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NASA NTRS2011

Habitat Demonstration Unit Project: Leadership and Management Strategies for a Rapid Prototyping Project

This paper gives an overview of the National Aeronautics and Space Administration (NASA) led multi-center Habitat Demonstration Unit (HDU) project leadership and management strategies being used by the NASA HDU team for a rapid prototyping project. The HDU project team constructed and tested an analog prototype lunar surface habitat/laboratory called the Pressurized Excursion Module (PEM) during 2010. The prototype unit subsystems were integrated in a short amount of time, utilizing a tiger team rapid prototyping approach that brought together over 20 habitation-related technologies and innovations from a variety of NASA centers. This paper describes the leadership and management strategies as well as lessons learned pertaining to leading and managing a multi-center diverse team in a rapid prototype environment. The PEM configuration went from a paper design to an operational surface habitat demonstration unit in less than 12 months. The HDU project is part of the strategic plan from the Exploration Systems Mission Directorate (ESMD) Directorate Integration Office (DIO) and the Exploration Mission Systems Office (EMSO) to test destination elements in analog environments. The 2011 HDU-Deep Space Habitat (DSH) configuration will build upon the PEM work, and emphasize validity of crew operations (remote working and living), EVA operations, mission operations, logistics operations, and science operations that might be required in a deep space context for Near Earth Object (NEO) exploration mission architectures. The 2011 HDU-DSH will be field-tested during the 2011 Desert Research and Technologies Studies (DRaTS) field tests. The HDU project is a "technology-pull" project that integrates technologies and innovations from multiple NASA centers. This project will repurpose the HDU 2010 demo unit that was field tested in the 2010 DRaTS, adding habitation functionality to the prototype unit. This paper will describe the strategy of establishing a multi-center project management team that put in place the key multi-center leadership skills and disciplines to enable a successful tiger team approach. Advocacy was established with key stakeholders and NASA Headquarters (HQ) by defining a strategic vision, mission, goals and objectives for the project and team. As a technology-pull testbed capability the HDU project was able to collaborate and leverage the Exploration Technology Development Program (ETDP) and individual NASA center investments which capitalized on their respective center core competencies and skills. This approach enable the leveraging of over $7.5m of value to create an operational habitat demonstration unit 2010 PEM configuration.

Kennedy, Kriss J.↗

NASA NTRS2012

The Design of Large-Scale Complex Engineered Systems: Present Challenges and Future Promise

Model-Based Systems Engineering techniques are used in the SE community to address the need for managing the development of complex systems. A key feature of the MBSE approach is the use of a model to capture the requirements, architecture, behavior, operating environment and other key aspects of the system. The focus on the model differentiates MBSE from traditional SE techniques that may have a document centric approach. In an effort to assess the benefit of utilizing MBSE on its flight projects, NASA Langley has implemented a pilot program to apply MBSE techniques during the early phase of the Materials International Space Station Experiment-X (MISSE-X). MISSE-X is a Technology Demonstration Mission being developed by the NASA Office of the Chief Technologist i . Designed to be installed on the exterior of the International Space Station (ISS), MISSE-X will host experiments that advance the technology readiness of materials and devices needed for future space exploration. As a follow-on to the highly successful series of previous MISSE experiments on ISS, MISSE-X benefits from a significant interest by the

Bloebaum, Christina L.↗

NASA NTRS2012

Cognitive Bias in Systems Verification

Working definition of cognitive bias: Patterns by which information is sought and interpreted that can lead to systematic errors in decisions. Cognitive bias is used in diverse fields: Economics, Politics, Intelligence, Marketing, to name a few. Attempts to ground cognitive science in physical characteristics of the cognitive apparatus exceed our knowledge. Studies based on correlations; strict cause and effect is difficult to pinpoint. Effects cited in the paper and discussed here have been replicated many times over, and appear sound. Many biases have been described, but it is still unclear whether they are all distinct. There may only be a handful of fundamental biases, which manifest in various ways. Bias can effect system verification in many ways . Overconfidence -> Questionable decisions to deploy. Availability -> Inability to conceive critical tests. Representativeness -> Overinterpretation of results. Positive Test Strategies -> Confirmation bias. Debiasing at individual level very difficult. The potential effect of bias on the verification process can be managed, but not eliminated. Worth considering at key points in the process.

