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At least 577 records · Page 32

Closed Environment Air Revitalization System Based on Metal Organic Framework Adsorbents

This project utilized a systems engineering methodology to develop a vacuum swing adsorption system with full Labview automated control. The project was successful and provided students with an introduction to systems engineering and air revitalization. Specifically, two stainless steel adsorption beds were custom designed and manufactured and a sequence of computer controlled valves were used to deliver CO 2 laden, humid air, to the adsorbent where the CO 2 was removed from the air stream. Runs were completed using 13X zeolite and bed timing and switching was controlled by the computer based on the data output of a CO 2 detector. Adsorption runs using the MOF have not been completed upon the writing of this report; however, the MOF material is currently being synthesized and the runs will be completed upon receipt of the material. A follow up meeting with NASA has been tentatively planned to discuss the output of these experiments. Consistent with systems engineering practice, an end of project assessment of the class was conducted with the students and several items were realized. Specifically, the short period of performance of this grant makes it necessary to maintain a narrowly focused scope on the project such that multiple experiments after systems development (T&E) need to be limited to ensure timely completion of the proposed tasks. Also, procurement of parts may need to be moved forward in time to allow for delivery delays, and it may be necessary to request SDR, PDR, and CDR dates from NASA that are ahead of the NASA anticipated schedule. These types of lessons provided valuable to both the PI and the students and ultimately illustrate the necessity of proper systems engineering schedule risk assessment. The class met the objectives of the project and provided an introduction to systems engineering to undergraduate students. As a metric of that success, the lead engineer of the undergraduate design team acquired a job with an aerospace defense contractor, which he attributed to his knowledge of systems engineering concepts that were acquired via the X-Hab class.

T. Grant Glover↗

Government-to-government cooperation in space station development

A memoranda of understanding was recently signed between the United States (NASA) and three international Space Station partners - Canada, European Space Agency (ESA), and Japan. The international partners are performing parallel Phase B preliminary design studies, concurrent with the U.S., on their proposed elements/systems for possible integration and operation with the U.S. Space Station System complex. During the 21-month Space Station Phase B study, a large amount of technical interface data will have to be transferred between the U.S. and the international partners. Scheduled bilateral technical coordination meetings will also be held. The coordination and large number of interfaces required to integrate the international requirements into the Space Station require a clean interface management organizational structure and operation procedures to accomplish the integration task. The international coordination management organizational structure, management tools, and communications network are discussed including the proposed international elements/systems being studied by the international partners.

Nassiff, S. H.↗

Testing of ROMPS robot mechanical interfaces and compliant device

The Robot Operated Materials Processing System (ROMPS) has been developed at Goddard Space Flight Center (GSFC) under a flight project to investigate commercially promising in-space material processes and to design reflyable robot automated systems to be used in the above processes for low-cost operations. The ROMPS is currently scheduled for flight in 1994 as a Hitchhiker payload in a Get Away Special (GAS) can. An important component of the ROMPS is a three degree-of-freedom (DOF) robot which will be responsible for carrying out the required tasks of in-space processing of selected materials. This report deals with testing of the mating capability of the ROMPS robot fingers with its various mechanical interfaces. In particular, the test plan will focus on studying the capability of a compliance mechanism mounted on the robot fingers in accommodating misalignments between the robot fingers and the interfaces during the mating. The report is organized as follows: Section 2 represents the main components of the ROMPS robot and briefly describes its operations. Section 3 presents the objectives of the test and outlines the test plan. The testbed comprising a Steward Platform-based high precision manipulator and associated data acquisition and control systems is described in Section 4. Section 5 presents results of numerous experiments conducted to study the mating capability of the robot fingers with its various interfaces under misalignments. The report is concluded with observations and recommendations based on the test results.

