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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1993

Programming Language Software For Graphics Applications

New approach reduces repetitive development of features common to different applications. High-level programming language and interactive environment with access to graphical hardware and software created by adding graphical commands and other constructs to standardized, general-purpose programming language, "Scheme". Designed for use in developing other software incorporating interactive computer-graphics capabilities into application programs. Provides alternative to programming entire applications in C or FORTRAN, specifically ameliorating design and implementation of complex control and data structures typifying applications with interactive graphics. Enables experimental programming and rapid development of prototype software, and yields high-level programs serving as executable versions of software-design documentation.

Beckman, Brian C.↗

DOE OSTI2026

Optimizing enzymes for plastic upcycling using machine learning design and high throughput experiments

Plastic use is ubiquitous in the modern world, and polyethylene terephthalate (PET) is one of the most abundantly produced plastics (and the most highly produced polyester), with ~65 million metric tons manufactured annually. To the consumer, PET is likely most recognizable as the plastic used to make beverage bottles. Like many plastics, traditional mechanical or chemical means of PET deconstruction and upcycling are costly and inefficient. Because of these challenges, recycled plastic is generally of lower quality and is more expensive to produce than virgin plastic derived from petroleum. Ultimately, this results in most plastic ending up as waste. We view plastic waste as an underutilized resource which, with the development of more efficient and high-quality recycling processes, could (1) generate significant economic value while (2) decreasing petroleum usage and greenhouse gas emissions, as well as (3) minimizing its negative environmental and health impacts. Biocatalytic recycling, or biomanufacturing the basic building blocks of new plastic from plastic waste, is a promising approach to plastic reuse that complements existing recycling technologies. Recently, biological enzymes capable of breaking down PET have garnered significant attention as an attractive means of dealing with the plastic problem. These enzymes are currently undergoing pilot studies for implementation in industrial-scale enzyme-based recycling. However, there are significant limitations to current enzymes, including the need to perform costly pre-processing of the plastic waste before the enzymes are able to work. Further optimization of these enzymes is necessary to make these technologies competitive, and ultimately incentivise industry-wide adoption of this biology-based green recycling technology. n this work we demonstrate a means to design and generate performant biological enzymes, capable of efficiently deconstructing plastic waste. Specifically, we applied recent advances in artificial intelligence, machine learning, and statistical analysis to design new versions and discover natural enzymes capable of breaking down PET. We focused on optimizing key properties that are important for industrial-scale enzymatic recycling such as pH and thermotolerance. Normal testing of enzymatic plastic-deconstruction is extremely labor intensive and so through this work we also developed a robotic-assisted experimental pipeline capable of characterizing thousands of candidate enzymes. The results of this iterative, AI-guided, multi-discipline approach have led to increases in enzymatic breakdown of over 150X over starting enzymes. This work supports the rapidly developing and transformative field of biocatalytic solutions to environmental problems beyond the discovery and predictive understanding of enzymes for polymer recycling, and has wide implications for tackling numerous energy problems such as carbon capture and fixation (e.g., engineering carbon monoxide dehydrogenase and the rubisco-pathway), biomining (e.g., design of lanthanide-binding proteins) and biomanufacturing (e.g., lignin-deconstruction enzymes).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2017

NASA Advanced Computing Environment for Science and Engineering

Vision: To reach for new heights and reveal the unknown so that what we do and learn will benefit all humankind. Mission: To pioneer the future in space exploration, scientific discovery, and aeronautics research. Aeronautics Research (ARMD): Pioneer and prove new flight technologies for safer, more secure, efficient, and environmental friendly air transportation. Human Exploration and Operations (HEOMD): Focus on ISS operations; and develop new spacecraft and other capabilities for affordable, sustainable exploration beyond low Earth orbit. Science (SCMD): Explore the Earth, solar system, and universe beyond; chart best route for discovery; and reap the benefits of Earth and space exploration for society. Space Technology (STMD): Rapidly develop, demonstrate, and infuse revolutionary, high-payoff technologies through collaborative partnerships, expanding the boundaries of aerospace enterprise.

