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NASA NTRS2020

Medical Data Architecture Prototype Development - Summary of Recent Work and Proposed Ideas for Upcoming Work

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions, and in ExMC Gap Med 10: We do not have the capability to provide computed medical decision support during exploration missions. These gaps recognize the need for a comprehensive medical data management system and the accompanying computational support to provide autonomous medical care during long duration exploration missions. As the MDA matures—including the capability to comprehensively process and discover medically-relevant information to support medical operations during exploration missions—project focus will shift to maturing and extending the MDA platform to enable clinical decision support and real-time guidance. To date, the MDA foundational architecture has recommended exploration medical system Level of Care IV requirements through a series of test bed prototype developments and analog demonstrations. The next stage in the development will focus on more autonomous clinical decision making necessary to address challenges in executing a self-contained medical system that enables health care both with and without assistance from ground support. A thorough understanding of current state of medical decision support systems, advanced machine learning algorithms and vast and varied data sources is required. The development of a clinical decision support for exploration missions (Level of Care V) roadmap is needed: one that assesses of current state of the art of clinical decision support systems (CDSS), interoperability issues, identification of challenges in health and performance monitoring, obtaining and processing information from biosensors, knowledge and data management, data integration and fusion, and advanced algorithm development. This roadmap must also include rapid prototype development in the areas of data processing, advanced analysis and prediction of medical events, and treatment based on medically relevant information processing and evidence-based best practices. In this presentation, an overview of the relevant issues and the beginning framework of a Level of Care V CDSS development roadmap will be provided.

Krihak, M.↗
NASA NTRS2010

Assessing the Hydrologic Performance of the EPA's Nonpoint Source Water Quality Assessment Decision Support Tool Using North American Land Data Assimilation System (Products)

The accuracy of streamflow predictions in the EPA's BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. The North American Land Data Assimilation System (NLDAS) data with high spatial and temporal resolutions provide an alternative to the NOAA National Climatic Data Center (NCDC)'s station data. This study assessed the improvement of streamflow prediction of the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS using the NLDAS 118 degree hourly precipitation and evapotranspiration estimates in seven watersheds of the Chesapeake Bay region. Our results demonstrated consistent improvements of daily streamflow predictions in five of the seven watersheds when NLDAS precipitation and evapotranspiration data was incorporated into BASINS. The improvement of using the NLDAS data is significant when watershed's meteorological station is either far away or not in a similar climatic region. When the station is nearby, using the NLDAS data produces similar results. The correlation coefficients of the analyses using the NLDAS data were greater than 0.8, the Nash-Sutcliffe (NS) model fit efficiency greater than 0.6, and the error in the water balance was less than 5%. Our analyses also showed that the streamflow improvements were mainly contributed by the NLDAS's precipitation data and that the improvement from using NLDAS's evapotranspiration data was not significant; partially due to the constraints of current BASINS-HSPF settings. However, NLDAS's evapotranspiration data did improve the baseflow prediction. This study demonstrates the NLDAS data has the potential to improve stream flow predictions, thus aid the water quality assessment in the EPA nonpoint water quality assessment decision tool.

Lee, S.↗
NASA NTRSDate not supplied

Summary of Technical Interchange Meetings (TIMs) Designed to Enable Earth Independent Medical Operations (EIMO)

The Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program hosted a series of TIMs in 2023-2024 designed to stimulate discussion around specific topics with the goal of enabling EIMO. In context of the thematic constituent elements of EIMO, namely pre-mission planning, acute/emergent/prolonged medical decision making, supply/resource management and task load management, subject matter experts from industry, academia and government (NASA and other Agencies) provided valuable and actionable guidance and recommendations. Earth-based medical experts will remain indispensable for pre-mission planning, however, management of acute/emergent medical contingencies will require a gradual transition of medical care and decision making from terrestrial to space-based assets to enable support of astronaut health and performance and reduce overall mission risk. Key to achieving these enhancements is providing an integrated data system platform capable of utilizing multiple data streams in concert with a variety of on-board databases and passive monitoring of video and wearable sensors to enable a multi-modal, agentic AI-based clinical decision support system (CDSS) to support crew medical officer (CMO) medical decision-making. The EIMO series of TIMs (I-V) have proven to be instructive and portend a significant paradigm shift will be necessary to maintain crew health and performance on exploration class missions. Importantly, since the expected paradigm shift will be significantly different from the methods of operation that have been employed for the majority of missions from the inception of human spaceflight to date, any proposed methods must be deployed in the setting of ongoing operations early and be “tested, reviewed and practiced” while reliable back-up is available to facilitate an Enterprise-wide level of comfort and acceptance. Serious constraints on data transmission coupled with a large and expanding universe of on-board medical informatics data streams will necessitate implementation of a CDSS to supplant the current reliance on support provided by ground-based SMEs. Establishment of trust in the system by CMO/crew and the ground-based medical support team will be essential. Co-development of a CDSS with industry partners will assure that state of the art tools can be employed, and industry efficiencies can be leveraged. Training regimens, materials and tools must evolve to be responsive (just-in-time training) and facilitate autonomous execution of procedures. Proficiency metrics should be established and be based on validated competencies or milestones as opposed to a prescribed number of training hours. Training should be prioritized for broad, translatable skills that have universal application across a variety of medical conditions. Repetition was deemed to be the key to achieving proficiency and emphasis should lie in procedural training which is known to extinguish more rapidly than diagnostic skills. Advanced tools, e.g., extended reality, can provide more realistic and effective training. Use of advanced probabilistic risk assessment tools will be essential to optimize the medical system capability while carefully balancing risk relative to mass/power/volume limitations. Importance of factoring use-life of medical supplies and maintaining awareness of redundancy and opportunity to re-purpose under off nominal situations was emphasized. Consideration of adopting optimized performance standards vs. “good-enough” performance thresholds is warranted. The use of legacy systems as opposed to creating new systems may be preferable. Managing task load and associated cognitive load will be essential to maintain operational safety and behavioral health. ExMC aspires to create a shared EIMO paradigm and strategic vision for advancing medical system design through novel technologies, training, protocols, and support capabilities, built upon the spirit of successful strategies and innovations over the past six decades of space medicine operations.

Jay Lemery↗
NASA NTRS2005

Air Traffic Management Research at NASA Ames Research Center

Since the late 1980's, NASA Ames researchers have been investigating ways to improve the air transportation system through the development of decision support automation. These software advances, such as the Center-TRACON Automation System (eTAS) have been developed with teams of engineers, software developers, human factors experts, and air traffic controllers; some ASA Ames decision support tools are currently operational in Federal Aviation Administration (FAA) facilities and some are in use by the airlines. These tools have provided air traffic controllers and traffic managers the capabilities to help reduce overall delays and holding, and provide significant cost savings to the airlines as well as more manageable workload levels for air traffic service providers. NASA is continuing to collaborate with the FAA, as well as other government agencies, to plan and develop the next generation of decision support tools that will support anticipated changes in the air transportation system, including a projected increase to three times today's air-traffic levels by 2025. The presentation will review some of NASA Ames' recent achievements in air traffic management research, and discuss future tool developments and concepts currently under consideration.

Lee, Katharine↗
NASA NTRS1997

Computational Models of Human Performance: Validation of Memory and Procedural Representation in Advanced Air/Ground Simulation

The Man-Machine Interaction Design and Analysis System (MIDAS) under joint U.S. Army and NASA cooperative is intended to assist designers of complex human/automation systems in successfully incorporating human performance capabilities and limitations into decision and action support systems. MIDAS is a computational representation of multiple human operators, selected perceptual, cognitive, and physical functions of those operators, and the physical/functional representation of the equipment with which they operate. MIDAS has been used as an integrated predictive framework for the investigation of human/machine systems, particularly in situations with high demands on the operators. We have extended the human performance models to include representation of both human operators and intelligent aiding systems in flight management, and air traffic service. The focus of this development is to predict human performance in response to aiding system developed to identify aircraft conflict and to assist in the shared authority for resolution. The demands of this application requires representation of many intelligent agents sharing world-models, coordinating action/intention, and cooperative scheduling of goals and action in an somewhat unpredictable world of operations. In recent applications to airborne systems development, MIDAS has demonstrated an ability to predict flight crew decision-making and procedural behavior when interacting with automated flight management systems and Air Traffic Control. In this paper, we describe two enhancements to MIDAS. The first involves the addition of working memory in the form of an articulatory buffer for verbal communication protocols and a visuo-spatial buffer for communications via digital datalink. The second enhancement is a representation of multiple operators working as a team. This enhanced model was used to predict the performance of human flight crews and their level of compliance with commercial aviation communication procedures. We show how the data produced by MIDAS compares with flight crew performance data from full mission simulations. Finally, we discuss the use of these features to study communication issues connected with aircraft-based separation assurance.

