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All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Shared Situation Awareness in the Flight Deck-ATC System

New technologies and operational concept changes have been proposed for implementation in the National Airspace System (NAS). These changes include improved datalink (CPDLC) technologies for providing improved weather, traffic, Flight Object (FO) and navigation information to the pilot and controller, and new forms of automation for both the flight deck and air traffic management system. In addition, the way business is conducted in the NAS is under consideration. Increases in the discretion provided to pilots (and dispatchers in commercial airlines) are being contemplated in an effort to increase system capacity and flexibility. New concepts of operation (e.g., Collaborative Decision Making and Free Flight) allow for more control to be given to the cockpit or airline with correspondingly greater monitoring responsibilities on the ground. In addition, new technologies and displays make possible much greater information flow between the ground and the cockpit and also dramatic changes in the type of information provided. Designing to support these changes suggests two integrally linked questions: (1) What display technologies and information are needed to support desired changes responsibilities? (2) How will the changes in information availability influence the negotiation process between the cockpit and the ground? Each of these proposed changes (both in technology and operational concept) will have a marked impact on the performance, workload, and Situation Awareness (SA) of both pilots and controllers. Typically such changes are evaluated independently in terms of the effects of the proposed change on either pilot performance or ATC performance. It is proposed here, however, that in order to fully understand the effects of such changes, the joint pilot/controller system must be considered.

Endsley, Mica R.↗
DOE OSTI2020

Method for Assessment of Security-Relevant Settings in Anomaly-Based Intrusion Detection for Industrial Control Systems

Ensuring the integrity of Ethernet-based networks is a challenging and constantly evolving domain. This problem is exacerbated for those operational technology (OT) networks supporting industrial control systems (ICS) since much of that equipment was originally designed to be on a network that was isolated and generally considered free of malefactors. Increasing pressure to bridge these systems with traditional information technology (IT) networks has introduced a bevy of new threats. In response, both academia and industry have responded with security solutions tailored to ICS environments. Deploying these protection systems often involves several configuration choices. While some of these choices are clear (e.g., block/enable protocol X) others are far more subjective (e.g. alert threshold == 3.43). Further complicating the situation, while often similar to IT networks, OT networks have unique challenges and characteristics that make the task of protecting them simultaneously more difficult and straight forward.Extant solutions for quantifying the relative security of intrusion detection systems fail to effectively support the operators of said systems with understanding the impact of various configuration changes. Further, they assume that the attacks are static and not subject to manipulation or alteration in the face of defenses. In this paper, we present a threat-based method for quantifying the relative impact of various security settings for intrusion detection systems (IDSs) within ICS environments. This method provides operational staff with a clear understanding of the relative impact of their settings and assumes that the attacks levied against them are dynamic. The model is described in detail, we apply the model to a synthetic data set, and discuss the inferences that can be made and what types of decisions they could be used to support.

Gillen, Rob↗
DOE OSTI2026

Reimagining How Flood Warnings Can Inform Decision‐Making and Community Actions

Society faces increasingly severe flood hazards, intensifying demand for flood early warning systems (FEWS) that deliver accurate and actionable information. However, most existing FEWS remain prediction‐centric, treating decision‐making as a downstream consumer of hazard forecasts while offering limited support for uncertainty interpretation, risk communication, and real‐world response. This Perspective presents a vision and blueprint for a novel inland FEWS‐decision‐making (FEWS‐DM) framework that repositions decision‐making as an equal partner in the forecasting process—not a passive recipient of its outputs. The framework is built on three tightly coupled, co‐evolving thrusts: Physical Science (T1), which advances flood prediction with quantified uncertainty informed by decision relevance; Human Science (T2), which incorporates psychology, behavior, and cultural and institutional context; and Decision Science (T3), which unifies physical predictions and human factors through principled, utility‐based decision support with end‐to‐end uncertainty management. Rather than treating T1 as a solved problem, FEWS‐DM recognizes that forecast development itself must be shaped by decision needs through continuous bidirectional feedback. We identify key scientific, behavioral, and operational challenges limiting such integration and discuss the enabling role of AI, while emphasizing human‐centered design and community feedback as essential for building trust and improving flood risk management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Microgrid Design Analysis Using Technology Management Optimization and the Performance Reliability Model

