Results for “operator decision support” — Page 60

NASA NTRS2012

Creating a Realistic Weather Environment for Motion-Based Piloted Flight Simulation

A flight simulation environment is being enhanced to facilitate experiments that evaluate research prototypes of advanced onboard weather radar, hazard/integrity monitoring (HIM), and integrated alerting and notification (IAN) concepts in adverse weather conditions. The simulation environment uses weather data based on real weather events to support operational scenarios in a terminal area. A simulated atmospheric environment was realized by using numerical weather data sets. These were produced from the High-Resolution Rapid Refresh (HRRR) model hosted and run by the National Oceanic and Atmospheric Administration (NOAA). To align with the planned flight simulation experiment requirements, several HRRR data sets were acquired courtesy of NOAA. These data sets coincided with severe weather events at the Memphis International Airport (MEM) in Memphis, TN. In addition, representative flight tracks for approaches and departures at MEM were generated and used to develop and test simulations of (1) what onboard sensors such as the weather radar would observe; (2) what datalinks of weather information would provide; and (3) what atmospheric conditions the aircraft would experience (e.g. turbulence, winds, and icing). The simulation includes a weather radar display that provides weather and turbulence modes, derived from the modeled weather along the flight track. The radar capabilities and the pilots controls simulate current-generation commercial weather radar systems. Appropriate data-linked weather advisories (e.g., SIGMET) were derived from the HRRR weather models and provided to the pilot consistent with NextGen concepts of use for Aeronautical Information Service (AIS) and Meteorological (MET) data link products. The net result of this simulation development was the creation of an environment that supports investigations of new flight deck information systems, methods for incorporation of better weather information, and pilot interface and operational improvements for better aviation safety. This research is part of a larger effort at NASA to study the impact of the growing complexity of operations, information, and systems on crew decision-making and response effectiveness; and then to recommend methods for improving future designs.

Daniels, Taumi S.↗

NASA NTRS2021

Towards the Development of a Multi-Agent Cognitive Networking System for the Lunar Environment

This paper details the development of a multi-agent cognitive system intended to optimize networking performance in the lunar environment. NASA’s current concept of the future of lunar communication, LunaNet [1], outlines a complex network of networks. Challenges such as scalability, interoperability and reliability must first be addressed to successfully fulfill this vision. Machine intelligence can greatly reduce the reliance on human operators and enable efficient operations for tasks such as scheduling and network management. The application of machine learning, artificial intelligence, and other automated decision-making techniques can be used to allow network nodes to intelligently sense and adapt to changes in the environment such as link disruptions, new nodes joining the network, and support for a diverse range of protocols. Cognitive networking seeks to evolve these technologies into an autonomous system with improved science data return, reliability, and scalability. In this paper, we study three main areas a means to further develop cognitive networking capabilities: networking and flight software development, analysis of wireless data for modeling and simulation, and development of algorithms for a multi-agent system.

Cognitive Networking↗

NASA NTRSDate not supplied

Towards the Development of a Multi-Agent Cognitive Networking System for the Lunar Environment

This paper details the development of a multi-agent cognitive system intended to optimize networking performance in the lunar environment. NASA’s current concept of the future of lunar communication, LunaNet, outlines a complex network of networks. Challenges such as scalability, interoperability and reliability must first be addressed to successfully fulfill this vision. Machine intelligence can greatly reduce the reliance on human operators and enable efficient operations for tasks such as scheduling and network management. The application of machine learning, artificial intelligence, and other automated decision-making techniques can be used to allow network nodes to intelligently sense and adapt to changes in the environment such as link disruptions, new nodes joining the network, and support for a diverse range of protocols. Cognitive networking seeks to evolve these technologies into an autonomous system with improved science data return, reliability, and scalability. In this paper, we study three main areas a means to further develop cognitive networking capabilities: networking and flight software development, analysis of wireless data for modeling and simulation, and development of algorithms for a multi-agent system.

