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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 NTRS2019

Assessment and Validation of Collision "Consequence" Method of Assessing Orbital Regime Risk Posed by Potential Satellite Conjunctions

Collision risk management theory requires a thorough assessment of both the likelihood and consequence of potential collision events. Satellite conjunction risk assessment has produced a highly-developed theory for assessing the likelihood of collision but neglects to account for the consequences of a given collision. While any collision may compromise the operational survival of a spacecraft, the amount of debris produced by the potential collision, and therefore the degree to which the orbital corridor may be compromised, can vary greatly among satellite conjunctions. Previous studies leveraged work on satellite collision modeling to develop a method to estimate whether a particular collision is likely to produce a relatively large or relatively small amount of resultant debris. The approximation of the number of debris pieces is dependent on a mass estimation process for the secondary objects utilizing the radar cross section of said object. This study examines the validity of the mass estimation process and establishes uncertainty bounds on the secondary object mass, which will be used to best approximate the possible consequences of a potential collision. This process is then applied to a large set of historical conjunctions to assess the frequency at which possible collisions may significantly augment the orbital debris environment in operational spacecraft.

Collision Consequence↗
NASA NTRS2022

Natural Language Processing Techniques for Intelligent Knowledge Management of Safety Reports

Safety, failure, and incident reports are common artifacts across various domains, including aviation and wildfire response. These reports are often mandatory to submit, resulting in the culmination of large repositories of text-based documents. Simultaneously, these reports and corresponding repositories are often only manually analyzed and queried by users via out-of-date search engines. As a consequence, we have been developing the Manager for Intelligent Knowledge Access (MIKA) toolkit, which uses natural language processing to improve information access and reuse. In this presentation, we discuss natural language processing techniques for knowledge discovery and apply these methods to a repository of aerial wildfire mishap reports. Two methods are used for knowledge discovery: topic modeling and named-entity recognition. We use topic modeling to identify hazards and perform a trend analysis to produce a data-driven risk matrix. A custom named-entity recognition model, build from fine tuning a pre-trained language model, is used to identify failure modes, failure causes, failure effects, control processes, and recommendations to aid in failure modes and effects analysis (FMEA). Throughout the presentation, we discuss and apply natural language processing techniques to better leverage the vast amount of information contained in report repositories.

Machine learning↗
NASA NTRS2010

Risk Assessment and Integration Team (RAIT) Portfolio Risk Analysis Strategy

Impact at management level: Qualitative assessment of risk criticality in conjunction with risk consequence, likelihood, and severity enable development of an "investment policy" towards managing a portfolio of risks. Impact at research level: Quantitative risk assessments enable researchers to develop risk mitigation strategies with meaningful risk reduction results. Quantitative assessment approach provides useful risk mitigation information.

Edwards, Michelle↗
NASA NTRS1999

Managing the Moon Program: Lessons Learned from Project Apollo

There have been many detailed historical studies of the process of deciding on and executing the Apollo lunar landing during the 1960s and early 1970s. From the announcement of President John F Kennedy on May 25, 1961, of his decision to land an American on the Moon by the end of the decade, through the first lunar landing on July 20, 1969, on to the last of six successful Moon landings with Apollo 17 in December 1972, NASA carried out Project Apollo with enthusiasm and aplomb. While there have been many studies recounting the history of Apollo, at the time of the 30th anniversary of the first lunar landing by Apollo 11, it seems appropriate to revisit the process of large-scale technological management as it related to the lunar mission. Consequently, the NASA History Office has chosen to publish this monograph containing the recollections of key partcipants in the management process. The collective oral history presented here was recorded in 1989 at the Johnson Space Center's Gilruth Recreation Center in Houston, Texas. It includes the recollections of key participants in Apollo's administration, addressing issues such as communication between field centers, the prioritization of technological goals, and the delegation of responsibility. The following people participated: George E. Muller, Owen W. Morris, Maxime A. Faget, Robert R. Gilruth, Christopher C. Kraft, and Howard W. (Bill) Tindall. The valuable perspectives of these individuals deepen and expand our understanding of this important historical event. This is the 14th in a series of special studies prepared by the NASA History Office. The Monographs in Aerospace History series is designed to provide a wide variety of investigations relative to the history of aeronautics and space. These publications are intended to be tightly focused in terms of subject, relatively short in length, and reproduced in an inexpensive format to allow timely and broad dissemination to researchers in aerospace history.