Nguyen, Charles C.↗

Daytime Cognitive Performance in Response to Sunlight or Fluorescent Light Controlling for Sleep Duration

Light is the primary synchronizer of the human circadian rhythm and also has acute alerting effects. Our study involves and comparing the alertness, performance and sleep of participants in the NASA Ames Sustainability Base, which uses sunlight as its primary light source, to in a traditional office building which uses overhead florescent lighting and varying exposure to natural light. The purpose of this study is to determine whether the use of natural lighting as a primary light source improves daytime cognitive function and promotes nighttime sleep. Participants from the Sustainability Base will be matched by gender and age to individuals working in other NASA buildings. In a prior study we found no differences in performance between those working in the Sustainability Base and those working in other buildings. Unexpectedly, we found that the average sleep duration among participants in both buildings was short, which likely obscured our ability to detect a difference the effect of light exposure on alertness. Given that such sleep deprivation has negative effects on cognitive performance, in this iteration of the study we are asking the participants to maintain a regular schedule with eight hours in bed each night in order to control for the effect of self-selected sleep restriction. Over the course of one week, we will ask the participants to wear actiwatches continuously, complete a psychomotor vigilance task (PVT) and digit symbol substitution task (DSST) three times per day, and keep daily sleepwork diaries. We hope that this study will provide data to support the idea that natural lighting and green architectural design are optimal to enhance healthy nighttime sleep patterns and daytime cognitive performance.

cognitive performance↗

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗

Modeling of flow systems for implementation under KATE

The modeling of flow systems is a task currently being investigated at Kennedy Space Center in parallel with the development of the KATE artificial intelligence system used for monitoring diagnosis and control. Various aspects of the modeling issues are focussed on with particular emphasis on a water system scheduled for demonstration within the KATE environment in September of this year. LISP procedures were written to solve the continuity equations for three internal pressure nodes using Newton's method for simultaneous nonlinear equations.

Whitlow, Jonathan E.↗

A mission planning concept and mission planning system for future manned space missions

The international character of future manned space missions will compel the involvement of several international space agencies in mission planning tasks. Additionally, the community of users requires a higher degree of freedom for experiment planning. Both of these problems can be solved by a decentralized mission planning concept using the so-called 'envelope method,' by which resources are allocated to users by distributing resource profiles ('envelopes') which define resource availabilities at specified times. The users are essentially free to plan their activities independently of each other, provided that they stay within their envelopes. The new developments were aimed at refining the existing vague envelope concept into a practical method for decentralized planning. Selected critical functions were exercised by planning an example, founded on experience acquired by the MSCC during the Spacelab missions D-1 and D-2. The main activity regarding future mission planning tasks was to improve the existing MSCC mission planning system, using new techniques. An electronic interface was developed to collect all formalized user inputs more effectively, along with an 'envelope generator' for generation and manipulation of the resource envelopes. The existing scheduler and its data base were successfully replaced by an artificial intelligence scheduler. This scheduler is not only capable of handling resource envelopes, but also uses a new technology based on neuronal networks. Therefore, it is very well suited to solve the future scheduling problems more efficiently. This prototype mission planning system was used to gain new practical experience with decentralized mission planning, using the envelope method. In future steps, software tools will be optimized, and all data management planning activities will be embedded into the scheduler.

Wickler, Martin↗

STS-113 Flight Day 3 Highlights

This video shows the activities of the STS-113 crew (Jim Wetherbee, Commander; Paul Lockhart, Pilot; Michael Lopez-Alegria, John Herrington, Mission Specialists) during flight day 3. The major tasks of flight day 3 were rendezvous and docking with the ISS (International Space Station), the transfer of the Expedition 6 crew (Kenneth Bowersox, Commander; Donald Pettit, Nikolai Budarin, Flight Engineers) to the ISS, and preparations for an EVA (extravehicular activity) scheduled for the following day. The approach of Space Shuttle Endeavour to the ISS is shown in detail, including the firing of the Left Orbital Maneuvering System, and the aiming maneuvers the orbiter makes to dock with the ISS. There are centerline views of the ISS before and during the final docking maneuver. The new ISS crew is received by the Expedition 5 crew (Valeri Korzun, Commander; Peggy Whitsun, Sergei Treschev; Flight Engineers), and the transfer of EVA suits is shown. Earth views include a pan along a reddish Earth limb, and the Pacific Ocean with Endeavour's Canadarm robotic arm in the foreground.

