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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 NTRS2016

Funding and Strategic Alignment Guidance for Infusing Small Business Innovation Research Technology Into Human Exploration and Operations Mission Directorate Projects at Glenn Research Center for 2015

This report is intended to help NASA program and project managers incorporate Glenn Research Center Small Business Innovation Research/Small Business Technology Transfer (SBIR)/(STTR) technologies into NASA Human Exploration and Operations Mission Directorate (HEOMD) programs and projects. Other Government and commercial project managers can also find this useful. Introduction Incorporating Small Business Innovation Research (SBIR)-developed technology into NASA projects is important, especially given the Agency's limited resources for technology development. The SBIR program's original intention was for technologies that had completed Phase II to be ready for integration into NASA programs, however, in many cases there is a gap between Technology Readiness Levels (TRLs) 5 and 6 that needs to be closed. After SBIR Phase II projects are completed, the technology is evaluated against various parameters and a TRL rating is assigned. Most programs tend to adopt more mature technologies-at least TRL 6 to reduce the risk to the mission rather than adopt TRLs between 3 and 5 because those technologies are perceived as too risky. The gap between TRLs 5 and 6 is often called the "Valley of Death" (Figure 1), and historically it has been difficult to close because of a lack of funding support from programs. Several papers have already suggested remedies on how to close the gap (Refs. 1 to 4).

infusion; space transportation;life support system↗
NASA NTRS2002

Second Generation RLV Space Vehicle Concept

NASA has a long history of conducting development programs and projects in a consistent fashion. Systems Engineering within those programs and projects has also followed a given method outlined by such documents as the NASA Systems Engineering Handbook. The relatively new NASA Space Launch Initiative (SLI) is taking a new approach to developing a space vehicle, with innovative management methods as well as new Systems Engineering processes. With the program less than a year into its life cycle, the efficacy of these new processes has yet to be proven or disproven. At $776M for phase 1, SLI represents a major portion of the NASA focus; however, the new processes being incorporated are not reflected in the training provided by NASA to its engineers. The NASA Academy of Program and Project Leadership (APPL) offers core classes in program and project management and systems engineering to NASA employees with the purpose of creating a "knowledge community where ideas, skills, and experiences are exchanged to increase each other's capacity for strong leadership". The SLI program is, in one sense, a combination of a conceptual design program and a technology program. The program as a whole doesn't map into the generic systems engineering project cycle as currently, and for some time, taught. For example, the NASA APPL Systems Engineering training course teaches that the "first step in developing an architecture is to define the external boundaries of the system", which will require definition of the interfaces with other systems and the next step will be to "define all the components that make up the next lower level of the system hierarchy" where fundamental requirements are allocated to each component. Whereas, the SLI technology risk reduction approach develops architecture subsystem technologies prior to developing architectures. The higher level architecture requirements are not allowed to fully develop and undergo decomposition and allocation down to the subsystems before the subsystems must develop allocated requirements based on the highest level of requirements. In the vernacular of the project cycles prior to the mid 1990's, the architecture definition portion of the program appears to be at a generic Phase A stage, while the subsystems are operating at Phase B. Even the management structure of the SLI program is innovative in its approach to Systems Engineering and is not reflected in the APPL training modules. The SLI program has established a Systems Engineering office as an office separate from the architecture development or the subsystem technology development, while that office does have representatives within these other offices. The distributed resources of the Systems Engineering Office are co-located with the respective Project Offices. This template is intended to provide systems engineering as an integrated function at the Program Level. the program management of SLI and the MAT agree that "program/project managers and the systems engineering team must work closely together towards the single objective of delivering quality products that meet the customer needs". This paper will explore the differences between the methods being taught by NASA, which represent decades of ideas, and those currently in practice in SLI. Time will tell if the innovation employed by SLI will prove to be the model of the future. For now, it is suggested that the training of the present exercise the flexibility of recognizing the new processes employed by a major new NASA program.

