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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 163 records · Page 9

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NASA NTRS1990

Computation of three-dimensional compressible boundary layers to fourth-order accuracy on wings and fuselages

A solution method, fourth-order accurate in the body-normal direction and second-order accurate in the stream surface directions, to solve the compressible 3-D boundary layer equations is presented. The transformation used, the discretization details, and the solution procedure are described. Ten validation cases of varying complexity are presented and results of calculation given. The results range from subsonic flow to supersonic flow and involve 2-D or 3-D geometries. Applications to laminar flow past wing and fuselage-type bodies are discussed. An interface procedure is used to solve the surface Euler equations with the inviscid flow pressure field as the input to assure accurate boundary conditions at the boundary layer edge. Complete details of the computer program used and information necessary to run each of the test cases are given in the Appendix.

Iyer, Venkit↗

NASA NTRS2018

Supplier Research & Analysis Approach

"The implementation of NASA GSFC's portfolio of mission projects relies upon inter-connected, multi-tiered supply chains of organizations operating under direct and indirect contracts and other agreements throughout the U.S. and around the world. These supply chains are subject to an inter-related array of technical/production, business, market and security risks that are amplified by the ongoing globalization of industry and technology and which can disrupt or threaten the production and delivery of products and services when needed and in conformance with requirements. In recognition of such risks and associated challenges, GSFC's SMA directorate launched an innovative Supplier Research and Analysis (SRA) capability three years ago to gain greater insight into the operating environment, performance, capabilities and viability of current and prospective suppliers for GSFC projects and proposals. The capability uses business intelligence techniques and primarily open source information resources as part of a cost-effective, non-intrusive methodology to produce several types of research and analysis reports. The reports are based on a holistic analytical framework encompassing key technical/production, business enterprise management, market and security factors, and feature in-depth information, summary information profiles, SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis, and candidate risk concerns in order to pro-actively support SMA and project management needs. The SRA capability, which is designed to complement and support ongoing SMA/project management activities and practices, has produced over 95 reports since its start-up in early 2015. This presentation addresses the approach, methodology and performance of the Supplier Research and Analysis (SRA) capability and its value in assuring the success of NASA mission projects. In doing so, the presentation provides lessons-learned, best practices, case examples and address how it fits into the development of an enterprise-level Supply Chain Risk Management capability."

supplier research and analysis↗

NASA NTRS2018

Supply Chain Research and Analysis for Space Systems

The implementation of NASA GSFC's portfolio of mission projects relies upon inter-connected, multi-tiered supply chains of organizations operating under direct and indirect contracts and other agreements throughout the U.S. and around the world. These supply chains are subject to an inter-related array of technical/production, business, market and security risks that are amplified by the ongoing globalization of industry and technology and which can disrupt or threaten the production and delivery of products and services when needed and in conformance with requirements. In recognition of such risks and associated challenges, GSFC's SMA directorate launched an innovative Supply Chain Research and Analysis capability three years ago to gain greater insight into the operating environment, performance, capabilities and viability of current and prospective suppliers for GSFC projects and proposals. The capability uses business intelligence techniques and primarily open source information resources as part of a cost-effective, non-intrusive methodology to produce several types of research and analysis reports. The reports are based on a holistic analytical framework encompassing key technical/production, business enterprise management, market and security factors, and feature in-depth information, summary information profiles, SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis, and candidate risk concerns in order to pro-actively support SMA and project management needs. The SRA capability, which is designed to complement and support ongoing SMA/project management activities and practices, has produced over 105 reports since its start-up in early 2015.This presentation addresses the approach, methodology and performance of the Supply Chain Research and Analysiscapability and its value in assuring the success of NASA mission projects. In doing so, the presentation provides lessons-learned, best practices, case examples and address how it fits into the development of an enterprise-level Supply Chain Risk Management capability.

supply chain risk management↗

NASA NTRS2021

Sample Return Containerization and Planetary Protection Using Brazing for Breaking the Chain of Contact to Mars

Planetary protection of Mars samples returned to Earth in a future NASA mission is a critical part of preventing uncontrolled biological materials being released from the samples. The planetary protection process requires addressing the potential risks and would involve “breaking the chain of contact (BTC)”, where any returned material reaching Earth for further analysis would have to be sealed inside a container with extremely high confidence. The sterilization process would require destroying any potential biological materials that may contaminate the external surface of the container. A novel process for containing the returned samples has been conceived and developed at JPL. The process consists of using induction heated brazing to synchronously sterilize, separate, seam and seal the container. In this case. the braze material is heated to the level of melting at temperatures higher than 500°C to assure sterilizing exposed areas since carbon bonds are broken above this temperature. The container that encloses the samples consists of double walls with interstitial space that is Earth-clean. The process consists of two-steps, where one was intended to be prepared on Earth and the second potentially executed on orbit around Mars. The latest results of this study that established the needed capability are described and discussed in this manuscript.