Rachel Dudukovich↗

DOE OSTI2015

Using simulation to evaluate warhead monitoring system effectiveness

There is a need to develop and demonstrate technical approaches for verifying potential future agreements to limit and reduce total warhead stockpiles. To facilitate this aim, warhead monitoring systems employ both concepts of operations (CONOPS) and technologies. A systems evaluation approach can be used to assess the relative performance of CONOPS and technologies in their ability to achieve monitoring system objectives which include: 1) confidence that a treaty accountable item (TAI) initialized by the monitoring system is as declared; 2) confidence that there is no undetected diversion from the monitoring system; and 3) confidence that a TAI is dismantled as declared. Although there are many quantitative methods that can be used to assess system performance for the above objectives, this paper focuses on a simulation perspective primarily for the ability to support analysis of the probabilities that are used to define operating characteristics of CONOPS and technologies. This paper describes a discrete event simulation (DES) model, comprised of three major sub-models: including TAI lifecycle flow, monitoring activities, and declaration behavior. The DES model seeks to capture all processes and decision points associated with the progressions of virtual TAIs, with notional characteristics, through the monitoring system from initialization through dismantlement. The simulation updates TAI progression (i.e., whether the generated test objects are accepted and rejected at the appropriate points) all the way through dismantlement. Evaluation of TAI lifecycles primarily serves to assess how the order, frequency, and combination of functions in the CONOPS affect system performance as a whole. It is important, however, to note that discrete event simulation is also capable (at a basic level) of addressing vulnerabilities in the CONOPS and interdependencies between individual functions as well. This approach is beneficial because it does not rely on complex mathematical models, but instead attempts to recreate the real world system as a decision and event driven simulation. Finally, because the simulation addresses warhead confirmation, chain of custody, and warhead dismantlement in a modular fashion, a discrete-event model could be easily adapted to multiple CONOPS for the exploration of a large number of “what if” scenarios.

Perkins, Casey J.↗

DOE OSTI2018

Energy Systems Integration Facility (ESIF) Facility Stewardship Plan: Revision 2.1

The U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), has established the Energy Systems Integration Facility (ESIF) on the campus of the National Renewable Energy Laboratory (NREL) and has designated it as a DOE user facility. This 182,500-ft2 research facility provides state-of-the-art laboratory and support infrastructure to optimize the design and performance of electrical, thermal, fuel, and information technologies and systems at scale. This Facility Stewardship Plan provides DOE and other decision makers with information about the existing and expected capabilities of the ESIF and the expected performance metrics to be applied to ESIF operations. This plan is a living document that will be updated and refined throughout the lifetime of the facility.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Investigation of Multiple Data Streams for Gearbox Bearing Fault Prediction Through Machine-Learning Models

Operations and maintenance (O&M) cost of wind plant accounts up to 30% of total energy cost, which can be reduced through continuous monitoring and successfully detecting incipient wind turbine failures. To accomplish this, condition monitoring and predictive maintenance systems are being implemented in wind industry to support O&M decision making. A wide range of approaches for condition monitoring and fault prediction have been developed. These approaches generally use historical data of wind turbines collected by Supervisory Control and Data Acquisition (SCADA) system to identify patterns that lead to failure. These SCADA data show the overall condition of a wind turbine and can be leveraged to detect when the turbine's performance is degrading and to identify if a fault is developing. However, it becomes challenging to predict the failure of a specific wind turbine gearbox bearing, because the SCADA data are often not directly linked to the component. To bridge the gap, we have investigated features calculated from SCADA data using physics-based models and the gearbox design over the years. The damaged metric we used in the physics domain is frictional energy. Combining these physics domain variables with SCADA data as inputs to various machine learning models for gearbox bearing fault prediction, we have demonstrated the benefits of leveraging both physics and data domain models. It was an attempt to improve frictional-energy-based damage metric by adding data domain inputs, as we had learned that the frictional-energy-based damage metric alone is not sufficient to single out failed bearings from healthy. As condition monitoring data (either vibration or oil debris data) has become available at more and more wind plants, we would like to evaluate whether by adding the condition monitoring data can help further improve the performance of frictional-energy-based damage metric for gearbox bearing fault prediction. Both cases by modeling through various machine learning algorithms are discussed in this study along with some observations.

fault prediction↗

DOE OSTI2015

Nuclear aircraft carrier inactivation - Execution of waste management initiatives - 15565