Cognitive bias↗

NASA NTRS2015

Off Grid Photovoltaic Wastewater Treatment and Management Lagoons

The SSC wastewater treatment system is comprised of key components that require a constant source of electrical power or diesel fuel to effectively treat the wastewater. In alignment with the President's new Executive Order 13653, Planning for Federal Sustainability in the Next Decade, this project aims to transform the wastewater treatment system into a zero emissions operation by incorporating the advantages of an off grid, photovoltaic system. Feasibility of implementation will be based on an analytical evaluation of electrical data, fuel consumption, and site observations.

LaPlace, Lucas A.↗

NASA NTRS2020

Key Opportunities in Aeronautics Enterprise

Opportunities in Aerospace for airspace management and aerospace manufacturing as more aircraft for new operations and automation are developed and introduced into the national airspace. This presentation is meant to inspire student aspirations and entrance into the aerospace industry.

Kopardekar, Parimal↗

NASA NTRS2013

TPSAS-NF1676L-17243-DND

This presentation captures ERA Project's effort in using integrated cost-schedule-risk analysis tool, identifying and capturing explicit relationships between program funds, schedule, and discrete risks. The project team merged a myriad of cost and schedule data for timely, objective, uncertainty analysis of the ITD's budget and schedule. The project team conducted detailed schedule uncertainty analysis showing schedule activities and how their interrelationships were impacted, representing an impressive advance beyond routine Gantt charts. Furthermore, the ERA Project collected discrete risk events including their impacts to costs and/or schedule and interwove these risks into cost and schedule logic networks, providing the foundation to conduct cost and schedule analyses. The team integrated this data into the analysis model, providing probabilistic results that were then used by the ERA Project's senior management for decision-making purposes. The ERA Project management team, through technical and pathfinder expertise in integrating cost, schedule, risk, and technical content, consistently provided risk-informed recommendations to Implementing Centers and ISRP senior management which ultimately ensured the successful ARMD Key Decision Point (KDP) review of the ERA Phase 2 ITD Portfolio and increased the likelihood of achieving technical objectives within cost and schedule constraints.

Gaudy M Bezos-O'Connor↗

NASA NTRSDate not supplied

Advancing Autonomy in Distributed Space Systems: Insights From on-Orbit Testing with the Starling 1.0 Mission

Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.

Caleb Ashmore Adams↗

NASA NTRSDate not supplied

Innovations in Distributed Spacecraft Autonomy

The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in distributed space systems through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. This talk describes recent successes of the DSA experiment onboard the Starling 1.0 mission.

Caleb Adams↗

NASA NTRS2008

Infusing Stretch Goal Requirements into the Constellation Program

In 2004, the Vision for Space Exploration (VSE) was announced by the United States President's Administration in an effort to explore space and to extend a human presence across our solar system. Subsequently, the National Aeronautics and Space Administration (NASA) established the Exploration Systems Mission Directorate (ESMD) to develop a constellation of new capabilities, supporting technologies, and foundational research that allows for the sustained and affordable exploration of space. Then, ESMD specified the primary mission for the Constellation Program to carry out a series of human expeditions, ranging from Low Earth Orbit (LEO) to the surface of Moon, Mars, and beyond for the purposes of conducting human exploration of space. Thus, the Constellation Program was established at the Lyndon B. Johnson Space Center (JSC) to manage the development of the flight and ground infrastructure and systems that can enable continued and extended human access to space. Constellation Program's "Design Objectives" call for an early attention to the program's life cycle costs management through the Program's Need, Goals, and Objectives (NGO) document, which provides the vision, scope, and key areas of focus for the Program. One general policy of the Constellation Program, found in the Constellation Architecture Requirements Document (CARD), states: "A sustainable program hinges on how effectively total life cycle costs are managed. Developmental costs are a key consideration, but total life cycle costs related to the production, processing, and operation of the entire architecture must be accounted for in design decisions sufficiently to ensure future resources are available for ever more ambitious missions into the solar system....It is the intent of the Constellation Program to aggressively manage this aspect of the program using the design policies and simplicity." To respond to the Program's strong desire to manage the program life cycle costs, special efforts were established to identify operability requirements to influence flight vehicle and ground infrastructure design in order to impact the life cycle operations costs, and stretch goal requirements were introduced to the Program. This paper will describe how these stretch goal requirements were identified, developed, refined, matured, approved, and infused into the CARD. The paper will also document several challenges encountered when infusing the stretch goal requirements into the Constellation Program.

