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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 NTRS2010

Analysis of Dependencies and Impacts of Metroplex Operations

This report documents research performed by Purdue University under subcontract to the George Mason University (GMU) for the Metroplex Operations effort sponsored by NASA's Airportal Project. Purdue University conducted two tasks in support of the larger efforts led by GMU: a) a literature review on metroplex operations followed by identification and analysis of metroplex dependencies, and b) the analysis of impacts of metroplex operations on the larger U.S. domestic airline service network. The tasks are linked in that the ultimate goal is an understanding of the role of dependencies among airports in a metroplex in causing delays both locally and network-wide. The Purdue team has formulated a system-of-systems framework to analyze metroplex dependencies (including simple metrics to quantify them) and develop compact models to predict delays based on network structure. These metrics and models were developed to provide insights for planners to formulate tailored policies and operational strategies that streamline metroplex operations and mitigate delays and congestion.

DeLaurentis, Daniel A.↗
NASA NTRS2010

Propulsion Technology Lifecycle Operational Analysis

The paper presents the results of a focused effort performed by the members of the Space Propulsion Synergy Team (SPST) Functional Requirements Sub-team to develop propulsion data to support Advanced Technology Lifecycle Analysis System (ATLAS). This is a spreadsheet application to analyze the impact of technology decisions at a system-of-systems level. Results are summarized in an Excel workbook we call the Technology Tool Box (TTB). The TTB provides data for technology performance, operations, and programmatic parameters in the form of a library of technical information to support analysis tools and/or models. The lifecycle of technologies can be analyzed from this data and particularly useful for system operations involving long running missions. The propulsion technologies in this paper are listed against Chemical Rocket Engines in a Work Breakdown Structure (WBS) format. The overall effort involved establishing four elements: (1) A general purpose Functional System Breakdown Structure (FSBS). (2) Operational Requirements for Rocket Engines. (3) Technology Metric Values associated with Operating Systems (4) Work Breakdown Structure (WBS) of Chemical Rocket Engines The list of Chemical Rocket Engines identified in the WBS is by no means complete. It is planned to update the TTB with a more complete list of available Chemical Rocket Engines for United States (US) engines and add the Foreign rocket engines to the WBS which are available to NASA and the Aerospace Industry. The Operational Technology Metric Values were derived by the SPST Sub-team in the form of the TTB and establishes a database for users to help evaluate and establish the technology level of each Chemical Rocket Engine in the database. The Technology Metric Values will serve as a guide to help determine which rocket engine to invest technology money in for future development.

Robinson, John W.↗
NASA NTRS2005

Transformational Spaceport and Range Concept of Operations: A Vision to Transform Ground and Launch Operations

The Transformational Concept of Operations (CONOPS) provides a long-term, sustainable vision for future U.S. space transportation infrastructure and operations. This vision presents an interagency concept, developed cooperatively by the Department of Defense (DoD), the Federal Aviation Administration (FAA), and the National Aeronautics and Space Administration (NASA) for the upgrade, integration, and improved operation of major infrastructure elements of the nation s space access systems. The interagency vision described in the Transformational CONOPS would transform today s space launch infrastructure into a shared system that supports worldwide operations for a variety of users. The system concept is sufficiently flexible and adaptable to support new types of missions for exploration, commercial enterprise, and national security, as well as to endure further into the future when space transportation technology may be sufficiently advanced to enable routine public space travel as part of the global transportation system. The vision for future space transportation operations is based on a system-of-systems architecture that integrates the major elements of the future space transportation system - transportation nodes (spaceports), flight vehicles and payloads, tracking and communications assets, and flight traffic coordination centers - into a transportation network that concurrently accommodates multiple types of mission operators, payloads, and vehicle fleets. This system concept also establishes a common framework for defining a detailed CONOPS for the major elements of the future space transportation system. The resulting set of four CONOPS (see Figure 1 below) describes the common vision for a shared future space transportation system (FSTS) infrastructure from a variety of perspectives.