Bailey, Michelle↗
NASA NTRS2002

A Virtual Mission Operations Center - Collaborative Environment

Development of technologies that enable significant reductions in the cost of space mission operations is critical if constellations, formations, federations and sensor webs, are to be economically feasible. One approach to cost reduction is to infuse automation technologies into mission operations centers so that fewer personnel are needed for mission support. But missions are more culturally and politically adverse to the risks of automation. Reducing the mission risk associated with increased use of automation within a MOC is therefore of great importance. The belief that mission risk increases as more automation is used stems from the fact that there is inherently less direct human oversight to investigate and resolve anomalies in an unattended MOC. The Virtual Missions Operations Center - Collaborative Environment (VMOC-CE) project was launched to address this concern. The goal of the VMOC-CE project is to identify, develop, and infuse technology to enable mission operations between onsite operators and on-call personnel in geographically dispersed locations. VMOC-CE enables missions to more readily adopt automation because off-site operators and engineers can more easily identify, investigate, and resolve anomalies without having to be present in the MOC. The VMOC-CE intent is to have a single access point for all resources used in a collaborative mission operations environment. Team members will be able to interact during spacecraft operations, specifically for resolving anomalies, utilizing a desktop computer and the Internet. Mission operations management can use the VMOC-CE as a tool to participate in and monitor status of anomaly resolution or other mission operations issues. In this paper we present the VMOC-CE project, system capabilities and technologies, operations concept, and results of its pilot in support of the Earth Science Mission Operations System (ESMOS).

Medina, Barbara↗
NASA NTRS2011

Systems Engineering Using Heritage Spacecraft Technology: Lessons Learned from Discovery and New Frontiers Deep Space Missions

In the design and development of complex spacecraft missions, project teams frequently assume the use of advanced technology or heritage systems to enable a mission or reduce the overall mission risk and cost. As projects proceed through the development life cycle, increasingly detailed knowledge of the advanced or heritage systems and the system environment identifies unanticipated issues that result in cost overruns or schedule impacts. The Discovery & New Frontiers (D&NF) Program Office recently studied cost overruns and schedule delays resulting from advanced technology or heritage assumptions for 6 D&NF missions. The goal was to identify the underlying causes for the overruns and delays, and to develop practical mitigations to assist the D&NF projects in identifying potential risks and controlling the associated impacts to proposed mission costs and schedules. The study found that the cost and schedule growth did not result from technical hurdles requiring significant technology development. Instead, systems engineering processes did not identify critical issues early enough in the design cycle to ensure project schedules and estimated costs address the inherent risks. In general, the overruns were traceable to: inadequate understanding of the heritage system s behavior within the proposed spacecraft design and mission environment; an insufficient level of experience with the heritage system; or an inadequate scoping of the system-wide impacts necessary to implement the heritage or advanced technology. This presentation summarizes the study s findings and offers suggestions for improving the project s ability to identify and manage the risks inherent in the technology and heritage design solution.

Barley, Bryan↗
DOE OSTI2022

Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry

Estimation of riverbed profiles, also known as bathymetry, plays a vital role in many applications, such as safe and efficient inland navigation, prediction of bank erosion, land subsidence, and flood risk management. The high cost and complex logistics of direct bathymetry surveys, i.e, depth imaging, have encouraged the use of indirect measurements such as surface flow velocities. However, estimating high-resolution bathymetry from indirect measurements is an inverse problem that can be computationally challenging. Here, we propose a reduced-order model (ROM) based approach that utilizes a variational autoencoder (VAE), a type of deep neural network with a narrow layer in the middle, to compress bathymetry and flow velocity information and accelerate bathymetry inverse problems from flow velocity measurements. In our application, the shallow-water equations (SWE) with appropriate boundary conditions (BCs), e.g., the discharge and/or the free surface elevation, constitute the forward problem, to predict flow velocity. Then, ROMs of the SWEs are constructed on a nonlinear manifold of low dimensionality through a variational encoder and the bathymetry inversion problem is derived on the low-dimensional latent space in a Hierarchical Bayesian setting. Further, the reformulation allows variational inference with a small number (e.g., $\mathscr{O}$ (100) of ROM runs and efficient uncertainty quantification. We have tested our inversion approach on a one-mile reach of the Savannah River, GA, USA. Once the neural network is trained (offline stage), the proposed technique can perform the inversion operation orders of magnitude faster than traditional inversion methods that are commonly based on linear projections, such as principal component analysis (PCA), or the principal component geostatistical approach (PCGA). Furthermore, tests show that the algorithm can estimate the bathymetry with good accuracy even with sparse flow velocity measurements.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