Source record↗
NASA NTRS1997

A Comprehensive Reliability Methodology for Assessing Risk of Reusing Failed Hardware Without Corrective Actions with and Without Redundancy

This paper deals with the development of a reliability methodology to assess the consequences of using hardware, without failure analysis or corrective action, that has previously demonstrated that it did not perform per specification. The subject of this paper arose from the need to provide a detailed probabilistic analysis to calculate the change in probability of failures with respect to the base or non-failed hardware. The methodology used for the analysis is primarily based on principles of Monte Carlo simulation. The random variables in the analysis are: Maximum Time of Operation (MTO) and operation Time of each Unit (OTU) The failure of a unit is considered to happen if (OTU) is less than MTO for the Normal Operational Period (NOP) in which this unit is used. NOP as a whole uses a total of 4 units. Two cases are considered. in the first specialized scenario, the failure of any operation or system failure is considered to happen if any of the units used during the NOP fail. in the second specialized scenario, the failure of any operation or system failure is considered to happen only if any two of the units used during the MOP fail together. The probability of failure of the units and the system as a whole is determined for 3 kinds of systems - Perfect System, Imperfect System 1 and Imperfect System 2. in a Perfect System, the operation time of the failed unit is the same as that of the MTO. In an Imperfect System 1, the operation time of the failed unit is assumed as 1 percent of the MTO. In an Imperfect System 2, the operation time of the failed unit is assumed as zero. in addition, simulated operation time of failed units is assumed as 10 percent of the corresponding units before zero value. Monte Carlo simulation analysis is used for this study. Necessary software has been developed as part of this study to perform the reliability calculations. The results of the analysis showed that the predicted change in failure probability (P(sub F)) for the previously failed units is as high as 49 percent above the baseline (perfect system) for the worst case. The predicted change in system P(sub F) for the previously failed units is as high as 36% for single unit failure without any redundancy. For redundant systems, with dual unit failure, the predicted change in P(sub F) for the previously failed units is as high as 16%. These results will help management to make decisions regarding the consequences of using previously failed units without adequate failure analysis or corrective action.

Putcha, Chandra S.↗
NASA NTRS2001

Reliability of Fault Tolerant Control Systems

This paper reports Part I of a two part effort, that is intended to delineate the relationship between reliability and fault tolerant control in a quantitative manner. Reliability analysis of fault-tolerant control systems is performed using Markov models. Reliability properties, peculiar to fault-tolerant control systems are emphasized. As a consequence, coverage of failures through redundancy management can be severely limited. It is shown that in the early life of a syi1ein composed of highly reliable subsystems, the reliability of the overall system is affine with respect to coverage, and inadequate coverage induces dominant single point failures. The utility of some existing software tools for assessing the reliability of fault tolerant control systems is also discussed. Coverage modeling is attempted in Part II in a way that captures its dependence on the control performance and on the diagnostic resolution.

Wu, N. Eva↗
NASA NTRS2006

LOX, GOX and Pressure Relief

Oxygen relief systems present a serious fire hazard risk with often severe consequences. This presentation offers a risk management solution strategy which encourages minimizing ignition hazards, maximizing best materials, and utilizing good practices. Additionally, the relief system should be designed for cleanability and ballistic flow. The use of the right metals, softgoods, and lubricants, along with the best assembly techniques, is stressed. Materials should also be tested if data is not available and a full hazard analysis should be conducted in an effort to minimize risk and harm.