Microgrids are a focus of localized energy production that support resiliency, security, local con- trol, and increased access to renewable resources (among other potential benefits). The Smart Power Infrastructure Demonstration for Energy Reliability and Security (SPIDERS) Joint Capa- bility Technology Demonstration (JCTD) program between the Department of Defense (DOD), Department of Energy (DOE), and Department of Homeland Security (DHS) resulted in the pre- liminary design and deployment of three microgrids at military installations. This paper is focused on the analysis process and supporting software used to determine optimal designs for energy surety microgrids (ESMs) in the SPIDERS project. There are two key pieces of software, an ex- isting software application developed by Sandia National Laboratories (SNL) called Technology Management Optimization (TMO) and a new simulation developed for SPIDERS called the per- formance reliability model (PRM). TMO is a decision support tool that performs multi-objective optimization over a mixed discrete/continuous search space for which the performance measures are unrestricted in form. The PRM is able to statistically quantify the performance and reliability of a microgrid operating in islanded mode (disconnected from any utility power source). Together, these two software applications were used as part of the ESM process to generate the preliminary designs presented by SNL-led DOE team to the DOD. Acknowledgements Sandia National Laboratories and the SPIDERS technical team would like to acknowledge the following for help in the project: * Mike Hightower, who has been the key driving force for Energy Surety Microgrids * Juan Torres and Abbas Akhil, who developed the concept of microgrids for military instal- lations * Merrill Smith, U.S. Department of Energy SPIDERS Program Manager * Ross Roley and Rich Trundy from U.S. Pacific Command * Bill Waugaman and Bill Beary from U.S. Northern Command * Tarek Abdallah, Melanie Johnson, and Harold Sanborn of the U.S. Army Corps of Engineers Construction Engineering Research Laboratory * Colleagues from Sandia National Laboratories (SNL) for their reviews, suggestions, and participation in the work.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS1992

An intelligent control and virtual display system for evolutionary space station workstation design

Research and development of the Advanced Display and Computer Augmented Control System (ADCACS) for the space station Body-Ported Cupola Virtual Workstation (BP/VCWS) were pursued. The potential applications were explored of body ported virtual display and intelligent control technology for the human-system interfacing applications is space station environment. The new system is designed to enable crew members to control and monitor a variety of space operations with greater flexibility and efficiency than existing fixed consoles. The technologies being studied include helmet mounted virtual displays, voice and special command input devices, and microprocessor based intelligent controllers. Several research topics, such as human factors, decision support expert systems, and wide field of view, color displays are being addressed. The study showed the significant advantages of this uniquely integrated display and control system, and its feasibility for human-system interfacing applications in the space station command and control environment.

Feng, Xin↗
DOE OSTI2013

Hanford Site 100-N Area In Situ Bioremediation of UPR-100-N-17, Deep Petroleum Unplanned Release - 13245

In 1965 and 1966, approximately 303 m{sup 3} of Number 2 diesel fuel leaked from a pipeline used to support reactor operations at the Hanford Site's N Reactor. N Reactor was Hanford's longest operating reactor and served as the world's first dual purpose reactor for military and power production needs. The Interim Action Record of Decision for the 100-N Area identified in situ bioremediation as the preferred alternative to remediate the deep vadose zone contaminated by this release. A pilot project supplied oxygen into the vadose zone to stimulate microbial activity in the soil. The project monitored respiration rates as an indicator of active biodegradation. Based on pilot study results, a full-scale system is being constructed and installed to remediate the vadose zone contamination. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Modernizing the Nuclear Industry and New Ways of Working