Corker, Kevin M.↗
NASA NTRS2004

NASA's Geospatial Interoperability Office(GIO)Program

NASA produces vast amounts of information about the Earth from satellites, supercomputer models, and other sources. These data are most useful when made easily accessible to NASA researchers and scientists, to NASA's partner Federal Agencies, and to society as a whole. A NASA goal is to apply its data for knowledge gain, decision support and understanding of Earth, and other planetary systems. The NASA Earth Science Enterprise (ESE) Geospatial Interoperability Office (GIO) Program leads the development, promotion and implementation of information technology standards that accelerate and expand the delivery of NASA's Earth system science research through integrated systems solutions. Our overarching goal is to make it easy for decision-makers, scientists and citizens to use NASA's science information. NASA's Federal partners currently participate with NASA and one another in the development and implementation of geospatial standards to ensure the most efficient and effective access to one another's data. Through the GIO, NASA participates with its Federal partners in implementing interoperability standards in support of E-Gov and the associated President's Management Agenda initiatives by collaborating on standards development. Through partnerships with government, private industry, education and communities the GIO works towards enhancing the ESE Applications Division in the area of National Applications and decision support systems. The GIO provides geospatial standards leadership within NASA, represents NASA on the Federal Geographic Data Committee (FGDC) Coordination Working Group and chairs the FGDC's Geospatial Applications and Interoperability Working Group (GAI) and supports development and implementation efforts such as Earth Science Gateway (ESG), Space Time Tool Kit and Web Map Services (WMS) Global Mosaic. The GIO supports NASA in the collection and dissemination of geospatial interoperability standards needs and progress throughout the agency including areas such as ESE Applications, the SEEDS Working Groups, the Facilities Engineering Division (Code JX) and NASA's Chief Information Offices (CIO). With these agency level requirements GIO leads, brokers and facilitates efforts to, develop, implement, influence and fully participate in standards development internationally, federally and locally. The GIO also represents NASA in the OpenGIS Consortium and ISO TC211. The OGC has made considerable progress in regards to relations with other open standards bodies; namely ISO, W3C and OASIS. ISO TC211 is the Geographic and Geomatics Information technical committee that works towards standardization in the field of digital geographic information. The GIO focuses on seamless access to data, applications of data, and enabling technologies furthering the interoperability of distributed data. Through teaming within the Applications Directorate and partnerships with government, private industry, education and communities, GIO works towards the data application goals of NASA, the ESE Applications Directorate, and our Federal partners by managing projects in four categories: Geospatial Standards and Leadership, Geospatial One Stop, Standards Development and Implementation, and National and NASA Activities.

Weir, Patricia↗
NASA NTRS1987

Compromise - An effective approach for the hierarchical design of structural systems

The use of the compromise decision support problem in hierarchical design of structural systems is described. The mathematical template that supports the underlying precepts of hierarchical design in the context of the decision support problem technique is presented. A structural example that demonstrates the efficacy of the approach is included.

Shupe, J. A.↗
DOE OSTI2026

Large Load Integration - Task List and Overview

Large Load Integration Tasks: Task 1 – Workshops Support stakeholder engagement across industry to promote collaboration and identify solutions to challenges that will guide other work Task 2 – Ancillary Services Characterize different types of large loads to assess under what conditions they may be utilized to provide grid stability services Task 3 – Communications Explore the cybersecurity and communications infrastructure required to enable large loads to interface with grid operations to provide ancillary services Task 4 – Nuclear Integration Explore risks and methods for supporting large load energy needs with SMRs and incorporating them into the wider power system Task 5 – Decision Support and TA Provide support to stakeholders through the creation of planning tools and direct technical assistance.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2005

An Exploration of Radiation Physics in Electromagnetics

Contents include the following: NASA's Missions and Aeronautics Research. Today's Air Traffic Control System. Development of Decision-Support Tools. The Center-TRACON Automation System (CTAS). The Traffic Management Advisor (TMA). The Multi-Center Traffic Management Advisor (McTMA). The Surface Management System (SMS). Future Directions: The Joint Planning and Development Office.