McLeod, Ken↗
NASA NTRSDate not supplied

Investigation of Intelligent Resource Management for Aviation Communications

The emergence of new aerial vehicles into the airspace as part of new initiatives, such as Advanced Air Mobility (AAM), will place growing demand for spectrum resources to support airspace operations. The traditional approach of using fixed channel allocations within standard service volumes will not allow for dynamic and efficient distribution of resources based on airspace demand; consequently, a new approach to aviation spectrum management will be required to meet the anticipated needs of airspace users. The National Aeronautics and Space Administration (NASA) is investigating the application of advanced concepts to implement a novel spectrum management approach that allows for the intelligent utilization of aviation spectrum throughout the airspace while maintaining the quality of service prescribed by aeronautical standards. This technical investigation evaluates the dynamic assignment of resources for both air-ground and air-air communication links applicable to both the emerging AAM initiative as well as the existing air traffic management system. The performance of the proposed spectrum management concepts will be evaluated using a custom modeling and simulation capability that is currently under development. The implementation of these approaches is anticipated to facilitate increased spectrum utilization efficiency and enhanced airspace capacity, which will better serve the needs of future applications.

Aeronautics↗
NASA NTRSDate not supplied

Investigation of Intelligent Resource Management for Aviation Communications

The emergence of new aerial vehicles into the airspace as part of new initiatives, such as Advanced Air Mobility (AAM), will place growing demand for spectrum resources to support airspace operations. The traditional approach of using fixed channel allocations within standard service volumes will not allow for dynamic and efficient distribution of resources based on airspace demand; consequently, a new approach to aviation spectrum management will be required to meet the anticipated needs of airspace users. The National Aeronautics and Space Administration (NASA) is investigating the application of advanced concepts to implement a novel spectrum management approach that allows for the intelligent utilization of aviation spectrum throughout the airspace while maintaining the quality of service prescribed by aeronautical standards. This technical investigation evaluates the dynamic assignment of resources for both air-ground and air-air communication links applicable to both the emerging AAM initiative as well as the existing air traffic management system. The performance of the proposed spectrum management concepts will be evaluated using a custom modeling and simulation capability that is currently under development. The implementation of these approaches is anticipated to facilitate increased spectrum utilization efficiency and enhanced airspace capacity, which will better serve the needs of future applications.

Eric Knoblock↗
NASA NTRS1997

An Automated Method for Identifying Inconsistencies within Diagrammatic Software Requirements Specifications

The development of large-scale, composite software in a geographically distributed environment is an evolutionary process. Often, in such evolving systems, striving for consistency is complicated by many factors, because development participants have various locations, skills, responsibilities, roles, opinions, languages, terminology and different degrees of abstraction they employ. This naturally leads to many partial specifications or viewpoints. These multiple views on the system being developed usually overlap. From another aspect, these multiple views give rise to the potential for inconsistency. Existing CASE tools do not efficiently manage inconsistencies in distributed development environment for a large-scale project. Based on the ViewPoints framework the WHERE (Web-Based Hypertext Environment for requirements Evolution) toolkit aims to tackle inconsistency management issues within geographically distributed software development projects. Consequently, WHERE project helps make more robust software and support software assurance process. The long term goal of WHERE tools aims to the inconsistency analysis and management in requirements specifications. A framework based on Graph Grammar theory and TCMJAVA toolkit is proposed to detect inconsistencies among viewpoints. This systematic approach uses three basic operations (UNION, DIFFERENCE, INTERSECTION) to study the static behaviors of graphic and tabular notations. From these operations, subgraphs Query, Selection, Merge, Replacement operations can be derived. This approach uses graph PRODUCTIONS (rewriting rules) to study the dynamic transformations of graphs. We discuss the feasibility of implementation these operations. Also, We present the process of porting original TCM (Toolkit for Conceptual Modeling) project from C++ to Java programming language in this thesis. A scenario based on NASA International Space Station Specification is discussed to show the applicability of our approach. Finally, conclusion and future work about inconsistency management issues in WHERE project will be summarized.

