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At least 703 records · Page 39

U-10Mo Monolithic Fuel Qualification Plan

The Material Management and Minimization (M3) Program’s primary objective within the U.S. Department of Energy/National Nuclear Security Administration is to achieve permanent threat reduction by minimizing and when possible, eliminating weapon-usable nuclear material around the world. Under M3’s Office of Conversion, the U.S. High Performance Research Reactor (USHPRR) Project, is pursuing a fuel qualification and licensing effort focused on converting high-performance research reactors in the United States from using highly enriched uranium (HEU) fuel to using low-enriched uranium (LEU) fuel. The body of this document is focused on defining the activities required for generic qualification of high density, LEU fuel that then allows reactor conversions to proceed for the four high-performance research reactors and the critical assembly that will operate using the U-10Mo monolithic fuel design (see Subsection 1.3): MITR, MURR, NBSR, ATR, and ATRC. Fuel qualification in this report means generic fuel acceptance of the U-10Mo monolithic fuel form by the NRC for use in reactor conversions in the United States, which allows the fuel to be used in subsequent reactor specific licensing requests. The U 10Mo Monolithic Fuel Research, Development, and Qualification Plan utilizes the functions and requirements of the USHPRR Project that was established in the Functions and Requirements Document (F&RD) [1] and expands on these requirements to ensure that planned tests have traceable results that will ensure the requirement has been met. The methods by which data will be collected to show that these requirements have been met are described in this document.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Baseline Characterization Database Verification Report – 2114 Billet A20568

This ECAR provides the results of a validity evaluation of the physical and mechanical property data collected on a billet of nuclear-grade graphite (i.e., 2114 Billet A20568) in support of the ART Baseline Graphite Characterization Program.1,2 Millions of raw data points have been collected during testing and quantification analyses for these billets. The summary scalar property values and supplementary traceability data are collected into comprehensive spreadsheets. Data sets are composed of single billets of graphite for any given grade, organized by mechanical test-specimen type, and further subdivided into individual spreadsheet tabs according to the specific test or evaluation being performed. A direct analysis of properties was not conducted, and this report does not provide information on the validity or performance characteristics of the graphite itself. Rather, this report is intended as a verification of the completeness of actual data collected in accordance with PLN-3467, “Baseline Graphite Characterization Plan: Electromechanical Testing,”3 and their representation of the measurement and test results with sole regard to the graphite billets under evaluation.

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Digitalization, Management and Synthesis of Thermal Hydraulic Legacy Data Using Dynamical System Scaling

A unique attribute of the nuclear industry is the extent by which designers, developers, operators, and regulators pay attention to demonstrating the safety case. The safety case for nuclear systems is a written, traceable expression of safety, demonstrating the system’s protective measures against uncontrolled radiological releases. The nuclear installation resiliency or safety takes overriding priority over function and performance. The preparation of the safety case heavily relies on extensive experimental campaigns that challenge the target design under a spectrum of postulated accident scenarios. For safety reasons, these experiments are typically conducted in sub-scale test apparatuses intended to reproduce the postulated accident scenarios and event sequences realistically but subject to proven similarity criteria, often referred to as scaling analyses. Since the dawn of the nuclear industry, significant resources have been committed to the construction and operation of such test facilities and a massive amount of data has been generated. Such test data have been and are still used to validate the fundamental assumptions of nuclear power plant phenomena. As we move into the digital world, capturing this multi-decades worth of information in a transparent, easily accessible, and usable manner for the public and industry stakeholders is of paramount importance. Over the last few years FPoliSolutions has been actively developing an enterprise digital data ontology platform (FPoliDON) intended to do just that. The concept was introduced in a paper at the previous NURETH edition and has been significantly enhanced since. With the vision of helping designers use the data to assess their safety case evaluation models, the platform was designed not only to ontologically organize the experimental data, but also to guide the user in the complex analytics associated with the interpretation and use of such test results. A new feature which has been recently added is the ability for the user to access a library of sophisticated mathematical procedures for performing scaling analyses. For this purpose, the Dynamical System Scaling (DSS) procedure invented by Dr. Jose’ Reyes was formulated as one of the services in the digital platform. These methods have been demonstrated to provide an excelled mathematical apparatus to identify similarity criteria or quantify distortions between measured data and the target prototypical conditions. Moreover, DSS can provide a level of synthesis across SETs and IETs which has the promise to yield efficiency in the evaluation code assessment activities. This is often a daunting and expensive task to set up evaluation models that support the safety case of current and future nuclear power plants.