Operability↗

NASA NTRSDate not supplied

Can We Model Forest Demography Globally? Benchmarking of State-of-the-Art Demographic DGVMs

Forests in Dynamic Global Vegetation Models (DGVMs) have historically been simulated as area-averaged plant functional types in each gridcell instead of representing communities of trees of different sizes and ages (demography). Just as the behaviour of a tree differs according to its ontogeny, so the behaviour of forests is known to differ depending on their demography. Accurately simulating demography is therefore key in order to address questions on afforestation and management strategies, as well as assessments of resilience of forests to disturbances such as drought and fire or diversity changes after a disturbance. Ultimately, demography determines the overall forest biomass in natural forests and is a key arbiter of growth and mortality rates. DGVMs are now able to simulate size and age structure of the trees in forests. However, these models have so far not been benchmarked alongside each other. We evaluate 6 DGVMs (BiomeE, CABLE-POP, FATES, LPJ-GUESS, JULES-RED, ORCHIDEE) against observations on regrowth dynamics as well as natural forests at boreal, temperate and tropical sites. We examine whether the models capture observed regrowth dynamics after disturbance, well-known stand size structure and well-established processes such as self-thinning. We outline the planned route forward towards a standardised international benchmarking framework for demographic DGVMs.

Dynamic Global Vegetation Models↗

NASA NTRS2018

History and Archives Contribute to the Success of Space Flight Programs

Final Paper, not the Abstract, is attached: This report discusses how history can be used by management, engineering, and operations personnel within space flight programs. Works by professional historians and sociologists inform key decision makers and policy specialists on lessons learned from space flight program management successes and failures, as well as from legislative affairs, policy making, and commercial space efforts. Vehicle engineering history written by engineers for an engineering or operations audience informs project management and technical personnel on lessons learned, best practices, and the rationale behind the design and operation of flight vehicles and supporting ground systems. Archives play a critical role in supporting the efforts of both professional historians and flight program personnel. Suggestions are made concerning how professional historians could leverage the interests and knowledge of flight program personnel to obtain more insight that is needed to support historical research efforts.

Archive↗

NASA NTRS2018

An Integrated Platform for Mission Performance: Goddard Space Flight Center's Meta Information System

Successful management of NASA Goddard Space Flight Centers portfolio of mission projects (i.e. spacecraft, spacecraft instruments / subsystems, and ground systems) depends upon numerous processes, data and information resources coming together throughout the life-cycle of the projects to enable sound decision-making, risk reduction, conformance with requirements and continual improvement. In the summer of 2012, GSFC SMA management recognized that the set of legacy data systems used to support the SMA mission and responsibilities at GSFC were not effective, integrated nor on par with best practices. Accordingly, GSFC SMA management launched a project to transform the GSFC electronic management system to create and deploy an integrated, state-of-the-market information system for process performance, data management and analytics that is currently operating in support of GSFC overall mission performance. The information system, known as Meta, provides controlled, process-based applications, integrated data management, and analytics for a robust set of integrated applications. Since the inception of the project, a lean, award-winning SMA project team has thus far designed, configured and managed the system to serve as an integrated platform for 18 applications that support key processes for GSFC and the Science Mission Directorate at NASA headquarters, such as internal Management System assessments, Supplier Assessments, Supplier Research & Analysis, Problem Reporting for in-house mission projects, On-orbit Anomaly Reporting for GSFC-operated spacecraft, GSFC Project Life-Cycle Reviews, Risk Management and Reporting, and SMA Project Team Reporting. The system has experienced steady growth in utilization with 1,917 users (NASA employees and support contractor personnel) and 44 gigabytes of data and related files managed by the system as of the end of April 2018. Overall, Meta has achieved increasing levels of process management and real-time data / information integration to enable improved process performance, richer analytics and informed decision-making. This paper will present and examine the need, goals, approach and design driving the management and operation of the Meta information system and its ongoing growth as an integrated platform for advancing NASA mission performance.