An Introduction to Flight Software Development: FSW Today, FSW 2010

Experience and knowledge gained from ongoing maintenance of Space Shuttle Flight Software and new development projects including Cockpit Avionics Upgrade are applied to projected needs of the National Space Exploration Vision through Spiral 2. Lessons learned from these current activities are applied to create a sustainable, reliable model for development of critical software to support Project Constellation. This presentation introduces the technologies, methodologies, and infrastructure needed to produce and sustain high quality software. It will propose what is needed to support a Vision for Space Exploration that places demands on the innovation and productivity needed to support future space exploration. The technologies in use today within FSW development include tools that provide requirements tracking, integrated change management, modeling and simulation software. Specific challenges that have been met include the introduction and integration of Commercial Off the Shelf (COTS) Real Time Operating System for critical functions. Though technology prediction has proved to be imprecise, Project Constellation requirements will need continued integration of new technology with evolving methodologies and changing project infrastructure. Targets for continued technology investment are integrated health monitoring and management, self healing software, standard payload interfaces, autonomous operation, and improvements in training. Emulation of the target hardware will also allow significant streamlining of development and testing. The methodologies in use today for FSW development are object oriented UML design, iterative development using independent components, as well as rapid prototyping . In addition, Lean Six Sigma and CMMI play a critical role in the quality and efficiency of the workforce processes. Over the next six years, we expect these methodologies to merge with other improvements into a consolidated office culture with all processes being guided by automated office assistants. The infrastructure in use today includes strict software development and configuration management procedures, including strong control of resource management and critical skills coverage. This will evolve to a fully integrated staff organization with efficient and effective communication throughout all levels guided by a Mission-Systems Architecture framework with focus on risk management and attention toward inevitable product obsolescence. This infrastructure of computing equipment, software and processes will itself be subject to technological change and need for management of change and improvement,

Gouvela, John↗
NASA NTRS2011

Fault Management Guiding Principles

Regardless of the mission type: deep space or low Earth orbit, robotic or human spaceflight, Fault Management (FM) is a critical aspect of NASA space missions. As the complexity of space missions grows, the complexity of supporting FM systems increase in turn. Data on recent NASA missions show that development of FM capabilities is a common driver for significant cost overruns late in the project development cycle. Efforts to understand the drivers behind these cost overruns, spearheaded by NASA's Science Mission Directorate (SMD), indicate that they are primarily caused by the growing complexity of FM systems and the lack of maturity of FM as an engineering discipline. NASA can and does develop FM systems that effectively protect mission functionality and assets. The cost growth results from a lack of FM planning and emphasis by project management, as well the maturity of FM as an engineering discipline, which lags behind the maturity of other engineering disciplines. As a step towards controlling the cost growth associated with FM development, SMD has commissioned a multi-institution team to develop a practitioner's handbook representing best practices for the end-to-end processes involved in engineering FM systems. While currently concentrating primarily on FM for science missions, the expectation is that this handbook will grow into a NASA-wide handbook, serving as a companion to the NASA Systems Engineering Handbook. This paper presents a snapshot of the principles that have been identified to guide FM development from cradle to grave. The principles range from considerations for integrating FM into the project and SE organizational structure, the relationship between FM designs and mission risk, and the use of the various tools of FM (e.g., redundancy) to meet the FM goal of protecting mission functionality and assets.

principles↗
NASA NTRS2013

A Proposed Approach for Prioritizing Maintenance at NASA Centers

The National Aeronautics and Space Administration (NASA) manages a vast array of infrastructure assets across ten National Centers with a worth of at least 30 billion dollars. Eighty percent of this infrastructure is greater than 40 years old and is in degraded condition. Maintenance budgets are typically less than one percent of current replacement value (CRV), much less than the 2-4% recommended by the National Research Council. The maintenance backlog was 2.55 billion dollars in FY10 and growing. NASA s annual budgets have flattened and are at risk of being reduced, so the problem is becoming even more difficult. NASA Centers utilize various means to prioritize and accomplish maintenance within available budgets, though data is suspect and processes are variable. This paper offers a structured means to prioritize maintenance based on mission criticality and facility performance (ability of the facility to deliver on its purpose). Mission alignment is assessed using the current timeframe Mission Dependence Index and a measure of facility alignment with the 2011 NASA Strategic Plan for the long-term perspective. Facility performance is assessed by combining specific findings from a structured facility condition assessment and an assessment of actual functional output. These are then combined in a matrix to identify the facilities most critical to mission and able to deliver services. The purpose of this approach is to provide the best benefits for the available funding. Additionally, this rationale can also be applied to the prioritization of investment (recapitalization) projects so that the ultimate customers of this paper, the senior infrastructure managers at each NASA Center, are better able to strategically manage their capabilities.

