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All sourcesNASA NTRSDOE OSTI
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↗
NASA NTRS2022

Sustainable Aviation Operations and the Role of Information Technology and Data Science: Background, Current Status and Future Directions

This paper reviews the achievements of the international community towards environmentally friendly aviation operations, also referred to as Sustainable Aviation Operations in the last 25 years and the aspirations and goals to limit the impact of aviation and climate in the future. The framework for achieving global progress is provided by the International Civil Aviation Organization. NASA and FAA supported research and development to advance ATM concepts, and implemented the technology, concepts, and procedures that were responsible for creating fuel efficient flights. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. Future developments in aviation operations require new concepts, procedure, modeling, and analysis techniques. There is an increasing interest in applying methods based on Machine Learning Techniques to problems in Air Traffic Management. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and the availability of a rich historical database provide opportunities to exploit the richness of data-driven methods. The promises and challenges in applying Machine Learning Techniques to Air Traffic Management are discussed in the paper along with the testing and trustworthiness required for adoption of the techniques in operations.

Sustainable Aviation, Data Science, Machine Learni↗
NASA NTRS2022

Sustainable Aviation Operations and the Role of Information Technology and Data Science: Background, Current Status and Future Directions

This paper reviews the achievements of the international community towards environmentally friendly aviation operations, also referred to as Sustainable Aviation Operations in the last 25 years and the aspirations and goals to limit the impact of aviation and climate in the future. The framework for achieving global progress is provided by the International Civil Aviation Organization. NASA and FAA supported research and development to advance ATM concepts, and implemented the technology, concepts, and procedures that were responsible for creating fuel efficient flights. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. Future developments in aviation operations require new concepts, procedure, modeling, and analysis techniques. There is an increasing interest in applying methods based on Machine Learning Techniques to problems in Air Traffic Management. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and the availability of a rich historical database provide opportunities to exploit the richness of data-driven methods. The promises and challenges in applying Machine Learning Techniques to Air Traffic Management are discussed in the paper along with the testing and trustworthiness required for adoption of the techniques in operations.

Sustainable Aviation, Data Science, Machine Learni↗
NASA NTRS2024

Exploration Systems Development Mission Directorate: Moon to Mars Architecture Definition Document

The National Aeronautics and Space Administration (NASA) explores the unknown in air and space, innovates for the benefit of humanity, and inspires the world through discovery. Extending the reach of humanity through the human exploration of the Moon, Mars, and beyond is key to that mission. NASA’s Moon to Mars Strategy and Objectives document establishes long-term goals and objectives for crewed deep space exploration; however, satisfying NASA’s Moon to Mars Objectives requires an innovative approach to the definition, management, and execution of NASA’s Moon to Mars Architecture. An architecture offers a high-level unifying structure and defines a system. It provides rules, guidelines, and constraints that define a cohesive and coherent framework that identifies constituent parts, relationships, and connections and establishes how those parts fit and work together. This Architecture Definition Document (ADD) establishes the process for the decomposition of objectives empowers the agency’s success in achieving human exploration of the cosmos. NASA updates this document annually to reflect the maturation of the architecture and the progress NASA and partners make toward achieving exploration objectives. The ADD is not a manifest or requirements document. Instead, it serves as a tool for the programs, projects, and engineers who will implement and execute NASA’s bold ambitions for crewed exploration of deep space. As established in the Moon to Mars Strategy and Objectives, “Why” we explore encompasses three pillars: Science, Inspiration, and National Posture. Ensuring success in all three areas requires an architectural approach that incorporates innovation, collaboration, and partnerships that can be sustained across a multi-decadal effort. This second revision (Rev-B) of the ADD, developed to support NASA’s 2024 Architecture Concept Review (ACR), incorporates several key updates to support the continued evolution of the architecture. Since the last revision of the ADD, NASA has significantly improved the clarity of the objective decomposition, which distills exploration objectives into the characteristics and needs and use cases and functions needed to achieve them. The updated decomposition incorporates findings from internal studies and diverse stakeholder feedback. A model-based systems engineering approach ensures coherence and consistency, removing inconsistency and repetition. Revision B also incorporates advancements to NASA’s Mars architecture, including insight into initial capabilities, systems, and operations necessary to support the Humans to Mars segment. Updates to objective decomposition for Mars add significant detail to the ADD and hint at areas of forward work and future study. An appendix adds greater depth in the future decisions needed for Mars that will drive lunar needs. They are not the only decisions to be made, but they will have huge effects on subsequent decisions. NASA continues to introduce new exploration systems into the architecture. Two new elements — initial surface habitat and lunar surface cargo lander—successfully passed mission concept review in 2024 as a result of extensive analysis, concept refinement, and studies. These elements and their respective reference missions appear in this revision. NASA also continues to apply architecture processes to cross-agency efforts and coordination with external stakeholders by including definitions of architecture technology gaps — essential areas for engagement across and beyond the agency. The technology gaps appendix identifies areas that need attention and innovation to enable future exploration. In publishing this information, NASA communicates the technologies and capabilities that may benefit from partnership with industry, academia, other U.S. government agencies, and international space agencies. Ultimately, NASA established the Moon to Mars Architecture approach to communicate and facilitate humanity’s journey into the universe according to the principles and recurring tenets of NASA’s Moon to Mars Strategy and Objectives. The NASA architecture team thanks their many stakeholders, participants, and partners for their efforts to review and provide feedback. Their support has been critical to the success of this approach.

