Results for “lessons learned process” — Page 15

NASA NTRS2017

Data Production on Past and Future NASA Missions

Data return is a metric that is commonly publicized for all space science missions. In the early days of the Space Program, this figure was small, and could be described in bits or maybe even megabits. But now, missions are capable of returning data volumes two or three orders of magnitude larger. For example, Voyager 1 and 2 combined produced a little over 5 Terabits of data in 39 years of operation. In contrast, the Cassini mission, launched two decades after Voyager, produced about one and a half times those data volumes in half the time. NISAR, an Earth Science Mission currently in implementation, plans to produce over 28 Petabits of raw data in just 3 years. This means that NISAR will produce about as many data in 30 days as the combined data production of nearly all planetary missions to date. These increases in capability are a result of technology enhancements in two main areas: telecommunications architecture (both space and ground segments) and data storage technology. This paper describes the progression of these two technologies over the course of more than three decades of space missions and provides additional insight into the design of the end-to-end NISAR Data System Architecture. Trends in the data are briefly explored and compared to Moore’s Law which provides only a qualitative model for memory growth but not for data production. In summary, early missions are found to be driven by unrefined processes while later missions, having utilized earlier lessons learned, focus more on improvements to flight and ground capabilities. Data return seems to fall into three categories. First, deep space missions are driven by the large distances that limit data return to the Earth. Next, the orbiter infrastructure around Mars helps these missions generate more data than other deep space spacecraft. Finally, near-Earth missions have the greatest capabilities for the studied metrics due to their close proximity to Earth and the ground network availability.

Xaypraseuth, Peter↗

NASA NTRS2024

Integrated Systems Engineering, Safety, Reliability and Risk Management – Minimizing Black Swan Events

This paper examines key barriers that can possibly inhibit safe and reliable mission execution and, in the worst case, result in loss of human life due to many unknown contributory factors that can lead to Black Swan events. Some of the representative contributory factors include decision errors, overconfidence and a host of common causes including cultural and human factors. Decisions are always easy to criticize in hindsight when more information is available after a major accident. Depending on the type and complexity of the project and/or mission, the catastrophic risks of drifting into failure can be alleviated by implementing uniquely and strategically tailored Integrated-System-of-Systems, dynamic, risk-informed decision management processes. This paper presents some of the lessons learned from James Webb Space Telescope (JWST), NASA’s Human Space Flight program, and industry that provide motivation to organizations working on mega-complex missions to prudently accomplish targeted mission success. These lessons are important for future human Lunar, Mars and Beyond missions planned to be pursued by NASA through a public-private partnership using nimble but effective safety-conscious, proven sound engineering practices including implementation of integrated risk mitigation practices.

SLS↗

NASA NTRS2022

Robotics Verification and Validation Strategies for Perseverance Rover Sampling and Caching

The Mars 2020 Sampling and Caching Subsystem(SCS) is the most complex robotic system ever fielded on a MarsRover. It includes a 5 degree-of-freedom Robotic Arm, coringdrill, gas Dust Removal Tool, interfaces for two turret-mountedinstruments, and an Adaptive Caching Assembly (ACA). TheACA is itself a complex robotic system, containing hardware tosupport docking and bit exchange, a 3 degree-of-freedomSample Handling Assembly for manipulating sample tubes,storage for several drill bits and sample tubes, and mechanismsto support observing and sealing samples collected by the drill.To successfully verify and validate the SCS hardware andsoftware and its integration with the Mars 2020 flight systemseveral key strategies were employed.The SCS Verification and Validation (V&V) program utilizedmultiple test venues with tiered levels of fidelity. These includedsimulation and visualization software environments, low fidelitydevelopment testbeds, testbeds with high fidelity SCS hardwareand commercial off-the shelf avionics, integrated systemtestbeds with flight-like avionics, and environmental testbedscapable of simulating Martian surface temperature andpressure. Multiple units of each SCS hardware componentmoved fluidly between test venues to accomplish myriadstandalone and coordinated test objectives. Test preparationand executions were performed by a diverse team of engineerswith training and technical ownership tailored for individualexperience and role. Despite significant differences between testvenues, the SCS V&V team established efficient and consistentprocesses and tools for procedure development, test execution,and data review that enabled personnel, as well as technicalproducts such as sequences and parameter configurations, toflow between venues effectively. A series of benchmark testsprovided evidence of performance consistency as elements weretransferred between venues and as system capability evolved.This paper provides an overview of the SCS V&V program andexplores several overarching strategies that enabled successfuloperation in the face of unprecedented complexity. Keyoutcomes of the SCS validation effort are summarized, alongwith lessons learned and beneficial integrations of validationtool and process innovations into Mars surface operations.

