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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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At least 1,297 records · Page 72

A New Vision and A More Rational Process Will Advance Space Life Support Through Better Projects

Many space life support assumptions are obviously mistaken but they are generally accepted because they mutually support each other and because they advance a mistaken futuristic vision of closed human ecosystems in space. Many projects have been mistakenly selected to increase life support system closure or reduce launch mass in order to implement this impractical vision. Project members rarely challenge their project’s assumptions and guiding vision. Systems engineering including cost, reliability, risk, and system trade-offs has been very strongly discouraged to prevent rational criticism of these dubious assumptions, the projects, and the ecosystem vision. A more realistic vision can define better near term life support goals and future aspirations that will improve mission support and increase public interest. Given more realistic goals, it will be possible to develop effective technical alternatives, use open rational project selection methods, conduct professional project management, and make swifter progress in the inevitable human advance into space. The current unworkable human space settlement scenario involves moon visits and permanent bases, zero gravity trips to Mars, Mars visits and bases, all leading to extensive human settlements on the moon and Mars. This is unrealistic because the moon and Mars have less than Earth normal gravity and high radiation that can seriously damage human health. A better alternative would use rotating space colonies that produce Earth gravity and are radiation shielded. The attractive fantasy of reproducing terrestrial ecology in space should be replaced by the idea of building a closed system based on advancing technology such as artificial photosynthesis. Past mistaken projects include growing plants for food to replicate terrestrial food sources, recovering small amounts of water from difficult to process waste to achieve high system closure, and using newly designed, lighter, but unreliable hardware to reduce launch mass. The political process supporting the false assumptions, projects, and vision has deliberately prevented the usual systems engineering and cost-benefit analysis. We are going to do much better.

Harry W. Jones↗

From Research to Reality -- Challenges and Opportunities in Complex System Design

The scope and scale of our interconnected society requires that we view the world through a complex system lens, where numerous parts interact, and emergent behaviors are the norm. Understanding complex systems is critical for decision-making and policy development in domains such as ecological systems, financial markets, supply chains, and global transportation systems, where decision-makers need reliable information to predict the impact of decisions that may play out over decades. Traditional approaches to the research that produces this information are often insufficient, where hypotheses are tested in an isolated environment, and where the results may not carry over to the integrated system. There are a multitude of advancements in system engineering, artificial intelligence, and test and evaluation that are emerging to meet the challenge. Approaches such as agile development, model-based system engineering, design of experiments, large language models, and formal ontologies are providing ways to manage complexity and increase our collective ability to make the changes that we want to see in the world. In this talk I will provide a few examples related to the architecture of the National Airspace System (NAS), where we have investigated the use of large language models, basic formal ontology, and applied category theory to help researchers and system engineers be more effective in this complex design space. Bio: Dr. Ian Levitt’s current research focus is on the complex evolution of the National Airspace System. Prior to joining NASA in 2020, he was with the FAA leading international standards and national laboratory development for the agency. Dr. Levitt earned his PhD in mathematics from Rutgers University in 2009. His mission is to promote a healthy and continuous transformation of society through open information and cooperation.

Ian Levitt↗

ECAR-7813 Rev 0 Secondary Coolant Cover Gas System Stirling Engine Tube Rupture Analysis, Insulation Block Analysis, and Labyrinth Seal Design

The purpose of this ECAR is to document compliance with best engineering practices for the Secondary Coolant Cover Gas System of the MARVEL microreactor which includes a Stirling Engine helium tube rupture analysis, an analysis to verify the strength of the insulation blocks, and the design of the Labyrinth Seal.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Exergy Efficiency of Interplanetary Transfer Vehicles

In order to optimize systems, systems engineers require some sort of measure with which to compare vastly different system components. One such measure is system exergy, or the usable system work. Exergy balance analysis models provide a comparison of different system configurations, allowing systems engineers to compare different systems configuration options. This paper presents the exergy efficiency of several Mars transportation system configurations, using data on the interplanetary trajectory, engine performance, and vehicle mass. The importance of the starting and final parking orbits is addressed in the analysis, as well as intermediate hyperbolic escape and entry orbits within Earth and Mars' spheres of influence (SOIs). Propulsion systems analyzed include low-enriched uranium (LEU) nuclear thermal propulsion (NTP), high-enriched uranium (HEU) NTP, LEU methane (CH4) NTP, and liquid oxygen (LOX)/liquid hydrogen (LH2) chemical propulsion.