Dunn, Steven C.↗
NASA NTRS2016

High Data Rate Architecture (HiDRA)

One of the greatest challenges in developing new space technology is in navigating the transition from ground based laboratory demonstration at Technology Readiness Level 6 (TRL-6) to conducting a prototype demonstration in space (TRL-7). This challenge is com- pounded by the relatively low availability of new spacecraft missions when compared with aeronautical craft to bridge this gap, leading to the general adoption of a low-risk stance by mission management to accept new, unproven technologies into the system. Also in consideration of risk, the limited selection and availability of proven space-grade components imparts a severe limitation on achieving high performance systems by current terrestrial technology standards. Finally from a space communications point of view the long duration characteristic of most missions imparts a major constraint on the entire space and ground network architecture, since any new technologies introduced into the system would have to be compliant with the duration of the currently deployed operational technologies, and in some cases may be limited by surrounding legacy capabilities. Beyond ensuring that the new technology is verified to function correctly and validated to meet the needs of the end users the formidable challenge then grows to additionally include: carefully timing the maturity path of the new technology to coincide with a feasible and accepting future mission so it flies before its relevancy has passed, utilizing a limited catalog of available components to their maximum potential to create meaningful and unprecedented new capabilities, designing and ensuring interoperability with aging space and ground infrastructures while simultaneously providing a growth path to the future. The International Space Station (ISS) is approaching 20 years of age. To keep the ISS relevant, technology upgrades are continuously taking place. Regarding communications, the state-of-the-art communication system upgrades underway include high-rate laser terminals. These must interface with the existing, aging data infrastructure. The High Data Rate Architecture (HiDRA) project is designed to provide networked store, carry, and forward capability to optimize data flow through both the existing radio frequency (RF) and new laser communications terminal. The networking capability is realized through the Delay Tolerant Networking (DTN) protocol, and is used for scheduling data movement as well as optimizing the performance of existing RF channels. HiDRA is realized as a distributed FPGA memory and interface controller that is itself controlled by a local computer running DTN software. Thus HiDRA is applicable to other arenas seeking to employ next-generation communications technologies, e.g. deep space. In this paper, we describe HiDRA and its far-reaching research implications.

DTN↗
NASA NTRSDate not supplied

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗
NASA NTRSDate not supplied

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism, behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗
NASA NTRS2005

Artificial Neural Network Test Support Development for the Space Shuttle PRCS Thrusters

A significant anomaly, Fuel Valve Pilot Seal Extrusion, is affecting the Shuttle Primary Reaction Control System (PRCS) Thrusters, and has caused 79 to fail. To help address this problem, a Shuttle PRCS Thruster Process Evaluation Team (TPET) was formed. The White Sands Test Facility (WSTF) and Boeing members of the TPET have identified many discrete valve current trace characteristics that are predictive of the problem. However, these are difficult and time consuming to identify and trend by manual analysis. Based on this exhaustive analysis over months, 22 thrusters previously delivered by the Depot were identified as high risk for flight failures. Although these had only recently been installed, they had to be removed from Shuttles OV103 and OV104 for reprocessing, by directive of the Shuttle Project Office. The resulting impact of the thruster removal, replacement, and valve replacement was significant (months of work and hundreds of thousands of dollars). Much of this could have been saved had the proposed Neural Network (NN) tool described in this paper been in place. In addition to the significant benefits to the Shuttle indicated above, the development and implementation of this type of testing will be the genesis for potential Quality improvements across many areas of WSTF test data analysis and will be shared with other NASA centers. Future tests can be designed to incorporate engineering experience via Artificial Neural Nets (ANN) into depot level acceptance of hardware. Additionally, results were shared with a NASA Engineering and Safety Center (NESC) Super Problem Response Team (SPRT). There was extensive interest voiced among many different personnel from several centers. There are potential spin-offs of this effort that can be directly applied to other data acquisition systems as well as vehicle health management for current and future flight vehicles.