Brooks, Sawyer↗

NASA NTRSDate not supplied

Metal Additive Manufacturing for Rocket Engines: Successes and Failures

NASA has been developing additive manufacturing (AM) for various technical and programmatic advantages for complex rocket engine and aerospace components. This maturation has focused on various AM processes, new alloys, characterizing material properties, developing standards, producing demonstrator parts, and integrating AM hardware in liquid rocket engines through test-fail-fix cycles, as well as application and dissemination of lessons learned of the AM lifecycle. The importance of proper AM processing was made evident in the failure of a Laser Powder Bed Fusion (L-PBF) copper-alloy combustion chamber during a hot-fire test due to a degraded material quality. The hot-fire test aimed to demonstrate high duty cycle under a risk-tolerant development project, where consequences of component failure would be minimal. However, the unintentional component failure emphasized the necessity of robust material characterization and rigorous process control procedures for the safe use of AM components in critical applications. This presentation provides an overview of the development failure, a discussion on the evaluation of the failed chamber and supplemental chambers produced at the same time, a representative material samples that included intentional build witness lines, and a summary of the key results and recommendations from the evaluations. NASA continues to approach AM processes and designs with a level of risk and acceptance of failures that is appropriate for the project objectives, with the overall goal of safe implementation of AM technology and transferring AM technology into commercial space applications. This presentation with provide critical awareness to the community lessons learned on proper implementation of AM.

L-PBF↗

NASA NTRSDate not supplied

Successes and Failures of Metal Additive Manufacturing for Rocket Engines

NASA has been developing additive manufacturing (AM) for various technical and programmatic advantages for complex rocket engine and aerospace components. This maturation has focused on various AM processes, new alloys, characterizing material properties, developing standards, producing demonstrator parts, and integrating AM hardware in liquid rocket engines through test-fail-fix cycles, as well as application and dissemination of lessons learned of the AM lifecycle. The importance of proper AM processing was made evident in the failure of a Laser Powder Bed Fusion (L-PBF) copper-alloy combustion chamber during a hot-fire test due to a degraded material quality. The hot-fire test aimed to demonstrate high duty cycle under a risk-tolerant development project, where consequences of component failure would be minimal. However, the unintentional component failure emphasized the necessity of robust material characterization and rigorous process control procedures for the safe use of AM components in critical applications. This presentation provides an overview of the development failure, a discussion on the evaluation of the failed chamber and supplemental chambers produced at the same time, a representative material samples that included intentional build witness lines, and a summary of the key results and recommendations from the evaluations. NASA continues to approach AM processes and designs with a level of risk and acceptance of failures that is appropriate for the project objectives, with the overall goal of safe implementation of AM technology and transferring AM technology into commercial space applications. This presentation with provide critical awareness to the community lessons learned on proper implementation of AM.