Biswas, Rupak↗

NASA NTRS2019

Paving the Way: The Influence of Early Research and Development Programs on Apollo, Saturn, and Legacy System Development

As we celebrate the 50th anniversary of the first successful human landings on the surface of the Moon in 1969, it is insightful to review the many historic accomplishments that contributed to this astounding human achievement. While the Apollo Program officially began following the charge by United States President John F. Kennedy in 1961, much of the foundation for Apollo was already underway with early research and development that began as early as the close of the second World War. Innovations and key decisions prior to the formal initiation of the Apollo Program, and even prior to the formation of the National Aeronautics and Space Administration (NASA), enabled the relatively rapid development of the Saturn V rocket, the Apollo capsule, and the Lunar Lander systems needed to achieve the goal of landing humans on the Moon and returning them safely to Earth by the close of the 1960s.

Cockrell, Charles E., Jr.↗

NASA NTRS2003

Web Program for Development of GUIs for Cluster Computers

WIGLAF (a Web Interface Generator and Legacy Application Facade) is a computer program that provides a Web-based, distributed, graphical-user-interface (GUI) framework that can be adapted to any of a broad range of application programs, written in any programming language, that are executed remotely on any cluster computer system. WIGLAF enables the rapid development of a GUI for controlling and monitoring a specific application program running on the cluster and for transferring data to and from the application program. The only prerequisite for the execution of WIGLAF is a Web-browser program on a user's personal computer connected with the cluster via the Internet. WIGLAF has a client/server architecture: The server component is executed on the cluster system, where it controls the application program and serves data to the client component. The client component is an applet that runs in the Web browser. WIGLAF utilizes the Extensible Markup Language to hold all data associated with the application software, Java to enable platform-independent execution on the cluster system and the display of a GUI generator through the browser, and the Java Remote Method Invocation software package to provide simple, effective client/server networking.

Czikmantory, Akos↗

NASA NTRS2005

A Facility for Testing High-Power Electric Propulsion Systems in Space: A Design Study

This paper will describe the results of the preliminary phase of a NASA design study for a facility to test high-power electric propulsion systems in space. The results of this design study are intended to provide a firm foundation for a subsequent detailed design and development activities leading to the deployment of a valuable space facility supporting the new vision of space exploration. The objectives for human and robotic exploration of space can be accomplished affordably, safely and effectively with high-power electric propulsion systems. But, as thruster power levels rise to the hundreds of kilowatts and up to megawatts, their testing will pose stringent and expensive demands on existing Earth-based vacuum facilities. These considerations and the access to near-Earth space provided by the International Space Station (ISS) have led to a renewed interest in space testing. The ISS could provide an excellent platform for a space-based test facility with the continuous vacuum conditions of the natural space environment and no chamber walls to modify the open boundary conditions of the propulsion system exhaust. The platform would be designed to accommodate the side-by-side testing of multiple types of electric thrusters currently under development and thus provide a strong basis for comparing their relative performance. The utility of testing on the station is further enhanced by the human presence, enabling close interaction with and modification of the test hardware in a true laboratory environment. These conditions facilitate rapid development and flight certification at potentially lower cost than with conventional Earth-bound facilities. As an added benefit, the propulsive effect of these tests could provide some drag compensation for the station, reducing the re-boost cost for the orbital facility. While it is expected that the ISS will not be capable of generating continuous levels of high power, the utilization of state-of-the-art energy storage media would be sufficient to achieve very high power levels over intervals short enough to be feasible and long enough to provide ample demonstration of steady-state operation. This paper will outline the results of the preliminary phase of the design study with emphasis on the requirements that will dictate the system design.