Owen, Sean T.↗

Exergy Efficiency of Interplanetary Transfer Vehicles

In order to optimize systems, systems engineers require some sort of measure with which to compare vastly different system components. One such measure is system exergy, or the usable system work. Exergy balance analysis models provide a comparison of different system configurations, allowing systems engineers to compare different systems configuration options. This paper presents the exergy efficiency of several Mars transportation system configurations, using data on the interplanetary trajectory, engine performance, and vehicle mass. The importance of the starting and final parking orbits is addressed in the analysis, as well as intermediate hyperbolic escape and entry orbits within Earth and Mars' spheres of influence (SOIs). Propulsion systems analyzed include low-enriched uranium (LEU) nuclear thermal propulsion (NTP), high-enriched uranium (HEU) NTP, LEU methane (CH4) NTP, and liquid oxygen (LOX)/liquid hydrogen (LH2) chemical propulsion.

Owen, Sean T.↗

Exergy Efficiency of Interplanetary Transfer Vehicles

In order to optimize systems, systems engineers require some sort of measure with which to compare vastly different system components. One such measure is system exergy, or the usable system work. Exergy balance analysis models provide a comparison of different system configurations, allowing systems engineers to compare different systems configuration options. This paper presents the exergy efficiency of several Mars transportation system configurations, using data on the interplanetary trajectory, engine performance, and vehicle mass. The importance of the starting and final parking orbits is addressed in the analysis, as well as intermediate hyperbolic escape and entry orbits within Earth and Mars' spheres of influence (SOIs). Propulsion systems analyzed include low-enriched uranium (LEU) nuclear thermal propulsion (NTP), high-enriched uranium (HEU) NTP, LEU methane (CH4) NTP, and liquid oxygen (LOX)/liquid hydrogen (LH2) chemical propulsion.

Owen, Sean T.↗

Power System Mass Analysis for Hydrogen Reduction Oxygen Production on the Lunar Surface

The production of oxygen from the lunar regolith requires both thermal and electrical power in roughly similar proportions. This unique power requirement is unlike most applications on the lunar surface. To efficiently meet these requirements, both solar PV array and solar concentrator systems were evaluated. The mass of various types of photovoltaic and concentrator based systems were calculated to determine the type of power system that provided the highest specific power. These were compared over a range of oxygen production rates. Also a hybrid type power system was also considered. This system utilized a photovoltaic array to produce the electrical power and a concentrator to provide the thermal power. For a single source system the three systems with the highest specific power were a flexible concentrator/Stirling engine system, a rigid concentrator/Stirling engine system and a tracking triple junction solar array system. These systems had specific power values of 43, 34, and 33 W/kg, respectively. The hybrid power system provided much higher specific power values then the single source systems. The best hybrid combinations were the triple junction solar array with the flexible concentrator and the rigid concentrator. These systems had a specific power of 81 and 68 W/kg, respectively.

Colozza, Anthony J.↗

MBSE Execution of Scalable Autonomous Operations for a High Density Vertiplex

The High Density Vertiplex (HDV) subproject of NASA’s Advanced Air Mobility (AAM) project adopted Model-Based Systems Engineering (MBSE) and NASA SE processes were executed via MBSE using MagicDraw. Since the adoption of MBSE and utilization of MagicDraw, the systems engineering team has made tremendous strides in each pillar of MBSE including, requirements, behavior, and structure. Scalable Autonomous Operations (SAO) was a stage in the development of the High Density Vertiplex focusing on the autonomous terminal operations of a vertiport with sUAS aircraft. MBSE served the systems engineering team to document and verify the physical architecture and capture a logical architecture of SAO for distribution to the AAM community. This paper will detail methodologies that were created to successfully execute NASA SE processes via MBSE in the SAO stage as well as highlight challenges and lessons learned.