Zhang, Zhong↗
NASA NTRSDate not supplied

Lessons Learned With Risk Management: A Systems Engineer's Perspective

Risk management is a communications device that, when executed as an essential task, enables systems engineering to effectively balance risk across the project. Developing and baselining risks is an essential continuous task to ensure top project concerns both from bottom up and top down are being mitigated. Risk management provides the opportunity to avoid the consequence of the risk when mitigation steps start early enough. Just discussing risk with all the project flight elements during development, even if no risks are open, provides an excellent communication opportunity between systems engineering and those elements, ensuring concerns and worries have a platform for discussion. A well-managed risk identification process will identify concerns that are serious but not being clearly communicated, and it will enable mitigation of those potential problems before they cause a failure. Effective risk management requires considerable time and effort, but that effort will save time and money across the development. Risk management must be frequent enough to be useful and in depth enough to bring out emerging issues. It also requires a trusting relationship between the lead systems engineer and element and/or subsystem leads. The discussions need to be with the right number of individuals (typically a handful) and the right duration in time (typically an hour a month). Outside of these risk working groups, there is a formal management process to input, status, and disposition risks, and a monthly Risk Management Board meeting where key project stakeholders are informed. This paper provides good guidance on effective risk management from a systems engineering perspective and provides project lessons learned from the NASA spaceflight missions NICER, Landsat 9, LRO, and OSIRIS-REx to demonstrate the effectiveness of risk management.

Lessons Learned↗
NASA NTRSDate not supplied

Lessons Learned With Risk Management: A Systems Engineer’s Perspective

Risk management is a communications device that, when executed as an essential task, enables systems engineering to effectively balance risk across the project. Developing and baselining risks is an essential continuous task to ensure top project concerns both from bottom up and top down are being mitigated. Risk management provides the opportunity to avoid the consequence of the risk when mitigation steps start early enough. Just discussing risk with all the project flight elements during development, even if no risks are open, provides an excellent communication opportunity between systems engineering and those elements, ensuring concerns and worries have a platform for discussion. A well-managed risk identification process will identify concerns that are serious but not being clearly communicated, and it will enable mitigation of those potential problems before they cause a failure. Effective risk management requires considerable time and effort, but that effort will save time and money across the development. Risk management must be frequent enough to be useful and in depth enough to bring out emerging issues. It also requires a trusting relationship between the lead systems engineer and element and/or subsystem leads. The discussions need to be with the right number of individuals (typically a handful) and the right duration in time (typically an hour a month). Outside of these risk working groups, there is a formal management process to input, status, and disposition risks, and a monthly Risk Management Board meeting where key project stakeholders are informed. This paper provides good guidance on effective risk management from a systems engineering perspective and provides project lessons learned from the NASA spaceflight missions NICER, Landsat 9, LRO, and OSIRIS-REx to demonstrate the effectiveness of risk management.

Lessons Learned↗
NASA NTRS1988

Automated cataloging and characterization of space-derived data

One of the most significant technical issues that NASA must address and resolve is the problem of managing the enormous amounts of scientific and engineering data that will be generated by the next generation of remote sensing systems such as the Hubble Space Telescope (HST) and the Earth Observing System (EOS). The amount of data these sensors are expected to produce will be orders of magnitude greater than NASA has ever experienced. Consequently new solutions must be developed for managing, accessing, and automatically inputting the data into a database in some expressive fashion that will provide a meaningful understanding and effective utilization of this data in a multidisciplinary environment. Presently, scientific data provided by satellites and other sources are processed, cataloged, and archived according to narrow mission or project-specific requirements with little regard to the semantics of the overall research. Scientists therefore lack knowledge of or access to potentially valuable data outside their own field. What is needed is an innovative approach that will allow collected data to be automatically cataloged, characterized, and managed in a domain-community. A concept and design approach that employs expert system-based knowledge controllers combined with advanced spatial database systems and graphical data structures is discussed.

