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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

On TTEthernet for Integrated Fault-Tolerant Spacecraft Networks

There has recently been a push for adopting integrated modular avionics (IMA) principles in designing spacecraft architectures. This consolidation of multiple vehicle functions to shared computing platforms can significantly reduce spacecraft cost, weight, and de- sign complexity. Ethernet technology is attractive for inclusion in more integrated avionic systems due to its high speed, flexibility, and the availability of inexpensive commercial off-the-shelf (COTS) components. Furthermore, Ethernet can be augmented with a variety of quality of service (QoS) enhancements that enable its use for transmitting critical data. TTEthernet introduces a decentralized clock synchronization paradigm enabling the use of time-triggered Ethernet messaging appropriate for hard real-time applications. TTEthernet can also provide two forms of event-driven communication, therefore accommodating the full spectrum of traffic criticality levels required in IMA architectures. This paper explores the application of TTEthernet technology to future IMA spacecraft architectures as part of the Avionics and Software (A&S) project chartered by NASA's Advanced Exploration Systems (AES) program.

Loveless, Andrew↗
NASA NTRS1985

Maintenance of Time and Frequency in the DSN Using the Global Positioning System

The Deep Space Network must maintain time and frequency within specified limits in order to accurately track the spacecraft engaged in deep space exploration. The DSN has three tracking complexes, located approximately equidistantly around the Earth. Various methods are used to coordinate the clocks among the three complexes. These methods include Loran-C, TV Line 10, very long baseline interferometry (VLBI), and the Global Positioning System (GPS). The GPS is becoming increasingly important because of the accuracy, precision, and rapid availability of the data; GPS receivers have been installed at each of the DSN complexes and are used to obtain daily time offsets between the master clock at each site and UTC(USNO/NBS). Calculations are made to obtain frequency offsets and Allan variances. These data are analyzed and used to monitor the performance of the hydrogen masers that provide the reference frequencies for the DSN frequency and timing system (DFT). A brief history of the GPS timing receivers in the DSN, a description of the data and information flow, data on the performance of the DSN master clocks and GPS measurement system, and a description of hydrogen maser frequency steering using these data are presented.

Clements, P. A.↗
NASA NTRS1991

Genetic algorithm based input selection for a neural network function approximator with applications to SSME health monitoring

A genetic algorithm is used to select the inputs to a neural network function approximator. In the application considered, modeling critical parameters of the space shuttle main engine (SSME), the functional relationship between measured parameters is unknown and complex. Furthermore, the number of possible input parameters is quite large. Many approaches have been used for input selection, but they are either subjective or do not consider the complex multivariate relationships between parameters. Due to the optimization and space searching capabilities of genetic algorithms they were employed to systematize the input selection process. The results suggest that the genetic algorithm can generate parameter lists of high quality without the explicit use of problem domain knowledge. Suggestions for improving the performance of the input selection process are also provided.

Peck, Charles C.↗
NASA NTRS2018

Automated Spacecraft Communications Service Demonstration Using NASA's SCaN Testbed

The traditional paradigm for space mission operations relies on inefficient, highly scripted pre-planned activities between space communications & navigation service providers and user ground mission operations centers. Typically there is limited or non-existent automation capabilities on the user spacecraft for requesting space communications services, and on the provider network for request dispositioning and service provisioning. In the past, using these processes for space networks was sufficient with the relatively small number of user spacecraft requesting services. However, with an ever increasing number of satellites being launched to orbit, more complex event-driven science objectives, exploration missions involving collaborative platforms, and more distant missions, approaches that improve automation, flexibility and efficiency are needed. This paper describes NASA's recently completed on-orbit demonstration results of a new space communications service concept called User Initiated Service, and a discussion for infusing this innovation into operations.

waveforms↗
NASA NTRS2018

Automated Spacecraft Communications Service Demonstration Using NASA's SCaN Testbed

The traditional paradigm for space mission operations relies on inefficient, highly scripted pre-planned activities between space communications and navigation service providers and user ground mission operations centers. Typically there is limited or non-existent automation capabilities on the user spacecraft for requesting space communications services, and on the provider network for request dispositioning and service provisioning. In the past, using these processes for space networks was sufficient with the relatively small number of user spacecraft requesting services. However, with an ever increasing number of satellites being launched to orbit, more complex event-driven science objectives, exploration missions involving collaborative platforms, and more distant missions, approaches that improve automation, flexibility and efficiency are needed. This paper describes NASA's recently completed on-orbit demonstration results of a new space communications service concept called User Initiated Service, and a discussion for infusing this innovation into operations.