Demetrios Katsaduros↗

Digital Model-Based Engineering: Expectations, Prerequisites, and Challenges of Infusion

Digital model-based engineering (DMbE) is the use of digital artifacts, digital environments, and digital tools in the performance of engineering functions. DMbE is intended to allow an organization to progress from documentation-based engineering methods to digital methods that may provide greater flexibility, agility, and efficiency. The term 'DMbE' was developed as part of an effort by the Model-Based Systems Engineering (MBSE) Infusion Task team to identify what government organizations might expect in the course of moving to or infusing MBSE into their organizations. The Task team was established by the Interagency Working Group on Engineering Complex Systems, an informal collaboration among government systems engineering organizations. This Technical Memorandum (TM) discusses the work of the MBSE Infusion Task team to date. The Task team identified prerequisites, expectations, initial challenges, and recommendations for areas of study to pursue, as well as examples of efforts already in progress. The team identified the following five expectations associated with DMbE infusion, discussed further in this TM: (1) Informed decision making through increased transparency, and greater insight. (2) Enhanced communication. (3) Increased understanding for greater flexibility/adaptability in design. (4) Increased confidence that the capability will perform as expected. (5) Increased efficiency. The team identified the following seven challenges an organization might encounter when looking to infuse DMbE: (1) Assessing value added to the organization. Not all DMbE practices will be applicable to every situation in every organization, and not all implementations will have positive results. (2) Overcoming organizational and cultural hurdles. (3) Adopting contractual practices and technical data management. (4) Redefining configuration management. The DMbE environment changes the range of configuration information to be managed to include performance and design models, database objects, as well as more traditional book-form objects and formats. (5) Developing information technology (IT) infrastructure. Approaches to implementing critical, enabling IT infrastructure capabilities must be flexible, reconfigurable, and updatable. (6) Ensuring security of the single source of truth (7) Potential overreliance on quantitative data over qualitative data. Executable/ computational models and simulations generally incorporate and generate quantitative vice qualitative data. The Task team also developed several recommendations for government, academia, and industry, as discussed in this TM. The Task team recommends continuing beyond this initial work to further develop the means of implementing DMbE and to look for opportunities to collaborate and share best practices.

Hale, J. P.↗

Project-domain Science Traceability and Alignment Framework (P-STAF): Analysis of a Payload Architecture

Large science-focused space missions often have multiple instruments working together to address broad science goals. Systems engineers on these types of projects must work with the project scientists to evaluate trades and make decisions that result in a system that efficiently serves the mission science goals. This collaboration is more effective if the systems engineers understand both the traceability from the L1 customer requirements to the selected instruments and the contributions of each instrument in the context of the whole payload suite. These relationships might be understood implicitly by the science team on a project, but there is value in formally codifying them so this understanding can be accessed and formally analyzed by a broader systems engineering effort. We first described a framework for this communication, called the Project-domain Science Traceability and Alignment Framework (P-STAF), in the IEEE 2017 paper “A Framework for Extending the Science Traceability Matrix: Application to the Planned Europa Mission.” This paper shows how that basic framework can be leveraged to not only formally capture these relationships between the instruments and the customer needs, but also how that information can be codified in an analyzable graph that can be queried to provide a better understanding of mission risks and scope. This work was drawn from the application of P-STAF to the Europa Clipper mission, but generic example networks are used to illustrate the power of this technique.

Reinholtz, Kirk↗

Scale model performance test investigation of mixed flow exhaust systems for an energy efficient engine /E3/ propulsion system

As part of the NASA Energy Efficient Engine program, scale-model performance tests of a mixed flow exhaust system were conducted. The tests were used to evaluate the performance of exhaust system mixers for high-bypass, mixed-flow turbofan engines. The tests indicated that: (1) mixer penetration has the most significant affect on both mixing effectiveness and mixer pressure loss; (2) mixing/tailpipe length improves mixing effectiveness; (3) gap reduction between the mixer and centerbody increases high mixing effectiveness; (4) mixer cross-sectional shape influences mixing effectiveness; (5) lobe number affects mixing degree; and (6) mixer aerodynamic pressure losses are a function of secondary flows inherent to the lobed mixer concept.