Petro, Andrew J.↗

NASA NTRS2001

Health Monitoring Technology for Thermal Protection Systems on Reusable Hypersonic Vehicles

Integrated subsystem health diagnostics is an area where major improvements have been identified for potential implementation into the design of new reusable launch vehicles (RLVs) in order to reduce life cycle costs, to increase safety margins, and to improve mission reliability. This talk summarizes a joint effort between NASA Ames and industry partners to develop rapid non-contact diagnostic tools for health and performance monitoring of thermal protection systems (TPS) on future RLVs. The specific goals for TPS health monitoring are to increase the speed and reliability of TPS inspections for improved operability at lower cost. The technology being developed includes a 3-D laser scanner for examining the exterior surface of the TPS, and a subsurface microsensor suite for monitoring the health and performance of the TPS. The sensor suite consists of passive overlimit sensors and sensors for continuous parameter monitoring in flight. The sensors are integrated with radio-frequency identification (RFID) microchips to enable wireless communication of-the sensor data to an external reader that may be a hand-held scanner or a large portal. Prototypes of the laser system and both types of subsurface sensors have been developed. The laser scanner was tested on Shuttle Orbiter Columbia and was able to dimension surface chips and holes on a variety of TPS materials. The temperature-overlimit microsensor has a diameter under 0.05 inch (suitable for placement in gaps between ceramic TPS tiles) and can withstand 700 F for 15 minutes.

Milos, Frank S.↗

NASA NTRS2021

Development of an Additive Manufacturing Ecosystem for Qualification of Additive Manufacturing Processes and Materials in Aviation

The major challenges associated with additive manufacturing (AM) are an ability to qualify parts and the costs associated with the technology. Our team will study and mature technologies as detailed below to develop an ecosystem for the qualification of AM machines, which in turn supports the certification of part production. Additive manufacturing offers unique opportunities for the aviation industry in the fabrication of original components and replacement parts. Aggressive use of metals AM has, for example, allowed the rapid development and production of new launch vehicle designs, at substantially reduced costs. Aviation has unique challenges, such as higher production volumes, but the potential value of integrating AM into aviation manufacturing is clear. To implement the ecosystem for AM qualification, the team will run a set of six multi-disciplinary projects. Each of these projects will address a current barrier to AM process qualification, and efficient production.

Koushik Datta↗

NASA NTRS2015

Assessing the Tangent Linear Behaviour of Common Tracer Transport Schemes and Their Use in a Linearised Atmospheric General Circulation Model

The linearity of a selection of common advection schemes is tested and examined with a view to their use in the tangent linear and adjoint versions of an atmospheric general circulation model. The schemes are tested within a simple offline one-dimensional periodic domain as well as using a simplified and complete configuration of the linearised version of NASA's Goddard Earth Observing System version 5 (GEOS-5). All schemes which prevent the development of negative values and preserve the shape of the solution are confirmed to have nonlinear behaviour. The piecewise parabolic method (PPM) with certain flux limiters, including that used by default in GEOS-5, is found to support linear growth near the shocks. This property can cause the rapid development of unrealistically large perturbations within the tangent linear and adjoint models. It is shown that these schemes with flux limiters should not be used within the linearised version of a transport scheme. The results from tests using GEOS-5 show that the current default scheme (a version of PPM) is not suitable for the tangent linear and adjoint model, and that using a linear third-order scheme for the linearised model produces better behaviour. Using the third-order scheme for the linearised model improves the correlations between the linear and non-linear perturbation trajectories for cloud liquid water and cloud liquid ice in GEOS-5.

Tangent Linear Model↗

DOE OSTI2025

Deciphering electrocatalysts with multimodal operando approaches

Here, the electrocatalytic processes of a copper catalyst during nitrate electroreduction are unveiled by correlated operando microscopy and spectroscopy. Catalysts are vital to the modern chemical industry, yet their development has largely relied on trial-and-error approaches. Optimizing catalysts requires a fundamental understanding of their structure–chemical property behaviour under operational conditions. However, operando characterization remains challenging, especially for reactions occurring in the complex and dynamic liquid environments of electrochemical systems. Over the past decade, the rapid development of in situ and operando environmental transmission electron microscopy (ETEM) and microelectromechanical system (MEMS)-based closed-cell holders, enabling environmental studies within the vacuum environment of transmission electron microscopy (TEM), has substantively advanced understanding of heterogeneous catalysis, notably for gas-phase reactions. In situ ETEM enables the direct observation of the catalyst evolution in terms of structure, morphology and chemical state at the nano-to-atomic scale, providing insights into their correlation with catalytic performance.