Shirajian, Nareg↗

NASA NTRS2004

Verification of Emergent Behaviors in Swarm-based Systems

The emergent properties of swarms make swarm-based missions powerful, but at the same time more difficult to design and to assure that the proper behaviors will emerge. We are currently investigating formal methods and techniques for verification and validation of swarm-based missions. The Autonomous Nano-Technology Swarm (ANTS) mission is being used as an example and case study for swarm-based missions to experiment and test current formal methods with intelligent swarms. Using the ANTS mission, we have evaluated multiple formal methods to determine their effectiveness in modeling and assuring swarm behavior. This paper introduces how intelligent swarm technology is being proposed for NASA missions, and gives the results of a comparison of several formal methods and approaches for specifying intelligent swarm-based systems and their effectiveness for predicting emergent behavior.

Rouff, Christopher↗

NASA NTRS1976

SRM attrition rate study of the aft motor case segments due to water impact cavity collapse loading

The attrition assessment of the aft segments of Solid Rocket Motor due to water impact requires the establishment of a correlation between loading occurrences and structural capability. Each discrete load case, as identified by the water impact velocities and angle, varies longitudinally and radially in magnitude and distribution of the external pressure. The distributions are further required to be shifted forward or aft one-fourth the vehicle diameter to assure minimization of the effect of test instrumentation location for the load determinations. The asymmetrical load distributions result in large geometric nonlinearities in structural response. The critical structural response is progressive buckling of the case. Discrete stiffeners have been added to these aft segments to aid in gaining maximum structural capability for minimum weight addition for resisting these loads. This report presents the development of the attrition assessment of the aft segments and includes the rationale for eliminating all assessable conservatisms from this assessment.

Crockett, C. D.↗

NASA NTRS1994

Production and quality assurance automation in the Goddard Space Flight Center Flight Dynamics Facility

The Flight Dynamics Facility (FDF) at the NASA Goddard Space Flight Center (GSFC) generates numerous products for NASA-supported spacecraft, including the Tracking and Data Relay Satellites (TDRS's), the Hubble Space Telescope (HST), the Extreme Ultraviolet Explorer (EUVE), and the space shuttle. These products include orbit determination data, acquisition data, event scheduling data, and attitude data. In most cases, product generation involves repetitive execution of many programs. The increasing number of missions supported by the FDF has necessitated the use of automated systems to schedule, execute, and quality assure these products. This automation allows the delivery of accurate products in a timely and cost-efficient manner. To be effective, these systems must automate as many repetitive operations as possible and must be flexible enough to meet changing support requirements. The FDF Orbit Determination Task (ODT) has implemented several systems that automate product generation and quality assurance (QA). These systems include the Orbit Production Automation System (OPAS), the New Enhanced Operations Log (NEOLOG), and the Quality Assurance Automation Software (QA Tool). Implementation of these systems has resulted in a significant reduction in required manpower, elimination of shift work and most weekend support, and improved support quality, while incurring minimal development cost. This paper will present an overview of the concepts used and experiences gained from the implementation of these automation systems.

Chapman, K. B.↗

NASA NTRS1992

Optimal and robust controllers for periodic and multirate systems

The problem of optimal rejection of bounded persistent disturbances is solved in the case of linear discrete-time periodic systems. The solution consists of solving an equivalent time-invariant standard l1 optimization problem subject to an additional constraint. This constraint assures the causality of the resulting periodic controller. By the duality theory, the problem is shown to be equivalent to a linear programming problem, which is no harder than the standard l1 problem. Also, it is shown that the method of solution presented applies exactly to the problem of disturbance rejection in the case of multirate sampled data systems. Finally, the results are applied to the problem of robust stabilization of periodic and multirate systems.

Dahleh, Munther A.↗

NASA NTRS2020

Unsupervised Anomaly Detection in High-Dimensional Flight Data Using Convolutional Variational Auto-Encoder

The modern National Airspace System (NAS) is an extremely safe system and the aviation industry has experienced a steady decrease in fatalities over the years. This can be attributed to both improved flight critical systems with redundant hardware and software protections, as well as an increased focus on active monitoring and response to real time and historically identified vulnerabilities by implementing more resilient procedures and protocols. The main approach for identifying vulnerabilities in operations leverages domain expertise using knowledge about how the system should behave within the expected tolerances to known safety margins. This approach works well when the system has a well-defined operating condition. However, the operations in the NAS can be highly complex with various nuances that render it difficult to clearly pre-define all known safety vulnerabilities. With the advancement of data science and machine learning techniques, the potential to automatically identify emerging vulnerabilities in the observed operations has become more practical in recent years. The state-of-the-art anomaly detection approaches in aerospace data usually rely on supervised or semi-supervised learning. However, in many real-world problems such as flight safety, creating labels for the data requires huge amount of effort and is largely impractical. To address this challenge, we developed a Convolutional Variational Auto-Encoder (CVAE), which is an unsupervised learning approach for anomaly detection in high-dimensional heterogeneous time-series data. We validate performance of CVAE compared to the state-of-the-art supervised learning approach as well as unsupervised clustering-based approach using KMeans++ and kernel-based approach using One-Class Support Vector Machine (OC-SVM) on Yahoo!'s benchmark time series anomaly detection data. Finally, we showcase performance of CVAE on a case study of identifying anomalies in the first 60 seconds of commercial flights' take-offs using Flight Operational Quality Assurance (FOQA) data.