Integration↗

NASA NTRSDate not supplied

Splashdown Visualization of Spent Stages

The state of the art for many Earth-to-orbit trajectory analysis toolsets used at NASA is somewhat dated in terms of the languages they are written in and their user interfaces. Many of these programs are written in languages like Fortran or C that are no longer considered modern in the technology industry, and are command-line based without any means of interpreting the data outputs. This presentation is meant to demonstrate a specific use case for a newly developed web app that visualizes the output data for one of these tools. Specifically, one key usage is to investigate and validate launches for notional multi-stage vehicle concepts to various non-standard high-inclination orbits. Some NASA requirements dictate that trajectories be designed such that no surviving debris lands closer than 200 nautical miles (nm) from foreign landmasses or 27 nm from the continental United States, therefore validating re-entry locations of spent stages is an integral part of the launch planning process. In addition, at programmatic levels it can prove insightful and clarifying for the decision-making process to enhance the technical results of numerical simulations with visualizations. The intent with this tool is to provide the mission analyst and program level management with an intuitive and clear grasp of key information on possible mission scenarios either departing from or arriving at Earth, and in the future, the moon or Mars as well. The software tool was developed with an agile development approach and utilizes the latest frameworks and technologies. The front end uses the React JavaScript library for making a state of the art frontend and a backend based on the Django Python framework for handling data using Python’s powerful and free scientific libraries. In addition, the CesiumJS open-source library is key for visualizing these end-to-end trajectories on a high-resolution Earth model. The presentation will demonstrate the current capability and tested use cases.

Jack Agolli↗

NASA NTRS1996

Translating Research Into Airline Practice: Case Studies In Collaboration

Airline training departments are avid customers for research that will help them enhance the effectiveness of training and the safety of flight operations. However, various factors often make it difficult for training department managers to draw upon the large body of human factors research, e.g.: research may not address the specific questions facing the training departments, the research literature may not be in a form that training managers can readily interpret, researchers' recommendations may be too expensive or impractical to implement, etc. This panel will discuss ways in which researchers can work with training departments to design research and translate findings into products that airlines can use readily. This collaboration is most effective when it is an integral part of the study from its inception. To illustrate the process of collaboration we will use as a case study the recently completed LOFT (Line Oriented Flight Training) Debriefing research project. We will summarize the findings from that study and discuss how we translated those findings into two training tools: a manual on how to facilitate LOFT debriefings and a video that illustrates facilitation techniques in a realistically enacted debriefing. In some cases, instead of starting a new research project, training department needs can be addressed by reviewing the existing research literature and using expert opinion to develop products that specifically address those needs. To illustrate this approach we will discuss a recent informal working group of scientists and airline personnel that met to develop training material to enhance situation awareness. This group reviewed scientific literature and ASRS (Aviation Safety Reporting System) reports, analyzed contributing factors, and produced a model for managing situation awareness.

