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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Galileo spacecraft anomaly and safing recovery

A high-level anomaly recovery plan which identifies the steps necessary to recover from a spacecraft 'Safing' incident was developed for the Galileo spacecraft prior to launch. Since launch, a total of four in-flight anomalies have lead to entry into a system fault protection 'Safing' routine which has required the Galileo flight team to refine and execute the recovery plan. These failures have allowed the flight team to develop an efficient recovery process when permanent spacecraft capability degradation is minimal and the cause of the anomaly is quickly diagnosed. With this previous recovery experience and the very focused boundary conditions of a specific potential failure, a Gaspra asteroid recovery plan was designed to be implemented in as quickly as forty hours (desired goal). This paper documents the work performed above, however, the Galileo project remains challenged to develop a generic detailed recovery plan which can be implemented in a relatively short time to configure the spacecraft to a nominal state prior to future high priority mission objectives.

Basilio, Ralph R.↗
DOE OSTI2018

Zero Energy University Campuses: A 2018 Progress Update on Reaching Campus Energy Goals: Preprint

Many universities have aggressive energy-reduction and climate action plans. To reach these goals, leading universities have developed a suite of common energy-efficiency and renewable generation strategies. In this paper, we present a common set of approaches across the following areas: zero energy campus definitions and planning, best practices for including energy targets in new construction procurement contracts and design guidelines, implementing pilot new construction zero energy projects, aggressively implementing best-in-class laboratory energy-efficiency strategies, planning for and optimizing on-site and off-site renewable energy projects, and high-performance district energy systems. Best practices are compiled from various experiences, including programs funded by the U.S. Department of Energy, Energy Efficiency and Renewable Energy program. The summary of these best practices is to reduce campus energy use and then meet the remaining campus energy needs with renewable energy. The fivestep process to developing and implementing campus energy-reduction plans is described: 1) determine baseline energy consumption, 2) analyze technology options, 3) develop a plan and set priorities, 4) implement the plan, and 5) evaluate progress. The process follows a logical hierarchy of actions to evaluate options by energy sector and set specific targets. It encompasses all energy systems on campus, recognizing that campus-wide measures have increased potential for reducing energy use. Common strategies are explained along with examples and results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Zero Energy University Campuses: A 2018 Progress Update on Reaching Campus Energy Goals

Many universities have aggressive energy-reduction and climate action plans. To reach these goals, leading universities have developed a suite of common energy-efficiency and renewable generation strategies. In this paper, we present a common set of approaches across the following areas: zero energy campus definitions and planning, best practices for including energy targets in new construction procurement contracts and design guidelines, implementing pilot new construction zero energy projects, aggressively implementing best-in-class laboratory energy-efficiency strategies, planning for and optimizing on-site and off-site renewable energy projects, and high-performance district energy systems. Best practices are compiled from various experiences, including programs funded by the U.S. Department of Energy, Energy Efficiency and Renewable Energy program. The summary of these best practices is to reduce campus energy use and then meet the remaining campus energy needs with renewable energy. The fivestep process to developing and implementing campus energy-reduction plans is described: 1) determine baseline energy consumption, 2) analyze technology options, 3) develop a plan and set priorities, 4) implement the plan, and 5) evaluate progress. The process follows a logical hierarchy of actions to evaluate options by energy sector and set specific targets. It encompasses all energy systems on campus, recognizing that campus-wide measures have increased potential for reducing energy use. Common strategies are explained along with examples and results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2006

Systems Engineering and Integration for Technology Programs

The Architecture, Habitability & Integration group (AH&I) is a system engineering and integration test team within the NASA Crew and Thermal Systems Division (CTSD) at Johnson Space Center. AH&I identifies and resolves system-level integration issues within the research and technology development community. The timely resolution of these integration issues is fundamental to the development of human system requirements and exploration capability. The integration of the many individual components necessary to construct an artificial environment is difficult. The necessary interactions between individual components and systems must be approached in a piece-wise fashion to achieve repeatable results. A formal systems engineering (SE) approach to define, develop, and integrate quality systems within the life support community has been developed. This approach will allow a Research & Technology Program to systematically approach the development, management, and quality of technology deliverables to the various exploration missions. A tiered system engineering structure has been proposed to implement best systems engineering practices across all development levels from basic research to working assemblies. These practices will be implemented through a management plan across all applicable programs, projects, elements and teams. While many of the engineering practices are common to other industries, the implementation is specific to technology development. An accounting of the systems engineering management philosophy will be discussed and the associated programmatic processes will be presented.