After 6 years of planning efforts, in June 2013, Newport News Shipbuilding (NNS) began the execution phase of the inactivation of the USS Enterprise. The USS Enterprise decommissioning involves implementation of a new approach to defueling aircraft carriers, utilizing new processes for defueling and shipment of spent nuclear fuel and waste. During planning for this complex endeavor, NNS developed several process improvement initiatives including streamlining waste management processes and technology insertion using modeling and simulation (M and S) capabilities. One of the new approaches involves the establishment of a Waste Packaging Area (WPA) onboard the ship. The process assists with maximizing waste loading and shipments directly from the ship. Another waste management initiative includes the NNS/ Waste Vendor teaming effort to facilitate more efficient loading and shipment of inactivation waste. With execution underway, these initiatives are being put to the test to see if they can withstand the rigors of day-to-day production. NNS has implemented the use of the Modeling and Simulation (M and S) technology. During the planning phase, the M and S 3D Spatial Arrangement Tool was utilized to determine the optimal equipment layout within the new M-290 facility used for spent fuel packaging and ship-out and to determine the appropriate shipping container placement on the ship to maximize waste loading. The M and S technology proved to be a beneficial application resulting in continued utilization through the execution phase of the carrier inactivation. NNS is currently expanding the M-290 Facility Model to provide a visual representation of the facility, its processes, resources, and variable parameters that can be utilized as a decision support tool through simulation of the spent fuel packaging and ship-out process through the facility's life-cycle. NNS is also expanding the application of the waste management model to effectively predict waste forecast. The simulation model is linked with the defueling schedule which captures the operational elements of the waste flow process. The model extrapolates the data to provide waste generation output to assess the most efficient and cost effective path for radiological waste shipments offsite. The ability to conduct waste forecasting allows streamlining of the waste management process in support of complex defueling operations. (authors)

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DOE OSTI2013

Soil Modeling Collaboration for Specific Soil Models in Support of Corn Stover Harvest

The objective of this milestone is to develop an integrated decision support platform for determining the impacts of agricultural and forestry management practices on the environmental and economic performance of a landscape. Vast datasets and many dynamic simulation models are available to evaluate environmental performance parameters, including soil erosion from wind and water, soil carbon dynamics, nitrogen cycles, greenhouse gas fluxes, nutrient runoff, and sediment runoff. The challenges are that these tools (1) are typically designed to consider a limited subset of critical environmental parameters, (2) often operate at different spatial and temporal scales, (3) are built using inconsistent computational approaches, and (4) are often not applicable across all regions and agronomic management systems. The Landscape Environmental Assessment Framework (LEAF) overcomes these challenges and integrates these varied tools into an effective, single computational platform. For the first time, because of LEAF, disparate models and datasets can seamlessly and comprehensively work together to provide decision makers with reliable, site-specific environmental performance assessments at the subfield scale.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on Banshee Distribution Network

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2003

Lunar Surface Reference Missions: A Description of Human and Robotic Surface Activities

Most medical equipment to the International Space Station (ISS) is manisfested as part of the U.S. or the Russian medical hardware systems. However, certain medical hardware is also available as part of the Human Research Facility. The HRF and the JSC Medical Operations Branch established a Memorandum of Agreement for joint use of certain medical hardware, including the HRF ultrasound system, the only diagnostic imaging device currently manifested to fly on ISS. The outcome of a medical contingency may be changed drastically, or an unnecessary evacuation may be prevented, if clinical decisions are supported by timely and objective diagnostic information. In many higher-probability medical scenarios, diagnostic ultrasound is a first-choice modality or provides significant diagnostic information. Accordingly, the Clinical Care Capability Development Project is evaluating the HRF ultrasound system for its utility in relevant clinical siruations on board ISS. For effective management of these ultrasound-supported ISS medical scenarios, the resulting data should be available for viewing and interpretation on the ground, and bidirectional voice communication should be readily available to allow ground experts (sonographers, physicians) to provide guidance to the Crew Medical Officer. It may also be vitally important to have the capability of real-time guidance via video uplink to the CMO-opertor during an exam to facilitate the diagnosis in a timely fashion.