Additive Manufacturing↗

NASA NTRS2007

Best Practices for Reliable and Robust Spacecraft Structures

A study was undertaken to capture the best practices for the development of reliable and robust spacecraft structures for NASA s next generation cargo and crewed launch vehicles. In this study, the NASA heritage programs such as Mercury, Gemini, Apollo, and the Space Shuttle program were examined. A series of lessons learned during the NASA and DoD heritage programs are captured. The processes that "make the right structural system" are examined along with the processes to "make the structural system right". The impact of technology advancements in materials and analysis and testing methods on reliability and robustness of spacecraft structures is studied. The best practices and lessons learned are extracted from these studies. Since the first human space flight, the best practices for reliable and robust spacecraft structures appear to be well established, understood, and articulated by each generation of designers and engineers. However, these best practices apparently have not always been followed. When the best practices are ignored or short cuts are taken, risks accumulate, and reliability suffers. Thus program managers need to be vigilant of circumstances and situations that tend to violate best practices. Adherence to the best practices may help develop spacecraft systems with high reliability and robustness against certain anomalies and unforeseen events.

Raju, Ivatury S.↗

NASA NTRS2005

Engineering Lessons Learned and Systems Engineering Applications

Systems Engineering is fundamental to good engineering, which in turn depends on the integration and application of engineering lessons learned and technical standards. Thus, good Systems Engineering also depends on systems engineering lessons learned from within the aerospace industry being documented and applied. About ten percent of the engineering lessons learned documented in the NASA Lessons Learned Information System are directly related to Systems Engineering. A key issue associated with lessons learned datasets is the communication and incorporation of this information into engineering processes. Systems Engineering has been defined (EINIS-632) as "an interdisciplinary approach encompassing the entire technical effort to evolve and verify an integrated and life-cycle balanced set of system people, product, and process solutions that satisfy customer needs". Designing reliable space-based systems has always been a goal for NASA, and many painful lessons have been learned along the way. One of the continuing functions of a system engineer is to compile development and operations "lessons learned" documents and ensure their integration into future systems development activities. They can produce insights and information for risk identification identification and characterization. on a new project. Lessons learned files from previous projects are especially valuable in risk

Gill, Paul S.↗

NASA NTRS2018

On-Orbit Results and Lessons Learned from the ASTERIA Space Telescope Mission

The Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) was deployed from the International Space Station (ISS) on 20 November 2017, beginning a technology demonstration and opportunistic science mission to advance the state of the art in nanosatellite performance for astrophysical observations. The goal of ASTERIA is to achieve arcsecond-level line-of-sight pointing error and highly stable focal plane temperature control. These capabilities enable precision photometry—i.e. the careful measurement of stellar brightness over time—which in turn allows investigation of astrophysical phenomena such as transiting exoplanets. By the end of the 90-day prime mission, ASTERIA had achieved line-of-sight pointing stability of approximately 0.5 arcseconds root mean square (RMS) over 20-minute observations, pointing repeatability of 1 milliarcsecond RMS from one observation to the next, and focal plane temperature stability better than ±0.01 K over 20-minute observations. This paper presents an overview of the ASTERIA flight and ground system, summarizes the pre-delivery test campaign, and discusses the on-orbit performance obtained by the pointing and thermal control subsystems. We also describe the process for planning opportunistic science observations and present lessons learned from development and operations. Having successfully operated for over 200 days as of this writing, ASTERIA is currently in an extended mission to observe nearby bright stars for transiting exoplanets.

Seager, Sara↗

NASA NTRS2000

Volatile Removal Assembly Flight Experiment and KC-135 Packed Bed Experiment: Results and Lessons Learned

The Volatile Removal Assembly (VRA) is a high temperature catalytic oxidation process that will be used as the final treatment for recycled water aboard the International Space Station (ISS). The multiphase nature of the process had raised concerns as to the performance of the VRA in a microgravity environment. To address these concerns, two experiments were designed. The VRA Flight Experiment (VRAFE) was designed to test a full size VRA under controlled conditions in microgravity aboard the SPACEHAB module and in a 1 -g environment and compare the performance results. The second experiment relied on visualization of two-phase flow through small column packed beds and was designed to fly aboard NASA's microgravity test bed plane (KC-135). The objective of the KC-135 experiment was to understand the two-phase fluid flow distribution in a packed bed in microgravity. On Space Transportation System (STS) flight 96 (May 1999), the VRA FE was successfully operated and in June 1999 the KC-135 packed bed testing was completed. This paper provides an overview of the experiments and a summary of the results and findings.