Elements↗
DOE OSTI2014

BioenergyKDF: Enabling Spatiotemporal Data Synthesis and Research Collaboration

The Bioenergy Knowledge Discovery Framework (BioenergyKDF) is a scalable, web-based collaborative environment for scientists working on bioenergy related research in which the connections between data, literature, and models can be explored and more clearly understood. The fully-operational and deployed system, built on multiple open source libraries and architectures, stores contributions from the community of practice and makes them easy to find, but that is just its base functionality. The BioenergyKDF provides a national spatiotemporal decision support capability that enables data sharing, analysis, modeling, and visualization as well as fosters the development and management of the U.S. bioenergy infrastructure, which is an essential component of the national energy infrastructure. The BioenergyKDF is built on a flexible, customizable platform that can be extended to support the requirements of any user community especially those that work with spatiotemporal data. While there are several community data-sharing software platforms available, some developed and distributed by national governments, none of them have the full suite of capabilities available in BioenergyKDF. For example, this component-based platform and database independent architecture allows it to be quickly deployed to existing infrastructure and to connect to existing data repositories (spatial or otherwise). As new data, analysis, and features are added; the BioenergyKDF will help lead research and support decisions concerning bioenergy into the future, but will also enable the development and growth of additional communities of practice both inside and outside of the Department of Energy. These communities will be able to leverage the substantial investment the agency has made in the KDF platform to quickly stand up systems that are customized to their data and research needs.

Bioenergy.↗
DOE OSTI2017

Nuclear Smuggling Detection and Deterrence FY 2016 Data Analysis Annual Report

The National Nuclear Security Administration’s Office of Nuclear Smuggling Detection and Deterrence (NSDD) has facilitated the installation of more than 3,500 radiation portal monitors (RPMs) at 606 sites in 56 countries worldwide. This collection of RPMs represents the world’s largest network of radiation detectors and provides one element in the defense-in-depth approach that supports the Global Nuclear Detection Architecture. These systems support NSDD’s mission to build partner country capability to deter, detect, and interdict the illicit transport of radiological and fissile material through strategic points of entry and exit at seaports, airports, and border crossings. NSDD works collaboratively with partner countries and international organizations to optimize the operation of these RPMs. The large amount of data provided by NSDD partner countries highlights the close cooperation and partnerships NSDD has built with 56 countries around the world. Thirty-seven of these countries shared at least some RPM-related data with NSDD in fiscal year 2016. This significant level of data sharing is a key element that distinguishes the NSDD office as unique among nuclear nonproliferation programs and initiatives: NSDD can provide specific, objective, data-driven decisions and support for sustaining the radiation detection systems it helped deploy. This data analysis report summarizes and aggregates the RPM data provided to the NSDD office for analysis and review in fiscal year 2016. The data can be used to describe RPM performance and characterize the wide diversity of NSDD deployment sites. For example, NSDD deploys detector systems across sites with natural background radiation levels that can vary by a factor of approximately six from site to site. Some lanes have few occupancies, whereas others have approximately 8,000 occupancies per day and the different types of cargo that travel through a site can result in site-wide alarm rates that range from near 0% at some sites to above 3% at others. Based on the data received, the global average uptime for NSDD RPMs was above 96% for fiscal year 2016. NSDD takes all of these factors into account in making recommendations to partner countries on how to most effectively manage and maintain site operations. NSDD utilizes reports and other information products created by data analysts to efficiently allocate the resources needed to detect and ultimately interdict illicit nuclear and radiological material.

