Documenting risk stories to extract best practices
Explore the source record for details and available documents.
SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
The goal of this plan is to briefly describe new technologies available to us in the arenas of information discovery and discuss the strategic value they have for the NASA enterprise with some considerations and suggestions for near term implementations using the NASA Engineering Network (NEN) as a delivery venue.
In this slide presentation the importance of collaboration in developing the next systems for space exploration is stressed. The mechanism of this collaboration are reviewed, and particular emphasis is given to our planned exploration of Mars and how this will require a great deal of collaboration. A system architecture for this collaboration is shown and the diagram for the collaborative environment is conceptualized.
Collection and processing of information are critical aspects of every business activity from raw data to information to an executable decision. Configuration Management (CM) supports KM practices through its automated business practices and its integrated operations within the organization. This presentation delivers an overview of JSC/Space Life Sciences Directorate (SLSD) and its methods to encourage innovation through collaboration and participation. Specifically, this presentation will illustrate how SLSD CM creates an embedded KM activity with an established IT platform to control and update baselines, requirements, documents, schedules, budgets, while tracking changes essentially managing critical knowledge elements.
In 2004, NASA faced major knowledge sharing challenges due to geographically isolated field centers that inhibited personnel from sharing experiences and ideas. Mission failures and new directions for the agency demanded better collaborative tools. In addition, with the push to send astronauts back to the moon and to Mars, NASA recognized that systems engineering would have to improve across the agency. Of the ten field centers, seven had not built a spacecraft in over 30 years, and had lost systems engineering expertise. The Systems Engineering Community of Practice came together to capture the knowledge of its members using the suite of collaborative tools provided by the NASA Engineering Network (NEN.) The NEN provided a secure collaboration space for over 60 practitioners across the agency to assemble and review a NASA systems engineering handbook. Once the handbook was complete, they used the open community area to disseminate it. This case study explores both the technology and the social networking that made the community possible, describes technological approaches that facilitated rapid setup and low maintenance, provides best practices that other organizations could adopt, and discusses the vision for how this community will continue to collaborate across the field centers to benefit the agency as it continues exploring the solar system.
This report has been developed by the National Aeronautics and Space Administration (NASA) Human Exploration and Operations Mission Directorate (HEOMD) Risk Management team knowledge capture forums.. This document provides a point-in-time, cumulative, summary of actionable key lessons learned in safety framework and concepts.
Explore the source record for details and available documents.
Relive the adrenaline pumping journey as NASA partners with Splunk to go beyond the app design gravity hold, through to the best practices asteroid belt, and eventually landing on NASA's solution for an on-the-fly conf file and knowledge object management solution. Break out of your black hole of conf stanza management. Discover NASA's concrete examples from apps they've developed to support NASA’s Earth Science Data and Information System’s operations. Rover over to this talk because after all, Splunk's not rocket science.
Artificial intelligence is it tool that has existed for many years. Recent developments in generative AI has rapidly expanded the applications for this tool across many domains such as writing, analyzing, summarizing, creating videos, creating graphics and others. Charts in this presentation will prompt attendees to discuss the pros and cons, and potential validation methodology for imbedding artificial intelligence tools in the NASA lessons learned knowledge sharing environment.
A major weakness of a Large Language Model (LLM) is its tendency to accept information at face value, often leading to injection of erroneous information and inducing a greater probability of hallucinating non-existent information. While Retrieval Augmented Generation (RAG) uses external knowledge sources to bolster LLMs through grounded truth, this work seeks to explore methods to engender a LLM with an intrinsic capability to evaluate an input’s believability without relying on external knowledge sources. We investigate unifying a LLM with a Knowledge Graph (KG) and using the KG to reinforce the LLM’s internal word embedding while also maintaining belief metrics along the edge’s in the KG.
Many knowledge based software generation methods have been proposed to improve software quality and programmer productivity. Several government and industry initiatives have focused on software reusability as one solution to these problems. DARTS (trademark), a General Dynamics proprietary symbolic processing technology, provides a unique solution to the reuse problem: archtyping. Archtyping is the embedding of high order language statements in text files. An advanced macroprocessor uses the text files to generate new versions of complex software systems. A DARTS program, the Software Generation and Configuration Management (SGCM) System automates the archtyping process and maintenance cycle. The DARTS technology is briefly discussed, archtyping is described, and the SGCM system is presented in detail.
