defense professionals who worked through a set of realistic network defense scenarios. We manipulated gain versus loss framing in a cyber defense scenario, and found significant effects in one of two focal problems. Defenders that began with a network already in quarantine (gain framing) used a quarantine system more than those that did not (loss framing). We also found some difference in perceived workload and efficacy. Alternate explanations of these findings and implications for network defense are discussed.

cyber security↗
DOE OSTI2018

A Rule-Based Expert System Applied to Moisture Durability of Building Envelopes

The moisture durability of an envelope component such as a wall or roof is difficult to predict. Moisture durability depends on all the construction materials used, as well as the climate, orientation, air tightness, and indoor conditions. Modern building codes require more insulation and tighter construction but provide little guidance about how to ensure these energy-efficient assemblies remain moisture durable. Furthermore, as new products and materials are introduced, builders are increasingly uncertain about the long-term durability of their building envelope designs. Oak Ridge National Laboratory and the US Department of Energy's Building America Program are applying a rule-based expert system methodology in a web tool to help designers determine whether a given wall design is likely to be moisture durable and provide expert guidance on moisture risk management specific to a wall design and climate. The expert system is populated with knowledge from both expert judgment and probabilistic hygrothermal simulation results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

RELAP5-3D Developmental Assessment: Comparison of Versions 4.3.4i and 4.2.1i

Figures have been generated comparing the parameters used in the developmental assessment of the RELAP5-3D code using versions 4.3.4i and 4.2.1i. The figures, which are the same as those used in Volume III of the RELAP5-3D code manual, compare calculations using the semi-implicit solution scheme with available experiment data. These figures provide a quick, visual indication of how the code predictions changed between these two code versions and can be used to identify cases in which the assessment judgment may need to be changed in Volume III of the code manual. Changes to the assessment judgments made after reviewing all of the assessment cases are also provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Electrification Futures Study: Scenarios of Electric Technology Adoption and Power Consumption for the United States

This report is the second in a series of Electrification Futures Study (EFS) publications, a multi-year research project to explore widespread electrification in the future energy system of the United States. The report presents scenarios of electric end-use technology adoption and resulting electricity consumption in the United States. The scenarios are used to characterize changes to end-use sectors under futures with increased electrification and to quantify how those changes might impact the amount and shape of electricity consumption. These scenarios were developed primarily using expert judgment and an energy system accounting framework. Of course, technology adoption will ultimately depend on a set of complex considerations that are not fully assessed using our methodology, but which are discussed extensively throughout the report. These interacting factors include technology and fuel cost trade-offs, infrastructure needs, environmental policies, and consumer preference. Within each of these factors are barriers that might challenge increased electrification - such as higher upfront costs or unfamiliarity with new electric technologies - but also opportunities that could yield greater adoption - such as increased productivity or expanded value streams enabled by electric and/or grid-connected technologies. Understanding and quantifying these factors are needed to both evaluate the implications of a potential increased electrification future and to influence the degree of future electrification. Overall, the report represents an initial step to inform researchers and decision-makers with data and context to plan for a potential future in which electricity powers an expanded share of the U.S. energy economy.This report is the second in a series of Electrification Futures Study (EFS) publications, a multi-year research project to explore widespread electrification in the future energy system of the United States. The report presents scenarios of electric end-use technology adoption in all major sectors - transportation, commercial and residential buildings, and industry - and resulting electricity consumption in the United States. The scenarios are used to characterize changes to end-use sectors under futures with increased electrification and to quantify how those changes might impact the amount and shape of electricity consumption. These scenarios were developed primarily using expert judgment and an energy system accounting framework. Of course, technology adoption will ultimately depend on a set of complex considerations that are not fully assessed using our methodology, but which are discussed extensively throughout the report. These interacting factors include technology and fuel cost trade-offs, infrastructure needs, environmental policies, and consumer preference. Within each of these factors are barriers that might challenge increased electrification - such as higher upfront costs or unfamiliarity with new electric technologies - but also opportunities that could yield greater adoption, such as increased productivity or expanded value streams enabled by electric and grid-connected technologies. Understanding and quantifying these factors are needed to both evaluate the implications of a potential increased electrification future and to influence the degree of future electrification. Overall, the report represents an initial step to inform researchers and decision-makers with data and context to plan for a potential future in which electricity powers an expanded share of the U.S. energy economy.

2050↗
DOE OSTI2019

Research Technology Laboratory (RTL) Disposition Program Final Status Survey Report