Dismukes, R. Key↗

NASA NTRSDate not supplied

Building Capacity to Use Earth Observations for Water Resource Management Applications: A Summary of NASA’s DEVELOP Program and Projects in Central and South America

NASA’s DEVELOP program engages individuals and organizations in 10-week feasibility studies to apply NASA Earth observations (EO) to decision makers’ needs. Since 2018, DEVELOP conducted 21 projects in Central and South America, eight of those in collaboration with Sistema de la Integración Centroamericana (SICA) and its member state partner agencies. These projects addressed a diverse set of community needs across multiple themes, including five that explored the use of both spaceborne and airborne EO to assess coastal water quality related to SDG monitoring of natural resources in Belize and Honduras, evaluating evapotranspiration and water balance in Argentina, and characterizing vegetation water use for informed water management in Panama. This poster introduces DEVELOP, its approach to capacity building, key partnerships, and project results highlighting the capabilities of EO for enhanced decision making in the area of sustainable water management.

Capacity Building↗

NASA NTRS2014

A Physics-Based Modeling Framework for Prognostic Studies

Prognostics and Health Management (PHM) methodologies have emerged as one of the key enablers for achieving efficient system level maintenance as part of a busy operations schedule, and lowering overall life cycle costs. PHM is also emerging as a high-priority issue in critical applications, where the focus is on conducting fundamental research in the field of integrated systems health management. The term diagnostics relates to the ability to detect and isolate faults or failures in a system. Prognostics on the other hand is the process of predicting health condition and remaining useful life based on current state, previous conditions and future operating conditions. PHM methods combine sensing, data collection, interpretation of environmental, operational, and performance related parameters to indicate systems health under its actual application conditions. The development of prognostics methodologies for the electronics field has become more important as more electrical systems are being used to replace traditional systems in several applications in the aeronautics, maritime, and automotive fields. The development of prognostics methods for electronics presents several challenges due to the great variety of components used in a system, a continuous development of new electronics technologies, and a general lack of understanding of how electronics fail. Similarly with electric unmanned aerial vehicles, electrichybrid cars, and commercial passenger aircraft, we are witnessing a drastic increase in the usage of batteries to power vehicles. However, for battery-powered vehicles to operate at maximum efficiency and reliability, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. We develop an electrochemistry-based model of Li-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles.

Li-ion Batteries↗

NASA NTRS2024

NASA Engineering and Safety Center Lunar Rover Design Concepts Assessments

Mass is a significant risk to programs and projects as they transition from formulation to implementation, especially in larger human space systems where delivery mass or volume can be a constrained commodity. • Concepts developed without an adequate systems-engineering basis, including design and operations experience, may miss significant functionality and subsequent mass required for integration or operations. • Further uncertainty can be associated with not fully understanding design best practices and standards that drive mass, such as design for minimum risk or fault tolerance.1 • Finally, the appropriate systems engineering mass properties management rigor and technical discipline insight are required to set the mass baseline, including appropriate mass growth allowance (MGA) to ensure program success. Mass is a key quantity that should be constantly monitored by the systems engineer and the program/project management stakeholder to ensure mission compatibility throughout the project life cycle. In addition, mass is a key programmatic performance metric monitored by the NASA Chief Financial Officer for current and future program cost estimating. NASA Exploration Systems sought an assessment of reasonableness with respect to different potential rover concepts that balances mass needs and human-class cargo lander capabilities. Appropriate systems engineering mass properties management rigor and technical discipline insight were used, and are required to set the mass baseline, including appropriate MGA to ensure program success. Two independent Lunar rover concepts were evaluated, with a goal to understand concept credibility and the Lunar rover designs potential extensibility for Mars surface operations. A notional generic rover concept is shown in Figure 1.

Systems Engineering↗

NASA NTRS1986

An architecture for intelligent interfaces - Outline of an approach to supporting operators of complex systems

The conceptual design of a comprehensive support system for operators of complex systems is presented. Key functions within the support system architecture include information management, error monitoring, and adaptive aiding. One of the central knowledge bases underlying this functionality is an operator model that involves a 'matrix' of algorithmic and symbolic models for assessing and predicting an operator's activities, awareness resources, intentions, and performance. Functional block diagrams are presented for the overall architecture as well as the key elements within this architecture. A variety of difficult design issues are discussed and ongoing efforts aimed at resolving these issues are noted.

Rouse, W. B.↗