Lehr, Mark E.↗
NASA NTRS2004

Evaluation of Open-Source Hard Real Time Software Packages

Reliable software is, at times, hard to find. No piece of software can be guaranteed to work in every situation that may arise during its use here at Glenn Research Center or in space. The job of the Software Assurance (SA) group in the Risk Management Office is to rigorously test the software in an effort to ensure it matches the contract specifications. In some cases the SA team also researches new alternatives for selected software packages. This testing and research is an integral part of the department of Safety and Mission Assurance. Real Time operation in reference to a computer system is a particular style of handing the timing and manner with which inputs and outputs are handled. A real time system executes these commands and appropriate processing within a defined timing constraint. Within this definition there are two other classifications of real time systems: hard and soft. A soft real time system is one in which if the particular timing constraints are not rigidly met there will be no critical results. On the other hand, a hard real time system is one in which if the timing constraints are not met the results could be catastrophic. An example of a soft real time system is a DVD decoder. If the particular piece of data from the input is not decoded and displayed to the screen at exactly the correct moment nothing critical will become of it, the user may not even notice it. However, a hard real time system is needed to control the timing of fuel injections or steering on the Space Shuttle; a delay of even a fraction of a second could be catastrophic in such a complex system. The current real time system employed by most NASA projects is Wind River's VxWorks operating system. This is a proprietary operating system that can be configured to work with many of NASA s needs and it provides very accurate and reliable hard real time performance. The down side is that since it is a proprietary operating system it is also costly to implement. The prospect of replacing this somewhat costly implementation is the focus of one of the SA group s current research projects. The explosion of open source software in the last ten years has led to the development of a multitude of software solutions which were once only produced by major corporations. The benefits of these open projects include faster release and bug patching cycles as well as inexpensive if not free software solutions. The main packages for hard real time solutions under Linux are Real Time Application Interface (RTAI) and two varieties of Real Time Linux (RTL), RTLFree and RTLPro. During my time here at NASA I have been testing various hard real time solutions operating as layers on the Linux Operating System. All testing is being run on an Intel SBC 2590 which is a common embedded hardware platform. The test plan was provided to me by the Software Assurance group at the start of my internship and my job has been to test the systems by developing and executing the test cases on the hardware. These tests are constructed so that the Software Assurance group can get hard test data for a comparison between the open source and proprietary implementations of hard real time solutions.

Mattei, Nicholas S.↗
NASA NTRS1996

Space Station Furnace Facility Management Information System (SSFF-MIS) Development

This report summarizes the chronology, results, and lessons learned from the development of the SSFF-MIS. This system has been nearly two years in development and has yielded some valuable insights into specialized MIS development. General: In December of 1994, the Camber Corporation and Science Applications International Corporation (SAIC) were contracted to design, develop, and implement a MIS for Marshall Space Flight Center's Space Station Furnace Facility Project. The system was to be accessible from both EBM-Compatible PC and Macintosh platforms. The system was required to contain data manually entered into the MIS as well as data imported from other MSFC sources. Electronic interfaces were established for each data source and retrieval was to be performed at prescribed time intervals. The SOW requirement that predominantly drove the development software selection was the dual-platform (IBM-PC and Macintosh) requirement. The requirement that the system would be maintained by Government personnel influenced the selection of Commercial Off-the-shelf software because of its inherent stability and readily available documentation and support. Microsoft FoxPro Professional 2.6 for Windows and Macintosh was selected as the development tool. This is a software development tool that has been in use for many years. It is stable and powerful. Microsoft has since released the replacement for this product, Microsoft Visual FoxPro, but at the time of this development, it was only available on the Windows platform. The initial contract included included the requirement for capabilities relating to the Work- and Organizational Breakdown Structures, cost (plan and actuals), workforce (plan and actuals), critical path scheduling, trend analysis, procurements and contracts, interface to manufacturing, Safety and Mission Assurance, risk analysis, and technical performance indicators. It also required full documentation of the system and training of users. During the course of the contract, the requirements for Safety and Mission Assurance interface, risk analysis, and technical performance indicators were deleted. Additional capabilities were added as reflected in the Contract Chronology below. Modification 4 added the requirement for Support Contractor manpower data, the ability to manually input data not imported from non-nal sources, a general 'health' indicator screen, and remote usage. Mod 6 included the ability to change the level of planning of Civil Service Manpower at any time and the ability to manually enter Op Codes in the manufacturing data where such codes were not provided by the EMPACS database. Modification 9 included a number of changes to report contents and formats. Modification 11 required the preparation of a detailed System Design Document.