Reyes, Jose↗

Role of Life Cycle Assessment in the Circular Economy

Industry leaders are increasingly turning to the circular economy to address a global need for reducing waste and reusing materials. Stakeholder pressure is mounting to establish better practices for more sustainable systems. Join your industry colleagues for an informative workshop to connect and accelerate standards development related to the circular economy of discarded manufacturing materials. The objective of the workshop is to develop a roadmap for ASTM technical standards to support the formation and engagement of manufacturers in a circular economy. Particular focus will be given to standards to support manufacturers in bringing their discarded materials into a mature materials marketplace as well as standards to measure and improve processing efficiencies resulting in reductions in discarded materials. The resulting roadmap will identify priorities for near-term standardization efforts. The roadmap will identify the necessary definitions for information flows supporting a sophisticate ecosystem for traceability and reuse of the materials. What is the role that life cycle assessment should have in setting manufacturing standards for applying circular economy strategies?

circular economy↗

A Blockchain Based Co-Simulation Framework for Integrating DERs into Wholesale Electricity Markets

As the number of distributed energy resources (DERs) continue to increase across energy-delivery systems, there remains a need for integrating their capabilities into traditional grid operations. In this paper, a blockchain-based solution is proposed to facilitate FERC's Order No. 2222 implementations. The presented use-case enables small-scale DERs to participate in wholesale market operations through DER aggregators, while also enabling local distribution system operators to enforce distribution system constraints in a secure and traceable manner. The presented use case is built around the Unified Testing Platform (UTP) being developed as a part of the Blockchain for Optimized Security and Energy Management (BLOSEM) project. This is a multi-lab effort intended to simplify the deployment of blockchain-powered grid solutions by enabling the integration of simulation tools, and blockchain technologies through the use of system-agnostic interfaces that provide a modular, interoperable, and reusable connectivity layer.

blockchain testing↗

Update on the High Precision Titration Method for Uranium Assay Supported by NBL Program Office

The NBL Program Office (NBL PO) has coordinated with Oak Ridge National Laboratory (ORNL) to implement the High Precision Titration (HPT) method for uranium assay measurements. The measurement method has been successfully developed and qualified, therefore ORNL has progressed to performing analyzes critical to the mission of the NBL PO. The HPT method is vital to producing the next generation of certified reference materials for uranium assay and isotopic abundance. The work described here focused on establishing traceability of the method to the NIST SRM 136 potassium dichromate series, and focused on investigating small differences between SRM 136e and 136f. The NBL PO evaluated the history of all of its primary uranium reference materials, including CRM 112A natural uranium metal, and worked with NIST in investigating the small differences in the dichromate SRM’s. ORNL performed comparative experiments on SRM 136e and 136f using CRM 112A. The results of the experiment will be presented here, along with NBL PO’s plans to re-evaluate the CRM 112A certified uncertainty to comply with JCGM 100, “Guide to the expression of uncertainty in measurement.”