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

Forming IDEAS: Interactive Data Exploration & Analysis System

Modern cyber security operations collect an enormous amount of logging and alerting data. While analysts have the ability to query and compute simple statistics and plots from their data, current analytical tools are too simple to admit deep understanding. To detect advanced and novel attacks, analysts turn to manual investigations. While commonplace, current investigations are time-consuming, intuition-based, and proving insufficient. Our hypothesis is that arming the analyst with easy-to-use data science tools will increase their work efficiency, provide them with the ability to resolve hypotheses with scientific inquiry of their data, and support their decisions with evidence over intuition. To this end, we present our work to build IDEAS (Interactive Data Exploration and Analysis System). We present three real-world use-cases that drive the system design from the algorithmic capabilities to the user interface. Finally, a modular and scalable software architecture is discussed along with plans for our pilot deployment with a security operation command.

Bridges, Robert↗
DOE OSTI2018

Evaluation of the Impacts of Heat Exchanger Operation on Quality of Water Used as Heat Source and Sink

To help inform future decisions about the subsequent uses of water that has served as a heat source and sink in the heat exchanger component of a geothermal heat pump system, ORNL performed an independent assessment of data characterizing the quality of water that had passed through a heat exchanger supporting a geothermal heat pump in a school building. Water supply to the heat exchanger is treated drinking water from a public water supply system that derives its water from a groundwater source. Water analyses and bacteriological measurements collected from heat exchanger and inflow and outflow lines were supplied to ORNL for review. Data were compared with regulatory standards and inflow and outflow data were compared to identify changes occurring in the water resulting from its passage through the heat exchanger. Review of the data identified no conditions that would prevent the use of heat exchange outflow water for water supply. Water quality conforms with applicable regulatory standards. There were no discernible differences between inflow and outflow water quality for any parameters other than water temperature and formation of heterotrophic bacterial biofilms. Changes in water temperature are an expected result of the operation of the heat exchanger system and do not by themselves affect the suitability of the water for human consumption. Bacterial biofilm formation can be affected by water temperature, but the data did not show a consistent or statistically significant relationship between temperature parameters and biofilm formation, and the observations of biofilms formed in the heat exchanger water lines do not affect the suitability of the outflow water for water supply. Legionella, a bacterial genus that has been associated with outbreaks of waterborne pathogenic disease, was detected in one biofilm sample, and the water company is performing follow-up testing to assess the significance of this detection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2012

Cognitive Systems Modeling and Analysis of Command and Control Systems

Military operations, counter-terrorism operations and emergency response often oblige operators and commanders to operate within distributed organizations and systems for safe and effective mission accomplishment. Tactical commanders and operators frequently encounter violent threats and critical demands on cognitive capacity and reaction time. In the future they will make decisions in situations where operational and system characteristics are highly dynamic and non-linear, i.e. minor events, decisions or actions may have serious and irreversible consequences for the entire mission. Commanders and other decision makers must manage true real time properties at all levels; individual operators, stand-alone technical systems, higher-order integrated human-machine systems and joint operations forces alike. Coping with these conditions in performance assessment, system development and operational testing is a challenge for both practitioners and researchers. This paper reports on research from which the results led to a breakthrough: An integrated approach to information-centered systems analysis to support future command and control systems research development. This approach integrates several areas of research into a coherent framework, Action Control Theory (ACT). It comprises measurement techniques and methodological advances that facilitate a more accurate and deeper understanding of the operational environment, its agents, actors and effectors, generating new and updated models. This in turn generates theoretical advances. Some good examples of successful approaches are found in the research areas of cognitive systems engineering, systems theory, and psychophysiology, and in the fields of dynamic, distributed decision making and naturalistic decision making.