Duke, Michael B.↗

NASA NTRS2011

NASA'S Water Resources Element Within the Applied Sciences Program

The NASA Earth Systems Division has the primary responsibility for the Applied Science Program and the objective to accelerate the use of NASA science results in applications to help solve problems important to society and the economy. The primary goal of the NASA Applied Science Program is to improve future and current operational systems by infusing them with scientific knowledge of the Earth system gained through space-based observation, assimilation of new observations, and development and deployment of enabling technologies, systems, and capabilities. This paper discusses major problems facing water resources managers, including having timely and accurate data to drive their decision support tools. It then describes how NASA's science and space based satellites may be used to overcome this problem. Opportunities for the water resources community to participate in NASA's Water Resources Applications Program are described.

Toll, David↗

NASA NTRSDate not supplied

Gateway Program Progress and Overview

This paper provides an overview and status of the Gateway, which will be a small, human-tended space station in orbit around the Moon. The National Aeronautics and Space Administration (NASA) leads the Program and serves as the integrator of the spaceflight capabilities and contributions of U.S. commercial partners and international partners to develop the Gateway. Gateway is the cornerstone of sustainable deep space human exploration and is an essential element of the infrastructure necessary for the execution of the Artemis missions to the Moon. This paper will outline the current planned configuration and deployment of the station, describing the concept of operations and how Gateway supports both lunar surface missions and also serves as the springboard for exploration deeper in space. Calendar year 2022 will see the accomplishments of major milestones such as over twenty systems preliminary design reviews (PDRs), a Program-wide PDR-informed synchronization review, and NASA Key Decision Point marking the evolution of the program as a whole from the formulation phase and into implementation. This paper will provide a progress update for each major component of the Gateway: The Power and Propulsion Element; the Habitation and Logistics Outpost (HALO); Deep Space Logistics; the International Habitation module; the European System Providing Refueling, Infrastructure, and Telecommunications (ESPRIT), which includes a Refueler Module and the HALO Lunar Communications System; External Robotics System; and an Airlock with both science and crew capabilities. For each component, the paper will describe the current maturity of the modules, acquisition strategy, contracts, and if applicable, international partnership status. This paper will also outline the integration function the Gateway Program Office performs at the NASA Johnson Space Center, including the multilateral governance structure and cross-program interfaces across Artemis.

Gateway↗

NASA NTRSDate not supplied

Leveraging Nurse Informaticists for Development of the Impact Tool

The American Nurses Association (ANA) defines nursing informatics as the integration of “nursing science, computer science, and information science to manage and communicate data, information, knowledge, and wisdom in nursing practice. [1]” In additional to nursing education and clinical experience, this field requires additional education in areas of data analysis, database management, and clinical information systems. Nursing informaticists help bridge the communication gap between clinical and technical stakeholders which help align common goals. NASA is currently developing a new medical system trade analysis and decision support tool called IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces). The development team is comprised of multiple specialties including but not limited to clinicians (pharmacists, physicians, and nurse informaticists), software and program developers, human factors experts, and engineers. The nurse informaticists play a significant role in the development, operation, and results interpretation of IMPACT. Their expert knowledge and skills in both clinical nursing, information science, and database management place them in a unique position to collaborate and integrate with the clinical, engineering, and software development members of the team to achieve a cohesive, functional, and user-friendly model.

Lynn Boley↗

DOE OSTI2026

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on the Banshee Distribution Network: Preprint