transmitters receivers↗
NASA NTRS2016

Space Mobile Network: A Near Earth Communications and Navigation Architecture

This paper shares key findings of NASA's Earth Regime Network Evolution Study (ERNESt) team resulting from its 18-month effort to define a wholly new architecture-level paradigm for the exploitation of space by civil space and commercial sector organizations. Since the launch of Sputnik in October 1957 spaceflight missions have remained highly scripted activities from launch through disposal. The utilization of computer technology has enabled dramatic increases in mission complexity; but, the underlying premise that the diverse actions necessary to meet mission goals requires minute-by-minute scripting, defined weeks in advance of execution, for the life of the mission has remained. This archetype was appropriate for a "new frontier" but now risks overtly constraining the potential market-based opportunities for the innovation considered necessary to efficiently address the complexities associated with meeting communications and navigation requirements projected to be characteristics of the next era of space exploration: a growing number of missions in simultaneous execution, increased variance of mission types and growth in location/orbital regime diversity. The resulting ERNESt architectural cornerstone - the Space Mobile Network (SMN) - was envisioned as critical to creating an environment essential to meeting these future challenges in political, programmatic, technological and budgetary terms. The SMN incorporates technologies such as: Disruption Tolerant Networking (DTN) and optical communications, as well as new operations concepts such as User Initiated Services (UIS) to provide user services analogous to today's terrestrial mobile network user. Results developed in collaboration with NASA's Space Communications and Navigation (SCaN) Division and field centers are reported on. Findings have been validated via briefings to external focus groups and initial ground-based demonstrations. The SMN opens new niches for exploitation by the marketplace of mission planners and service providers.

Space Communication Spacecraft↗
NASA NTRS2012

Safety Risk Knowledge Elicitation in Support of Aeronautical R and D Portfolio Management: A Case Study

Aviation is a problem domain characterized by a high level of system complexity and uncertainty. Safety risk analysis in such a domain is especially challenging given the multitude of operations and diverse stakeholders. The Federal Aviation Administration (FAA) projects that by 2025 air traffic will increase by more than 50 percent with 1.1 billion passengers a year and more than 85,000 flights every 24 hours contributing to further delays and congestion in the sky (Circelli, 2011). This increased system complexity necessitates the application of structured safety risk analysis methods to understand and eliminate where possible, reduce, and/or mitigate risk factors. The use of expert judgments for probabilistic safety analysis in such a complex domain is necessary especially when evaluating the projected impact of future technologies, capabilities, and procedures for which current operational data may be scarce. Management of an R&D product portfolio in such a dynamic domain needs a systematic process to elicit these expert judgments, process modeling results, perform sensitivity analyses, and efficiently communicate the modeling results to decision makers. In this paper a case study focusing on the application of an R&D portfolio of aeronautical products intended to mitigate aircraft Loss of Control (LOC) accidents is presented. In particular, the knowledge elicitation process with three subject matter experts who contributed to the safety risk model is emphasized. The application and refinement of a verbal-numerical scale for conditional probability elicitation in a Bayesian Belief Network (BBN) is discussed. The preliminary findings from this initial step of a three-part elicitation are important to project management practitioners as they illustrate the vital contribution of systematic knowledge elicitation in complex domains.

Shih, Ann T.↗
NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗
NASA NTRS1977

A GSTDN/TDRSS compatible RF system for the Solar Maximum Mission /SMM/

The Solar Maximum Mission (SMM) is a major NASA observatory to be launched in late 1979. SMM will be supported by NASA's existing Ground Spaceflight Tracking and Data Network (GSTDN) and the planned Tracking and Data Relay Satellite System (TDRSS). Design of a GSTDN/TDRSS compatible RF system for SMM poses multiple problems related to the complex nature of the observatory command, telemetry, and tracking support requirements and the fundamental differences in signal design, antenna characteristics, data rates, and link performance criteria for GSTDN vs. TDRSS support. The RF system described in this paper achieves full compatibility with a minimum of hardware complexity by use of an integrated antenna system, the NASA standard S-Band transponder, and utilization of both the single access and multiple access support capabilities of the TDRSS to handle both real time data and tape recorder dumps.

Heffernan, P. J.↗
NASA NTRS1988

Programmable Data Formatter

System adapts data in diverse formats for transmission. Microprocessor controls complex activities of data formatting, error checking, and transmission-priority arbitration. System developed for formatting signals from and to telemetry units on spacecraft for widespread telecommunication network.

Martin, Robert E.↗
NASA NTRS1990

Application of the TRANAIR rectangular grid approach to the aerodynamic analysis of complex configurations

A numerical method is described which uses a rectangular grid to solve the nonlinear full potential equation about complex configurations. The grid is locally refined to resolve high velocity gradients arising from leading edge expansions or shock waves. The grid penetrates the boundary (described by networks of quadrilateral panels) and is generated automatically. Discrete operators are constructed using the finite element method. The system of nonlinear discrete equations is solved iteratively using a Krylov subspace method preconditioned by an exterior Poisson solver and a direct sparse solver. The primary emphasis is to provide design engineers with an aerodynamic analysis tool (the TRANAIR code) which is accurate, reliable, economical, and flexible to use. Computational results for many interesting configurations are presented.