Norlander, Arne↗
DOE OSTI2018

Special Purpose Application Reactors: Systems Integration Decision Support

Microreactors, also known as very-Small Modular Reactors (vSMRs) or Special Purpose Reactors (SPRs), are being considered for use in unique applications where other methods of megawatt level energy production are uneconomical or unavailable. For the purposes of this report, a microreactor is defined as meeting the following criteria: • Factory manufacturable • Easily transportable by truck, plane, train, and/or ship • Produce no more than 20 megawatt thermal (MWth) energy, in order to qualify as Hazard Category 2 under 10CFR830 • Maintains neutronic simplicity, allowing semi- or fully-autonomous operation In the United States (U.S.), there are two general types of microreactors under development: high-temperature gas reactors (HTGRs) and heat pipe reactors. These two reactor types may, due to their differences in working fluid temperatures, be more effectively suited to different use cases. Additionally, they will require different interfacing components depending on their intended use. This report identifies a broad range of use cases for micro-reactors. Additionally, multiple reactor technologies are examined with an emphasis on the reactor sub-systems and interconnections. Using this information, a decision framework is developed to guide future efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Regional inertia dynamics of U.S. interconnections: An event-based measurement approach

Power grid inertia plays a vital role in frequency stability following large disturbances, yet its distribution across the U.S. grid is highly uneven. While interconnection-wide inertia benchmarks are useful, they can mask regional variability driven by resource mix, network coupling, and geographic separation. This paper extends event-driven inertia estimation to the regional scale using field measurements from the Frequency Monitoring Network (FNET/GridEye). Starting from balancing authority and independent system operator footprints, candidate regions are refined using a composite coherency score that combines frequency-trajectory shape similarity, timing spread, and lead/lag behavior to ensure dynamic consistency. A filtered sliding difference method (FSDM) is then used to construct regional frequency trajectories, detect disturbance onset, and compute robust regional rate-of-change of frequency (RoCoF). Regional, local, and interconnection inertia are estimated by combining RoCoF with event power imbalance, and additional indicators (regional-to-system inertia ratio and inertial-support arrival time) quantify regional-to-interconnection coupling and relative regional contributions. The method is demonstrated on eleven regions across the Eastern Interconnection (EI) and the Western Electricity Coordinating Council (WECC), with the Electric Reliability Council of Texas (ERCOT) used for validation. In ERCOT, estimates compared against energy management system (EMS) values achieve a mean absolute percentage error of 17.94%. WECC exhibits consistently shorter inertial-support arrival times (0.15–0.3 s) than EI (0.7–1.1 s), highlighting contrasting coupling and disturbance-propagation behavior. Overall, the results reveal pronounced spatial heterogeneity in inertia and coupling, underscoring the value of regional monitoring for both operational decision-making and long-term system planning.

Disturbance events↗
NASA NTRS1989

Data-Processing System For Test Airplane

Real-time display of data on performance supports decisions regarding maneuvers. Data from sensors aboard airplane transmitted to control station on ground for immediate processing and display. Data-acquisition subsystem aboard airplane uses both pulse code modulation and frequency modulation for transmission of sensor data on operation of engine, performance of airplane, and conditions in atmosphere. No data recorded on aircraft.

Ray, R. J.↗
NASA NTRS1992

A decision support tool for synchronizing technology advances with strategic mission objectives

Successful accomplishment of the objectives of many long-range future missions in areas such as space systems, land-use planning, and natural resource management requires significant technology developments. This paper describes the development of a decision-support data-derived tool called MisTec for helping strategic planners to determine technology development alternatives and to synchronize the technology development schedules with the performance schedules of future long-term missions. Special attention is given to the operations, concept, design, and functional capabilities of the MisTec. The MisTec was initially designed for manned Mars mission, but can be adapted to support other high-technology long-range strategic planning situations, making it possible for a mission analyst, planner, or manager to describe a mission scenario, determine the technology alternatives for making the mission achievable, and to plan the R&D activity necessary to achieve the required technology advances.

Hornstein, Rhoda S.↗
NASA NTRS2015

Air Traffic Management Technology Demostration: 1 Research and Procedural Testing of Routes

NASA's Air Traffic Management Technology Demonstration-1 (ATD-1) will operationally demonstrate the feasibility of efficient arrival operations combining ground-based and airborne NASA technologies. The ATD-1 integrated system consists of the Traffic Management Advisor with Terminal Metering which generates precise time-based schedules to the runway and merge points; Controller Managed Spacing decision support tools which provide controllers with speed advisories and other information needed to meet the schedule; and Flight deck-based Interval Management avionics and procedures which allow flight crews to adjust their speed to achieve precise relative spacing. Initial studies identified air-ground challenges related to the integration of these three scheduling and spacing technologies, and NASA's airborne spacing algorithm was modified to address some of these challenges. The Research and Procedural Testing of Routes human-in-the-loop experiment was then conducted to assess the performance of the new spacing algorithm. The results of this experiment indicate that the algorithm performed as designed, and the pilot participants found the airborne spacing concept, air-ground procedures, and crew interface to be acceptable. However, the researchers concluded that the data revealed issues with the frequency of speed changes and speed reversals.

