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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 19 records

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NASA NTRS1987

KBS V and V as related to automation of space station subsystems: Rationale for a KBS lifecycle

The role of verification and validation (V and V) in software has been to support and strengthen the software lifecycle and to ensure that the resultant code meets the standards of the requirements document. Knowledge based systems (KBS) V and V should serve the same role, but the KBS lifecycle is ill-defined. Here, the rationale of the simple form of the KBS lifecycle is explained. Special KBS development requirements are accommodated where possible by modifications to the traditional software lifecycle. Research areas are suggested for those aspects which present new or unusual difficulties for V and V.

Richardson, K.↗

NASA NTRS1998

Telescience Resource Kit Software Lifecycle

The challenge of a global operations capability led to the Telescience Resource Kit (TReK) project, an in-house software development project of the Mission Operations Laboratory (MOL) at NASA's Marshall Space Flight Center (MSFC). The TReK system is being developed as an inexpensive comprehensive personal computer- (PC-) based ground support system that can be used by payload users from their home sites to interact with their payloads on board the International Space Station (ISS). The TReK project is currently using a combination of the spiral lifecycle model and the incremental lifecycle model. As with any software development project, there are four activities that can be very time consuming: Software design and development, project documentation, testing, and umbrella activities, such as quality assurance and configuration management. In order to produce a quality product, it is critical that each of these activities receive the appropriate amount of attention. For TReK, the challenge was to lay out a lifecycle and project plan that provides full support for these activities, is flexible, provides a way to deal with changing risks, can accommodate unknowns, and can respond to changes in the environment quickly. This paper will provide an overview of the TReK lifecycle, a description of the project's environment, and a general overview of project activities.

Griner, Carolyn S.↗

NASA NTRS2010

Materials Lifecycle and Environmental Consideration at NASA

The aerospace community faces tremendous challenges with continued availability of existing material supply chains during the lifecycle of a program. Many obsolescence drivers affect the availability of materials: environmental safety ahd health regulations, vendor and supply economics, market sector demands,and natural disasters. Materials selection has become increasingly more critical when designing aerospace hardware. NASA and DoD conducted a workshop with subject matter experts to discuss issues and define solutions for materials selections during the lifecycle phases of a product/system/component. The three primary lifecycle phases were: Conceptualization/Design, Production & Sustainment, and End of life / Reclamation. Materials obsolescence and pollution prevention considerations were explored for the aforementioned lifecycle phases. The recommended solutions from the workshop are being presented.

Clark-Ingram, Marceia↗

NASA NTRS2010

Product Lifecycle Management and the Quest for Sustainable Space Exploration Solutions

Product Lifecycle Management (PLM) is an outcome of lean thinking to eliminate waste and increase productivity. PLM is inextricably tied to the systems engineering business philosophy, coupled with a methodology by which personnel, processes and practices, and information technology combine to form an architecture platform for product design, development, manufacturing, operations, and decommissioning. In this model, which is being implemented by the Engineering Directorate at the National Aeronautics and Space Administration's (NASA's) Marshall Space Flight Center, total lifecycle costs are important variables for critical decisionmaking. With the ultimate goal to deliver quality products that meet or exceed requirements on time and within budget, PLM is a powerful tool to shape everything from engineering trade studies and testing goals, to integrated vehicle operations and retirement scenarios. This paper will demonstrate how the Engineering Directorate is implementing PLM as part of an overall strategy to deliver safe, reliable, and affordable space exploration solutions. It has been 30 years since the United States fielded the Space Shuttle. The next generation space transportation system requires a paradigm shift such that digital tools and knowledge management, which are central elements of PLM, are used consistently to maximum effect. The outcome is a better use of scarce resources, along with more focus on stakeholder and customer requirements, as a new portfolio of enabling tools becomes second nature to the workforce. This paper will use the design and manufacturing processes, which have transitioned to digital-based activities, to show how PLM supports the comprehensive systems engineering and integration function. It also will go through a launch countdown scenario where an anomaly is detected to show how the virtual vehicle created from paperless processes will help solve technical challenges and improve the likelihood of launching on schedule, with less hands-on labor needed for processing and troubleshooting. Sustainable space exploration solutions demand that all lifecycle phases be optimized. Adopting PLM, which has been used by the automotive industry for many years, for aerospace applications provides a foundation for strong, disciplined systems engineering and accountable return on investment by making lifecycle considerations variables in an iterative decision-making process. This paper combines the perspectives of the founding father of PLM, along with the experience of Engineering leaders who are implementing these processes and practices real-time. As the nation moves from an industrial-based society to one where information is a valued commodity, future NASA programs and projects will benefit from the experience being gained today for the exploration missions of tomorrow.