Holder, Donald W.↗

NASA NTRSDate not supplied

From BERTopic to SysML: Informing Model-Based Failure Analysis With Natural Language Processing for Complex Aerospace Systems

The development of emerging complex aerospace systems will require new approaches for capturing safety incident scenarios as early as possible in the design phase. However, for novel systems, relevant data available is limited. In this work, we propose a framework informing model-based mission assurance activities with historical incident reports, lessons learned, or other relevant engineering documents using natural language processing. In doing so, we investigate whether there is useful information in data sets that are relevant, if not identical, to the system under design and whether, through rigorous systems engineering practice, this information can be effectively leveraged through model-based failure analysis. In a worked case study, we apply state-of-the-art topic modeling techniques to two data sets, a mission relevant data set and a system relevant data set. The sets of topics are merged and interpreted to form a preliminary list of failure topics that can be used to inform the identification of off-nominal modes in the model-based failure modes and effects analysis development. Once data from the system in operation is available, it can be used to update the topics identified. By extracting information about likely failures from relevant historical data sets and utilizing model-based mission assurance to ensure relevance and rigor, unanticipated failures can be reduced, and projects can more effectively learn from past missions.

Failure Analysis↗

NASA NTRSDate not supplied

From BERTopic to SysML: Informing Model-Based Failure Analysis With Natural Language Processing for Complex Aerospace Systems

The development of emerging complex aerospace systems will require new approaches for capturing safety incident scenarios as early as possible in the design phase. However, for novel systems, relevant data available is limited. In this work, we propose a framework informing model-based mission assurance activities with historical incident reports, lessons learned, or other relevant engineering documents using natural language processing. In doing so, we investigate whether there is useful information in data sets that are relevant, if not identical, to the system under design and whether, through rigorous systems engineering practice, this information can be effectively leveraged through model-based failure analysis. In a worked case study, we apply state-of-the-art topic modeling techniques to two data sets, a mission relevant data set and a system relevant data set. The sets of topics are merged and interpreted to form a preliminary list of failure topics that can be used to inform the identification of off-nominal modes in the model-based failure modes and effects analysis development. Once data from the system in operation is available, it can be used to update the topics identified. By extracting information about likely failures from relevant historical data sets and utilizing model-based mission assurance to ensure relevance and rigor, unanticipated failures can be reduced, and projects can more effectively learn from past missions.

Failure Analysis↗

NASA NTRS2006

Advancing the practice of systems engineering at JPL

In FY 2004, JPL launched an initiative to improve the way it practices systems engineering. The Lab's senior management formed the Systems Engineering Advancement (SEA) Project in order to "significantly advance the practice and organizational capabilities of systems engineering at JPL on flight projects and ground support tasks." The scope of the SEA Project includes the systems engineering work performed in all three dimensions of a program, project, or task: 1. the full life-cycle, i.e., concept through end of operations 2. the full depth, i.e., Program, Project, System, Subsystem, Element (SE Levels 1 to 5) 3. the full technical scope, e.g., the flight, ground and launch systems, avionics, power, propulsion, telecommunications, thermal, etc. The initial focus of their efforts defined the following basic systems engineering functions at JPL: systems architecture, requirements management, interface definition, technical resource management, system design and analysis, system verification and validation, risk management, technical peer reviews, design process management and systems engineering task management, They also developed a list of highly valued personal behaviors of systems engineers, and are working to inculcate those behaviors into members of their systems engineering community. The SEA Project is developing products, services, and training to support managers and practitioners throughout the entire system lifecycle. As these are developed, each one needs to be systematically deployed. Hence, the SEA Project developed a deployment process that includes four aspects: infrastructure and operations, communication and outreach, education and training, and consulting support. In addition, the SEA Project has taken a proactive approach to organizational change management and customer relationship management - both concepts and approaches not usually invoked in an engineering environment. This paper'3 describes JPL's approach to advancing the practice of systems engineering at the Lab. It describes the general approach used and how they addressed the three key aspects of change: people, process and technology. It highlights a list of highly valued personal behaviors of systems engineers, discusses the various products, services and training that were developed, describes the deployment approach used, and concludes with several lessons learned.