Kennedy, Kruss J.↗
DOE OSTI2014

TH-A-19A-02: Expanding TOPAS Towards Biological Modeling

Purpose: To expand Monte Carlo simulations of TOPAS to directly calculate radiobiological effects using various biological models. Methods: We use the TOPAS toolkit version beta9 and expand the provided scoring system to directly include scorers for relative biological effect (RBE) modeling. A scorer is a class to record a given physical property in the Monte Carlo simulations. We developed a scorer for the dose averaged linear energy transfer (LETd). This scorer was used to compare RBE weighted dose distributions assuming a constant RBE of 1.1 with the RBE weighted dose using a variable RBE based on a model using LETd and dose as input. Additionally, the local effect model (LEM) was implemented in TOPAS to estimate RBE weighted dose distributions. Survival curves for the LEM were simulated for a monoenergetic proton beams impinging on phantoms and for full patient treatment plans. Results: We have implemented radiobiological effect models in TOPAS, providing users with the possibility to directly obtain parameters related to radiobiological dose and use those as additional information to assess the quality of treatment plans. We applied the scorers to clinical patient treatments and phantom simulations. We find that for the proton therapy plans investigated the regions with the highest LETd are generally outside of the target volume, coinciding with the distal edge of treatment fields. LETd-based variable RBE weighted dose models predict higher doses at the distal edge of over 10% of the prescribed dose than when assuming a constant RBE. Conclusion: By implementing radiobiological effect models into a Monte Carlo simulation package we combine accurate dose calculation with biological modeling. TOPAS thereby provides distributions of multiple physical quantities such as the dose and LETd, and estimates of biological parameters (RBE, survival) thus allowing direct comparison of biological effective dose predictions between different models.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2020

Planning and Optimization for Multi-robot Planetary Cave Exploration under Intermittent Connectivity Constraints

Exploring subsurface structures with autonomous robots is of growing interest in the context of planetary caves studies. Communication between robots in these environments is severely degraded which complicates coordination and information distribution. In this paper we focus on planning for mobility and communication in a cave exploration scenario where the situational awareness of a static base station is critical. We propose a notion of information-consistency where a plan itself is part of the information to be shared between robots, and propose a method for generating information-consistent plans. We discuss in detail how the resulting plan can be robustly implemented with minimal communication through local mission executives that run on individual robots. We describe preliminary results on the performance of the planning algorithm and integration of the local mission executives in a high-fidelity simulation environment.

Murray, Richard M.↗
NASA NTRS1985

Report of the LSPI/NASA Workshop on Lunar Base Methodology Development

Groundwork was laid for computer models which will assist in the design of a manned lunar base. The models, herein described, will provide the following functions for the successful conclusion of that task: strategic planning; sensitivity analyses; impact analyses; and documentation. Topics addressed include: upper level model description; interrelationship matrix; user community; model features; model descriptions; system implementation; model management; and plans for future action.