36 MATERIALS SCIENCE↗

DOE OSTI2024

GraphAide: Advanced Graph-Assisted Query and Reasoning System

Curating knowledge from multiple siloed sources that contain both structured and unstructured data is a major challenge in many real-world applications. Pattern matching and querying represent fundamental tasks in modern data analytics that leverage this curated knowledge. The development of such applications necessitates overcoming several research challenges, including data extraction, named entity recognition, data modeling, and designing query interfaces. Moreover, the explainability of these functionalities is critical for their broader adoption. The emergence of Large Language Models (LLMs) has accelerated the development lifecycle of new capabilities. Nonetheless, there is an ongoing need for domain-specific tools tailored to user activities. The creation of digital assistants has gained considerable traction in recent years, with LLMs offering a promising avenue to develop such assistants utilizing domain-specific knowledge and assumptions. In this context, we introduce an advanced query and reasoning system, GraphAide, which constructs a knowledge graph (KG) from diverse sources and allows to query and reason over the resulting KG. GraphAide harnesses both the KG and LLMs to rapidly develop domain-specific digital assistants. It integrates design patterns from retrieval augmented generation (RAG) and the semantic web to create an agentic LLM application. GraphAide underscores the potential for streamlined and efficient development of specialized digital assistants, thereby enhancing their applicability across various domains.

Purohit, Sumit [BATTELLE (PACIFIC NW LAB)] (ORCID:↗

DOE OSTI2025

Lessons Learned on Prize Design in the Perovskite Startup Prize

In 2018, the U.S. Department of Energy's Solar Energy Technologies Office and the National Renewable Energy Laboratory set out to develop a repeatable, predictable prize model with the American-Made Challenges. A new model launched by the Solar Energy Technologies Office in March 2021 was the American-Made Perovskite Startup Prize. This new prize aimed to accelerate the growth of the domestic perovskite industry and support the rapid development of solar cells and modules that use perovskite materials. By sharing the outputs of the prize, we hope that our lessons learned will help continue to build the clean tech entrepreneurship support ecosystem and influence how a successful prize design can be achieved.

14 SOLAR ENERGY↗

DOE OSTI2024

Developing Data-Driven Synthetic Infrastructure Models for Resilience Analysis

Research on infrastructure resilience has produced promising methods to simulate and optimize complex networks to improve performance. However, restrictions on sharing infrastructure models and the steep cost of developing and maintaining infrastructure models presents a roadblock to adoption. To overcome this limitation, this research focuses on methods to create data-driven infrastructure models that will help improve infrastructure resilience and security. The analysis couples incomplete utility data, geospatial data, machine learning, and synthetic network generation methods to rapidly develop and update infrastructure models. The methods are validated using realistic utility models and site-specific data, with a focus on Puerto Rico due to its unique infrastructure challenges and available data. This research highlights promising opportunities for the use of synthetic network generation and machine learning to create infrastructure models when very little data is available. Results demonstrate that hybrid methods, which combine sparse utility data with synthetic models, can enhance model accuracy, and machine learning can predict model attributes using training data from other models. However, the complexity of infrastructure systems means that even minor changes in network connectivity can significantly impact simulation results. Resilience analysis using synthetic infrastructure models shows that while some system behaviors are preserved, the magnitude of disruptions may not be accurately represented, indicating the need for more research and validation before using synthetic models for critical infrastructure investment decisions. The framework outlined in this report represents a significant advance to infrastructure model development and could be applied to additional domains and sites. Future research will continue to streamline and validate methods to help reduce roadblocks to resilience analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRSDate not supplied