Rogers, Kayron↗

A Blockchain Based Co-Simulation Framework for Integrating DERs to Wholesale Electricity Markets: Preprint

As the number of distributed energy resources (DERs) continue to increase across energy-delivery systems, there remains a need for integrating their capabilities into traditional grid operations. In this paper, a blockchain-based solution is proposed to facilitate FERC's Order No. 2222 implementations. The presented use-case enables small-scale DERs to participate in wholesale market operations through DER aggregators, while also enabling local distribution system operators to enforce distribution system constraints in a secure and traceable manner. The presented use case is built around the Unified Testing Platform (UTP) being developed as a part of the Blockchain for Optimized Security and Energy Management (BLOSEM) project. This is a multi-lab effort intended to simplify the deployment of blockchain-powered grid solutions by enabling the integration of simulation tools, and blockchain technologies through the use of system-agnostic interfaces that provide a modular, interoperable, and reusable connectivity layer.

blockchain testing↗

Update of Radiation References: Results from the WMO Expert Team on Radiation References

Primary metrological references for solar (shortwave) & terrestrial (longwave) radiation are instrument-based, managed by PMOD/WRC. New references (new instruments) have been proposed with improved traceability to SI. However, comparisons show bias between the old and new references. ET-RR should advise WMO whether and how to proceed with the change in radiation references without disrupting climate (and meteorological) science.

ACP↗

Toward designing effective exascale scientific computing workflows: experiences and best practices

Many fields within scientific computing have embraced advances in big-data analysis and machine learning, which often requires the deployment of large, distributed and complicated workflows that may combine training neural networks, performing simulations, running inference, and performing database queries and data analysis in asynchronous, parallel and pipelined execution frameworks. Such a shift has brought into focus the need for scalable, efficient workflow management solutions with reproducibility, error and provenance handling, traceability, and checkpoint-restart capabilities, among other needs. Here, we discuss challenges and best-practices for deploying exascale-generation computational science workflows on resources at the Oak Ridge Leadership Computing Facility (OLCF). We present our experiences with large-scale deployment of distributed workflows on the Summit supercomputer, including for bioinformatics and computational biophysics, materials science, and deep learning model optimization. We also present problems and solutions created by working within a Python-centric software base on traditional HPC systems, and discuss steps that will be required before the convergence of HPC, AI, and data science can be fully realized. Our results point to a wealth of exciting new possibilities for harnessing this convergence to tackle new scientific challenges.

Coletti, Mark↗

A Plan to Qualify New Fuel for the High Flux Isotope Reactor for Material Minimization

The High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) is one of five high power research reactors the Office of Material Management and Minimization (M3) Program, Office of Conversion is working to convert from using highly enriched uranium (HEU) fuel to using low-enriched uranium (LEU) fuel. This effort stems from the primary objective within the U.S. Department of Energy (DOE) National Nuclear Security Administration (NNSA) to achieve permanent threat reduction by minimizing, and when possible, eliminating weapon-usable nuclear material around the world. Under M3’s Office of Conversion, the U.S. High Performance Research Reactor (USHPRR) Project is pursuing fuel qualification and licensing of LEU fuels to support the high-performance reactors. All high-performance reactors except HFIR will be converted to LEU monolithic uranium-molybdenum alloy fuel. HFIR will be evaluated for conversion to LEU using a uranium silicide fuel, namely, U3Si2-Al dispersion fuel. The mission of the USHPRR Project is to develop the technology needed to reduce, and eventually eliminate, worldwide use of HEU in civilian applications. The goal is to develop the technical means needed to use low enriched uranium (LEU) instead of HEU fuel in research and test reactors without significant penalties in performance, economics, or safety of the reactors. The USHPRR Project has four major elements, called Pillars: Fuel Qualification (FQ) managed at Idaho National Laboratory (INL), Fuel Fabrication (FF) managed at Pacific Northwest National Laboratory (PNNL), Reactor Conversion (RC) managed at Argonne National Laboratory (Argonne), and Cross-Cutting (CC) managed at Savannah River National Laboratory (SRNL). FQ is responsible for the qualification of the fuel type. RC is responsible for supporting reactor conversion analysis and overseeing licensing submittals leading to conversions of domestic reactors to LEU fuel. For the FQ effort, FQ (INL) worked in collaboration with RC (Argonne) and ORNL to develop the plan for the uranium silicide fuel qualification for HFIR. The resulting HFIR Fuel Qualification Plan provides the general approach for the USHPRR team to move the selected uranium silicide fuel design for HFIR conversion through qualification. Authorization and use in HFIR will be approved through the DOE’s Office of Science. Uranium silicide fuel was previously qualified in NUREG-1313 at an approximate maximum heat flux of 1.4 MW/m2 and a maximum fuel section temperature of about 130°C. In addition to the different regulator process utilized by DOE, these upper limits will be exceeded in HFIR; therefore, further testing will be necessary to ensure the fuel can meet HFIR qualification requirements. The HFIR fuel loading may exceed 4.8 gU/cm3 which was determined in the NUREG-1313 safety evaluation to be acceptable for use in non-power NRC-licensed reactors provided there exist no other safety considerations. In addition, the uranium silicide fuel will need to be qualified in a HFIR-specific design. This plan includes the currently available information from the USHPRR Project Functions and Requirements document and expands these requirements to ensure that planned tests have traceable results providing evidence that the requirements have been met. Data collection methods are discussed as well as the process to show that the requirements have been met. This document is designed to provide a pathway for researchers to obtain data necessary and at the appropriate quality level for HFIR fuel qualification