Caruso, Pamela W.↗

NASA NTRS2011

Product Lifecycle Management and the Quest for Sustainable Space Exploration Solutions

Caruso, Pamela W.↗

NASA NTRS2019

Machine Learning Lifecycle for Earth Science Application: A Practical Insight into Production Deployment

Earth science domain presents unique sets of problems that are increasingly being solved using data driven approaches. The availability of big Earth science data offers immense potential for Machine learning (ML) as evident from numerous research publications lately. However, many of these publications are not ending up as production applications mainly because the data scientists who develop the ML models are now expected to complete the ML lifecycle by deploying and scaling the models in production. We introduce ML lifecycle to the Earth science community including the opportunities and challenges that lie ahead in each phase of the lifecycle. We demonstrate the lifecycle using an Earth science problem that we used ML to address and transitioned to production.

Maskey, Manil↗

NASA NTRSDate not supplied

Contracting Quality Early in the Lifecycle Using AS9145 Data Deliverables

Development schedules and a highly dynamic supply chain are a challenge to developers of complex systems produced at low volume. Flaws in designs, parts and materials availability problems, poor manufacturability, and a lack of knowledge about critical items and key process attributes can be realized well before traditional second-party quality assurance activities begin. Supplier audits and product inspections may have little mitigating effect once these foundational problems have been realized. Their impacts can be significant lifecycle disruption, cost overruns, inability to deliver to plan, and even project cancellation. AS9145, Requirements for Advanced Product Quality Planning and Production Part Approval Process, can be used to drive quality engineering practices into early development lifecycles to significantly reduce this late-cycle risk and to reduce the cost of quality overall. Since its initial publication in 2016, it has had very limited adoption by the DoD, no adoption by NASA, and sparse adoption in the aerospace and defense supply chain. A task group within the Aerospace Industries Association's (AIA) Joint Strategic Quality Council (JSQC) identified that both acquirers and suppliers see as AS9145 as a cost-adder and are hesitant to use it as an alternative to late-stage-heavy quality assurance approaches. A lack of prior use creates large capability gaps in request-for-proposal (RFP) teams, proposal teams, suppliers’ quality management systems (QMS), and in experienced personnel executing the early lifecycle approach. To create a more realizable on-ramp for using AS9145 in the space and defense sectors, the AIA JSQC task team created five deliverable requirements descriptions (DRDs) that can be used in a contract to begin to engage both parties in early lifecycle quality engineering and quality assurance activities, that reduce exposure to late-stage cost and schedule collapse due to unidentified risks in design, supply chain, and manufacturability. These DRDs drive the parties to engage in planning and analysis discussions early on to understand what production risks can be known and how they will focus resources based on safety criticality and the key elements of design and construction. The suppliers and acquirers who will produce the data and information required by the DRD will be able to incrementally evolve their QMS and the acquirer will incrementally be able to track and understand the benefits of cost shifting from late to early development phases. A white paper describing this approach and the five recommended DRDs will be published by the AIA in late 2024 or early 2025.

Jeannette Plante↗

NASA NTRS1988

Knowledge based system verification and validation as related to automation of space station subsystems: Rationale for a knowledge based system lifecycle

The role of verification and validation (V and V) in software has been to support and strengthen the software lifecycle and to ensure that the resultant code meets the standards of the requirements documents. Knowledge Based System (KBS) V and V should serve the same role, but the KBS lifecycle is ill-defined. The rationale of a simple form of the KBS lifecycle is presented, including accommodation to certain critical KBS differences from software development.

Richardson, Keith↗

NASA NTRS1988

Knowledge based system verification and validation as related to automation of Space Station subsystems - Rationale for a knowledge based system lifecycle

The role of verification and validation (V and V) in software has been to support and strengthen the software lifecycle and to ensure that the resultant code meets the standards of the requirements documents. Knowledge-based system (KBS) V and V should serve the same role, but the KBS lifecycle is ill-defined. The rationale of a simple form of the KBS lifecycle is presented, including accommodation to certain critical KBS differences from software development.

Richardson, Keith↗

NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided many statistics on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution possible for capturing cloud initiation and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool, strategies to identify development stages from cloud tracks, and preliminary results that document cumulus lifecycle properties from satellite. The application of AHI 0.5-km reflectance has both strengths and limitations when attempting to track lifecycles of the smallest resolvable clouds. We show that by aggregating cloud tracks from a few case studies of CAMP2EX, we can discern differences in cloud lifetime and development according to ensembles selected from areas of interest. The results demonstrate an ability to quantify lifetimes and assess rates of change in cloud characteristics that are likely controlled by the surrounding environment and meteorology.