TPSAS-NF1676L-21193-DND

Researchers at NASA Langley Research Center have been developing an automated pattern recognition algorithm to identify overshooting convective cloud tops (OTs) in support of the GOES-R satellite program. This algorithm identify regions of overshooting at the individual 1-4 km geostationary satellite pixel scale using visible (during daytime only) and infrared channel imagery and numerical weather analysis data. The algorithm has been developed based upon analysis of 0.25-1 km spatial resolution Aqua MODIS imagery, using a database of over 2000 manually identified OT features throughout the world in storms with varying intensity and morphology. The OT database includes storms ranging from small, warm topped cells in Alaska and Mongolia, tornadic supercells over the U.S. Central Plains and Europe, large tropical mesoscale convective systems, and overshooting in the eyewalls and spiral bands of category 5 tropical cyclones. This database is available for use by the research community. The algorithm is designed to operate on data from any current and historical satellite imager, allowing for development of a highly accurate global OT detection climatology that extends back into the 1990's at up to a 15-30 min temporal resolution throughout the diurnal cycle. As members of the McIDAS Users Group, NASA LaRC has immediate access to the full global archive of geostationary imager data which would allows rapid development of OT climatologies and short-term databases. This type of capability has never been available within the weather and climate research community. Regional geostationary OT databases have been already developed over CONUS during SEAC4RS, for 18-years over the Eastern U.S., and for 5-10 years over Australia, Europe, Southeast Asia, and East Africa among many other regions. Some of these datasets are being used by climate researchers and private industry to examine UTLS-penetrating storm spatial distributions and their temporal variability, in addition to weather hazards associated with these storms at unprecedented spatial detail. This presentation will describe the OT pattern recognition algorithm and highlight recent product applications.

Kristopher Bedka↗

NASA NTRS2016

Modeling and Simulation of Phased Array Antennas to Support Next-Generation Satellite Design

Developing enhanced simulation capabilities has become a significant priority for the Space Communications and Navigation (SCaN) project at NASA as new space communications technologies are proposed to replace aging NASA communications assets, such as the Tracking and Data Relay Satellite System (TDRSS). When developing the architecture for these new space communications assets, it is important to develop updated modeling and simulation methodologies, such that competing architectures can be weighed against one another and the optimal path forward can be determined. There have been many simulation tools developed here at NASA for the simulation of single RF link budgets, or for the modeling and simulation of an entire network of spacecraft and their supporting SCaN network elements. However, the modeling capabilities are never fully complete and as new technologies are proposed, gaps are identified. One such gap is the ability to rapidly develop high fidelity simulation models of electronically steerable phased array systems. As future relay satellite architectures are proposed that include optical communications links, electronically steerable antennas will become more desirable due to the reduction in platform vibration introduced by mechanically steerable devices. In this research, we investigate how modeling of these antennas can be introduced into out overall simulation and modeling structure. The ultimate goal of this research is two-fold. First, to enable NASA engineers to model various proposed simulation architectures and determine which proposed architecture meets the given architectural requirements. Second, given a set of communications link requirements for a proposed satellite architecture, determine the optimal configuration for a phased array antenna. There is a variety of tools available that can be used to model phased array antennas. To meet our stated goals, the first objective of this research is to compare the subset of tools available to us, trading-off modeling fidelity of the tool with simulation performance. When comparing several proposed architectures, higher- fidelity modeling may be desirable, however, when iterating a proposed set of communication link requirements across ranges of phased array configuration parameters, the practicality of performance becomes a significant requirement. In either case, a minimum simulation - fidelity must be met, regardless of performance considerations, which will be discussed in this research. Given a suitable set of phased array modeling tools, this research then focuses on integration with current SCaN modeling and simulation tools. While properly modeling the antenna elements of a system are vital, this is only a small part of the end-to-end communication path between a satellite and the supporting ground station and/or relay satellite assets. To properly model a proposed simulation architecture, this toolset must be integrated with other commercial and government development tools, such that the overall architecture can be examined in terms of communications, reliability, and cost. In this research, integration with previously developed communication tools is investigated.