Nuclear energy is recognized as the most feasible energy source towards achieving nation-wide net-zero goals (COP 208, MIT). Additionally, the demand for reliable, consistent energy supply is soaring with the construction of energy hungry data centers and AI tools. This means the construction of new nuclear and the continuation of current nuclear are a high national priority. However, this leaves the nuclear industry with a workforce challenge. The rising demand for nuclear power is threatened by an underpopulated workforce. There exist a few contributors to the decreased workforce such as skewed workforce demographics resulting in large-scale workforce retirement. Also, some plants have observed difficulty hiring and retaining skill sets that typically comprise the nuclear power workforce – specifically skilled craftsman. Those who are graduating with desirable skills are seeking employment in sectors that are more modern and culturally more aligned with younger generational values. Lastly, within the nuclear sector, skilled employees will be a competitive commodity as advanced plants come online offering work environments that incorporate modern technologies, skill sets, and opportunities for career advancement. These factors emphasize the need for legacy plants to modernize with a focus on the workplace environment and culture that meets younger generations’ skills, cultural expectations, and desire for advancement opportunities. Nuclear plants are actively engaged in deploying advancements that improve the management of systems, structures, and components as well as process improvements and technologies that can reduce the costs of operation and maintenance. However, the advancements must also be analyzed, reviewed and deployed in a manner that considers the impact on how people within the organization collaborate, communicate, make decisions, and solve problems. Neglecting to consider the cultural impact of modernization risks poor adoption, unrealized opportunities, or insignificant change toward helping attract new employees. The traditional way of working is not necessarily the way new generations want to engage with their employer. For instance, in a survey performed by North American Young Generation in Nuclear the top three reasons for younger nuclear employees to seek other job opportunities was seeking better work-life balance, a lack of advancement opportunities, and work culture and leadership style differences (Smyth et al. 2022). Integrated Operations for Nuclear (ION) is an approach for the nuclear industry to create long-term strategic modernization plans and analyze each advancement for the impact on people and processes and measure how those impacts flow up to support high-level, long-term plant goals and requirements. One principle of ION is to replace the current labor-centric operation style in legacy nuclear plants with data-centric collaborative operation styles. This paper will explain how transitioning operations to leverage centralized skills and responsibility, multi-skilled teams, and collaborative decision making can flatten the hierarchical structure in plants, enable greater individual efficacy while also offering more experiences and advancement opportunities to staff. Adopting the ION way of working shifts the industry mind-set towards more networked, collaborative, and modern way of working that will attract skilled, next-generation workers to operate the legacy nuclear fleet.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Urban Nexus Science for Future Cities: Focus on the Energy-Water-Food-X Nexus

Rapid urban expansion of the world's cities is placing unprecedented demands on the energy, water, food, and other (X) systems (e.g., mobility) that each offer multiple life-supporting services. Coordination that considers inter-sectoral connections among these urban systems and services remains nascent in practice, yet are critical to the future well-being, resource/operational efficiency, and resilience of urban areas. This paper therefore proposes an applied 'urban nexus science' framework to identify integrated and synergistic pathways toward achieving urban sustainability. The design, planning, and operation of urban W-E-F systems can benefit from integrated analyses to accelerate infrastructure, land use, and hazard mitigation planning and decision-making. New knowledge quantifying the key effects of W-E-F systems designed in isolation versus an increasingly integrated systems, especially when exposed to hazards, health risks, or extreme events, are a critical need. Interactive system modeling and participatory technologies are needed to support stakeholder engagement and two-way (and multi-directional) information flow, for exploring outcomes of alternative solutions for integrating W-E-F sectors. To support such important efforts, research is needed to fill critical gaps in data, identify tradeoffs, and develop synergistic solutions that measure sustainability co-benefits based on different levels of urban integration among W-E-F systems and services.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

End-to-end microgrid protection using distributed data-driven methods

This paper introduces an end-to-end microgrid protection framework that offers real-time system monitoring, fault-related decision making, and circuit breaker control. This is achieved through the design of distributed data-driven techniques based on the support vector machine method, where each relay is responsible for distributed data collection, fault detection, fault localization, and fault isolation. Local communication is established among neighboring relays, fostering cooperative fault localization and isolation. This decentralized design not only reduces the computational and communication requirements but also enables the adaptability of each relay under varying operational dynamics. The proposed end-to-end protection framework was validated using MATLAB/Simulink simulations on a 100% renewable microgrid, achieving an accuracy of 93.1% with response time of 0.0523 s, in protecting against a range of fault scenarios that are characterized by various types, locations, impedances, load conditions, photovoltaic power levels, and microgrid operating modes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Online LIBS–ML Framework for Dynamic Characterization of Heterogeneous Waste-Derived Gasification Feedstocks