process improvement↗

NASA NTRSDate not supplied

Best Practices from NASA's Open Science Response to the Satellite Needs Working Group (SNWG) Process

The Satellite Needs Working Group (SNWG) in the U.S. Group on Earth Observations (USGEO) provides dedicated analysis and advice to the Office of Science and Technology Policy (OSTP), and is charged with identifying satellite data needs across the U.S. Government agencies to which the National Aeronautics and Space Administration (NASA) responds with solutions aligning with its missions and goals. The SNWG puts out a biennial survey to the U.S. Government agencies asking a variety of questions aimed at gleaning their current needs for satellite data. NASA’s response to the SNWG since 2016 has been to serve the community at large with open science and open data products derived through the SNWG process. With the next SNWG cycle set to kick off in 2022, the NASA SNWG team has been actively working to incorporate lessons learned from the past three cycles into the NASA-side process and tools. We will discuss the best practices and tools NASA has developed in response to the SNWG survey assessment process. These assist NASA’s decisions on how best to utilize existing, and proposing new, products and services to address the needs of other U.S. agencies.

Cerese Albers↗

NASA NTRSDate not supplied

NASA's Biosentinel Mission: Lessons Learned and What's Next

In the last two years, two BioSentinel payloads were launched to space. The ISS mission launched in December 2021, and returned to the ground in August 2022 after successfully completing eight biological experiments while validating the different instruments. On the other hand, the deep space mission launched onboard Artemis I in November 2022, and is currently in a heliocentric orbit over 20 million kilometers away from the Earth. Even though all hardware subsystems were validated in deep space, the microfluidic subsystems experienced anomalies throughout the initial 6-month mission. The main goals of this presentation are (1) to present flight data from the deep space payload, including biology, fluidics, electronics, data processing, and mission operations, and (2) to discuss the lessons learned – what worked and what did not – from this unique complex mission, and how these lessons are aiding in the development of the Lunar Exploration Instrument for space biology Applications (LEIA) mission, launching to the lunar surface on a commercial lander in 2026. As of the writing of this abstract, the satellite continues to work nominally, communicating to Earth via the Deep Space Network (DSN) twice per week. Importantly, the mission received and extension to continue recording data on the deep space radiation environment on its way to solar maximum (i.e., higher probability of solar particle events). BioSentinel is supported by NASA Exploration Systems Development Mission Directorate (ESDMD).

BioSentinel↗

NASA NTRS1992

Integration and use of Microgravity Research Facility: Lessons learned by the crystals by vapor transport experiment and Space Experiments Facility programs