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2013

New Approaches in Reusable Booster System Life Cycle Cost Modeling

This paper presents the results of a 2012 life cycle cost (LCC) study of hybrid Reusable Booster Systems (RBS) conducted by NASA Kennedy Space Center (KSC) and the Air Force Research Laboratory (AFRL). The work included the creation of a new cost estimating model and an LCC analysis, building on past work where applicable, but emphasizing the integration of new approaches in life cycle cost estimation. Specifically, the inclusion of industry processes/practices and indirect costs were a new and significant part of the analysis. The focus of LCC estimation has traditionally been from the perspective of technology, design characteristics, and related factors such as reliability. Technology has informed the cost related support to decision makers interested in risk and budget insight. This traditional emphasis on technology occurs even though it is well established that complex aerospace systems costs are mostly about indirect costs, with likely only partial influence in these indirect costs being due to the more visible technology products. Organizational considerations, processes/practices, and indirect costs are traditionally derived ("wrapped") only by relationship to tangible product characteristics. This traditional approach works well as long as it is understood that no significant changes, and by relation no significant improvements, are being pursued in the area of either the government acquisition or industry?s indirect costs. In this sense then, most launch systems cost models ignore most costs. The alternative was implemented in this LCC study, whereby the approach considered technology and process/practices in balance, with as much detail for one as the other. This RBS LCC study has avoided point-designs, for now, instead emphasizing exploring the trade-space of potential technology advances joined with potential process/practice advances. Given the range of decisions, and all their combinations, it was necessary to create a model of the original model and use genetic algorithms to explore results. A strong business case occurs when viable paths are identified for an affordable up-front investment, and these paths can credibly achieve affordable, responsive operations, characterized by smaller direct touch labor efforts at the wing level from flight to flight. The results supporting this approach, its potential, and its conclusions are presented here.

Zapata, Edgar↗

NASA NTRS2013

New Approaches in Reuseable Booster System Life Cycle Cost Modeling

This paper presents the results of a 2012 life cycle cost (LCC) study of hybrid Reusable Booster Systems (RBS) conducted by NASA Kennedy Space Center (KSC) and the Air Force Research Laboratory (AFRL). The work included the creation of a new cost estimating model and an LCC analysis, building on past work where applicable, but emphasizing the integration of new approaches in life cycle cost estimation. Specifically, the inclusion of industry processes/practices and indirect costs were a new and significant part of the analysis. The focus of LCC estimation has traditionally been from the perspective of technology, design characteristics, and related factors such as reliability. Technology has informed the cost related support to decision makers interested in risk and budget insight. This traditional emphasis on technology occurs even though it is well established that complex aerospace systems costs are mostly about indirect costs, with likely only partial influence in these indirect costs being due to the more visible technology products. Organizational considerations, processes/practices, and indirect costs are traditionally derived ("wrapped") only by relationship to tangible product characteristics. This traditional approach works well as long as it is understood that no significant changes, and by relation no significant improvements, are being pursued in the area of either the government acquisition or industry?s indirect costs. In this sense then, most launch systems cost models ignore most costs. The alternative was implemented in this LCC study, whereby the approach considered technology and process/practices in balance, with as much detail for one as the other. This RBS LCC study has avoided point-designs, for now, instead emphasizing exploring the trade-space of potential technology advances joined with potential process/practice advances. Given the range of decisions, and all their combinations, it was necessary to create a model of the original model and use genetic algorithms to explore results. A strong business case occurs when viable paths are identified for an affordable up-front investment, and these paths can credibly achieve affordable, responsive operations, characterized by smaller direct touch labor efforts at the wing level from flight to flight. The results supporting this approach, its potential, and its conclusions are presented here.

Zapata, Edgar↗

NASA NTRS2010

The Habitat Demonstration Unit System Integration

The Lunar Surface System Habitat Demonstration Unit (HDU) will require a project team to integrate a variety of contributions from National Aeronautics and Space Administration (NASA) centers and potential outside collaborators and poses a challenge in integrating these disparate efforts into a cohesive architecture. To accomplish the development of the first version of the HDU, the Pressurized Excursion Module (PEM), from conception in June 2009 to rollout for operations in July 2010, the HDU project team is using several strategies to mitigate risks and bring the separate efforts together. First, a set of design standards is being developed to define the interfaces between the various systems of PEM and to the payloads, such as the Geology Laboratory, that those systems will support. Scheduled activities such as early fit-checks and the utilization of a habitat avionics test bed prior to equipment installation into HDU PEM are planned to facilitate the integration process. A coordinated effort to establish simplified Computer Aided Design (CAD) standards and the utilization of a modeling and simulation systems will aid in design and integration concept development. Finally, decision processes on the shell development including the assembly sequence and the transportation have been fleshed out early on HDU design to maximize the efficiency of both integration and field operations.