Source record↗

Managing Large Scale Project Analysis Teams through a Web Accessible Database

Large scale space programs analyze thousands of requirements while mitigating safety, performance, schedule, and cost risks. These efforts involve a variety of roles with interdependent use cases and goals. For example, study managers and facilitators identify ground-rules and assumptions for a collection of studies required for a program or project milestone. Task leaders derive product requirements from the ground rules and assumptions and describe activities to produce needed analytical products. Disciplined specialists produce the specified products and load results into a file management system. Organizational and project managers provide the personnel and funds to conduct the tasks. Each role has responsibilities to establish information linkages and provide status reports to management. Projects conduct design and analysis cycles to refine designs to meet the requirements and implement risk mitigation plans. At the program level, integrated design and analysis cycles studies are conducted to eliminate every 'to-be-determined' and develop plans to mitigate every risk. At the agency level, strategic studies analyze different approaches to exploration architectures and campaigns. This paper describes a web-accessible database developed by NASA to coordinate and manage tasks at three organizational levels. Other topics in this paper cover integration technologies and techniques for process modeling and enterprise architectures.

O'Neil, Daniel A.↗

Overview of NASA's Break the Ice Lunar Challenge

The goal of NASA’s Artemis program is to return to the Moon and put in place a sustainable infrastructure that will enable permanent presence on the Moon. In-Situ Resource Utilization (ISRU) is critical in making the permanent presence on the Moon possible. One of the most important of these resources is water. On the Moon, water is trapped in icy regolith at the lunar poles, including inside permanently dark and cold craters. Excavating icy regolith and extracting water from it needs development of technologies that can operate reliably in the extreme lunar environmental conditions. Prize competitions are a well-known way of accelerating the development of new technologies and have been successfully used throughout the history. NASA’s Centennial Challenges Program(CCP) has been developing and executing prize competitions for past 15 years. Several of these competitions resulted in breakthrough technologies for in-space and terrestrial applications. In 2019, NASA Space Technology Mission Directorate (STMD) tasked CCP to develop a challenge to address the technology gaps in the areas of Lunar Excavation, Manufacturing, and Construction. This paper provides the background, status and ongoing plans by CCP in developing “Break the Ice Lunar Challenge”. The challenge is scheduled to open for registration in late 2020. This challenge will enable the development of excavation technologies that can operate in the extreme conditions on the Moon.

centennial challenges↗

iDDS: intelligent distributed dispatch and scheduling for workflow orchestration

The intelligent distributed dispatch and scheduling (iDDS) service is a versatile workflow orchestration system designed for large-scale, distributed scientific computing. iDDS extends traditional workload and data management by integrating data-aware execution, conditional logic, and programmable workflows, enabling automation of complex and dynamic processing pipelines. Originally developed for the ATLAS experiment at the large hadron collider, iDDS has evolved into an experiment-agnostic platform that supports both template-driven workflows and a Function-as-a-Task model for Python-based orchestration. This paper presents the architecture and core components of iDDS, highlighting its scalability, modular message-driven design, and integration with systems such as PanDA and Rucio. We demonstrate its versatility through real-world use cases: fine-grained tape resource optimization for ATLAS, orchestration of large Directed Acyclic Graph (DAG) workflows for the Rubin Observatory, distributed hyperparameter optimization for machine learning applications, active learning for physics analyses, and AI-assisted detector design at the electron–ion collider. By unifying workload scheduling, data movement, and adaptive decision-making, iDDS reduces operational overhead and enables reproducible, high-throughput workflows across heterogeneous infrastructures. We conclude with current challenges and future directions, including interactive, cloud-native, and serverless workflow support.