Lee, Katherine K.↗
DOE OSTI2020

Electric Distribution System Planning with DERs - High-level Assessment of Tools and Methods

This document addresses analytical tools and methods to support electric distribution system planning with distributed energy resources (DERs) and grid modernization, drawing on leading-edge research and examples from around the United States. In this report, tools include computer models and software, as well as other analytical aids and practices that support distribution system planning. At its core, distribution system planning is about supporting investment decisions. Enhanced and integrated distribution system planning allows utilities to move from a passive reactive role to smart proactive planning with respect to DERs. Distribution system planning can increase transparency around utility distribution system investments before they are brought to the regulatory body for cost recovery, can support deferring traditional infrastructure investments, and can provide information and incentives to customers and third parties about where DERs can help the grid. A growing number of states are beginning to consider a comprehensive distribution system planning process that addresses the costs and benefits of DERs, reflects more choices coming from the customer/third-party domains, is integrated with resource and transmission planning, and incorporates planning scenarios that reflect the dynamic and changing nature of the electricity system

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2019

Future Surface Decision Support Overview

This presentation presents the capabilities of the Airspace Technology Demonstration 2 (ATD-2) Integrated Arrival, Departure, and Surface (IADS) system as a surface decision support tool for users, including Air Traffic Control (ATC) personnel working at the tower and Center facilities and airline Ramp personnel. The ATD-2 IADS capabilities include data exchange and integration, modeling and scheduling, surface metering, and departure scheduling for overhead stream insertion of constrained flights.

Surface Decision Support↗
NASA NTRS2013

Evaluation of the Terminal Area Precision Scheduling and Spacing System for Performance-Based Navigation Arrivals

The growth of global demand for air transportation has put increasing strain on the nation's air traffic management system. To relieve this strain, the International Civil Aviation Organization has urged all nations to adopt Performance-Based Navigation (PBN), which can help to reduce air traffic congestion, decrease aviation fuel consumption, and protect the environment. NASA has developed a Terminal Area Precision Scheduling and Spacing (TAPSS) system that can support increased use of PBN during periods of high traffic, while supporting fuel-efficient, continuous descent approaches. In the original development of this system, arrival aircraft are assigned fuel-efficient Area Navigation (RNAV) Standard Terminal Arrival Routes before their initial descent from cruise, with routing defined to a specific runway. The system also determines precise schedules for these aircraft that facilitate continuous descent through the assigned routes. To meet these schedules, controllers are given a set of advisory tools to precisely control aircraft. The TAPSS system has been evaluated in a series of human-in-the-loop (HITL) air traffic simulations during 2010 and 2011. Results indicated increased airport arrival throughput up to 10 over current operations, and maintained fuel-efficient aircraft decent profiles from the initial descent to landing with reduced controller workload. This paper focuses on results from a joint NASA and FAA HITL simulation conducted in 2012. Due to the FAA rollout of the advance terminal area PBN procedures at mid-sized airports first, the TAPSS system was modified to manage arrival aircraft as they entered Terminal Radar Approach Control (TRACON). Dallas-Love Field airport (DAL) was selected by the FAA as a representative mid-sized airport within a constrained TRACON airspace due to the close proximity of a major airport, in this case Dallas-Ft Worth International Airport, one of the busiest in the world. To address this constraint, RNAV routes and Required Navigation Performance with the particular capability known as Radius-to-Fix (RNP-RF) approaches to a short final were used. The purpose of this simulation was to get feedback on how current operations could benefit with the TAPSS system and also to evaluate the efficacy of the advisory tools to support the broader use of PBN in the US National Airspace System. For this NASA-FAA joint experiment, an Air Traffic Control laboratory at NASA Ames was arranged to simulate arrivals into DAL in Instrument Meteorological Conditions utilizing parallel dependent approaches, with two feeder positions that handed off traffic to one final position. Four FAA controllers participated, alternately covering these three positions. All participants were Full-Performance Level terminal controllers and members of the National Air Traffic Controllers Association. During the simulation, PBN arrival operations were compared and contrasted in three conditions. They were the Baseline, where none of the TAPSS systems TRACON controller decision support advisories were provided, the Limited Advisories, reflecting the existing but dormant capabilities of the current terminal automation equipment with providing a subset of the TAPSS systems advisories; numerical delay, landing sequence, and runway assignment information, and the Full Advisories, with providing the following in addition to the ones in the Limited condition; trajectory slot markers, timelines of estimated times of arrivals and sched