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Plan to Qualify New Fuel for the High Flux Isotope Reactor for Material Minimization

The High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) is one of five high power research reactors the Office of Material Management and Minimization (M3) Program, Office of Conversion is working to convert from using highly enriched uranium (HEU) fuel to using low-enriched uranium (LEU) fuel. This effort stems from the primary objective within the U.S. Department of Energy (DOE) National Nuclear Security Administration (NNSA) to achieve permanent threat reduction by minimizing, and when possible, eliminating weapon-usable nuclear material around the world. Under M3’s Office of Conversion, the U.S. High Performance Research Reactor (USHPRR) Project is pursuing fuel qualification and licensing of the high-performance reactors to operate with LEU fuels. All high-performance reactors except HFIR will be converted to LEU monolithic uranium-molybdenum alloy fuel. HFIR will be evaluated for conversion to LEU using a uranium silicide fuel, namely, U3Si2-Al dispersion fuel.The mission of the USHPRR Project is to develop the technology needed to reduce, and eventually eliminate, worldwide use of HEU in civilian applications. The goal is to develop the technical means needed to use low enriched uranium (LEU) instead of HEU fuel in research and test reactors without significant penalties in performance, economics, or safety of the reactors. The USHPRR Project has four major elements, called Pillars: Fuel Qualification (FQ) managed at Idaho National Laboratory (INL), Fuel Fabrication (FF) managed at Pacific Northwest National Laboratory (PNNL), Reactor Conversion (RC) managed at Argonne National Laboratory (Argonne), and Cross-Cutting (CC) managed at Savannah River National Laboratory (SRNL). FQ is responsible for the qualification of the fuel type. RC is responsible for supporting reactor conversion analysis and overseeing licensing submittals leading to conversions of domestic reactors to LEU fuel. For the FQ effort, FQ (INL) worked in collaboration with RC (Argonne) and ORNL to develop the plan for the uranium silicide fuel qualification for HFIR.The resulting HFIR Fuel Qualification Plan provides the general approach for the USHPRR team to move the selected uranium silicide fuel design for HFIR conversion through qualification. Authorization and use in HFIR will be approved through the DOE’s Office of Science. Uranium silicide fuel was previously qualified in NUREG-1313 at an approximate maximum heat flux of 1.4 MW/m2 and a maximum fuel section temperature of about 130°C. In addition to the different regulator process utilized by DOE, these upper limits will be exceeded in HFIR; therefore, further testing will be necessary to ensure the fuel can meet HFIR qualification requirements. The HFIR fuel loading may exceed 4.8 gU/cm3 which was determined in the NUREG-1313 safety evaluation to be acceptable for use in non-power NRC-regulated reactors provided there exist no other safety considerations. In addition, the uranium silicide fuel will need to be qualified in a HFIR-specific design. This plan includes the currently available information from the USHPRR Project Functions and Requirements document and expands these requirements to ensure that planned tests have traceable results providing evidence that the requirements have been met. Data collection methods are discussed as well as the process to show that the requirements have been met. This document is designed to provide a pathway for researchers to obtain data necessary and at the appropriate quality level for HFIR fuel qualification.