Nozette, Stewart↗
NASA NTRSDate not supplied

James Webb Space Telescope Navigation Optimization Challenges

The James Webb Space Telescope (JWST) is a NASA flagship mission launched on December 25, 2021. The early orbit phase was highlighted by three midcourse correction burns that were performed to maneuver the vehicle into a libration orbit at the second Sun-Earth-Moon (SEM) libration point (L2). During the coast to L2, the vehicle’s primary observatory and sunshield were deployed. Once the tennis-court-sized sunshield was unfurled and tensioned into place, the large area exposed to solar radiation pressure (SRP) dictated that the SRP force model would need to account for the vehicle’s geometry, reflective properties, and orientation relative to the Sun. Following the insertion of JWST into its L2 libration orbit on January 24, 2022, the commissioning phase for the vehicle’s observatory commenced along with the first cycle of routine station-keeping maneuvers. The NASA Goddard Space Flight Center’s Flight Dynamics Facility (FDF) provides navigation services for the JWST mission. The FDF serves as the prime or backup navigation operations center for more than 30 active missions spanning a wide array of flight regimes performing orbit determination, maneuver planning, trajectory optimization, and tracking data evaluation. Definitive orbit determination for JWST is performed by the FDF using an Extended Kalman Filter (EKF) to estimate the vehicle’s trajectory and reflective properties using Deep Space Network (DSN) TRK-2-34 tracking data and spacecraft attitude telemetry. For the purposes of orbit prediction and station-keeping maneuver targeting, the sensitivity of the SRP force to the vehicle’s orientation requires that predictive attitude information must be incorporated to generate accurate orbit predictions and maneuver plans. Predictive attitude plans are provided to the FDF by the JWST Spacecraft Operations Center (SOC). Short-term (28 day) orbit predictions are propagated using a Short Range Attitude Plan (SRAP) to model the vehicle’s future attitude states for up to a week. SRAP attitude data is highly reliable, as it reflects finalized planned attitude states that the vehicle will be commanded to attain during the ensuing week. A Long Range Attitude Plan (LRAP) can be implemented to model predicted attitude states beyond one week, but these predictions are tentative and subject to revision due to changes in science operations plans. Instead, a conservative approach of applying a Sun-Pointing Neutral (SPN) attitude configuration is utilized for long-term (2 year) orbit predictions where reliable planned attitude data is not available. SPN attitude mode aligns the net SRP force along the JWST-to-Sun vector where it becomes independent of the vehicle’s angle of rotation about this vector, defined as the Sun yaw. Given the dynamic instability of the libration orbit, station-keeping thrust must be applied in either the sunward or anti-sunward direction to balance the resulting orbit. The attitude constraints of the vehicle also impose limits on the available pointing directions for station-keeping thrusters. The thrusters cannot be aligned with the optimal pointing direction for sunward maneuvers, rendering sunward maneuvers to be significantly less fuel efficient than anti-sunward maneuvers. Consequently, station-keeping maneuvers must be targeted to balance the orbit while ensuring that the next maneuver will also be performed in the anti-sunward direction to optimize propellant usage. When targeting a station-keeping maneuver, the attitude and SRP modeling configuration which is applied to the predicted post-maneuver trajectory will dictate the direction of the subsequent station-keeping maneuver, assuming nominal propulsion system performance. If the predicted post-maneuver attitude states result in an SRP model which under-predicts the cumulative SRP impact on the post-maneuver orbit, a targeted anti-sunward maneuver will be larger than necessary and the next maneuver will need to be executed sunward in order to compensate. In contrast, an anti-sunward maneuver which is targeted using an SRP model which over-predicts the cumulative SRP impact will achieve station-keeping while ensuring that the next maneuver will likewise be performed anti-sunward. For this reason, station-keeping maneuvers are targeted while applying the SPN attitude mode, as this mode entails the largest possible SRP area cross-section and therefore a larger modeled cumulative SRP impact. This paper documents the NASA Goddard Space Flight Center’s FDF support for JWST on-orbit operations and the analysis projects undertaken utilizing the experiences and data accumulated throughout the first full year of routine science operations. The results of these analysis efforts have been used to implement improvements to orbit prediction accuracy and maneuver efficiency which have the potential to prolong the lifespan of JWST to continue to conduct ground-breaking infrared astronomy for decades to come.

Flight Dynamics↗
DOE OSTI2014

TU-C-17A-01: A Data-Based Development for Pratical Pareto Optimality Assessment and Identification