97 MATHEMATICS AND COMPUTING↗

Investigating the Effects of Exposure to Blue-Enriched Light or Peppermint Odor on Alertness, Mood, and Performance Upon Awakening from Deep Sleep at Night

Introduction: Sleep inertia refers the transient neurobehavioral impairments experienced immediately after waking from sleep. This period of reduced alertness and performance poses a significant safety risk to on-call workers who may be required to perform a safety-critical task immediately after waking (e.g., emergency services, health care, and military). In these operations, the need for a rapid return to full alertness is critical to mission safety and success. Several factors may exacerbate sleep inertia, resulting in greater impairment upon waking, including: waking from deep sleep, (i.e., slow wave sleep, SWS), waking at night, and waking following prior sleep loss. Awakenings under these conditions are common for on-call and extended shift workers who may need to perform safety-critical tasks soon after waking from unprotected sleep opportunities. Therefore, there is a need for evidence-based reactive countermeasures (i.e., used upon waking) to the cognitive consequences sleep inertia. Specifically, countermeasures that can rapidly restore alertness and performance immediately following sleep. A recent review of the literature on reactive countermeasures highlighted several research gaps and promising candidates for further investigation. The review also emphasized the need for countermeasures that are operationally viable and readily deployed in occupational settings. This study aims to address the identified gaps and limitations by assessing the efficacy of exposure to two known acute alerting stimuli - blue-enriched light and peppermint odor - to improve cognitive performance, alertness, and mood immediately after waking from SWS at night. Materials and Methods: Twelve participants completed a two-week within-subject, randomized, cross-over intervention study including two in-laboratory overnight visits. During each experimental week, the subjects experienced one intervention (light or peppermint) and a control condition upon awakening from SWS at night. The presentation order of the two conditions (intervention or control) at wake-up and the order of intervention (light or peppermint) by week was randomized by sex. Prior to each in-laboratory visit, participants maintained a sleep schedule of 8.5 h for 5 nights and 5 h for one night. Compliance with this sleep schedule was confirmed by actigraphy. In the laboratory, participants went to bed at their habitual bedtime and were monitored by standard polysomnography. After at least five minutes of continuous SWS, participants were awoken and exposed, in a randomized order, to either the control or intervention condition. During the hour after awakening from SWS (at 2, 17, 32, and 47 minutes after waking), participants completed a battery of tasks including a 5-minute psychomotor vigilance task (PVT), a subjective scale of alertness (Karolinska Sleepiness Scale, KSS), and visual analogue scales (VAS) of mood. Following this sleep inertia measurement period, all lights were turned off and participants were allowed to return to sleep. They were then awoken again from their subsequent SWS period and exposed to the alternative condition (control or intervention). Following this second awakening, participants were allowed to sleep until their habitual wake time and were then released from the laboratory. Participants then followed the at-home sleep schedule and returned to the laboratory for the second intervention (light or peppermint) following the procedures described above. The light intervention involved exposure to a blue-enriched light canvas illuminated for 1 hour at a distance of ~56 cm from the participant (~200 lux and ~60 melanopic lux at angle of gaze). For the peppermint intervention, peppermint oil was pipetted onto a mask, and participants inhaled the odor with the mask covering the nose and mouth for 1 minute. The control condition for both weeks involved a dim, red ambient light (<1 lux). An odorless mask, without any oil pipetted onto the mask, was also worn in the peppermint control condition. Results: Compared to the control condition, participants exposed to blue-enriched light had fewer PVT lapses (χ2 = 5.285, p = .022), reported feeling more alert (KSS: F1,77 = 4.955, p = .029; VASalert: F1,77 = 8.226, p = .005), and had improved mood (VAScheerful: F1,77 = 8.615, p = .004; VASdepressed: F1,77 = 4.649, p = .034; VASlethargic: F1,77 = 5.652, p = .020). Exposure to peppermint oil did not improve any outcome measures on any of the tasks compared to control condition (p > .05). Conclusions: We found that participants had fewer lapses of attention upon awakening when exposed to blue-enriched light compared to dim, red light. In addition, participants reported feeling more alert, more cheerful, less depressed, and less lethargic in the blue-enriched light condition. Brief exposure to a peppermint odor, however, did not appear to improve performance, alertness, or mood under the experimental conditions. Our null results in the peppermint condition may have been due to methodological limitations such as the duration and method of administration. Given the need to mitigate the potential impact of sleep inertia on safety-critical tasks in on-call operations, our findings suggest that blue-enriched light exposure upon awakening may help to improve performance and alertness during the sleep inertia period following awakening from deep, nocturnal sleep. We are currently exploring the potential mechanisms for the effect of light on cognitive performance upon awakening as well as investigating its application in real-world settings to explore the translational efficacy of this countermeasure to occupational environments. Continued exploration into light and other reactive countermeasures, and potentially their combination, is needed in order to provide evidence-based guidance on effective sleep inertia countermeasures to improve the alertness and performance of those required to perform safety-critical tasks soon after waking.