Shokes, Tamara↗

Operation Optimization Using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

Kim, Junyung↗

The D and D of Nuclear Facilities: a Systemic Approach for Project Organization and Monitoring - 18099

The Decontamination and Decommissioning (D and D) of Licensed Nuclear facilities takes place under circumstances which make it a very complex field. On the one hand, more and more facilities of widely varying types are concerned, and many D and D projects are currently running or planned. A nuclear facility's life cycle is often very long and the building may be modified or impacted by incidents during its operation. These changes need to be known and taken into account for the D and D plans, in order to ensure safety at all times. In addition, the numerous stakeholders involved in a project express needs which impose many requirements. These encompass various points of view, and data from different detail levels must be managed to satisfactorily meet them. On the other hand, legacy data (including records, plans etc.) is a recurring issue for D and D projects. The quality and availability of relevant data regarding the different phases of the nuclear facility lifetime may be insufficient, for instance due to the lack of traceability practices in the past. The uncertainty level is not always specified and explained, old documents can be damaged and are not necessarily digitized, etc. It is therefore particularly important to define the relevant type of raw data to be collected and traced for D and D projects as early as possible. In this context, CEA (Commissariat a l'energie Atomique et aux energies Alternatives) has been analyzing past D and D projects for many years. The goal is to facilitate reproducibility by generalizing best practices and promoting efficient organizational rules and technical solutions. A method is currently being studied to help project managers to prepare specifications for future D and D operations and improve both the efficiency and the relevance of the decommissioning strategy throughout each project, depending on the expected quality of its end-state. This method first consists in formalizing and specifying the entire set of requirements to be taken into consideration, e.g. technical, operational, logistical, regulatory, financial, organizational, safety and security, human, ethical, or, naturally, environmental aspects. Second, based on these requirements, it will enable the project team to structure, check, and then to demonstrate the coherence and feasibility of the project from both the technological and organizational points of view. Lastly, the method will enable the evaluation of the various possible solutions for the management of dismantling products, for instance, regarding the waste outlets: direct disposal or interim storage. To conclude, the method should permit a constant re-evaluation of the D and D strategy depending on the possible evolution of the stakeholders' requirements, and thus it should optimize the monitoring of D and D projects. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Novel Platform for Digitization of Radiation Measurements, Decommissioning and Dismantling and Nuclear Waste Management - 18229

An innovative Platform for a seamless digitization of the information produced during the characterization of radioactive waste, contaminated objects, and in general radioprotection measurements has ben developed by CAEN SyS. The Platform is based on a spectroscopic handheld instrument integrating RFID technology, barcode reader, camera, voice recorder, and geo-localization, a selection of radiation tolerant RFID tags tested above 300 Gy integrated dose, ruggedized portable RFID readers and a secure database framework capable to collect data also from external sources such as gamma scanners and imaging systems. The Platform allows for real-time measurement of dose rate, radiation spectroscopy, tagging, tracking and inventorying of items. All data produced by the Platform are securely stored into the non-volatile memory of the RFID tags and in the database for both onsite and remote access to the information by operators. This paper presents the current development of the Platform and shows the advantages of such approach to achieve an easy yet reliable waste traceability, waste bagging optimization, and a structured methodology for radiation measurements, meeting an excellent quality control as increasingly required by Safety Authorities. Applications here envisaged and explored are dismantling and decontamination operations, radioprotection measurements and patrols, nuclear material management, safeguards and verification inspections. More in general, the Platform can address the needs of all plants, research laboratories and facilities that are looking to improve their Safety Standards, decrease operational costs, have a precise knowledge of the contaminated environment and objects as well as optimization for personnel dose minimization. (authors)