Purpose: To develop an efficient Pareto optimality assessment scheme to support plan comparison and practical determination of best-achievable practical treatment plan goals. Methods: Pareto efficiency reflects the tradeoffs among competing target coverage and normal tissue sparing in multi-criterion optimization (MCO) based treatment planning. Assessing and understanding Pareto optimality provides insightful guidance for future planning. However, current MCO-driven Pareto estimation makes relaxed assumptions about the Pareto structure and insufficiently account for practical limitations in beam complexity, leading to performance upper bounds that may be unachievable. This work proposed an alternative data-driven approach that implicitly incorporates the practical limitations, and identifies the Pareto frontier subset by eliminating dominated plans incrementally using the Edgeworth Pareto hull (EPH). The exactness of this elimination process also permits the development of a hierarchical procedure for speedup when the plan cohort size is large, by partitioning the cohort and performing elimination in each subset before a final aggregated elimination. The developed algorithm was first tested on 2D and 3D where accuracy can be reliably assessed. As a specific application, the algorithm was applied to compare systematic plan quality for lower head-and-neck, amongst 4 competing treatment modalities. Results: The algorithm agrees exactly with brute-force pairwise comparison and visual inspection in low dimensions. The hierarchical algorithm shows sqrt(k) folds speedup with k being the number of data points in the plan cohort, demonstrating good efficiency enhancement for heavy testing tasks. Application to plan performance comparison showed superiority of tomotherapy plans for the lower head-and-neck, and revealed a potential nonconvex Pareto frontier structure. Conclusion: An accurate and efficient scheme to identify Pareto frontier from a plan cohort has been developed. This implementation would guide generating good yet practically achievable plan quality goals for further planning. The observation of a systematic performance bias and a nonconvex Pareto frontier warrants further investigation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2010

Staubli TX-90XL robot qualification at the LLIHE.

The Light Initiated High Explosive (LIHE) Facility uses a robotic arm to spray explosive material onto test items for impulse tests. In 2007, the decision was made to replace the existing PUMA 760 robot with the Staubli TX-90XL. A qualification plan was developed and implemented to verify the safe operating conditions and failure modes of the new system. The robot satisfied the safety requirements established in the qualification plan. A performance issue described in this report remains unresolved at the time of this publication. The final readiness review concluded the qualification of this robot at the LIHE facility.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2018

Hanford Site Ecological Monitoring Report for Calendar Year 2017

The U.S. Department of Energy, Richland Operations Office (DOE-RL) conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing the U.S. Department of Energy’s (DOE) activities. Ecological monitoring data provide baseline information about the plants, animals, and habitats under DOE-RL stewardship at the Hanford Site required for decision making under the National Environmental Policy Act and Comprehensive Environmental Response, Compensation, and Liability Act. DOE/EIS-0222-FU, Final Hanford Comprehensive Land Use Plan Environmental Impact Statement, (CLUP) evaluates potential environmental impacts associated with implementing a comprehensive land use plan for the Hanford Site over the next 50 years. The vision for the DOE-RL-managed portion of the Hanford Site focuses not only on the cleanup of nuclear facilities and waste sites but on the protection of groundwater, the Columbia River, and the restoration of the land for access and use. To reach these goals DOE-RL is working closely with partners, such as the U. S. Fish and Wildlife Service (FWS) and National Park Service, to enable use of the Hanford land consistent with the CLUP. As DOE-RL moves toward accomplishing this vision, monitoring the ecological resources present to determine whether there is a need for conservation and/or protection of any resources will be critical for making informed decisions for responsible site stewardship.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

All Kitted Out

The Hydropower Knowledge Sharing and Succession Planning Toolkit, created by the National Renewable Energy Laboratory (NREL) in collaboration with the U.S. Department of Energy’s Water Power Technologies Office (WPTO), can help your organization effectively plan for workforce changes and share knowledge across employees. By proactively implementing knowledge sharing and succession planning strategies, hydropower organizations can safeguard institutional knowledge, enhance workforce resilience, and ensure long-term operational stability in an evolving industry landscape.

13 HYDRO ENERGY↗
DOE OSTI2010

Enhancements to commissioning techniques and quality assurance of brachytherapy treatment planning systems that use model-based dose calculation algorithms