Source record↗
NASA NTRS2012

NASA Tech Briefs, March 2012

The topics include: 1) Spectral Profiler Probe for In Situ Snow Grain Size and Composition Stratigraphy; 2) Portable Fourier Transform Spectroscopy for Analysis of Surface Contamination and Quality Control; 3) In Situ Geochemical Analysis and Age Dating of Rocks Using Laser Ablation-Miniature Mass Spectrometer; 4) Physics Mining of Multi-Source Data Sets; 5) Photogrammetry Tool for Forensic Analysis; 6) Connect Global Positioning System RF Module; 7) Simple Cell Balance Circuit; 8) Miniature EVA Software Defined Radio; 9) Remotely Accessible Testbed for Software Defined Radio Development; 10) System-of-Systems Technology-Portfolio-Analysis Tool; 11) VESGEN Software for Mapping and Quantification of Vascular Regulators; 12) Constructing a Database From Multiple 2D Images for Camera Pose Estimation and Robot Localization; 13) Adaption of G-TAG Software for Validating Touch and Go Asteroid Sample Return Design Methodology; 14) 3D Visualization for Phoenix Mars Lander Science Operations; 15) RxGen General Optical Model Prescription Generator; 16) Carbon Nanotube Bonding Strength Enhancement Using Metal Wicking Process; 17) Multi-Layer Far-Infrared Component Technology; 18) Germanium Lift-Off Masks for Thin Metal Film Patterning; 19) Sealing Materials for Use in Vacuum at High Temperatures; 20) Radiation Shielding System Using a Composite of Carbon Nanotubes Loaded With Electropolymers; 21) Nano Sponges for Drug Delivery and Medicinal Applications; 22) Molecular Technique to Understand Deep Microbial Diversity; 23) Methods and Compositions Based on Culturing Microorganisms in Low Sedimental Fluid Shear Conditions; 24) Secure Peer-to-Peer Networks for Scientific Information Sharing; 25) Multiplexer/Demultiplexer Loading Tool (MDMLT); 26) High-Rate Data-Capture for an Airborne Lidar System; 27) Wavefront Sensing Analysis of Grazing Incidence Optical Systems; 28) Foam-on-Tile Damage Model; 29) Instrument Package Manipulation Through the Generation and Use of an Attenuated-Fluent Gas Fold; 30) Multicolor Detectors for Ultrasensitive Long-Wave Imaging Cameras; 31) Lunar Reconnaissance Orbiter (LRO) Command and Data Handling Flight Electronics Subsystem; and 32) Electro-Optic Segment-Segment Sensors for Radio and Optical Telescopes.

Source record↗
NASA NTRS2012

System-of-Systems Technology-Portfolio-Analysis Tool

Advanced Technology Life-cycle Analysis System (ATLAS) is a system-of-systems technology-portfolio-analysis software tool. ATLAS affords capabilities to (1) compare estimates of the mass and cost of an engineering system based on competing technological concepts; (2) estimate life-cycle costs of an outer-space-exploration architecture for a specified technology portfolio; (3) collect data on state-of-the-art and forecasted technology performance, and on operations and programs; and (4) calculate an index of the relative programmatic value of a technology portfolio. ATLAS facilitates analysis by providing a library of analytical spreadsheet models for a variety of systems. A single analyst can assemble a representation of a system of systems from the models and build a technology portfolio. Each system model estimates mass, and life-cycle costs are estimated by a common set of cost models. Other components of ATLAS include graphical-user-interface (GUI) software, algorithms for calculating the aforementioned index, a technology database, a report generator, and a form generator for creating the GUI for the system models. At the time of this reporting, ATLAS is a prototype, embodied in Microsoft Excel and several thousand lines of Visual Basic for Applications that run on both Windows and Macintosh computers.