sleep inertia↗

Development of Human and Technology Integration Guidance for Work Optimization and Effective Use of Information

Existing nuclear power contributes to roughly 20% of the total electricity generation, and consistently provides the highest capacity factor of any other electricity generating resource in the United States. Despite these advantages, the existing nuclear power plant fleet in the United States has been enduring significant challenges in providing electricity in a cost-competitive manner, which has ultimately threatened the long-term economic viability of these plants. A major contributor to these increased operating and maintenance costs has been the continued reliance of a large workforce who perform their work under an operating model that has largely remained unchanged since the commissioning of these nuclear power plants. Unfortunately, while this operating model has provided safe and reliable electricity, other industries have already began transforming their workforce through the use of advanced digital technology and automation that has reduced their operating and maintenance cost significantly. In order for the United States nuclear industry to remain economically viable, a similar transformation must be considered in which digital technologies and automation capabilities are brought in to support key plant functions across all work functions across plant operation, maintenance, and support. To effectively integrate digital technology and automation in the existing nuclear power plant operating model, a multidisciplinary approach is needed that addresses technological and sociotechnical (i.e., human and technology integration) considerations. This report describes an extension to the human and technology integration methodology, herein referred to as Human Integration and Technology Task Force for Work Management Optimization (HITT), to support the safe, reliable, and efficient use of proposed innovations with the intended users in their intended environment to perform their intended tasks. By effectively incorporating human and technology integration into a plant modernization effort by using HITT, we believe that a utility can significantly improve work performance and overall workforce quality of life. For instance, if HITT is performed to optimize work management, scheduling performance and scope stability can be improved by up to 10%. HITT enables these benefits through developing a rich understanding of the work being performed, the utility’s vision, and the opportunities that provide greatest value to optimize performance through a 10-step process illustrated below as a quick guide. The quick guide contains links in the righthand side of each step that allows for navigation to the detailed section (Section 4) of HITT in this technical report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Digital flight control for the NASA 737 airplane

A brief description of the hardware and software for the digital flight control computers for the NASA 737 airplane is given. Software modules include the basic executive, scheduler, redundancy management, software signal selection, system test, mode logic, pitch axis flight control program and the lateral axis flight control program. A more detailed description of the software development effort is given for the digital flight control software. The software development tasks discussed are: software requirements, development, documentation, control, lab evaluation and formal lab tests. The software development costs are identified and conclusions are drawn concerning the software development effort required to support digital flight control for commercial jet transport applications.

Malcom, L. G.↗

Joint ASI/NASA efforts on tether flight demonstrations

Technological and organizational aspects of joint efforts by NASA and the Italian space agency ASI to develop tethered spacecraft systems are briefly discussed. The members of the ASI/NASA Task Group for Tether Flight Demonstrations are listed; the history of Task Group activities since 1986 is reviewed; and the current status of the main projects is indicated in a series of charts. Particular attention is given to the Tether Initiated Space Recovery System, a 450-lb spacecraft with a 20-km tether scheduled for Space Shuttle or Delta II launch to a 250-km 27.5-deg circular orbit in 1992.

Loria, Alberto↗

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol (Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

Kanefsky, Bob↗