LIBS−ML framework for real time feedstock characterization during continuous conveyor transport Heterogeneous waste derived feedstocks (e.g., waste coal, biomass and blends) introduce rapid variability in heating value and ash chemistry that affect gasifier operation, yet conventional laboratory characterization techniques are too slow to support proactive control. To address this gap, this study reports on an online, in situ, dynamic characterization framework that couple’s laser-induced breakdown spectroscopy (LIBS) with leakage safe machine learning (ML) regression to deliver real time, decision quality predictions of gasifier relevant properties. A controlled sample matrix spanning two different waste coals, two different biomasses, and engineered blends under two particle size conditions were constructed and benchmarked using standardized laboratory analyses for proximate/ultimate properties and ash composition. LIBS spectra were acquired dynamically as material flowed on a conveyor belt, using high energy 1064 nm laser ablation and shot averaging to improve repeatability and precision. Supervised regression models (multi layer perceptron (MLP) /artificial neural network (ANN), random forest (RF), and support vector regression (SVR)) and an optimized weighted ensemble were trained on emission line feature sets using nested cross validation with Bayesian hyperparameter tuning and validated against an independent hold out set. The proposed LIBS−ML workflow achieves near laboratory predictive fidelity across parametric targets (including higher heating value (HHV), ash content, fixed carbon, sulfur, major ash forming oxides, and initial deformation temperature (IDT)), with the weighted ensemble providing a robust default predictor under dynamic measurement conditions. These results demonstrate a practical pathway for real time feedstock characterization that can enable feedforward adjustments and more resilient gasifier operation for variable quality waste derived fuels.

Biomass↗
NASA NTRS2018

Concept of Operations for Management by Trajectory

This document describes Management by Trajectory (MBT), a concept for future air traffic management (ATM) in which every flight operates in accordance with a four-dimensional trajectory (4DT) that is negotiated between the airspace user and the Federal Aviation Administration (FAA) to respect the airspace user's goals while complying with National Airspace System (NAS) constraints. In the present-day NAS, the ATM system attempts to predict the trajectory for each flight based on the approved flight plan and scheduled or controlled departure time. However, once the aircraft starts to move, controllers tactically manage the aircraft to implement traffic management restrictions, separate otherwise conflicting aircraft, and address arising NAS constraints. Tactical controller actions are not directly communicated to the automation systems or other stakeholders. Furthermore, the initial trajectory prediction does not anticipate these disruptions or how they will impact the flight. Consequently, and compounded by gaps in required data and models, trajectory predictions are less accurate than possible, which affects Traffic Flow Management (TFM) performance. A cornerstone of the MBT concept is that all air vehicles have, at all times, an assigned 4DT from their current state to their destination. These assigned trajectories consist of trajectory constraints and descriptions. Pilots and air traffic controllers, with the aid of automation, operate the aircraft to comply with the assigned trajectory, unless first negotiating a revision. Equipped aircraft have substantial responsibility for complying with the assigned trajectory without controller intervention. To maximize the operational flexibility available to the airspace user, the assigned trajectory only imposes trajectory constraints as required to achieve the ATM goals of NAS constraint compliance and aircraft separation. Trajectory descriptions are added to the assigned trajectory to ensure sufficient predictability. To further improve trajectory prediction accuracy, airspace users supplement the assigned trajectory by broadcasting intent information and updating it as necessary. Air vehicle intent is a more detailed description of the airspace user's plan for how the flight will fly the assigned trajectory. Air vehicle intent can change freely, without negotiation, as long as it remains in compliance with the assigned trajectory. Aircraft assigned trajectories, air vehicle intent, and predicted trajectories are shared, creating a common view among stakeholders. A NAS Constraint Service gathers and publishes information about all known NAS constraints, enabling airspace users to be informed participants in trajectory negotiation. Trajectory constraints in the assigned trajectory are mapped to NAS constraints to facilitate identifying which aircraft are affected when NAS constraints change. To support efficient trajectory negotiation, all aircraft provide current information about air vehicle capabilities. Assigned trajectories are constructed to satisfy all known NAS constraints, improving trajectory stability and predictability. Uncertainty and disruptions are handled by modifying the assigned trajectory as far in advance as possible. By proactively negotiating changes to the assigned trajectory, rather than relying on controller-selected tactical actions such as vectors to resolve traffic conflicts or implement miles-in-trail restrictions, MBT keeps aircraft on closed trajectories that are fully known to all stakeholders. Since reactive air traffic control actions cannot be predicted in advance, the downstream trajectory cannot be accurately predicted until they happen. Reliable trajectory predictions allow the system to identify needed modifications to trajectories further in advance, where they can be negotiated and communicated as amendments (i.e., additional or altered trajectory constraints) to the assigned trajectory. Decision Support Tools (DSTs) aid controllers in rapidly defining and communicating closed trajectories to the aircraft and support all stakeholders in trajectory negotiation. Anticipated MBT benefit mechanisms include more accurate trajectory predictions, improved ATM performance and robustness to off-nominal conditions, increased flexibility and operational efficiency, reduced impediments to emerging classes of airspace users accessing NAS resources, reduced environmental impacts, and enhanced safety.