As part of the Battelle Facility Restoration Program (Smoter and Biebesheimer 2017), the Research Technology Laboratory (RTL) Complex was remediated through demolition and surveyed to show it meets the radiological release criteria for unrestricted use under the clearance process (DOE 2011). The restoration program has directed the implementation of the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) methodology (NRC 2011) to verify the suitability of the site to be released for unrestricted use under the clearance process in U.S. Department of Energy (DOE) Order 458.1 (Biebesheimer 2018a; DOE 2011). The use of MARSSIM is accepted by federal and state agencies, including DOE. This report documents how the MARSSIM process was used to assure any residual radioactivity is within acceptable levels and as low as reasonably achievable. Past land use for the RTL Complex property included agricultural, residential, and industrial activity. The historical site assessment (HSA) (Lindenmeier et al. 2015; Biebesheimer 2018b) identified use of radionuclides in past RTL Complex research and development activities from commissioning in 1966 until it was vacated in 2017. Based on the information provided in the HSA, the RTL Complex was delineated into six survey units. The 520 building footprint, tank vault and 530 building footprint, other building footprints, and pipeline survey units included excavated areas. The paved areas and open areas survey units were unexcavated areas. Survey units were all determined to be Class 3, with low probability of containing residual radioactivity, after demolition of the structures within the RTL Complex. The Research Technology Laboratory (RTL) Disposition Program: Final Status Survey Plan (Bunn et al. 2018) was designed and conducted to provide quantitative data regarding the residual radioactivity present in each survey unit. Authorized radiological release limits were developed and approved by the DOE Office of Science in December 2016 (DOE 2017). Fourteen random sample locations were identified within each survey unit. Forty-four specific judgmental sample locations were selected across the site based on information in the HSA. The number of sample locations within a survey unit ranged from 15 to 28, for a total of 127 random and judgmental sample locations identified across the RTL Complex. Sampling for the final status survey occurred over 12 days between November 11 and December 7, 2018. Laboratory results were independently validated by Analytical Quality Associates prior to evaluation. All of the over 880 residual radioactivity measurements were less than the release limits and action levels established through the RTL Disposition Program. A sum of fractions calculation for each survey unit resulted in values that were less than unity. Based on the results presented in this report, the restoration program recommends that the RTL Complex be released for unrestricted use.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

A paradigm shift - the key to optimal, defensible and transparent waste management, disposal and remediation decisions - 15236

Current methods for structuring nuclear waste management, disposal, and remediation decisions are subject to three major limitations. First, they are based on a series of extraordinarily conservative assumptions. The dominant way of thinking is that, for example, conservative models yield better, safer decisions. Second, they lack methods to meaningfully address and incorporate the 'human dimension'. The dominant way of thinking is that the current approach is sufficient to bring together the values and interests of both internal and external stakeholders in making a decision. And third, they lack a formal method through which both internal and external stakeholders are encouraged collectively to 'think through' complex problems that contain multiple competing objectives so that wise, socially acceptable, and scientifically-defensible decisions are made. To overcome these limitations, a paradigm shift is needed towards a holistic, integrated approach to structure nuclear waste management, disposal and remediation decisions. The first requirement of this paradigm shift is the realization and recognition that the problems faced are decision problems, and that there is a formal theory of decision analysis that can, and should, be used to support finding the best solutions. Decision analysis, very simply, is formalized common sense. The reason it is needed for complex problems is that there are too many moving parts (variables) for humans to manage with out the formalism. Decision analysis leads to addressing problem solving using a combination of a science-based model and a costs/values model. Expectation ('realism') and uncertainty are addressed in the science-based models, whereas stakeholder values, preferences, and desires are addressed when modeling costs and value judgments. Science-based modeling tools have been developed, improved, and used since the current regulatory setting was introduced about 30 years ago. However, modeling of costs and value judgments has not often been addressed using any formal approach, despite the openings that exist in regulations (e.g., CERCLA's modifying criteria and the concept of 'as low as reasonably achievable' referenced in DOE Orders). A discussion of the need and rationale for this paradigm shift is presented, followed by a description of the technical basics of this approach to decision modeling, and ending with an explanation of the steps that are taken in this approach to structured decision-making. A software framework program called Guided Interactive Statistical Decision Tools (GiSdT - pronounced 'gist') is introduced that supports this paradigm shift. (authors)

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

A Paradigm Shift continued: An Application of Structured Decision Making for Sustainable Waste Management - 16486

Structured decision making presents an opportunity for DOE and others engaged in solving complex environmental and waste management problems to find solutions that are stakeholder engaged and cost effective. This approach represents a paradigm shift that was introduced in a series of papers and a panel session at the WM2015 Symposium. The advantages of structured decision making over less formal approaches to decision making include technical defensibility, traceability and transparency. Structured decision making also overcomes the limitations of misapplication of conservatism in modeling, addresses stakeholder concerns and competing objectives directly, and provides a formal method through which internal and external stakeholders are encouraged to collectively and carefully consider all relevant attributes of solving complex problems. The first requirement of this paradigm shift is a realization and recognition that the problems faced are inherently decision problems, and that there is a formal theory of decision analysis that can, and should, be used to support finding the best solutions. Structured decision making is, very simply, formalized common sense. The formalities include: framing the problem; identification of objectives and measures for valuing those objectives; costs or values associated with those objectives; management options or alternatives for taking action that are tied directly to the objectives; and, science-based models to evaluate the options. Decision analysis is used to evaluate objectives and choose management options by balancing probability and consequence. The science-based models are built probabilistically based on expectation and uncertainty, and costs and value judgments are used to fulfill addressing stakeholder concerns. Consequently, this approach avoids misplaced conservatism in science-based modeling and properly places values in the objectives component of a decision model. This approach honestly addresses uncertainty and value judgments and balances these competing components to find the most effective decision. A software framework program called Guided Interactive Statistical Decision Tools (GiSdT - pronounced 'gist') is used to support an application of this paradigm shift towards structured decision making. In this application objectives and management options for a waste disposal problem at the Los Alamos National Laboratory are identified, and features, events and processes are described and defined to form the basis of a conceptual site model. This establishes the decision model structure. Objectives are addressed through the three pillars of sustainability - economic, environmental, and social - and also address regulatory concerns or constraints. Management options include removal of waste to another location and engineering designs for leaving waste in place. Using structured decision making, the relationship between objectives, management options, and the conceptual site model is made clear, and leads to a comprehensive, defensible, transparent and traceable approach to effective decision making. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