Gill, Tracy R.↗

DOE OSTI2019

Designing a Site Closure Strategy for Uranium in Groundwater and Surface Water - 19534

A site closure strategy was designed and mapped for residual uranium present in groundwater and surface water at the US DOE Office of Legacy Management (LM) Monticello Mill Tailings Site (MMTS) Operable Unit (OU) III, which is regulated under CERCLA. The MMTS is a former mill site that was used to process uranium and vanadium ore in southeastern Utah until 1960. OU III includes surface water in Montezuma Creek and groundwater present in a shallow alluvial aquifer along the creek valley for several kilometers downgradient of the former mill site. The current remedy consists of an operating pump-and-treat system, monitored natural attenuation (MNA), and institutional controls (ICs). Performance evaluations indicate that a prolonged restoration period is likely, as well as an asymptotic trend in uranium concentrations that still exceed the remediation goal. Multiple strategies and scenarios were evaluated before selecting a preferred site closure strategy. Recommendations were developed to support advancing the site towards closure over the next few years and guide the process of regulatory interactions and decision making at the MMTS OU III. Site closure is an important milestone that reflects successful remedial progress at LM sites. Post-closure site management would be maintained to ensure conditions are protective of human health and the environment. The site closure strategy was considered in the context of site remedial progress. The primary sources of groundwater contamination have been removed, including mill tailings and contaminated soils, sediment, and debris. Five-year reviews have regularly concluded that the remedy is protective of human health and environment and that ICs are effective in preventing exposure to contaminated groundwater. The affected aquifer is low-yielding and has no history of domestic use. In 2004, the final remedy selected in the Record of Decision (ROD) was MNA with ICs. However, a pump-and-treat system was installed and continues to operate as a contingency remedy in the area with the highest residual uranium concentrations. The need for a contingency pump-and-treat system was triggered by a departure of the long-term monitoring data from model projections that were used as the basis for remedy performance metrics specified in the ROD. In 2015, the pump-and-treat system was expanded. Average uranium concentrations have declined locally over time. However, monitoring data and column studies indicate that the system effectiveness will eventually become ineffective in reducing uranium concentrations, likely due to the reequilibration of uranium present in the solid matrix in various states (i.e., sorbed, precipitated). Currently, there are no agreed-upon metrics for discontinuing the contingency pump-and-treat system. Three closure strategies effectively applied at other CERCLA sites were considered at MMTS OU III: (1) restoring natural attenuation conditions and conducting MNA; (2) applying alternate concentration limits (ACLs); and (3) waiving a remedial goal based on technical impracticability (TI). Each closure strategy was evaluated in the following manner: (1) identifying the criteria and requirements associated with current regulations, policy, and guidance, (2) assessing the ability to meet those criteria based on the current site knowledge and the conceptual site model, and (3) identifying data gaps that need to be filled to further assess the closure strategy. Following this evaluation, a preferred closure strategy was selected: to transition to a remedy based on MNA and maintenance of ICs, without active remediation. Several scenarios for transitioning to the preferred closure strategy were identified. Each scenario consisted of 'if/then logic' associated with a larger decision diagram. The decision diagram considered the current conceptual site model (CSM) and potential outcomes of studies that will be conducted to fill data gaps, as well as the performance of the existing treatment system and long-term monitoring data. Two scenarios for transitioning to the preferred closure strategy were highlighted for future planning and were described in detail. For both scenarios, the preferred closure strategy includes demonstrating criteria for MNA acceptance, pump-and-treat termination, long-term monitoring, and eventual site delisting. Recommended actions over the next few years were also developed, including updating the CSM, conducting numerical modeling to predict remedial performance and time frames, conducting geochemical analyses to assess uranium fate and transport, and summarizing the lines of evidence and basis for MNA. This detailed example of the development of a site-specific closure strategy provides the thought process and decision logic used to assess uncertainty using an if/then framework; identify common elements and recommended actions to advance the site towards closure; and navigate the inherent uncertainty in the timing of future events, outcome of regulatory discussions, and remedial progress over time that is common to many complex US DOE facilities. In addition, the national regulations, policy, guidance, and state of practice regarding commonly used site closure strategies was summarized for consideration, including MNA, ACLs, and TI. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