Performance based navigation↗
NASA NTRSDate not supplied

Utilizing Gaps and Performance Measures to Inform NASA Environmental Control and Life Support Systems and Crew Health and Performance Technology Decisions

Human spaceflight is a complex endeavor requiring multiple capabilities for transportation, crew health, scientific goals, and safe return to Earth. The difference between spaceflight proven capabilities and those needed for future exploration architectures is defined as a capability gap. Capability gaps are not technology specific. Each capability gap may be closed with a wide array of technologies that have unique benefits and challenges. Determining what a capability’s relevant and distinguishing key performance parameters (KPPs) are for a mission is critical. Mass, power, and volume are always constrained and important, but defining these in a way normalized by performance is very important. KPP definition for reliability, dormancy, and integration needs are hard to define but critical. Outside of technical considerations, the programmatic factors of the estimated time to develop the technology and how the technology validation objectives are matured are strong considerations in which technologies should be pursued and how they should leverage earlier mission elements. The Environmental Control and Life Support (ECLSS) and Crew Health and Performance (CHP) capability areas are decomposed to high level gaps. While KPPs should be technology agnostic, they can be used to both compare technologies and measure progress of technology development over time. KPPs help define when the gap is closed, and the core mission objectives can be accomplished. Proposed technology improvements to enhance a capability should balance improved KPPs and against investments in other capabilities that are not yet closed. A selection of gaps, KPPs, and validation objectives and their formulation, current state, and how they inform capability roadmap planning are discussed.

Life Support↗
NASA NTRS1994

Risk reduction methodologies and technologies for the Earth Observing System (EOS) Operations Center (EOC)

This paper will discuss proposed Flight Operations methodologies and technologies for the Earth Observing System (EOS) Operations Center (EOC), to reduce risks associated with the operation of complex multi-instrument spacecraft in a multi-spacecraft environment. The EOC goals are to obtain 100 percent science data capture and maintain 100 percent spacecraft health, for each EOS spacecraft. Operations risks to the spacecraft and data loss due to operator command error, mission degradation due to mis-identification of an anomalous trend in component performance or mis-management of resources, and total mission loss due to improper subsystem configuration or mis-identification of an anomalous condition. This paper discusses automation of routine Flight Operations Team (FOT) responsibilities, Expert systems for real-time non-nominal condition decision support, and Telemetry analysis systems for in-depth playback data analysis and trending.

Hudson, Richard K.↗
DOE OSTI2021

Development of an Assessment Methodology That Enables the Nuclear Industry to Evaluate Adoption of Advanced Automation

Nuclear power has a crucial role in providing safe, reliable, and economical carbon-free electricity for today and the future. For continued operation, many of the existing United States nuclear power plants will begin the subsequent license renewal process for extending their operating license periods. As plants extend their expected operating lifetimes, there is a significant opportunity to modernize. These plants have a much stronger business case with these extended mission periods to modernize and significantly enhance their economic viability in current and future energy markets by implementing digital technologies that support innovation, efficiency gains, and business-model transformation. Ensuring continued safety and reliability is crucial. Transformative digital technologies—including automation—that fundamentally change the concept of operation for the nuclear power plant operating model requires a critical focus on the human and technology integration element. Further, the nuclear industry has historically been reluctant to modernize due to having a risk adverse culture and lack of clarity for a transformative new state vision (Joe & Remer, 2019; Thomas et al., 2020). Common barriers include (1) the perceived value and return on investment (ROI) of digital technology, (2) the perceived risk associated with licensing, regulatory, and cybersecurity, and (3) insufficient guidance for performing digital modifications to power generation systems. This work presents a methodology to address these barriers and support the industry in adopting advanced automation and digital technology through developing a transformative vision and implementation strategy that will address the human and technology integration element. This research leverages previous LWRS Program and industry results. It draws specifically on previous LWRS Program research in the areas of advanced alarm systems, computer-based procedures, model informed decision support, and advanced human-system interface displays (e.g., overviews and task-based). The modernization methodology can be used to guide transformative thinking when integrating a set of vendor-specific capabilities to support a new concept of operations and a utility’s end-state vision. The results of this research are organized into six major sections: - Section 1 introduces the need for supporting large-scale digital modifications that will renew the technology base for extended operating life beyond 60 years - Section 2 describes the challenges that the nuclear industry is enduring with modernizing. - Section 3 summarizes the primary standards and guidance. - Section 4 presents earlier work from the LWRS Program regarding the development of a transformative conceptual design for an advanced control room of a hybrid plants. - Section 5 presents a methodology that is designed at addressing the challenges in the industry today in achieving a transformative new state vision and concept of operations. - Conclusions and next steps of this research are provided in Section 6.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRSDate not supplied