Campbell, William J.↗
NASA NTRS1988

Automated cataloging and characterization of space-derived data

One of the most significant technical issues that NASA must address and resolve is the problem of managing the enormous amounts of scientific and engineering data that will be generated by the next generation of remote sensing systems such as the Hubble Space Telescope (HST) and the Earth Observing System (EOS). The amount of data these sensors are expected to produce will be orders of magnitude greater than NASA has ever experienced. Consequently, new solutions must be developed for managing, accessing, and automatically inputting the data into a database in some expressive fashion that will provide a meaningful understanding and effective utilization of this data in a multidisciplinary environment. Presently, scientific data provided by satellites and other sources are processed, cataloged, and archived according to narrow mission or project-specific requirements with little regard to the semantics of the overall research. Scientists therefore lack knowledge of or access to potentially valuable data outside their own field. What is needed is an innovative approach that will allow collected data to be automatically cataloged, characterized, and managed in a domain-community. A concept and design approach that employs expert system-based knowledge controllers combined with advanced spatial database systems and graphical data structures is discussed.

Campbell, William J.↗
NASA NTRS2016

Analyzing Double Delays at Newark Liberty International Airport (EWR)

When weather or congestion impacts the National Airspace System, multiple different Traffic Management Initiatives can be implemented, sometimes with unintended consequences. One particular perceived inequity that is commonly identified is in the interaction between Ground Delay Programs (GDPs) and time based scheduling of internal departures by the Traffic Management Advisor (TMA) (now operationally superseded by the FAA's the Time-Based Flow Management system). Internal departures under TMA scheduling can take large GDP delays, followed by large TMA scheduling delays, because they cannot easily fit into the arrival flow at the runway. In this paper we examine the causes of these double delays through an analysis of arrival operations at Newark Liberty International Airport (EWR) from June to August 2010. TMA scheduling delays are found to be generally higher than TMA airborne metering delays, regardless of prior GDP delays. Depending on how the double delay is defined, between 42 and 62 of all internal departures in GDP and TMA scheduling experienced double delays in this period. A deep dive into the data reveals that contributors to double delays include upstream flights departing before their Expect Departure Clearance Times (EDCTs); differences in the rates used for setting EDCTs and TMA Scheduled Times of Arrival; differences in the arrival demand expected based on EDCTs and the arrival demand entering TMA; and shorter en route times between takeoff and entry into TMA than assumed in the calculation of flight EDCTs, all of which undermine the sequencing and spacing underlying flight EDCTs. Double delays are also found to coincide with periods in which the virtual runway arrival queue being served by a TMA is large, there are periods of high demand relative to capacity, and there are high airborne metering delays. Data mining techniques are used to confirm that each of these factors contribute to the occurrence of double delay andor high internal departure scheduling delay across three months of data from June to August 2010. Predictors of the occurrence of double delay and high TMA scheduling delay are built using logistic regression, providing prediction accuracies of 69 and 73, respectively.