The current standard for brachytherapy dose calculations is based on the AAPM TG-43 formalism. Simplifications used in the TG-43 formalism have been challenged by many publications over the past decade. With the continuous increase in computing power, approaches based on fundamental physics processes or physics models such as the linear-Boltzmann transport equation are now applicable in a clinical setting. Thus, model-based dose calculation algorithms (MBDCAs) have been introduced to address TG-43 limitations for brachytherapy. The MBDCA approach results in a paradigm shift, which will require a concerted effort to integrate them properly into the radiation therapy community. MBDCA will improve treatment planning relative to the implementation of the traditional TG-43 formalism by accounting for individualized, patient-specific radiation scatter conditions, and the radiological effect of material heterogeneities differing from water. A snapshot of the current status of MBDCA and AAPM Task Group reports related to the subject of QA recommendations for brachytherapy treatment planning is presented. Some simplified Monte Carlo simulation results are also presented to delineate the effects MBDCA are called to account for and facilitate the discussion on suggestions for (i) new QA standards to augment current societal recommendations, (ii) consideration of dose specification such as dose to medium in medium, collisional kerma to medium in medium, or collisional kerma to water in medium, and (iii) infrastructure needed to uniformly introduce these new algorithms. Suggestions in this Vision 20/20 article may serve as a basis for developing future standards to be recommended by professional societies such as the AAPM, ESTRO, and ABS toward providing consistent clinical implementation throughout the brachytherapy community and rigorous quality management of MBDCA-based treatment planning systems.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2010

Evolving the Technical Infrastructure of the Planetary Data System for the 21st Century

The Planetary Data System (PDS) was established in 1989 as a distributed system to assure scientific oversight. Initially the PDS followed guidelines recommended by the National Academies Committee on Data Management and Computation (CODMAC, 1982) and placed emphasis on archiving validated datasets. But overtime user demands, supported by increased computing capabilities and communication methods, have placed increasing demands on the PDS. The PDS must add additional services to better enable scientific analysis within distributed environments and to ensure that those services integrate with existing systems and data. To face these challenges the Planetary Data System (PDS) must modernize its architecture and technical implementation. The PDS 2010 project addresses these challenges. As part of this project, the PDS has three fundamental project goals that include: (1) Providing more efficient client delivery of data by data providers to the PDS (2) Enabling a stable, long-term usable planetary science data archive (3) Enabling services for the data consumer to find, access and use the data they require in contemporary data formats. In order to achieve these goals, the PDS 2010 project is upgrading both the technical infrastructure and the data standards to support increased efficiency in data delivery as well as usability of the PDS. Efforts are underway to interface with missions as early as possible and to streamline the preparation and delivery of data to the PDS. Likewise, the PDS is working to define and plan for data services that will help researchers to perform analysis in cost-constrained environments. This presentation will cover the PDS 2010 project including the goals, data standards and technical implementation plans that are underway within the Planetary Data System. It will discuss the plans for moving from the current system, version PDS 3, to version PDS 4.

Beebe, Reta F.↗
NASA NTRS2005

Designing and Implementing a Distributed System Architecture for the Mars Rover Mission Planning Software (Maestro)

Distributed systems allow scientists from around the world to plan missions concurrently, while being updated on the revisions of their colleagues in real time. However, permitting multiple clients to simultaneously modify a single data repository can quickly lead to data corruption or inconsistent states between users. Since our message broker, the Java Message Service, does not ensure that messages will be received in the order they were published, we must implement our own numbering scheme to guarantee that changes to mission plans are performed in the correct sequence. Furthermore, distributed architectures must ensure that as new users connect to the system, they synchronize with the database without missing any messages or falling into an inconsistent state. Robust systems must also guarantee that all clients will remain synchronized with the database even in the case of multiple client failure, which can occur at any time due to lost network connections or a user's own system instability. The final design for the distributed system behind the Mars rover mission planning software fulfills all of these requirements and upon completion will be deployed to MER at the end of 2005 as well as Phoenix (2007) and MSL (2009).

Goldgof, Gregory M.↗
DOE OSTI2011

NEAMS Nuclear Waste Management IPSC : evaluation and selection of tools for the quality environment.

