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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 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↗

DOE OSTI2024

A Comprehensive Northern Hemisphere Particle Microphysics Data Set From the Precipitation Imaging Package

Microphysical observations of precipitating particles are critical data sources for numerical weather prediction models and remote sensing retrieval algorithms. However, obtaining coherent data sets of particle microphysics is challenging as they are often unindexed, distributed across disparate institutions, and have not undergone a uniform quality control process. This work introduces a unified, comprehensive Northern Hemisphere particle microphysical data set from the National Aeronautics and Space Administration precipitation imaging package (PIP), accessible in a standardized data format and stored in a centralized, public repository. Data is collected from 10 measurement sites spanning 34° latitude (37°N–71°N) over 10 years (2014–2023), which comprise a set of 1,070,000 precipitating minutes. The provided data set includes measurements of a suite of microphysical attributes for both rain and snow, including distributions of particle size, vertical velocity, and effective density, along with higher-order products including an approximation of volume-weighted equivalent particle densities, liquid equivalent snowfall, and rainfall rate estimates. The data underwent a rigorous standardization and quality assurance process to filter out erroneous observations to produce a self-describing, scalable, and achievable data set. Case study analyses demonstrate the capabilities of the data set in identifying physical processes like precipitation phase-changes at high temporal resolution. Bulk precipitation characteristics from a multi-site intercomparison also highlight distinct microphysical properties unique to each location. This curated PIP data set is a robust database of high-quality particle microphysical observations for constraining future precipitation retrieval algorithms, and offers new insights toward better understanding regional and seasonal differences in bulk precipitation characteristics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Multi-scenario Extreme Weather Simulator application to heat waves: Ko’olauloa community resilience hub

Heat waves are increasing in severity, duration, and frequency. The Multi-Scenario Extreme Weather Simulator (MEWS) models this using historical data, climate model outputs, and heat wave multipliers. In this study, MEWS is applied for planning of a community resilience hub in Hau'ula, Hawaii. The hub will have normal operations and resilience operations modes. Both these modes were modeled using EnergyPlus. The resilience operations mode includes cutting off air conditioning for many spaces to decrease power requirements during emergencies. Results were simulated for 300 future weather files generated by MEWS for 2020, 2040, 2060, and 2080. Shared socioeconomic pathways 2-4.5, 3-7.0 and 5-8.5 were used. The resilience operations mode results show two to six times increase of hours of exceedance beyond 32.2 °C from present conditions, depending on climate scenario and future year. The resulting decrease in thermal resilience enables an average decrease of energy use intensity of 26% with little sensitivity to climate change. The decreased thermal resilience predicted in the future is undesirable, but was not severe enough to require a more energy-intensive resilience mode. Instead, planning is needed to assure vulnerable individuals are given prioritized access to air-conditioned parts of the hub if worst-case heat waves occur.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

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.↗

DOE OSTI2021

Transition to Online Cable Insulation Condition Monitoring

Nuclear power plant cables were originally qualified for 40 year life and generally have not required specific test verification to assure service availability through the initial plant qualification period. However, license renewals to 60 and 80 years of operation require a cable aging management program that depends on some form of test and verification to assure fitness for service. Environmental stress (temperature, radiation, chemicals, water, and mechanical) varies dramatically within a nuclear power plant and, in some cases, cables have degraded and required repair or replacement before their qualified end-of-life period. In other cases, cable conditions have been mild and dependable cable performance confirmed to extend well beyond the initial qualified life. Most offline performance-based testing requires cables to be de-coupled and de-energized for specially trained technicians to perform testing. These offline tests constitute an expensive operational burden that limits the economic viability of nuclear power plants. Although initial investment may be higher, new online test practices are emerging as options or complements to offline testing that avoid or minimize the regularly scheduled offline test burden. These online methods include electrical and fiber-optic partial discharge measurement, spread spectrum time or frequency domain reflectometry, distributed temperature profile measurements, and local interdigital capacitance measurement of insulation characteristics. Introduction of these methods must be supported by research to confirm efficacy plus either publicly financed or market driven investment to support the start-up expense of cost-effective instrumentation to monitor cable condition and assure reliable operation. This work summarizes various online cable assessment technologies plus introduces a new cable motor test bed to assess some of these technologies in a controlled test environment.

Glass, Samuel W.↗

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↗

DOE OSTI2022

Energy Resilience for Mission Assurance: Agile Co-simulation for Cyber Energy System Security (ACCESS), Model Advancements for Resilience Analysis

Agile Co-simulation for Cyber Energy System Security (ACCESS) is a co-simulation platform developed by Lawrence Livermore National Laboratory (LLNL). The primary high-level use-case for ACCESS is to study existing or new cyber-physical critical infrastructure systems, with a heavy emphasis on 1) systems that utilize communication networks, and 2) studies that seek to understand cyber-related system impacts. ACCESS is currently used for several energy system resilience projects at LLNL. In the Energy Resilience for Mission Assurance (ERMA) project, ACCESS is used in the Modeling for Metric Calculation task (specifically, subtask 4.3, Communications and Cyber Modeling) to model and simulate the cyber and communication system aspects of Defense Critical Electric Infrastructure (DCEI) systems, with a focus on computing specific communication system metrics that can impact system resilience and mission performance. Simulated communication system performance will be fed back to other ERMA system components so that mission performance can be evaluated holistically. This report describes several enhancements to the ACCESS platform that were implemented during the execution of the ERMA project in support of reslience analysis. This includes the addition of new models and subsystems, enhancements to existing models, and integration with external systems. The remainder of this report is structured as follows. In Section 2, a brief background description of the ACCESS platform is provided, including an outline of ACCESS components, example usecases, and a set of communication network resilience metrics that can be computed with ACCESS. Section 3 describes the ACCESS model enhancements for ERMA in detail. Finally, Section 4 briefly outlines future integration opportunities between ACCESS and project participant capabilities identified during the progression of the project.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Energy Resilience for Mission Assurance, Agile Co-simulation for Cyber Energy System Security (ACCESS) Model Advancements for Resilience Analysis (Version 3, July 2023)

Agile Co-simulation for Cyber Energy System Security (ACCESS) is a co-simulation platform developed by Lawrence Livermore National Laboratory (LLNL). The primary high-level use-case for ACCESS is to study existing or new cyber-physical critical infrastructure systems, with a heavy emphasis on 1) systems that utilize communication networks, and 2) studies that seek to understand cyber-related system impacts. ACCESS is currently used for several energy system resilience projects at LLNL. In the Energy Resilience for Mission Assurance (ERMA) project, ACCESS is used in the Mod eling for Metric Calculation task (specifically, subtask 4.3, Communications and Cyber Modeling) to model and simulate the cyber and communication system aspects of Defense Critical Electric Infrastructure (DCEI) systems, with a focus on computing specific communication system metrics that can impact system resilience and mission performance. Simulated communication system per formance will be fed back to other ERMA system components so that mission performance can be evaluated holistically. This report describes several enhancements to the ACCESS platform that were implemented during the execution of the ERMA project in support of reslience analysis. This includes the addition of new models and subsystems, enhancements to existing models, and integration with external systems. The remainder of this report is structured as follows. In Section 2, a brief background description of the ACCESS platform is provided, including an outline of ACCESS components, example use cases, and a set of communication network resilience metrics that can be computed with ACCESS. Section 3 describes the ACCESS model enhancements for ERMA in detail. Finally, Section 4 briefly outlines future integration opportunities between ACCESS and project participant capabilities identified during the progression of the project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

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.↗