Phased Array↗

NASA NTRSDate not supplied

Pathfinder Technology Demonstrator (PTD) Status

This paper will provide the status of the NASA Small Spacecraft Technology (SST) program’s Pathfinder Technology Demonstrator (PTD) series. Details on the development, launch, and operations of the recently completed PTD-1, as well as the planned operations of the upcoming PTD-3 and PTD-4 flights will be presented. Significant advances in the capabilities of nano-spacecraft over the past 15 years, coupled with improved access to space for CubeSats, have created new opportunities for scientific exploration using these high-value platforms. Continued development and demonstration of key technologies are improving the performance of the 1-unit (U) and 3U class CubeSats while expanding the reach of nano-spacecraft technologies into larger platforms, such as the 12-kilogram class “6U” buses. NASA’s PTD series is demonstrating a variety of new technologies on-orbit, providing proof of the maturity of these significant new technologies, and enhancing the performance of future CubeSats. Each of the four PTD flights consists of one 6U CubeSat weighing approximately 12 kilograms and measuring approximately 36 centimeters x 25 centimeters x 10 centimeters. Each flight is planned to characterize its payload within 90 days of insertion into low-Earth orbit. The PTD flights will demonstrate key technologies such as novel nano-spacecraft compatible propulsion systems, which enable deep space and maneuverable CubeSat flights; optical communications systems to facilitate high data rate collection and communications; and highly integrated systems that combine power and communication system elements to enable high power generation and novel integrated communication systems. The first PTD spacecraft, PTD-1, was placed in orbit by a SpaceX Falcon 9 launch in January of 2021 and demonstrated the functionality of the HYDROS propulsion system, developed by Tethers Unlimited of Bothell, Washington, over a period of six months. The PTD-3 flight, scheduled for launch in summer 2022, will demonstrate the TeraByte InfraRed Delivery, or TBIRD, optical communications payload developed by Massachusetts Institute of Technology Lincoln Laboratory in Lexington. The PTD-4 flight will demonstrate the Lightweight Integrated Solar Array and anTenna, or LISA-T, a payload that consists of an integrated solar array and transceiver developed by NASA’s Marshall Spaceflight Center in Huntsville, Alabama. The PTD spacecraft bus, integration and test, and flight operations services are provided by Tyvak Nano-Satellite Systems, Inc. (“Tyvak”) of Irvine, California. NASA’s SST program within the agency’s Space Technology Mission Directorate funds the PTD demonstration flights. The SST program rapidly develops and demonstrates capabilities for small spacecraft applicable to exploration, science, and the commercial sector. The program is based at NASA’s Ames Research Center.

Small Spacecraft↗

NASA NTRS2013

Towards a Decision Support System for Space Flight Operations

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The discrepancy of the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the three increments of this vision. These increments include (1) hardware and software system components and interfaces with the NASA ground system, (2) uncertainty management and (3) re-planning and automated execution. Each of these increments provide value independently; but some may also enable building of a subsequent increment.

Meshkat, Leila↗

NASA NTRS2013

Towards a decision support system for space flight operations

The Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) has put in place a Model Based Systems Engineering (MBSE) technological framework for the development and execution of the Flight Production Process (FPP). This framework has provided much added value and return on investment to date. This paper describes a vision for a model based Decision Support System (DSS) for the development and execution of the FPP and its design and development process. The envisioned system extends the existing MBSE methodology and technological framework which is currently in use. The MBSE technological framework currently in place enables the systematic collection and integration of data required for building an FPP model for a diverse set of missions. This framework includes the technology, people and processes required for rapid development of architectural artifacts. It is used to build a feasible FPP model for the first flight of spacecraft and for recurrent flights throughout the life of the program. This model greatly enhances our ability to effectively engage with a new customer. It provides a preliminary work breakdown structure, data flow information and a master schedule based on its existing knowledge base. These artifacts are then refined and iterated upon with the customer for the development of a robust end-to-end, high-level integrated master schedule and its associated dependencies. The vision is to enhance this framework to enable its application for uncertainty management, decision support and optimization of the design and execution of the FPP by the program. Furthermore, this enhanced framework will enable the agile response and redesign of the FPP based on observed system behavior. The differences between the anticipated system behavior and the observed behavior may be due to the processing of tasks internally, or due to external factors such as changes in program requirements or conditions associated with other organizations that are outside of MOD. The paper provides a roadmap for the four increments of this vision. These increments include (1) the existing capabilities (2) hardware and software system components and interfaces with the NASA ground system, (3) uncertainty management and (4) re-planning and automated execution. Each of these increments provides value independently; but some may also enable building of a subsequent increment.

Ruszkowski, James↗