O'Neil, Daniel↗
NASA NTRS2012

Architecting the Human Space Flight Program with Systems Modeling Language (SysML)

The next generation of missions in NASA's Human Space Flight program focuses on the development and deployment of highly complex systems (e.g., Orion Multi-Purpose Crew Vehicle, Space Launch System, 21st Century Ground System) that will enable astronauts to venture beyond low Earth orbit and explore the moon, near-Earth asteroids, and beyond. Architecting these highly complex system-of-systems requires formal systems engineering techniques for managing the evolution of the technical features in the information exchange domain (e.g., data exchanges, communication networks, ground software) and also, formal correlation of the technical architecture to stakeholders' programmatic concerns (e.g., budget, schedule, risk) and design development (e.g., assumptions, constraints, trades, tracking of unknowns). This paper will describe how the authors have applied System Modeling Language (SysML) to implement model-based systems engineering for managing the description of the End-to-End Information System (EEIS) architecture and associated development activities and ultimately enables stakeholders to understand, reason, and answer questions about the EEIS under design for proposed lunar Exploration Missions 1 and 2 (EM-1 and EM-2).

scheduling↗
NASA NTRS2014

Modeling for Integrated Science Management and Resilient Systems Development

Many physiological, environmental, and operational risks exist for crewmembers during spaceflight. An understanding of these risks from an integrated perspective is required to provide effective and efficient mitigations during future exploration missions that typically have stringent limitations on resources available, such as mass, power, and crew time. The Human Research Program (HRP) is in the early stages of developing collaborative modeling approaches for the purposes of managing its science portfolio in an integrated manner to support cross-disciplinary risk mitigation strategies and to enable resilient human and engineered systems in the spaceflight environment. In this talk, we will share ideas being explored from fields such as network science, complexity theory, and system-of-systems modeling. Initial work on tools to support these explorations will be discussed briefly, along with ideas for future efforts.

Shelhamer, M.↗
NASA NTRS2009

Layered Systems Engineering Engines

A notation is described for depicting the relationships between multiple, contemporaneous systems engineering efforts undertaken within a multi-layer system-of-systems hierarchy. We combined the concepts of remoteness of activity from the end customer, depiction of activity on a timeline, and data flow to create a new kind of diagram which we call a "Layered Vee Diagram." This notation is an advance over previous notations because it is able to be simultaneously precise about activity, level of granularity, product exchanges, and timing; these advances provide systems engineering managers a significantly improved ability to express and understand the relationships between many systems engineering efforts. Using the new notation, we obtain a key insight into the relationship between project duration and the strategy selected for chaining the systems engineering effort between layers, as well as insights into the costs, opportunities, and risks associated with alternate chaining strategies.

Vee Diagram↗
NASA NTRS2017

System-of-Systems Considerations in the Notional Development of a Metropolitan Aerial Transportation System

There are substantial future challenges related to sustaining and improving efficient, cost-effective, and environmentally friendly transportation options for urban regions. Over the past several decades there has been a worldwide trend towards increasing urbanization of society. Accompanying this urbanization are increasing surface transportation infrastructure costs and, despite public infrastructure investments, increasing surface transportation "gridlock." In addition to this global urbanization trend, there has been a substantial increase in concern regarding energy sustainability, fossil fuel emissions, and the potential implications of global climate change. A recently completed study investigated the feasibility of an aviation solution for future urban transportation (refs. 1, 2). Such an aerial transportation system could ideally address some of the above noted concerns related to urbanization, transportation gridlock, and fossil fuel emissions (ref. 3). A metro/regional aerial transportation system could also provide enhanced transportation flexibility to accommodate extraordinary events such as surface (rail/road) transportation network disruptions and emergency/disaster relief responses.

Alonso, Juan J.↗
NASA NTRS2017

Machine Learning Approaches to Increasing Value of Spaceflight Omics Databases

The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may soon enable unique insight into which measured phenomena correlate to biological mechanisms that are truly affected by spaceflight conditions; which are most likely to be confounded by other variables; and which are insufficiently characterized, significantly increasing existing and future science return from ISS and spaceflight missions.