Meade, Robert M.↗
NASA NTRS2020

Use of Climate Change Projections for Resilience Planning in Rio de Janeiro, Brazil

In this study we use three different methodologies to document and compare temperature and precipitation projections for the city of Rio de Janeiro (RJ) over the 21st century. It aims to explore in what way the differences and similarities of those methodologies and their outcomes support the incorporation of climate risks in urban planning and improve effective urban climate change governance. We compared the projections for RJ from the Eta Regional Climate Model from the Brazilian National Institute for Space Research nested in two Hadley Center Global Climate Models (GCMs) (Eta-HadCM3 method and Eta-HadGEM2-ES method) and 33 GCMs from the Coupled Model Intercomparison Project Phase 5 multi-model dataset (Urban Climate Change Research Network - UCCRN method). The three methods showed increasing temperatures for RJ at the end of the century. Precipitation projections span a 13% decrease to a 12% increase when using the UCCRN method or are reduced between 0.4 and 0.5%, when using the Eta-HadGEM2-ES method. However, the middle range of the projections from UCCRN and Eta-HadGEM2-ES is similar. The three methods project an increase of warm days and nights and a decrease of cold days and nights. Nevertheless, although the directions of change are the same applying the three methods, the magnitude differs when considering warm and cold nights. Hence, city stakeholders are better informed when we apply different projection methods as it gives them the opportunity to consider the level of risk they are willing to bear in the future. We observed that defining climate change projections on the city scale based on clear communication and an interactive process between scientists and stakeholders can be used to inform citywide adaptation strategies and sector-specific uses, as well as promote urban climate risk governance.

urban governance and management↗
NASA NTRSDate not supplied

Utilization of Machine Learning Techniques for Managing the Tracking and Data Relay Satellite Constellation

National Aeronautics and Space Administration’s (NASA) Goddard Space Flight Center (GSFC) operates a constellation of ten geosynchronous Tracking and Data Relay Satellites (TDRS). The TDRS constellation consists of multiple geosynchronous communication relay satellites located around the equator so they can provide continual coverage of any mission in low earth orbit. The TDRS are located primarily in three oceanic regions around the earth. NASA’s White Sands Complex provides the ground communication support for TDRS located over the Atlantic and Pacific Oceans. Another TDRS ground station in Guam supports the TDRS over the Indian Ocean. With these satellites the TDRS network can provide continuous coverage of satellites in low-earth orbit. The NASA Space Network (SN) project office at GSFC manages the constellation of spacecraft. Major customers of the TDRS constellation include, but are not limited to, the International Space Station and the Hubble Space Telescope. The TDRS constellation has three generations of satellites and has been active for over 30 years providing reliable communication links between customer satellites and corresponding ground stations. However, one of the major concerns for TDRS, and in any space mission, is to ensure the health and safety of the spacecraft. Generally, engineers use telemetry data to monitor and analyze the performance and state of health of the spacecraft. Telemetry data contains hundreds of parameters that monitor each important component in the spacecraft, which can be utilized to recognize and characterize the behavior of the spacecraft. Each parameter contains considerable information to represent time-dependent properties of each spacecraft subsystem and component. During the entire life of a TDRS spacecraft, thousands of gigabytes of telemetry data are transmitted in real-time from the spacecraft to the ground station at the White Sands Complex in Las Cruces, New Mexico, and recorded as historical data sets for engineers to process and analyze the events that occurred on-orbit. These parameters contain the function of multiple spacecraft subsystems, such as the attitude control system (ACS), Thermal, Electrical Power Subsystem (EPS), etc. . The first and second generations have exceeded their required lifetime and NASA is keen to manage these spacecrafts carefully in order to maximize the remaining life using the spacecraft telemetry. The challenge is to know when the risk of losing a spacecraft in geosynchronous orbit exceeds the benefit of continued operations for customer support. In the TDRS fleet, the EPS is the most critical subsystem related to spacecraft operations. Failure of the EPS would strand a spacecraft in geosynchronous orbit. Since EPS provides power to the spacecraft, component failures ultimately lead to the inability to support the spacecraft loads and the communications payload. For instance, TDRS-8 has several anomalies in EPS including the Bus Voltage Limiter (BVL) shunt current, solar array loss of circuits, and failed battery cells. Any of these anomalies can cause critical issues to the spacecraft. Therefore, developing a system to analyze and perform early detection of a potential anomaly is an important issue in telemetry data analysis. In recent years, Telemetry Mining (TM) has been proposed to process telemetry data by using Data Mining (DM) techniques such as classification, clustering, regression and anomaly detection. Anomaly detection, also known as outlier detection, has been widely used in many data mining areas such as remote sensing, medical data processing and digital image processing. The goal of anomaly detection is to detect abnormal data, which contains a relatively low probability of occurrence among the entire data set. Early detection of anomalies is one of the most significant issues in managing the spacecraft configuration. If anomalies can be detected early enough, then the redundant resources can be used to extend the life of the operational spacecraft. We present an unsupervised anomaly detection method to process the EPS data extracted from TDRS-8. This is different from traditional analytical methods, which use telemetry data to illustrate behavior and physical meaning of each spacecraft component. TM connects multiple parameters as a vector and then conducts data analysis on this high dimension telemetry vector. This method is looking at the properties of a high dimensional vector that is able to consider the relationship between different parameters in the anomaly detection problem. This kind of method performs much better than the traditional limit checking method. In addition, we propose a new approach of real-time anomaly detection to process telemetry data in real-time, which can then be applied to spacecraft monitoring with high reliability, low cost and high accuracy.