Cloud Tracking↗

NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided valuable insight on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus were segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution available for capturing cloud initiation, growth, and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool and its results for cloud fields sampled throughout CAMP2EX by the airborne P-3. Cloud tracks were selected from about 10 flights to form ensembles, specific groups of tracks occurring in a region with airborne sampling. Cloud lifecycle properties, including duration and maximum area, are calculated for all ensemble members, and analyzed for cloud behavior and P-3 coincidences. By following this strategy, we quantitatively assess the degree of airborne sampling for specific cloud classes defined by the lifecycle calculations. We can summarize which cloud classes had more sampling, the stage of development during sampling, and general differences in character (e.g., isolated congestus vs. cold-pool producer).

Cloud Tracking↗

NASA NTRSDate not supplied

The Human Research Program Grant Lifecycle & Data Integration Schedule: Infographic

The Human Research Program (HRP) Grant Lifecycle process can be described using information from several government authoritative sources with overlapping generalizations. It is the responsibility of the HRP Program Planning & Control (PP&C) Office and the Data Management Integration Office (DMIO)to interpret this information into a cohesive process that can be communicated to the human research organization. PP&C and DMIO have been exploring training opportunities to facilitate understanding through the form of infographics. This communication tool combines eye-catching visuals and text making complex information and data more digestible and shareable. The infographic poster tells a short story about a federally awarded grant and is intended to help both the new and experienced HRP workforce understand the timeline for a research procurement and where their specific tasks fall within the 4 phases of the grant lifecycle. The Pre-Award, Award, Post-Award, and Closeout phases are overlayed with business swimlanes so HRP stakeholders can see where they fit into the timeline rather than working in an isolated part. This includes the Chief Scientist Office (CSO), PP&C, the Data Management Integration Office (DMIO), the Principal Investigator (PI), the Element stakeholders, the LSDA Archivists, and the Research & Operations Integration (ROI) team along with the stakeholders in the Human Health and Performance Directorate. Additionally, the poster introduces (1) the HRP Data Integration Schedule identified in the HRP Data Management Plan HRP-48047, Table 8-2 and (2) a Smartsheet Solution to automate the grants tracking business process. Emphasis is given to the Data Integration Schedule which is the basis for the milestone tasks that are to be completed during the Post-Award phase in the grant lifecycle. The poster is also an opportunity to present the Smartsheet Solution, a software collaboration and work management tool used to assign tasks and track project progress. This PP&C FY24 effort will facilitate an end-to-end solution to track grants and provide insight to the health of HRP grant research procurements using metrics, reports, and dashboards.

J Peace↗

NASA NTRS1998

A Decision Making Methodology in Support of the Business Rules Lifecycle

The business rules that underlie an enterprise emerge as a new category of system requirements that represent decisions about how to run the business, and which are characterized by their business-orientation and their propensity for change. In this report, we introduce a decision making methodology which addresses several aspects of the business rules lifecycle: acquisition, deployment and evolution. We describe a meta-model for representing business rules in terms of an enterprise model, and also a decision support submodel for reasoning about and deriving the rules. The possibility for lifecycle automated assistance is demonstrated in terms of the automatic extraction of business rules from the decision structure. A system based on the metamodel has been implemented, including the extraction algorithm. This is the final report for Daniela Rosca's PhD fellowship. It describes the work we have done over the past year, current research and the list of publications associated with her thesis topic.

Wild, Christopher↗

NASA NTRS2001

Linking Science Analysis with Observation Planning: A Full Circle Data Lifecycle

A clear goal of the Virtual Observatory (VO) is to enable new science through analysis of integrated astronomical archives. An additional and powerful possibility of the VO is to link and integrate these new analyses with planning of new observations. By providing tools that can be used for observation planning in the VO, the VO will allow the data lifecycle to come full circle: from theory to observations to data and back around to new theories and new observations. The Scientist's Expert Assistant (SEA) Simulation Facility (SSF) is working to combine the ability to access existing archives with the ability to model and visualize new observations. Integrating the two will allow astronomers to better use the integrated archives of the VO to plan and predict the success of potential new observations. The full circle lifecycle enabled by SEA can allow astronomers to make substantial leaps in the quality of data and science returns on new observations. Our paper will examine the exciting potential of integrating archival analysis with new observation planning, such as performing data calibration analysis on archival images and using that analysis to predict the success of new observations, or performing dynamic signal-to-noise analysis combining historical results with modeling of new instruments or targets. We will also describe how the development of the SSF is progressing and what has been its successes and challenges.