Memarzadeh, Milad↗

NASA NTRSDate not supplied

Unsupervised Anomaly Detection in High-Dimensional Flight Data Using Convolutional Variational Auto-Encoder

The modern National Airspace System (NAS) is an extremely safe system. The industry has experienced a steady decrease in fatalities over the years. This can be contributed to both improved flight critical systems with redundant hardware and software protections as well as an increased focus on active monitoring and response to real time and historically identified vulnerabilities by implementing more resilient procedures and protocols. The main practice for identifying vulnerabilities in operations leverages domain expertise using knowledge about how the system should behave with the expected tolerances to known safety margins. This approach works well when the system has a well-defined operating condition. However, the operations in the NAS can be highly complex with various nuances that render it difficult to clearly pre-define all known safety vulnerabilities. With the advancement of data science and machine learning techniques, the potential to automatically identify emerging vulnerabilities in the observed operations has become more practical in recent years. The state-of-the-art anomaly detection approaches in aerospace data usually rely on supervised or semi-supervised learning. However, in many real-world problems such as flight safety creating labels for the data requires huge amount of efforts and is largely expensive. As a result, in this article, we develop a Convolutional Variational Auto-Encoder (CVAE), an unsupervised learning approach for anomaly detection in high-dimensional heterogeneous time-series data. We validate performance of CVAE compared to the state-of-the-art supervised learning approach (as an upper bound) as well as an supervised clustering based on K-Means (as a lower bound) on Yahoo!'s benchmark time series anomaly detection data. Finally, we showcase performance of CVAE on a case study of identifying anomalies in the first 60 seconds of commercial flights' take-offs using Flight Operational Quality Assurance (FOQA) data.

Milad Memarzadeh↗

NASA NTRS2007

Space Flight Requirements for Fiber Optic Components; Qualification Testing and Lessons Learned

"Qualification" of fiber optic components holds a very different meaning than it did ten years ago. In the past, qualification meant extensive prolonged testing and screening that led to a programmatic method of reliability assurance. For space flight programs today, the combination of using higher performance commercial technology, with shorter development schedules and tighter mission budgets makes long term testing and reliability characterization unfeasible. In many cases space flight missions will be using technology within years of its development and an example of this is fiber laser technology. Although the technology itself is not a new product the components that comprise a fiber laser system change frequently as processes and packaging changes occur. Once a process or the materials for manufacturing a component change, even the data that existed on its predecessor can no longer provide assurance on the newer version. In order to assure reliability during a space flight mission, the component engineer must understand the requirements of the space flight environment as well as the physics of failure of the components themselves. This can be incorporated into an efficient and effective testing plan that "qualifies" a component to specific criteria defined by the program given the mission requirements and the component limitations. This requires interaction at the very initial stages of design between the system design engineer, mechanical engineer, subsystem engineer and the component hardware engineer. Although this is the desired interaction what typically occurs is that the subsystem engineer asks the components or development engineers to meet difficult requirements without knowledge of the current industry situation or the lack of qualification data. This is then passed on to the vendor who can provide little help with such a harsh set of requirements due to high cost of testing for space flight environments. This presentation is designed to guide the engineers of design, development and components, and vendors of commercial components with how to make an efficient and effective qualification test plan with some basic generic information about many space flight requirements. Issues related to the ~ physics of failure, acceptance criteria and lessons learned will also be discussed to assist with understanding how to approach a space flight mission in an ever changing commercial photonics industry.

Ott, Melanie N.↗

NASA NTRS2002

Airborne Use of Traffic Intent Information in a Distributed Air-Ground Traffic Management Concept: Experiment Design and Preliminary Results

This paper presents initial findings of a research study designed to provide insight into the issue of intent information exchange in constrained en-route air-traffic operations and its effect on pilot decision making and flight performance. The piloted simulation was conducted in the Air Traffic Operations Laboratory at the NASA Langley Research Center. Two operational modes for autonomous operations were compared under conditions of low and high operational complexity. The tactical mode was characterized primarily by the use of state information for conflict detection and resolution and an open-loop means for the pilot to meet operational constraints. The strategic mode involved the combined use of state and intent information, provided the pilot an additional level of alerting, and allowed a closed-loop approach to meeting operational constraints. Operational constraints included separation assurance, schedule adherence, airspace hazard avoidance, flight efficiency, and passenger comfort. Potential operational benefits of both modes are illustrated through several scenario case studies. Subjective pilot ratings and comments comparing the tactical and strategic modes are presented.