Developing Mars-Based Clinical Scenarios for an Earth Independent Medical Operations (EIMO) – Based Decision Support Service

As crewed missions move beyond Low-Earth Orbit, pre-mission planning cannot fully buy down the medical risks of exploration-class missions. Martian missions, where increased hazards exist, (such as long-duration spaceflight, surface-level EVA operations, and communications delays) will require a paradigm shift in the structure of a medical system. An Earth-Independent Medical Operations-based Medical System (EIMO-MS) will need to optimize four critical domains to help provide medical care: utilization of Pre-Mission Planning, augmentation of Acute and Prolonged Medical Decision Making, automated tracking of Resource Management, and assistance in Task Load Balance. The ideal EIMO-MS will be able to accomplish this goal by having an interactive, adaptable interface that will be able to provide real-time medical services. It must respond based on the level of crewmember training, medical situation, and available medical and non-medical resources. To showcase the capabilities and requirements of such a sophisticated automated MS, a series of clinical scenarios of escalating complexity were developed with clinical and systems engineering input. These scenarios describe in clinical detail what a theoretical future medical system, enhanced with multiple information streams (such as a medical database, an AI-based Decision Support System, real-time monitoring, enhanced in-situ laboratory imaging, etc.) can achieve in conjunction with a trained and experienced crew. Scenarios are comprised of: a context section including objectives and applicable spaceflight environment, a highlighted assumptions section, a clinical narrative section, and a systems engineering activity diagram demonstrating the integrated Medical System (MS). The “swim lanes” of the activity diagram act as the logistical core of each scenario and show how the MS will interact with the crew, ground support, and other in-flight systems. The Design Reference Mission that is used for the scenarios is based on existing reference mission profiles [1] with a projected 30-sol stay on the Martian surface. Scenarios span the spectrum from planned evaluations, minor medical care, urgent care, surgical guidance, critical and expectant management, and behavioral health care. Mission complexity will exponentially increase during deep space and Mars exploration-class missions, and medical support for these missions will likewise need to increase in autonomy and adaptability. The integrated system that will support these missions will need to provide assistance in a variety of anticipated and unforeseen scenarios. These medical scenarios, guided by clinician input, are initial steps in crafting the requirements for an EIMO-based medical system. By working in a systems engineering framework, requirements and capabilities can be extracted and mapped while maintaining a clinical core.