ConOps↗
DOE OSTI2023

Resource Adequacy for State Utility Regulators: Current Practices and Emerging Reforms

This report was developed by staff in the National Association of Regulatory Utility Commissioners (NARUC) Center for Partnerships and Innovation (CPI). Additional support was provided from commissioners, commission staff, and other technical experts to provide foundational information for state utility regulators on the evolving nature of resource adequacy for the electric system. With the changing nature of the system, state commissioners will continue to play a vital role in their respective jurisdictions. Their roles in overseeing resource decisions are growing in complexity, with consideration for customer costs, state and federal environmental requirements, extreme weather events, fuel supply limitations, generation retirements, shifting requirements for system operators, and growing levels of intermittent and energy-limited resources (e.g., wind, solar, and battery storage). Reliability concerns continue to be an urgent and immediate priority for utility regulators in most parts of the United States. The information in this report is designed to support state commissioners and their respective staff members as they navigate an evolving resource adequacy landscape to maintain reliability amidst a rapidly changing system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2017

Supportability Challenges, Metrics, and Key Decisions for Future Human Spaceflight

Future crewed missions beyond Low Earth Orbit (LEO) represent a logistical challenge that is unprecedented in human space flight. Astronauts will travel farther and stay in space for longer than any previous mission, far from timely abort or resupply from Earth. Under these conditions, supportability { defined as the set of system characteristics that influence the logistics and support required to enable safe and effective operations of systems { will be a much more significant driver of space system lifecycle properties than it has been in the past. This paper presents an overview of supportability for future human space flight. The particular challenges of future missions are discussed, with the differences between past, present, and future missions highlighted. The relationship between supportability metrics and mission cost, performance, schedule, and risk is also discussed. A set of pro- posed strategies for managing supportability is presented (including reliability growth, uncertainty reduction, level of repair, commonality, redundancy, In-Space Manufacturing (ISM) (including the use of material recycling and In-Situ Resource Utilization (ISRU) for spares and maintenance items), reduced complexity, and spares inventory decisions such as the use of predeployed or cached spares - along with a discussion of the potential impacts of each of those strategies. References are provided to various sources that describe these supportability metrics and strategies, as well as associated modeling and optimization techniques, in greater detail. Overall, supportability is an emergent system characteristic and a holistic challenge for future system development. System designers and mission planners must carefully consider and balance the supportability metrics and decisions described in this paper in order to enable safe and effective beyond-LEO human space flight.