Johnson, Forrester T.↗
NASA NTRS1999

The Unit of Lightning

For the past century, scientists have made quantitative measurements of lightning discharges. In the process, they refined the definition of a lightning unit, or basic quantum of lightning, in order to base it on observable parameters. Although many components of a lightning discharge have been identified, lightning usually occur in groups of discharges or pulses that, although complex, can be organized into units of flashes. This unit definition is based mainly on measurements of lightning from electric field, video, and ground flash lightning locating networks. More recent instrumentation with various combinations of high sensitivity, high temporal, or high spatial resolution often measure signals produced by lightning that do not cleanly divide into flashes. The data from these systems indicate the need or a more fundamental unit for lightning. Such a unit would be of benefit for both basic understanding of lightning and comparing lightning information between instruments. Without a common lightning unit definition, intercomparisons are difficult. For an example, the Lightning Detection And Ranging system (LDAR) at Kennedy Space Center (KSC) have detected ,flash' rates as high as 600 per minute while analysis based on the Advanced Ground Based Field Mill network (AGBFM) detect only 33 "flashes" per minute in the same area and time periods. The satellite based Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) sometimes see single "flashes" that last longer than 10 seconds. Such long duration flashes are not found in electric field records or ground strike location system data sets. The unit of lightning should be based on the fundamental components of the lightning discharge. This should make the unit as generally applicable as possible. For example, studies of NO(x) production by lightning depend on parameters of the individual lightning channels and not the summary flash characteristics. For such studies, the best unit of lightning may be closer to the classical stroke in the electric field data sets, flash in the LDAR data sets, and group in the OTD/LIS data sets. For this type of study, however, more than just the stroke count information is needed. In this paper, we will outline the current definitions of the unit of lightning and propose new basic definitions for the unit of lightning. Since different instruments detect lightning in different ways and different studies may need almost mutually exclusive aspects of the lightning discharge, there may not be a single definition of the unit of lightning that can be applied to all systems and all studies. However, common components can be found since all instrumentation are detecting aspects of the same phenomenon.

Mach, Douglas M.↗
NASA NTRS2002

Solving Problems With SINDA/FLUINT

SINDA/FLUINT, the NASA standard software system for thermohydraulic analysis, provides computational simulation of interacting thermal and fluid effects in designs modeled as heat transfer and fluid flow networks. The product saves time and money by making the user's design process faster and easier, and allowing the user to gain a better understanding of complex systems. The code is completely extensible, allowing the user to choose the features, accuracy and approximation levels, and outputs. Users can also add their own customizations as needed to handle unique design tasks or to automate repetitive tasks. Applications for SINDA/FLUINT include the pharmaceutical, petrochemical, biomedical, electronics, and energy industries. The system has been used to simulate nuclear reactors, windshield wipers, and human windpipes. In the automotive industry, it simulates the transient liquid/vapor flows within air conditioning systems.

Source record↗
NASA NTRS2004

Silicon-Germanium Films Grown on Sapphire for Ka-Band Communications Applications

NASA's vision in the space communications area is to develop a broadband data network in which there is a high degree of interconnectivity among the various satellite systems, ground stations, and wired systems. To accomplish this goal, we will need complex electronic circuits integrating analog and digital data handling at the Ka-band (26 to 40 GHz). The purpose of this project is to show the feasibility of a new technology for Ka-band communications applications, namely silicon germanium (SiGe) on sapphire. This new technology will have several advantages in comparison to the existing silicon-substrate- based circuits. The main advantages are extremely low parasitic reactances that enable much higher quality active and passive components, better device isolation, higher radiation tolerance, and the integration of digital and analog circuitry on a single chip.

Alterovitz, Samuel A.↗
NASA NTRS2006

Probabilistic Classification Using Elemental Abundance Distributions and Lossless Image Compression in Apollo 17 Lunar Dust Samples from Mare Serenitatis