Gentry, Diana↗
NASA NTRS2018

Impacts on High-level Systems-of-Systems Figures of Merit due to Integrated Architecture Sizing and Technology Evaluation at the Subsystem-Level

Understanding the impacts on high-level system-of-systems (SOS) figures of merit (FOMs) due to the design of architectures and technologies is critical in providing decision makers sufficient information in selecting suitable alternatives in an effort to reduce costly financial and schedule overruns. Several techniques exist within academia and industry for performing SOS architecture design and technology evaluation. However, these techniques fail to solve the problem in an integrated fashion when defined at the subsystem-level. In order to understand the impacts on high-level SOS FOMs due to integrated architecture sizing and technology evaluation, a general concept exploration process is utilized to perform a notional 2033 manned Mars fly by study. The notional study draws out observation with regard to specific FOMs traditionally used during the subsystem-level sizing and technology evaluation processes which can result in misleading conclusions regarding the overall SOS design. Furthermore, these observations suggest that selection of FOMs for the subsystems of an architecture should be influenced by the desired objectives of the high-level SOS objectives and FOMs.

Trent, Douglas J.↗
NASA NTRS2018

System-of-Systems Tools for the Analysis of Technological Choices in Space Propulsion

Difficulties in space mission architecture design arise from many factors. Performance, cost, and risk constraints become less obvious due to complex interactions between the systems involved in the mission; decisions regarding long-term goals can heavily impact technological choices for short-term parts of the mission, while conversely decisions in the near future will impact the whole flexibility of long-term plans. Furthermore, the space community is broadening its borders, and space agencies from different countries are collaborating with industry and commercial partners towards large-scale endeavors. This paradigm shift is prompting the development of non-traditional approaches to the design of space missions. This paper reports the results of the first year of a continuing collaboration of the authors to develop and demonstrate System-of-System engineering methodologies for the deep analysis of dependencies and synthesis of robust architectures in exploration mission contexts. We present the procedure that we followed to develop and apply our methodology, obstacles found, steps taken to improve the methods based on the needs of experts and decision makers, required data for the analysis, and results produced by our holistic analysis. In particular, we focus on the analysis of technological choices for space propulsion for a generic cislunar mission, including both complex interactions between subsystems in different type of propulsion and availability of different providers. We identify critical systems and sets of systems based on cascading effects of performance degradation, assessment of the robustness of different designs in the operational domain, and simultaneous analysis of schedule dependencies between the constituent systems.

Guariniello, Cesare↗
NASA NTRSDate not supplied

Digital Prototyping Methods to Enable Product Development Analysis Cycle Compression in Aerospace Systems

Historically, the product development life cycle (spanning from origination of a systems concept to initial delivery or fielding) for large-scale aerospace systems is 10-25 years. Examples of recent programs exhibiting this timeline are the Space Shuttle (13 years), , International Space Station (18 years), NASA Hubble telescope (16 years), USAF F-35 Strike Fighter (22 years), Missile Defense Agency THAAD (21 years), USAF V-22 Osprey (26 years), USAF B-2 Spirt (19 years), US Army RAH-66 Comanche (22 years, cancelled prior to fielding), James Webb Space Telescope (25 years), Space Launch System (10 years). This list illustrates the challenges of developing and fielding a modern integrated multi-disciplinary aerospace system. These development timelines are often preceded by significant research and development programs and followed by multiple increments, blocks, or spirals to reach planned operational capability. In the modern era of aerospace system acquisition, there is significant pressure to reduce system development timelines to meet system objectives and enable competitiveness in the current industry and landscape. Across the aerospace industry, a range of rapid acquisition and prototyping programs are seeking to achieve system development within timelines considerably less than 10 years. Notably, in September of 2019, NASA issued a solicitation for the development and demonstration of a Human Landing System (HLS) to deliver humans to the lunar surface by 2024 (5 years) and for the development and demonstration of a more sustainable HLS by 2026 (7 years). Lengthy product development cycle timelines are a product of multiple factors ranging from programmatic, sociological, technical, and systems engineering issues. New approaches in systems engineering provide new ways to enable these compressed development timelines. These approaches employ expanded application of advanced systems engineering methods and cross-cutting digital tools to accelerate system development, utilizing digital prototyping to connect maturing sub-system or component technologies into system or system-of-systems hardware prototypes. Approaches such as the use of system integrating physics relationships to reduce the number of design analysis cycle iterations and state analysis modeling to reduce necessary software testing (and improving coverage of system execution scenarios) represent steps forward in reducing the engineering time needed to field new systems. In addition to cost, schedule and performance benefits, expanded digital exploration and demonstration reduce risk in live system test and demonstration. This incremental demonstration approach, where digital prototyping and demonstration leads and informs full system test and demonstration, could be more important for space applications because of the increased difficulty of test and demonstration of space systems and architectures. The Advanced Concepts Office (ACO) at Marshall Space Flight Center merges traditional multi-disciplinary concept definition methods with modern, cross-cutting systems engineering concepts to enable iterative design and analysis of space architectures and systems through coordinated, strategic management of human capital, technical processes, and technology. This paper provides an overview of that approach, including recent examples and a strategic path forward to enabling continued reduction of aerospace system product development life cycles.