Technical knowledge is essential to the work done by NASA practitioners. So it may be surprising to learn that the most ingenious and elegant solutions to project challenges often arise not from a specific technical discipline perspective, but from a systems-focused mindset. While technical discipline expertise is a critical component of project success, sometimes the simplest resolution to a problem involves a systems-wide solution. Because of this, encouraging a systems mentality among project team members can be a powerful tool in mitigating risk and eliminating threats. Join us for an exploration of the critical ways in which a systems engineering and integration perspective can enhance project management efforts. Presenter Bo Bejmuk is the former Space Shuttle Orbiter Program Director and manager of Sea Launch Program operations and development for Boeing. He recently served as Chairman of the Standing Review Board for the NASA Constellation Program. Moderator Ramien Pierre is from NASA's Academy for Program/Project and Engineering Leadership (APPEL).
The use of artificial intelligence techniques that are applicable to Geographic Information Systems (GIS) are examined. Questions involving the performance and modification to the database structure, the definition of spectra in quadtree structures and their use in search heuristics, extension of the knowledge base, and learning algorithm concepts are investigated.
APPL is a research-based organization that serves NASA program and project managers, as well as project teams, at every level of development. In 1997, APPL was created from an earlier program to underscore the importance that NASA places on project management and project teams through a wide variety of products and services, including knowledge sharing, classroom and online courses, career development guidance, performance support, university partnerships, and advanced technology tools. ASK Magazine grew out of APPL's Knowledge Sharing Initiative. The stories that appear in ASK are written by the 'best of the best' project managers, primarily from NASA, but also from other government agencies and industry. Contributors to this issue include: Teresa Bailey, a librarian at the Jet Propulsion Laboratory, Roy Malone, Deputy Director in the Safety and Mission Assurance (S&MA) Office at the NASA Marshall Space Flight Center (MSFC), W. Scott Cameron, Capital Systems Manager for the Food and Beverage Global Business Unit of Procter and Gamble, Ray Morgan, recent retiree as Vice President of AeroVironment, Inc., Marty Davis, Program Manager of the Geostationary Operational Environmental Satellite (GOES) at the NASA Goddard Space Flight Center (GSFC) in Greenbelt, Maryland, Todd Post, editor of ASK Magazine, and works for EduTech Ltd. in Silver Spring, Maryland, Dr. Owen Gadeken, professor of Engineering Management at the Defense Acquisition University, Ken Schwer, currently the Project Manager of Solar Dynamics Observatory, Dr. Edward Hoffmwan, Director of the NASA Academy of Program and Project Leadership, Frank Snow, a member of the NASA Explorer Program at Goddard Space Flight Center since 1992, Dr. Alexander Laufer, Editor-in-Chief of ASK Magazine and a member of the Advisory Board of the NASA Academy of Program and Project Leadership, Judy Stokley, presently Air Force Program Executive Officer for Weapons in Washington, D.C. and Terry Little, Director of the Kinetic Energy Boost Office of the Missile Defense Agency.
This document is a catalog and readers guide to lessons learned, experience, and technical history reports, as well as compilation volumes prepared by United Space Alliance personnel for the NASA/Johnson Space Center (JSC) Flight Dynamics Division.1 It is intended to make it easier for future generations of engineers to locate knowledge capture documentation from the Shuttle Program. The first chapter covers observations on documentation quality and research challenges encountered during the Space Shuttle and Orion programs. The second chapter covers the knowledge capture approach used to create many of the reports covered in this document. These chapters are intended to provide future flight programs with insight that could be used to formulate knowledge capture and management strategies. The following chapters contain descriptions of each knowledge capture report. The majority of the reports concern the Space Shuttle. Three are included that were written in support of the Orion Program. Most of the reports were written from the years 2001 to 2011. Lessons learned reports concern primarily the shuttle Global Positioning System (GPS) upgrade and the knowledge capture process. Experience reports on navigation and rendezvous provide examples of how challenges were overcome and how best practices were identified and applied. Some reports are of a more technical history nature covering navigation and rendezvous. They provide an overview of mission activities and the evolution of operations concepts and trajectory design. The lessons learned, experience, and history reports would be considered secondary sources by historians and archivists.
The main contribution of the effort in the last two years is the introduction of the MOPPS system. After doing extensive literature search, we introduced the system which is described next. MOPPS employs a new solution to the problem of managing programs which solve scientific and engineering applications on a distributed processing environment. Autonomous computers cooperate efficiently in solving large scientific problems with this solution. MOPPS has the advantage of not assuming the presence of any particular network topology or configuration, computer architecture, or operating system. It imposes little overhead on network and processor resources while efficiently managing programs concurrently. The core of MOPPS is an intelligent program manager that builds a knowledge base of the execution performance of the parallel programs it is managing under various conditions. The manager applies this knowledge to improve the performance of future runs. The program manager learns from experience.