Jones, Jeremy↗

NASA NTRS2001

Linking Science Analysis with Observation Planning: A Full Circle Data Lifecycle

A clear goal of the Virtual Observatory (VO) is to enable new science through analysis of integrated astronomical archives. An additional and powerful possibility of the VO is to link and integrate these new analyses with planning of new observations. By providing tools that can be used for observation planning in the VO, the VO will allow the data lifecycle to come full circle: from theory to observations to data and back around to new theories and new observations. The Scientist's Expert Assistant (SEA) Simulation Facility (SSF) is working to combine the ability to access existing archives with the ability to model and visualize new observations. Integrating the two will allow astronomers to better use the integrated archives of the VO to plan and predict the success of potential new observations more efficiently, The full circle lifecycle enabled by SEA can allow astronomers to make substantial leaps in the quality of data and science returns on new observations. Our paper examines the exciting potential of integrating archival analysis with new observation planning, such as performing data calibration analysis on archival images and using that analysis to predict the success of new observations, or performing dynamic signal-to-noise analysis combining historical results with modeling of new instruments or targets. We will also describe how the development of the SSF is progressing and what have been its successes and challenges.

Grosvenor, Sandy↗

NASA NTRS2004

The Lifecycle of NASA's Earth Science Enterprise Data Resources

A major endeavor of NASA's Earth Science Enterprise (ESE) is to acquire, process, archive and distribute data from Earth observing satellites in support of a broad set of science research and applications in the U. S. and abroad. NASA policy directives specifically call for the agency to collect, announce, disseminate and archive all scientific and technical data resulting from NASA and NASA-funded research. During the active life of the satellite missions, while the data products are being created, validated and refined, a number of NASA organizations have the responsibility for data and information system functions. Following the completion of the missions, the responsibility for the long-term stewardship of the ocean and atmospheric, and land process data products transitions to the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS), respectively. Ensuring that long-term satellite data be preserved to support global climate change studies and other research topics and applications presents some major challenges to NASA and its partners. Over the last several years, with the launch and operation of the EOS satellites and the acquisition and production of an unprecedented volume of Earth science data, the importance of addressing these challenges has been elevated. The lifecycle of NASA's Earth science data has been the subject of several agency and interagency studies and reports and has implications and effects on agency charters, policies and budgets and on their data system's requirements, implementation plans and schedules. While much remains to be done, considerable progress has been made in understanding and addressing the data lifecycle issues.

McDonald, Kenneth R.↗

NASA NTRS2005

Second NASA Technical Interchange Meeting (TIM): Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box (TTB)

The Advanced Technology Lifecycle Analysis System (ATLAS), a spreadsheet analysis tool suite, applies parametric equations for sizing and lifecycle cost estimation. Performance, operation, and programmatic data used by the equations come from a Technology Tool Box (TTB) database. In this second TTB Technical Interchange Meeting (TIM), technologists, system model developers, and architecture analysts discussed methods for modeling technology decisions in spreadsheet models, identified specific technology parameters, and defined detailed development requirements. This Conference Publication captures the consensus of the discussions and provides narrative explanations of the tool suite, the database, and applications of ATLAS within NASA s changing environment.

ONeil, D. A.↗

NASA NTRS2010

Product Lifecycle Management and the Quest for Sustainable Space Explorations

Product Lifecycle Management (PLM) is an outcome of lean thinking to eliminate waste and increase productivity. PLM is inextricably tied to the systems engineering business philosophy, coupled with a methodology by which personnel, processes and practices, and information technology combine to form an architecture platform for product design, development, manufacturing, operations, and decommissioning. In this model, which is being implemented by the Engineering Directorate at the National Aeronautics and Space Administration's (NASA's) Marshall Space Flight Center, total lifecycle costs are important variables for critical decision-making. With the ultimate goal to deliver quality products that meet or exceed requirements on time and within budget, PLM is a powerful concept to shape everything from engineering trade studies and testing goals, to integrated vehicle operations and retirement scenarios. This paper will demonstrate how the Engineering Directorate is implementing PLM as part of an overall strategy to deliver safe, reliable, and affordable space exploration solutions. It has been 30 years since the United States fielded the Space Shuttle. The next generation space transportation system requires a paradigm shift such that digital tools and knowledge management, which are central elements of PLM, are used consistently to maximum effect. The outcome is a better use of scarce resources, along with more focus on stakeholder and customer requirements, as a new portfolio of enabling tools becomes second nature to the workforce. This paper will use the design and manufacturing processes, which have transitioned to digital-based activities, to show how PLM supports the comprehensive systems engineering and integration function. It also will go through a launch countdown scenario where an anomaly is detected to show how the virtual vehicle created from paperless processes will help solve technical challenges and improve the likelihood of launching on schedule, with less hands-on labor needed for processing and troubleshooting.

Caruso, Pamela W.↗