The Crystals by Vapor Transport Experiment (CVTE) and Space Experiments Facility (SEF) are materials processing facilities designed and built for use on the Space Shuttle mid deck. The CVTE was built as a commercial facility owned by the Boeing Company. The SEF was built under contract to the UAH Center for Commercial Development of Space (CCDS). Both facilities include up to three furnaces capable of reaching 850 C minimum, stand-alone electronics and software, and independent cooling control. In addition, the CVTE includes a dedicated stowage locker for cameras, a laptop computer, and other ancillary equipment. Both systems are designed to fly in a Middeck Accommodations Rack (MAR), though the SEF is currently being integrated into a Spacehab rack. The CVTE hardware includes two transparent furnaces capable of achieving temperatures in the 850 to 870 C range. The transparent feature allows scientists/astronauts to directly observe and affect crystal growth both on the ground and in space. Cameras mounted to the rack provide photodocumentation of the crystal growth. The basic design of the furnace allows for modification to accommodate techniques other than vapor crystal growth. Early in the CVTE program, the decision was made to assign a principal scientist to develop the experiment plan, affect the hardware/software design, run the ground and flight research effort, and interface with the scientific community. The principal scientist is responsible to the program manager and is a critical member of the engineering development team. As a result of this decision, the hardware/experiment requirements were established in such a way as to balance the engineering and science demands on the equipment. Program schedules for hardware development, experiment definition and material selection, flight operations development and crew training, both ground support and astronauts, were all planned and carried out with the understanding that the success of the program science was as important as the hardware functionality. How the CVTE payload was designed and what it is capable of, the philosophy of including the scientists in design and operations decisions, and the lessons learned during the integration process are descussed.

Heizer, Barbara L.↗

NASA NTRS2014

Model-Based GN and C Simulation and Flight Software Development for Orion Missions beyond LEO

For Orion missions beyond low Earth orbit (LEO), the Guidance, Navigation, and Control (GN&C) system is being developed using a model-based approach for simulation and flight software. Lessons learned from the development of GN&C algorithms and flight software for the Orion Exploration Flight Test One (EFT-1) vehicle have been applied to the development of further capabilities for Orion GN&C beyond EFT-1. Continuing the use of a Model-Based Development (MBD) approach with the Matlab®/Simulink® tool suite, the process for GN&C development and analysis has been largely improved. Furthermore, a model-based simulation environment in Simulink, rather than an external C-based simulation, greatly eases the process for development of flight algorithms. The benefits seen by employing lessons learned from EFT-1 are described, as well as the approach for implementing additional MBD techniques. Also detailed are the key enablers for improvements to the MBD process, including enhanced configuration management techniques for model-based software systems, automated code and artifact generation, and automated testing and integration.

Odegard, Ryan↗

NASA NTRS2006

Advancing the practice of systems engineering at JPL

This paper describes JPL's approach to advancing the practice of systems engineering at the Lab. It describes the people, process and technology aspects of the SEA Project, discusses the various products, services and training that were developed, describes the development approach used, and concludes with several observations or 'lessons learned'.

process improvement↗

NASA NTRS1999

Managing the Moon Program: Lessons Learned from Project Apollo

There have been many detailed historical studies of the process of deciding on and executing the Apollo lunar landing during the 1960s and early 1970s. From the announcement of President John F Kennedy on May 25, 1961, of his decision to land an American on the Moon by the end of the decade, through the first lunar landing on July 20, 1969, on to the last of six successful Moon landings with Apollo 17 in December 1972, NASA carried out Project Apollo with enthusiasm and aplomb. While there have been many studies recounting the history of Apollo, at the time of the 30th anniversary of the first lunar landing by Apollo 11, it seems appropriate to revisit the process of large-scale technological management as it related to the lunar mission. Consequently, the NASA History Office has chosen to publish this monograph containing the recollections of key partcipants in the management process. The collective oral history presented here was recorded in 1989 at the Johnson Space Center's Gilruth Recreation Center in Houston, Texas. It includes the recollections of key participants in Apollo's administration, addressing issues such as communication between field centers, the prioritization of technological goals, and the delegation of responsibility. The following people participated: George E. Muller, Owen W. Morris, Maxime A. Faget, Robert R. Gilruth, Christopher C. Kraft, and Howard W. (Bill) Tindall. The valuable perspectives of these individuals deepen and expand our understanding of this important historical event. This is the 14th in a series of special studies prepared by the NASA History Office. The Monographs in Aerospace History series is designed to provide a wide variety of investigations relative to the history of aeronautics and space. These publications are intended to be tightly focused in terms of subject, relatively short in length, and reproduced in an inexpensive format to allow timely and broad dissemination to researchers in aerospace history.

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