The objective of the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation Nuclear Waste Management Integrated Performance and Safety Codes (NEAMS Nuclear Waste Management IPSC) is to provide an integrated suite of computational modeling and simulation (M&S) capabilities to quantitatively assess the long-term performance of waste forms in the engineered and geologic environments of a radioactive-waste storage facility or disposal repository. These M&S capabilities are to be managed, verified, and validated within the NEAMS Nuclear Waste Management IPSC quality environment. M&S capabilities and the supporting analysis workflow and simulation data management tools will be distributed to end-users from this same quality environment. The same analysis workflow and simulation data management tools that are to be distributed to end-users will be used for verification and validation (V&V) activities within the quality environment. This strategic decision reduces the number of tools to be supported, and increases the quality of tools distributed to end users due to rigorous use by V&V activities. This report documents an evaluation of the needs, options, and tools selected for the NEAMS Nuclear Waste Management IPSC quality environment. The objective of the U.S. Department of Energy (DOE) Office of Nuclear Energy Advanced Modeling and Simulation Nuclear Waste Management Integrated Performance and Safety Codes (NEAMS Nuclear Waste Management IPSC) program element is to provide an integrated suite of computational modeling and simulation (M&S) capabilities to assess quantitatively the long-term performance of waste forms in the engineered and geologic environments of a radioactive-waste storage facility or disposal repository. This objective will be fulfilled by acquiring and developing M&S capabilities, and establishing a defensible level of confidence in these M&S capabilities. The foundation for assessing the level of confidence is based upon the rigor and results from verification, validation, and uncertainty quantification (V&V and UQ) activities. M&S capabilities are to be managed, verified, and validated within the NEAMS Nuclear Waste Management IPSC quality environment. M&S capabilities and the supporting analysis workflow and simulation data management tools will be distributed to end-users from this same quality environment. The same analysis workflow and simulation data management tools that are to be distributed to end-users will be used for verification and validation (V&V) activities within the quality environment. This strategic decision reduces the number of tools to be supported, and increases the quality of tools distributed to end users due to rigorous use by V&V activities. NEAMS Nuclear Waste Management IPSC V&V and UQ practices and evidence management goals are documented in the V&V Plan. This V&V plan includes a description of the quality environment into which M&S capabilities are imported and V&V and UQ activities are managed. The first phase of implementing the V&V plan is to deploy an initial quality environment through the acquisition and integration of a set of software tools. An evaluation of the needs, options, and tools selected for the quality environment is given in this report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2021

Concept of Operations for OSIRIS-REx Optical Navigation Image Planning

Optical navigation (OpNav) is a critical subsystem of the OSIRIS-REx asteroid sample return mission, which operated in the vicinity of near-Earth asteroid (101955) Bennu from August 2018 through April 2021. A substantial amount of mission resources across multiple subsystems and institutions is required to ensure that the OpNav data are successfully acquired. The KinetX OpNav team, part of the Flight Dynamics System (FDS), is responsible for performing required analysis to develop the OpNav operations plans; requesting, reviewing and verifying the plans; and ultimately using the image data for critical navigation operations. The FDS team, responsible for the mission navigation, is operated by KinetX Aerospace with management and operations support from NASA’s Goddard Space Flight Center. The Science Processing and Operations Center (SPOC), located at the University of Arizona’s Lunar and Planetary Laboratory, is responsible for generating the planning products for all science and most OpNav data. These plans are integrated into the spacecraft sequences, tested, and commanded by the Mission Support Area (MSA) at Lockheed Martin Space. To ensure mission-critical navigation image data are successfully acquired, the plan is developed through a waterfall of planning cycles over the course of 3 months prior to onboard plan execution. During the initial strategic planning for a mission phase, detailed analysis is performed by the OpNav team to conceptualize the concept of operations (ConOps) for image data collection. This phase OpNav Narrative is included along with other strategic planning documents for the key ground segment stakeholders to review and provide feedback. The detailed OpNav plans get defined in the tactical planning cycle, which spans 8 to 3 weeks before the week-long integrated sequence is executed on-board the spacecraft. During the tactical cycle, the initial OpNav Request is submitted along with the science requests, kicking off development of the science and OpNav plans. Once the initial plan is drafted, interfaces are exercised so that the plan can be reviewed and iterated, if necessary. A rigorous schedule is followed by the planning teams during the implementation cycle, spanning the last 18 days before uplink, to ensure all the necessary integration, testing, and reviewing can occur on time. The development of the OpNav planning ConOps, including responsibilities, interfaces, timelines, and procedures, took extensive collaboration across mission elements and institutions. The process was robust throughout the 137 weeks of continuous Optical Navigation Operations at Bennu, which concluded on April 9th, 2021.

Coralie D. Adam↗