Machine Learning (ML)↗
NASA NTRS2009

Flight and Integrated Vehicle Testing: Laying the Groundwork for the Next Generation of Space Exploration Launch Vehicles

Integrated vehicle testing will be critical to ensuring proper vehicle integration of the Ares I crew launch vehicle and Ares V cargo launch vehicle. The Ares Projects, based at Marshall Space Flight Center in Alabama, created the Flight and Integrated Test Office (FITO) as a separate team to ensure that testing is an integral part of the vehicle development process. As its name indicates, FITO is responsible for managing flight testing for the Ares vehicles. FITO personnel are well on the way toward assembling and flying the first flight test vehicle of Ares I, th Ares I-X. This suborbital development flight will evaluate the performance of Ares I from liftoff to first stage separation, testing flight control algorithms, vehicle roll control, separation and recovery systems, and ground operations. Ares I-X is now scheduled to fly in summer 2009. The follow-on flight, Ares I-Y, will test a full five-segment first stage booster and will include cryogenic propellants in the upper stage, an upper stage engine simulator, and an active launch abort system. The following flight, Orion 1, will be the first flight of an active upper stage and upper stage engine, as well as the first uncrewed flight of an Orion spacecraft into orbit. The Ares Projects are using an incremental buildup of flight capabilities prior to the first operational crewed flight of Ares I and the Orion crew exploration vehicle in 2015. In addition to flight testing, the FITO team will be responsible for conducting hardware, software, and ground vibration tests of the integrated launch vehicle. These efforts will include verifying hardware, software, and grou handling interfaces. Through flight and integrated testing, the Ares Projects will identify and mitigate risks early the United States prepares to take its next giant leaps to the Moon and beyond.

Taylor, Jim↗
NASA NTRS2009

Flight and Integrated Vehicle Testing: Laying the Groundwork for the Next Generation of Space Exploration Launch Vehicles

Integrated vehicle testing will be critical to ensuring proper vehicle integration of the Ares I crew launch vehicle and Ares V cargo launch vehicle. The Ares Projects, based at Marshall Space Flight Center in Alabama, created the Flight and Integrated Test Office (FITO) as a separate team to ensure that testing is an integral part of the vehicle development process. As its name indicates, FITO is responsible for managing flight testing for the Ares vehicles. FITO personnel are well on the way toward assembling and flying the first flight test vehicle of Ares I, the Ares I-X. This suborbital development flight will evaluate the performance of Ares I from liftoff to first stage separation, testing flight control algorithms, vehicle roll control, separation and recovery systems, and ground operations. Ares I-X is now scheduled to fly in summer 2009. The follow-on flight, Ares I-Y, will test a full five-segment first stage booster and will include cryogenic propellants in the upper stage, an upper stage engine simulator, and an active launch abort system. The following flight, Orion 1, will be the first flight of an active upper stage and upper stage engine, as well as the first uncrewed flight of an Orion spacecraft into orbit. The Ares Projects are using an incremental buildup of flight capabilities prior to the first operational crewed flight of Ares I and the Orion crew exploration vehicle in 2015. In addition to flight testing, the FITO team will be responsible for conducting hardware, software, and ground vibration tests of the integrated launch vehicle. These efforts will include verifying hardware, software, and ground handling interfaces. Through flight and integrated testing, the Ares Projects will identify and mitigate risks early as the United States prepares to take its next giant leaps to the Moon and beyond.

Taylor, J. L.↗