traffic flow management↗
NASA NTRSDate not supplied

A Queuing Theory Approach to Pilot-Controller Coordination for m:N Operations

In recent years, attention and interest by industry and researchers has grown in a control paradigm for remotely piloted aircraft termed “m:N operations.” In an m:N operation, a team of m remote pilots in command (RIPCs) collaboratively manage the flights of N aircraft. A consequence of an m:N concept of operations is that the RPICs will have to switch attention from one aircraft to another and from one task to another. Previous research in m:N operations has focused on the workload experienced by an RPIC and their level of situation awareness on their flights. Researchers have found that RPIC workload and situation awareness are generally sensitive to increasing N, although NASA’s Multi-Vehicle (m:N) Working Group has suggested that the driver of workload/situation awareness is the number of exceptions requiring human intervention as opposed to the value of N itself. In any case, a natural antecedent of workload is task load. In this paper, queueing theory is applied to a 1:N Urban Air Mobility (UAM) air taxi operation in order to estimate pilot task load for managing radio communications with air traffic controllers (ATCs) under increasing N. An M/M/1 queueing system is used to model the RIPC’s servicing of calls and clearance requests (e.g., departure, arrival, or airspace transition) to ATC for the N aircraft. Important parameters for the queueing model are the task arrival rate and the average service time for task completion. Radio communication times from past human-in-the-loop simulation studies are used to measure service times for a 1:4 and 1:12 UAM operation and to interpolate service times for 4 < N < 12. A Monte Carlo method is then employed, using the measured and interpolated service times, to estimate arrival rate and related queueing statistics. The paper concludes by considering the estimated queuing statistics, particularly the RPIC’s utilization (i.e., proportion of time actively servicing tasks), the length of the task queue over time, and the implications for task-balanced system design.

task load↗
NASA NTRS2018

Recommendations Emerging from an Analysis of NASA's Deep Space Communications Capacity

During 2016-2017, NASA’s Space Communications and Navigation (SCaN) Office chartered a study of Deep Space Network (DSN) communications capacity relative to projected future-mission demand over the next 30 years. In this paper, we briefly describe the methodology used to analyze capacity vs. demand over such a broad timeframe, summarize key findings emerging from the analysis, and discuss the associated recommendations. Performing the analysis entailed: identifying key factors shaping the anticipated future mission set, identifying several alternative future mission set scenarios consistent with these factors, and then analyzing each mission set scenario in terms of required antenna capacity, downlink and uplink capabilities, and spectrum as a function of time. On the basis of these aggregate requirements, DSN loading simulations were then conducted that examined how well each of the postulated mission sets could load up onto the the DSN’s “in-plan” architecture. To the extent that capacity shortfalls emerged during these baseline simulations, architectural solutions to the shortfalls were then postulated and tested via additional simulations. In general, the trend analyses and baseline loading simulations indicated a significant progression in challenges over the next three decades. In the current decade, the DSN appeared to be operating very close to capacity. The first human exploration mission and its secondary payload launch opportunities for cubesats traveling beyond GEO contributed to this loading. As a consequence, the main challenge appeared to be managing peak assetcontention periods. In the next decade, the DSN continued to operate close to capacity but also began transitioning to more frequent human mission support. Upgrading for, and operating, a human-rated system while continuing to meet robotic mission customer requirements emerged as the key challenge. In the 2030’s and beyond, simulations suggested a need for fundamentally new capability and capacity. The high data rates and long link distances characteristic of human Mars exploration drove requirements far beyond what is currently “in plan.” The key challenge then became determining the most cost-effective combination of RF and optical assets for communicating with the postulated human Mars assets while still providing for the needs of all the other missions across the solar system. Various link budget, visibility, and loading analyses ultimately suggested that the human Mars exploration demands of the 2030’s could best be addressed with two cross-linked RF-optical areostationary relays (or an areostationary relay and deep space habitat) providing a dual “trunk link” to an array of 2-to-3 additional 34m beam waveguide antennas and an ~8.5m optical antenna at each DSN Complex. The dual “trunk link” would enable the same amount of total data return to Earth as a single trunk link at twice the data rate, but with only half the required array size on the ground, assuming use of Multiple Spacecraft Per Antenna (MSPA) techniques. MSPA techniques, including a Multiple Uplink Per Antenna (MUPA) technique currently under investigation, also showed promise for reducing asset contention in the decades prior to human Mars exploration.

Lee, Carlyn-Ann↗
NASA NTRS2022

Application Table: A Bridge Connecting the Designing “With-The-Material” and “The-Material” Paradigms

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Materials↗