Wilson, Sara R.↗
DOE OSTI2019

Assessment of Low Enriched Uranium Fueled Core Configurations for the Versatile Test Reactor

The Versatile Test Reactor (VTR) Program was initiated in FY-2017. This multi-laboratory effort supported by the U.S. Department of Energy has the long-term objective of completing a Versatile Test Reactor concept with associated cost and schedule estimate that enables a fully informed DOE decision within 3 years, to have a fully operating VTR by 2026 if acquisition is authorized, and to enable accelerated testing of advanced reactor fuels and materials required for advanced reactor technologies. The VTR concept uses sodium as coolant, features a core power of 300 MWth, and employs reactor-grade plutonium as fissile material in a U-Pu-10Zr fuel alloy. The reference core layout provides 10 assembly locations for high-flux irradiation testing with peak fast flux in excess of 4x1015 n/cm2-s. In order to establish a comparison point with other types of fuel, alternative core configurations were investigated using Low Enriched Uranium (LEU) fuel. The objective of this study was to modify the reference VTR core such as to use LEU fuel and assess the performance tradeoff, while retaining the same core envelope.

Stauff, Nicolas E.↗
DOE OSTI2022

Development of novel dynamic machine learning-based optimization of a coal-fired power plant

The increasing fraction of intermittent renewable energy in the electrical grid is resulting in coal-fired boilers now routinely ramp up and down. The current state-of-the-art operation for such boilers is to apply steady-state, neural network-based optimization to make control decisions in real-time, and this report demonstrates the feasibility of extending this to dynamic, neural network-based optimization using a long short-term memory neural network. A simplified numerical simulation of a t-fired coal boiler and supporting equipment is used to represent a real plant subjected to both steady-state, neural network-based optimization and dynamic, neural network-based optimization. Using the same intervals and a particle swarm optimization algorithm, the dynamic optimization outperforms the steady-state optimization and realizes up to 4.58% improvement in thermal efficiency. Dynamic optimization with a long short-term memory neural network is shown to both be feasible and beneficial for operation of a coal-fired boiler under changing load.

42 ENGINEERING↗
NASA NTRS2005

Health Management Applications for International Space Station

Traditional mission and vehicle management involves teams of highly trained specialists monitoring vehicle status and crew activities, responding rapidly to any anomalies encountered during operations. These teams work from the Mission Control Center and have access to engineering support teams with specialized expertise in International Space Station (ISS) subsystems. Integrated System Health Management (ISHM) applications can significantly augment these capabilities by providing enhanced monitoring, prognostic and diagnostic tools for critical decision support and mission management. The Intelligent Systems Division of NASA Ames Research Center is developing many prototype applications using model-based reasoning, data mining and simulation, working with Mission Control through the ISHM Testbed and Prototypes Project. This paper will briefly describe information technology that supports current mission management practice, and will extend this to a vision for future mission control workflow incorporating new ISHM applications. It will describe ISHM applications currently under development at NASA and will define technical approaches for implementing our vision of future human exploration mission management incorporating artificial intelligence and distributed web service architectures using specific examples. Several prototypes are under development, each highlighting a different computational approach. The ISStrider application allows in-depth analysis of Caution and Warning (C&W) events by correlating real-time telemetry with the logical fault trees used to define off-nominal events. The application uses live telemetry data and the Livingstone diagnostic inference engine to display the specific parameters and fault trees that generated the C&W event, allowing a flight controller to identify the root cause of the event from thousands of possibilities by simply navigating animated fault tree models on their workstation. SimStation models the functional power flow for the ISS Electrical Power System and can predict power balance for nominal and off-nominal conditions. SimStation uses realtime telemetry data to keep detailed computational physics models synchronized with actual ISS power system state. In the event of failure, the application can then rapidly diagnose root cause, predict future resource levels and even correlate technical documents relevant to the specific failure. These advanced computational models will allow better insight and more precise control of ISS subsystems, increasing safety margins by speeding up anomaly resolution and reducing,engineering team effort and cost. This technology will make operating ISS more efficient and is directly applicable to next-generation exploration missions and Crew Exploration Vehicles.

Alena, Richard↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