Owens, Andrew C.↗
DOE OSTI2016

Detection of Local Cancer Recurrence After Stereotactic Ablative Radiation Therapy for Lung Cancer: Physician Performance Versus Radiomic Assessment

Purpose: Stereotactic ablative radiation therapy (SABR) is a guideline-specified treatment option for early-stage lung cancer. However, significant posttreatment fibrosis can occur and obfuscate the detection of local recurrence. The goal of this study was to assess physician ability to detect timely local recurrence and to compare physician performance with a radiomics tool. Methods and Materials: Posttreatment computed tomography (CT) scans (n=182) from 45 patients treated with SABR (15 with local recurrence matched to 30 with no local recurrence) were used to measure physician and radiomic performance in assessing response. Scans were individually scored by 3 thoracic radiation oncologists and 3 thoracic radiologists, all of whom were blinded to clinical outcomes. Radiomic features were extracted from the same images. Performances of the physician assessors and the radiomics signature were compared. Results: When taking into account all CT scans during the whole follow-up period, median sensitivity for physician assessment of local recurrence was 83% (range, 67%-100%), and specificity was 75% (range, 67%-87%), with only moderate interobserver agreement (κ = 0.54) and a median time to detection of recurrence of 15.5 months. When determining the early prediction of recurrence within <6 months after SABR, physicians assessed the majority of images as benign injury/no recurrence, with a mean error of 35%, false positive rate (FPR) of 1%, and false negative rate (FNR) of 99%. At the same time point, a radiomic signature consisting of 5 image-appearance features demonstrated excellent discrimination, with an area under the receiver operating characteristic curve of 0.85, classification error of 24%, FPR of 24%, and FNR of 23%. Conclusions: These results suggest that radiomics can detect early changes associated with local recurrence that are not typically considered by physicians. This decision support system could potentially allow for early salvage therapy of patients with local recurrence after SABR.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

A cosine-based correlation information entropy approach for building automatic fault detection baseline construction

Building automatic fault detection and diagnosis (AFDD) technologies have shown great potential for energy savings. To enable AFDD, a baseline depicting the normal operation mode is needed to detect whether the building operation deviates from normality. Existing research using physics-based knowledge and models for AFDD has mainly taken a trial-and-error approach to determine if a given baseline is sufficient via empirical experiments. A mechanism to support decisions such as how many samples and what samples should be included in the baseline is currently lacking. In this study, a data-driven method for AFDD baseline construction based on information entropy is developed. The entropy is derived based on cosine similarity among typical building automation system measurements in conjunction with outdoor weather information. The performance of the proposed method is evaluated using real building data. Evaluation results indicate that the fault detection strategy adopting the proposed method has similar or better accuracy in detecting faults compared to the same fault detection strategy using the baseline construction method from the literature. Additionally, the use of entropy enables the proposed method to automatically construct and assess the baseline consisting of information-rich samples.

42 ENGINEERING↗
DOE OSTI2021

COVID-19 Testing R&D (Final Report)

Eleven Labs within the US Department of Energy (DOE), National Virtual Biotechnology Laboratory (NVBL), came together as a team to address significant R&D gaps in COVID-19 testing. Beginning in March 2020, the NVBL COVID Testing Team developed an R&D agenda, worked with DOE and other agencies to set priorities, and collaborated to deliver timely results. Priority was given to quick implementation as well as development of novel capabilities for immediate and evolving pandemic needs without placing additional burden on operational performers. Priority elements capitalized on DOE National Laboratory strengths and expertise. The Team delivered: testing and evaluation that enabled decisions on testing options, forwardleaning approaches to prepare for future scale-up needs, and models and experiments that supported prioritization of diagnostic and therapeutic candidates.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Hydrogen Sustainable Infrastructure Guidelines (H2SIG)