Michael D Watson↗
NASA NTRSDate not supplied

Multidisciplinary Dynamic Testing Challenges in Validating the NASA Artemis Architecture

NASA is in the midst of bold and exciting next steps in human exploration and spaceflight. The designs of the new Space Launch System (SLS), the Orion spacecraft and the Exploration Ground Systems (EGS) for vehicle processing and launch are essentially complete and there has been significant progress in manufacturing and assembly of specific hardware for the Artemis I and Artemis II missions. Equally as important, the program level and integrated system level testing and analyses are also well underway to support integrated verification, validation, and certificate of flight readiness (CoFR) for the first Artemis mission. Testing and analysis are key to addressing technical challenges that the Artemis missions offer. Building block approaches are required that provide the right balance between component, system, and/or element level testing that satisfies verification and validation objectives and where, uncertainties are quantified and minimized. Artemis I is a system of systems that requires a fusion of test and analysis that adeptly characterizes critical interfaces between major program elements. NASA is implementing new in-situ testing that fuse traditional aerospace structures with civil structures, such as the Integrated Modal Test for the Artemis I vehicle where the Mobile Launcher and Crawler Transporter serve as a support structure whose dynamics couple with that of the Artemis I vehicle. This new paradigm requires a closer inspection of structural behavior of the Crawler Transporter and the Mobile Launcher as they now serve multiple purposes. This requires a paradigm shift to look beyond experimental modal techniques and incorporates operational modal analysis techniques to validate dynamic models from data collected during rollout to the launch pad. A further complicating factor is the Crawler Transporter generated ground forces have numerous harmonics making extracting dynamic responses of the Artemis I, Mobile Launcher, and Crawler Transporter coupled system challenging. This discussion explores all these challenges with and attempts to understand how we best build confidence in systems and system-of-systems performance capabilities and margins and understand uncertainties.

Joel W Sills↗
NASA NTRSDate not supplied

Examining the Changing Roles and Responsibilities of Humans in Envisioned Future In-Time Aviation Safety Management Systems

Advances in technology are enabling new concepts of operations that will trans-form aviation including increasingly autonomous capabilities to handle evolving complex dynamic ecosystems like those associated with Advanced Aerial Mobility. A major challenge is how to ensure today’s safety levels are maintained as the system scales for rapid detection and timely mitigation of safety issues. NASA has developed a concept of operation for In-Time Aviation Safety Management Systems (IASMS) that represents a system-of-system perspective on interconnected capabilities needed to proactively reduce risk in complex operational environments where unknown hazards may exist. As a result, NASA research priorities include under-standing how the balance between humans and automation changes in such envisioned systems, which may lead to novel human-machine interaction paradigms and human-autonomy teaming for informed contingency management.