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Stakeholder Engaged Structured Decision Making to Improve Performance and Reduce Costs While Protecting Human Health and the Environment - 18645

The objective of the Best Practice is to facilitate a paradigm shift when it comes to approaches to the decision making process for nuclear waste management, disposal, and remediation decisions. The stakeholder-engaged structured decision making (SDM) paradigm shift provides a transparent framework for developing optimal solutions to complex problems (Keeney, 1992, Gregory et al, 2012). This is a deliberative-analytical process. The deliberative side centers on understanding stakeholder concerns and values, and developing objectives while identifying options that may achieve those objectives. SDM is implemented with the aid of computer tools that are aimed specifically at capturing these deliberative aspects of a decision analysis. SDM captures this information in a structured format that allows access to the values, objectives, and options that have been identified to help. Through this approach we achieve transparency, traceability, and reproducibility. The goal of SDM at this stage is to provide a formal structure for capturing and processing deliberative information. The deliberative part sets the stage for the analytical part of SDM. A variety of Subject matter experts (SMEs) are engaged in how to evaluate the options through the objectives. Objectives often include minimizing human health risk and minimizing cost, but in the full scope of a sustainability-based approach to decision making, it can include objectives related to economic, environmental and social issues. Subject matter experts might provide other options for achieving the objectives, but their primary role is to evaluate/model the options to the endpoint defined by the objectives or in other words perform a consequence analysis. The structure of SDM makes it clear exactly what is needed from the SMEs, because the options are identified, and the endpoint (objectives) are defined - evaluations and/or models are needed to connect options to objectives. This consequence analysis completes the evaluation, and directly addresses which of the options is the best option. The same SDM approach to finding the best options can also be used for prioritization and resource allocation. Because all of the information is captured in a formal system with the help of computer tools (a software framework for implementing SDM), the decision models that are developed for an application can be fully evaluated numerically and for the insights gained from using a formal process for managing the multiple factors that need to be considered for complex decisions. This includes uncertainty and sensitivity analysis that can be used to guide the need for further data/information collection if the optimal decision is not adequately supported - that is, if there is insufficient confidence in the decision. Also, this feeds directly into adaptive management therefore if more data/information are collected then the efficacy of the current decision can be evaluated, potentially leading to a change in decisions if warranted. (authors)

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IAEA Initiatives that Integrate Stakeholders, Models and Decision Making - 18646