Prashant Parmar↗
NASA NTRS1998

Collaborative Arrival Planning: Data Sharing and User Preference Tools

Air traffic growth and air carrier economic pressures have motivated efforts to increase the flexibility of the air traffic management process and change the relationship between the air traffic control service provider and the system user. One of the most visible of these efforts is the U.S. government/industry "free flight" initiative, in which the service provider concentrates on safety and cross-airline fairness, and the user on their business objectives and operating preferences, including selecting their own path and speed in real-time. In the terminal arrival phase of flight, severe restrictions and rigid control are currently placed on system users, typically without regard for individual user operational preferences. Airborne delays applied to arriving aircraft into capacity constrained airports are imposed on a first-come, first-serve basis, and thus do not allow the system user to plan for or prioritize late arrivals, or to economically optimize their arrival sequence. A central tenant of the free-flight operating paradigm is collaboration between service providers and users in reaching air traffic management decisions. Such collaboration would be particularly beneficial to an airline's "hub" operation, where off-schedule arrival aircraft are a consistent problem, as they cause serious air-port ramp difficulties, rippling airline scheduling effects, and result in large economic inefficiencies. Greater collaboration can also lead to increased airport capacity and decrease the severity of over-capacity rush periods. In the NASA Collaborative Arrival Planning (CAP) project, both independent exchange of real-time data between the service provider and system user and collaborative decision support tools are addressed. Data exchange of real-time arrival scheduling, airspace management, and air carrier fleet data between the FAA service provider and an air carrier is being conducted and evaluated. Collaborative arrival decision support tools to allow intra-airline arrival preferences are being developed and simulated. The CAP project is part of and leveraged from the NASA/FAA Center TRACON Automation System (CTAS), a fielded set of decision support tools that provide computer generated advisories for both enroute and terminal area controllers to manage and control arrival traffic more efficiently. In this paper, the NASA Collaborative Arrival Planning project is outlined and recent results detailed, including the real-time use of CTAS arrival scheduling data by a major air carrier and simulations of tactical and strategic user preference decision support tools.

Zelenka, Richard E.↗
DOE OSTI2021

Numerical Simulations of Geologic Storage Reservoir Management to Support Risk Mitigation Evaluation

This report provides a detailed description of a set of numerical simulations that represent reservoir behavior over time in response to different operational decision scenarios for detection of potential leakage and reduction or avoidance of leakage impact at a hypothetical geological carbon storage (GCS) site. These simulations serve as the basis for a series of GCS leakage risk forecasts that are to be developed using the National Risk Assessment Partnership’s Open-Source Integrated Assessment Model (NRAP-Open-IAM), and a demonstration of a simple decision support workflow for evaluation of mitigation strategies based on results of those system model forecasts. This risk assessment and decision support study is forthcoming. Four injection scenarios were considered: a constant rate carbon dioxide (CO 2 ) injection case (base case), a case with CO 2 injection rate adjustment, a case with early termination of injection operations, and a case with brine extraction. CO 2 injection operations were controlled to ensure that the pressure transient remains below the defined manageable reservoir fracture pressure, with consideration shown to hypothetical locations within the modeled spatial domain where the overburden was weaker and lower transient pressure increases were allowable. Additionally, a brine extraction alternative was considered as a reservoir management and risk mitigation option to reduce reservoir pressure, steer the plume away from any hypothetical geohazard such as fault as needed, and enhance storage capacity. Such operational actions contribute to risk management overtime. This study explores the potential utility of reservoir management for risk reduction at GCS sites. This study shows that the injection design may modify the time to CO 2 breakthrough at a legacy well; in particular, these results show that brine extraction can add value for mitigating risk both by delaying leakage and reducing pressure build-up. For the scenario considered, both pressure plots and pressure distributions demonstrate that pressure build-up was decreased by 3% with brine extraction. Additionally, extraction of brine afforded enhancement of CO 2 storage capacity by 5% compared to the base case. These findings suggest that brine extraction has substantial potential to steer the risk-related reservoir effects away from known geohazards (e.g., faults and legacy wells) by conducting pressure transient effects and CO 2 plume movement toward the production well. Injection rate adjustment scenarios considered in this study show potential value for managing both reservoir pressure transients and CO 2 plume behavior. Operational actions for reducing injection and/or early termination of injection (as compared to the base case), however, require careful design; tailoring both the extent and timing of injection rate adjustment over the injection and post-injection operational period must be thoroughly planned to balance maximizing storage and minimizing subsurface environmental risk. The study also gives preliminary consideration to the effectiveness that monitoring strategy may play in providing useful information to inform reservoir management decisions for risk reduction. Two types of monitoring were considered: 1) pressure build-up or pressure transient; and 2) potential leakage detection from a CO 2 mass or plume. Four hypothetical legacy wells, two plugged and two abandoned, were placed in the model domain. Monitoring along these wells was measured over time in individual stacked reservoir formations and shale formations to support risk mitigation decisions, especially operational decisions that assisted in risk reduction. These simulations will serve as the basis for a series of GCS leakage risk forecasts that are to be developed using NRAP’s Open-IAM, and demonstration of a simple decision support workflow for comparative assessment of mitigation alternatives based on results of those system model forecasts. This risk assessment and decision support study is forthcoming.

54 ENVIRONMENTAL SCIENCES↗