Kuchar, A. P.↗

Enhancements to the Engine Data Interpretation System (EDIS)

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The results of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.

Hofmann, Martin O.↗

Enhancements to the Engine Data Interpretation System (EDIS)

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The result of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.

Hofmann, Martin O.↗

Human Systems Intergration & Engineering: HSI & E Design Influence

The design of space systems is a long and complicated process where changes to the design increase cost and schedule as the design progresses into implementation. Human Systems Integration uses tools such as mockups, Virtual Reality, Augmented Reality and human simulations early in the design process to evaluate designs for usability, operability, and maintainability. This early design influence provides cost and schedule savings during manufacturing and operations. Examples of how MSFC EV74 Human Systems Integration Team have used these tools to evaluate hardware designs will be discussed.

Tanya Andrews↗

Spark-ignited direct-injection engine combustion systems

A direct-injection stratified charge internal combustion engine includes a combustion cylinder to receive an air-fuel mixture, and an air intake port to inlet air into the combustion cylinder. The direct-injection engine also includes a fuel injector configured to deliver fuel within the cylinder in a spray pattern substantially aligned to a cylinder central axis to create the air-fuel mixture. A spark igniter is located within a path of the spray pattern to ignite combustion of the air-fuel mixture. The direct-injection engine further includes a movable piston defining a lower boundary of the combustion cylinder to contain the combustion of the air-fuel mixture. The piston is configured to include a bowl portion having local geometric features located on an intake port side of the combustion cylinder to redirect fluid flow towards a vortex in fluid communication with a combustion location near the cylinder central axis.

42 ENGINEERING↗

Highly integrated digital engine control system on an F-15 airplane

The highly integrated digital electronic control (HIDEC) program will demonstrate and evaluate the improvements in performance and mission effectiveness that result from integrated engine-airframe control systems. This system is being used on the F-15 airplane at the Dryden Flight Research Facility of NASA Ames Research Center. An integrated flightpath management mode and an integrated adaptive engine stall margin mode are being implemented into the system. The adaptive stall margin mode is a highly integrated mode in which the airplane flight conditions, the resulting inlet distortion, and the engine stall margin are continuously computed; the excess stall margin is used to uptrim the engine for more thrust. The integrated flightpath management mode optimizes the flightpath and throttle setting to reach a desired flight condition. The increase in thrust and the improvement in airplane performance is discussed in this paper.

Burcham, F. W., Jr.↗

NASA's Solar Dynamics Observatory (SDO): A Systems Approach to a Complex Mission

The Solar Dynamics Observatory (SDO) includes three advanced instruments, massive science data volume, stringent science data completeness requirements, and a custom ground station to meet mission demands. The strict instrument science requirements imposed a number of challenging drivers on the overall mission system design, leading the SDO team to adopt an integrated systems engineering presence across all aspects of the mission to ensure that mission science requirements would be met. Key strategies were devised to address these system level drivers and mitigate identified threats to mission success. The global systems engineering team approach ensured that key drivers and risk areas were rigorously addressed through all phases of the mission, leading to the successful SDO launch and on-orbit operation. Since launch, SDO's on-orbit performance has met all mission science requirements and enabled groundbreaking science observations, expanding our understanding of the Sun and its dynamic processes.

systems engineering↗

A Representative Application of a Layered Interface Modeling Pattern

Model-based systems engineering (MBSE) is intended to improve how systems engineering is performed compared with a more traditional document-based approach by effectively using models to analyze, specify, design, and verify systems. The OMG Systems Modeling Language (OMG SysML™) enables the practice of MBSE by providing a robust and expressive language for representing systems.

Shames, Peter M.↗