Infrastructure interacts with major global challenges inclusive of climate change, resilience, equity and social justice, environmental protection and biodiversity, public health, and economic recovery. This effort directly addresses how to apply sustainability assessments to the unique aspects of hydrogen (H2) infrastructure projects using the Envision® sustainability framework developed by the Institute for Sustainable Infrastructure (ISI). Envision is a flexible system of criteria and performance objectives to aid decision makers and help project teams identify sustainable approaches during planning, design and construction of infrastructure projects that will continue throughout the project’s operations, maintenance, and end-of-life phases. The goal of this work is to support those interested in conducting sustainability assessments for hydrogen infrastructure projects. Through this work the team has developed hydrogen-specific guidelines and best practices to assist project developers, investors and regulators in straightforward application of the Envision framework to systematically enhance clarity and increase objectivity across hydrogen projects. Subject matter experts from 20 different organizations (industry, non-profits, municipalities, emissions regulators, national labs) were engaged through 7 focus groups to discuss the H2-prioritized Envision requirements and elements to be included in the guidelines. In addition to these guidelines, the team conducted case studies as a way of demonstrating and informing the guidelines and providing examples or ideas for implementing sustainability in future projects. Through this study, the authors found that hydrogen infrastructure projects can incorporate many sustainable practices including reducing GHG emissions affecting climate change, reducing air pollutant emissions affecting the health of communities, synergistically handling waste byproducts, integrating into existing infrastructure, incorporating renewable energy, and addressing equity and environmental justice. Additionally, hydrogen infrastructure projects could benefit from 2-way communication engagement and collaborative planning with stakeholders, educational awareness of hydrogen technology, tracking and reporting on water use and water quality, and including monetized environmental and social benefits in life-cycle cost estimates. This document is the final technical report for the Hydrogen Sustainability Assessment Methods for Project Development project. While the main focus of the report is to provide guidelines for applying sustainability to hydrogen infrastructure, there are sections within the appendix providing completed project tasks and methodology.

08 HYDROGEN↗
NASA NTRS2016

An Integrated Gate Turnaround Management Concept Leveraging Big Data Analytics for NAS Performance Improvements

"Gate Turnaround" plays a key role in the National Air Space (NAS) gate-to-gate performance by receiving aircraft when they reach their destination airport, and delivering aircraft into the NAS upon departing from the gate and subsequent takeoff. The time spent at the gate in meeting the planned departure time is influenced by many factors and often with considerable uncertainties. Uncertainties such as weather, early or late arrivals, disembarking and boarding passengers, unloading/reloading cargo, aircraft logistics/maintenance services and ground handling, traffic in ramp and movement areas for taxi-in and taxi-out, and departure queue management for takeoff are likely encountered on the daily basis. The Integrated Gate Turnaround Management (IGTM) concept is leveraging relevant historical data to support optimization of the gate operations, which include arrival, at the gate, departure based on constraints (e.g., available gates at the arrival, ground crew and equipment for the gate turnaround, and over capacity demand upon departure), and collaborative decision-making. The IGTM concept provides effective information services and decision tools to the stakeholders, such as airline dispatchers, gate agents, airport operators, ramp controllers, and air traffic control (ATC) traffic managers and ground controllers to mitigate uncertainties arising from both nominal and off-nominal airport gate operations. IGTM will provide NAS stakeholders customized decision making tools through a User Interface (UI) by leveraging historical data (Big Data), net-enabled Air Traffic Management (ATM) live data, and analytics according to dependencies among NAS parameters for the stakeholders to manage and optimize the NAS performance in the gate turnaround domain. The application will give stakeholders predictable results based on the past and current NAS performance according to selected decision trees through the UI. The predictable results are generated based on analysis of the unique airport attributes (e.g., runway, taxiway, terminal, and gate configurations and tenants), and combined statistics from past data and live data based on a specific set of ATM concept-of-operations (ConOps) and operational parameters via systems analysis using an analytic network learning model. The IGTM tool will then bound the uncertainties that arise from nominal and off-nominal operational conditions with direct assessment of the gate turnaround status and the impact of a certain operational decision on the NAS performance, and provide a set of recommended actions to optimize the NAS performance by allowing stakeholders to take mitigation actions to reduce uncertainty and time deviation of planned operational events. An IGTM prototype was developed at NASA Ames Simulation Laboratories (SimLabs) to demonstrate the benefits and applicability of the concept. A data network, using the System Wide Information Management (SWIM)-like messaging application using the ActiveMQ message service, was connected to the simulated data warehouse, scheduled flight plans, a fast-time airport simulator, and a graphic UI. A fast-time simulation was integrated with the data warehouse or Big Data/Analytics (BAI), scheduled flight plans from Aeronautical Operational Control AOC, IGTM Controller, and a UI via a SWIM-like data messaging network using the ActiveMQ message service, illustrated in Figure 1, to demonstrate selected use-cases showing the benefits of the IGTM concept on the NAS performance.

Efficent ATM systems↗