Wing, David J.↗

NASA NTRS2001

Airborne Use of Traffic Intent Information in a Distributed Air-Ground Traffic Management Concept: Experiment Design and Preliminary Results

Wing, David J.↗

NASA NTRS2008

Closing the Certification Gaps in Adaptive Flight Control Software

Over the last five decades, extensive research has been performed to design and develop adaptive control systems for aerospace systems and other applications where the capability to change controller behavior at different operating conditions is highly desirable. Although adaptive flight control has been partially implemented through the use of gain-scheduled control, truly adaptive control systems using learning algorithms and on-line system identification methods have not seen commercial deployment. The reason is that the certification process for adaptive flight control software for use in national air space has not yet been decided. The purpose of this paper is to examine the gaps between the state-of-the-art methodologies used to certify conventional (i.e., non-adaptive) flight control system software and what will likely to be needed to satisfy FAA airworthiness requirements. These gaps include the lack of a certification plan or process guide, the need to develop verification and validation tools and methodologies to analyze adaptive controller stability and convergence, as well as the development of metrics to evaluate adaptive controller performance at off-nominal flight conditions. This paper presents the major certification gap areas, a description of the current state of the verification methodologies, and what further research efforts will likely be needed to close the gaps remaining in current certification practices. It is envisioned that closing the gap will require certain advances in simulation methods, comprehensive methods to determine learning algorithm stability and convergence rates, the development of performance metrics for adaptive controllers, the application of formal software assurance methods, the application of on-line software monitoring tools for adaptive controller health assessment, and the development of a certification case for adaptive system safety of flight.

Jacklin, Stephen A.↗

NASA NTRS2011

State-Based Implicit Coordination and Applications

In air traffic management, pairwise coordination is the ability to achieve separation requirements when conflicting aircraft simultaneously maneuver to solve a conflict. Resolution algorithms are implicitly coordinated if they provide coordinated resolution maneuvers to conflicting aircraft when only surveillance data, e.g., position and velocity vectors, is periodically broadcast by the aircraft. This paper proposes an abstract framework for reasoning about state-based implicit coordination. The framework consists of a formalized mathematical development that enables and simplifies the design and verification of implicitly coordinated state-based resolution algorithms. The use of the framework is illustrated with several examples of algorithms and formal proofs of their coordination properties. The work presented here supports the safety case for a distributed self-separation air traffic management concept where different aircraft may use different conflict resolution algorithms and be assured that separation will be maintained.

Narkawicz, Anthony J.↗

NASA NTRS2016

Traveler Trustworthy Autonomy

NASAs Armstrong Flight Research Center has been engaged in the development of highly automatic safety systems for aviation since the mid 80s. For the past three years under Seedling and Center Innovation funding this work has moved toward the development of a software architecture applicable to autonomous safety. This work is now broadening and accelerating to address the airworthiness issues surrounding making a case for trustworthy autonomy. This software architecture is called the expandable variable-autonomy architecture (EVAA) and utilizes a run-time assurance approach to safety assurance.

autonomy↗

NASA NTRS1978

On-line parameter estimation using a high sensitivity estimator

An on-line parameter identification method is presented. The method is based on a recursive formulation of the maximum likelihood method, with a significant modification on the gains of the state estimator. In the conventional maximum likelihood method, the Kalman gains are used in the state estimator. This produces unbiased, minimum variance parameter estimates in the presence of process noise and measurement noise, but it also slows the convergence rate when the identification is done on-line. Here we suggest choosing the gains to maximize a measure of the sensitivities of the state estimates to parameter variations. One such criterion is to minimize the trace of the inverse information matrix. This increases the convergence rate significantly. After one or two time constants, the gains are switched to the Kalman values to assure unbiased, minimum-variance estimates. The state estimate will initially be nonoptimal, and may not be adequate for control purposes. In this case, a parallel Kalman filter which uses the identifier's parameter estimates can be used. This method is applied here for the identification of a simple first-order system, and for the identification of short-period stability derivatives of an F-8 aircraft from simulated data.

Mishne, D.↗

NASA NTRS1985

Assuring structural integrity in Army systems

The object of this study was to recommend possible improvements in the manner in which structural integrity of Army systems is assured. The elements of a structural integrity program are described, and relevant practices used in various industries and government organizations are reviewed. Some case histories of Army weapon systems are examined. The mandatory imposition of a structural integrity program patterned after the Air Force Aircraft Structural Integrity Program is recommended and the benefits of such an action are identified.

Source record↗