Lawrence Prinzel↗
NASA NTRS2021

New Observing Strategies Testbed (NOS-T)

The New Observing Strategies (NOS) initiative within the NASA Earth Science Technology Office(ESTO)Advanced Information Systems Technology(AIST) program envisions future Earth science missions with distributed sensors(nodes) interconnected by a communications fabric that enables dynamic and intelligent operations [1].Some NOS concepts resemble systems-of-systems or collaborative systems where operational authority is distributed among multiple systems, necessitating new methods for systems engineering and design to cope with more decentralized control over constituent systems[2].The New Observing Strategies Testbed (NOS-T, verbalized as "enoh es tee") is a computational environment to develop, test, mature, and socialize new operating concepts and technology for NOS. NOS-T provides infrastructure to integrate and orchestrate user-contributed applications for system-of-systems test cases with true distributed control over constituent systems. The overall concept, illustrated in Figure 1, interconnects individual user applications and a NOS-T manager application via common information system infrastructure to coordinate the execution of virtual Earth science missions. NOS-T enables principal investigators to conduct test runs in the same environment, systematically changing variables to assess the overall efficacy of the proposed new observing strategies. Recorded data and outcomes provide evidence to advance technology readiness level and improve or innovate upon existing Earth science measurement techniques

Paul Grogan↗
NASA NTRSDate not supplied

Defining Services, Functions, and Capabilities for an Advanced Air Mobility (AAM) In-time Aviation Safety Management System (IASMS)

NASA’s vision for Advanced Air Mobility (AAM) Mission is to help emerging aviation markets to safely develop an air transportation system that moves people and cargo between places previously not served or underserved by aviation. The integration of new operational paradigms and vehicle classes in this system requires a transformation of the National Airspace System (NAS) that includes substantive changes critical for assuring safety. These changes are compelled by unique challenges posed by AAM to the safety management system (SMS). These challenges were assessed by committees of the National Academies in their reports on a vision for an In-time Aviation Safety Management System (IASMS) and a blueprint for AAM [1,2]. In their description of an IASMS, the top recommendation was development of a concept of operations (ConOps) for IASMS. This paper describes the high-priority recommendations from the National Academies for its IASMS vision and how they are addressed through a distributed system-of-systems architecture. The IASMS architecture is structured on the services, functions, and capabilities (SFCs) necessary for In-time System-wide Safety Assurance (ISSA)initially developed for urban air mobility (UAM). The paper then posits where these SFCs would reside across vehicles, airspace, or service suppliers such as Supplemental Data Service Providers (SDSPs), and how SFCs scale with increasing complexity in design and operations of AAM. SFCs are foundational building blocks for a system that targets an individual or family of risks using a Monitor-Assess-Mitigate risk paradigm for anomalies, precursors and trends. An IASMS could be conceived that uses a portfolio of SFCs for AAM in general or prioritizes SFCs for a specific domain or operation.

K Ellis↗
NASA NTRS2022

Evaluation and Improvement of System-of-Systems Resilience in a Simulation of Wildfire Emergency Response

Because of the increasing threat that wildfires pose, there is interest in leveraging new technologies to improve firefighting. Specifically, Unmanned Aerial Systems (UAS) and UAS Traffic Management (UTM) promise to improve firefighters’ situational awareness, coordination, communications, safety, and strategy. While these technologies could be beneficial, there has been little formal investigation into how much benefit would occur and whether these benefits would outweigh hazards introduced by these systems. To better understand the impacts of these technologies, this paper presents a high-level dynamic simulation for evaluating wildfire response performance and resilience incorporating fire propagation, surveillance and communication, response planning, and the resulting mitigation actions. This simulation is then used to study the impact of communications and surveillance improvement, considering (1) the effect on fire containment and ground crew injuries and (2) the effect of introduced and existing disruptive fault scenarios. Simulating this model over a large number of scenarios finds that these changes can improve containment and reduce ground crew injuries. While these improvements generalize over both existing and introduced single-fault scenarios and thus result in a more resilient system, they could be negated if the introduced communications infrastructure is prone to full-scale outages.

modeling↗