The International Atomic Energy Agency (IAEA) has initiated an effort to provide stakeholder support services as part of Phase II of the Constraints to Implementing Decommissioning and Environmental Remediation (CIDER II) programs. The intent of this sub-group of CIDER II is to provide members states support in areas of stakeholder communication, engagement and participation, with the goal of building trust in decommissioning and environmental remediation (D and ER) decisions for radioactive contamination and facilities. IAEA has also initiated a follow-on effort to address Modeling and Data for Radiological Impact Assessments (MODARIA II), which is aimed at enhancing the capabilities of Member States to simulate radionuclide transfer in the environment, and to ensure appropriate levels of protection from ionizing radiation. Working Group 1 of MODARIA II is focused on the integration of modeling and decision analysis. These two groups have complementary and supporting objectives, which provides an opportunity for collaboration and mutual benefit. The technical integrator is the approach of structured decision making, which follows a five-step process that combines stakeholder values with models through a technically defensible decision analysis. Briefly, the steps are: 1. Provide the context and decision context for the problem; 2. Obtain costs, values and concerns from stakeholders, to develop objectives that need to be achieved (e.g., improve human health, minimize costs, increase jobs); 3. Identify options that might achieve the objectives (e.g., cleanup, institutional controls, education); 4. Develop probabilistic models that connect options to objectives so that the objectives can be evaluated collectively (e.g., a fate and transport and risk model to address the objective of reducing human health risk, a cost model to address costs of taking action); and, 5. Model evaluation, including sensitivity analysis, to determine if an action can be taken with sufficient certainty, or if collection of more data is needed to decrease uncertainty before a decision is made. This approach also supports adaptive management as new data are collected. This approach clarifies the roles of stakeholders and subject matter experts in the decision-making process, where stakeholders specify values, and subject matter experts focus on the models that are needed to evaluate the options. It also provides a technically defensible, reproducible, transparent and traceable approach to all of the components necessary to properly solve the types of complex decision problems that plague radioactive waste management, decommissioning and environmental remediation. This paper introduces the major challenges to implementing such a broad scale of decision analysis, and approaches to overcoming those challenges, which include not only the technical challenges, but also the need to develop capacity in a range of skills not usually accommodated in environmental modeling and includes the need for the IAEA to address decision making in different countries, and with different cultures, religions, political affiliations, and languages. This paper explores the potential for IAEA to benefit from both the CIDER II and MODARIA II programs, and hence to develop a fully integrated approach to effective decision making for radioactive waste management and environmental remediation. Note that there are many people involved in these efforts at the IAEA, and credit belongs to those people for the progress that has been made to date. Our intent here is simply to introduce these IAEA programs at the WM2018 Symposium to provide our perspective and some awareness of some of the directions in which IAEA appears to be headed regarding stakeholder engagement, environmental and risk modeling, data science, and decision analysis. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Managing Knowledge Over Time for Supporting Radioactive Waste Geological Disposal Project Development - 19028

Projects designed to define, build, operate and monitor radioactive waste disposal solutions require the transmission of knowledge over several decades and the preservation of memory over several centuries. This is particularly acute for the geological disposal project 'Cigeo' led by the French national radioactive waste management agency (Andra) as far as the requirements in terms of reversibility lead to the choice of an incremental design that allows to integrate learning resulting from continuous improvement of knowledge. For instance, for robustness purposes, Cigeo is designed on the basis of currently proven technologies, but its step-by-step construction in successive stages must make it possible to integrate improvements derived from the scientific and technical progress as well as from experience feedback from its exploitation. In the field of industrial activity, a significant proportion of the knowledge and skills implemented by employees of a company are not known or even identified by the human resources organization or the mid-management staff. This is mainly due to the fact that (i) the organized knowledge-sharing is often based on documentary tools but little on social modalities and (ii) the organization of knowledge is mostly cross-cutting to the managerial lines. To overcome this bias, a global and integrated approach to knowledge management is currently the focus of Andra's specific efforts. Cross-disciplinary groups and close intergenerational links positioned throughout the life of the projects aim specifically at continuous and participative knowledge sharing, capitalization and transmission. Then, devices aiming at systematic dissemination of and access to knowledge support experience feedback and provide unified collaboration, traceability and decision-support at all scales. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NPP SCCs Based Deregulation Process Application Case Design with Internal Block Diagram of SysML - 19237

- It will be possible to group the radioactive wastes from the perspectives on Systems, Structures and Components (SSCs). This paper covers systematic approaches for deregulating grouped decommissioning wastes. SSCs decomposition structure, mass flow of decommissioning waste, sequence and storage time estimation method for deregulation, and interrelationship between them are presented. The expected benefit is the ability possibly to apply deregulation process to SSCs because SSCs breakdown structure is connected with mass flow of decommissioning waste, deregulation option, and storage time. This allows for the application of deregulation strategies and processes on SSCs basis and can enhance the rationale and traceability of the waste grouping. The sequence for deregulation reflects the logic of ensuring that radioactive nuclides meet self-disposal criteria and storing or disposing radioactive wastes if not met. (authors)

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