We have previously outlined a strategy for the detection of fossils [Storrie-Lombardi and Hoover, 2004] and extant microbial life [Storrie-Lombaudi and Hoover, 20051 during robotic missions to Mars using co-registered structural and chemical signatures. Data inputs included image lossless compression indices to estimate relative textural complexity and elemental abundance distributions. Two exploratory classification algorithms (principal component analysis and hierarchical cluster analysis) provide an initial tentative classification of all targets. Nonlinear stochastic neural networks are then trained to produce a Bayesian estimate of algorithm classification accuracy. The strategy previously has been successful in distinguishing regions of biotic and abiotic alteration of basalt glass from unaltered samples. [Storrie-Lombardi and Fisk, 2004; Storrie-Lombardi and Fisk, 2004] Such investigations of abiotic versus biotic alteration of terrestrial mineralogy on Earth are compromised by .the difficulty finding mineralogy completely unaffected by the ubiquitous presence of microbial life on the planet. The renewed interest in lunar exploration offers an opportunity to investigate geological materials that may exhibit signs of aqueous alteration, but are highly unlikely to contain contaminating biological weathering signatures. We here present an extension of our earlier data set to include lunar dust samples obtained during the Apollo 17 mission. Apollo 17 landed in the Taurus-Littrow Valley in Mare Serenitatis. Most of the rock samples from this region of the lunar highlands are basalts comprised primarily of plagioclase and pyroxene and selected examples of orange and black volcanic glass. SEM images and elemental abundances (C6, N7, O8, Na11, Mg12, Al13, Si14, P15, S16, Cll7, K19, Ca20, Fe26) for a series of targets in the lunar dust samples are compared to the extant cyanobacteria, fossil trilobites, Orgueil meteorite, and terrestrial basalt targets previously discussed. The data set provides a first step in producing a quantitative probabilistic methodology for geobiological analysis of returned lunar samples or in situ exploration.

Storrie-Lombardi, Michael C.↗
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 NTRS2015

Regolith and Environment Science and Oxygen and Lunar Volatile Extraction (RESOLVE): Lunar Advanced Volatile Analysis (LAVA) Capillary Fluid Dynamic Restriction Effects on Gas Chromatography

The Resource Prospector (RP) mission with the Regolith and Environment Science and Oxygen Lunar Volatile Extraction (RESOLVE) payload aims to show the presence of water in lunar regolith, and establish a proving ground for NASAs mission to Mars. One of the analysis is performed by the Lunar Advanced Volatiles Analysis (LAVA) subsystem, which consists of a fluid network that facilitates the transport of volatile samples to a gas chromatograph and mass spectrometer (GC-MS) instrument. The understanding of fluid dynamics directed from the GC to the MS is important due to the influence of flow rates and pressures that affect the accuracy of and prevent the damage to the overall GC-MS instrument. The micro-scale capillary fluid network within the GC alone has various lengths and inner-diameters; therefore, determination of pressure differentials and flow rates are difficult to model computationally, with additional complexity from the vacuum conditions in space and lack of a lunar atmosphere. A series of tests were performed on an experimental set-up of the system where the inner diameters of the GC transfer line connecting to the MS were varied. The effect on chromatography readings were also studied by applying these lines onto a GC instrument. It was found that a smaller inner diameter transfer line resulted in a lower flow rate, as well as a lower pressure differential across the thermal conductivity detector (TCD) unit of the GC and a negligible pressure drop across the mock-up capillary column. The chromatography was affected with longer retention times and broader peak integrations. It was concluded that a 0.050 mm inner diameter line still proved most suitable for the systems flow rate preferences. In addition, it was evident that this small transfer line portrayed some expense to GC signal characteristics and the wait time for steady-state operation.

RESOLVE↗
NASA NTRSDate not supplied

I’ve Looked at Clouds from Both Sides, Now: Viewpoints from Surface and Spaceborne Lidar Systems

Clouds play a critical role in the Earth’s climate system because they are inextricably linked to the hydrological cycle and radiation budget. Information about cloud height, thickness, occurrence, and amount are critical inputs for a host of numerical applications involving climate research. Therefore, it is important to have highly accurate and quantitative data records of cloud properties that span several years and geographic regions. Verification of even the most basic modeling processes demands long term and continuous observations of global cloud occurrence, if there is to be any confidence in their fidelity. For a number of reasons, however, it is impossible to gauge the complexities of clouds from a single source. Fundamentally, an array of remote sensing methods is needed in order to provide a complete picture. Within the Micropulse Lidar Network (MPLNET), we have developed a new algorithm to improve the quality of our cloud products. The largest impact of the changes to the cloud detection algorithm is evident with high clouds (those with cloud base > 5 km). Furthermore, polarized measurements enable us to determine the cloud thermodynamic phase. Naturally, the next step is to investigate how these improvements compare with observations from spaceborne lidars (e.g. CALIOP) which have a better (unobstructed) view of high clouds. Recent advances in remote sensing have revealed that cirrus clouds are the most common cloud genus observed in the atmosphere. Furthermore, cirrus skew highly towards relatively low cloud optical depths, as observed from both surface and spaceborne viewpoints. The radiative impacts of these findings are quite significant, considering the cumulative effect cirrus exhibit when compared to low clouds.

Jasper R Lewis↗