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At least 91 records · Page 5

Probabilistic Survivability Versus Time Modeling

This technical paper documents Kennedy Space Centers Independent Assessment team work completed on three assessments for the Ground Systems Development and Operations (GSDO) Program to assist the Chief Safety and Mission Assurance Officer (CSO) and GSDO management during key programmatic reviews. The assessments provided the GSDO Program with an analysis of how egress time affects the likelihood of astronaut and worker survival during an emergency. For each assessment, the team developed probability distributions for hazard scenarios to address statistical uncertainty, resulting in survivability plots over time. The first assessment developed a mathematical model of probabilistic survivability versus time to reach a safe location using an ideal Emergency Egress System at Launch Complex 39B (LC-39B); the second used the first model to evaluate and compare various egress systems under consideration at LC-39B. The third used a modified LC-39B model to determine if a specific hazard decreased survivability more rapidly than other events during flight hardware processing in Kennedys Vehicle Assembly Building (VAB).Based on the composite survivability versus time graphs from the first two assessments, there was a soft knee in the Figure of Merit graphs at eight minutes (ten minutes after egress ordered). Thus, the graphs illustrated to the decision makers that the final emergency egress design selected should have the capability of transporting the flight crew from the top of LC 39B to a safe location in eight minutes or less. Results for the third assessment were dominated by hazards that were classified as instantaneous in nature (e.g. stacking mishaps) and therefore had no effect on survivability vs time to egress the VAB. VAB emergency scenarios that degraded over time (e.g. fire) produced survivability vs time graphs that were line with aerospace industry norms.

Joyner, James J., Sr.↗

Probabilistic Survivability Versus Time Modeling

This presentation documents Kennedy Space Center's Independent Assessment work completed on three assessments for the Ground Systems Development and Operations (GSDO) Program to assist the Chief Safety and Mission Assurance Officer during key programmatic reviews and provided the GSDO Program with analyses of how egress time affects the likelihood of astronaut and ground worker survival during an emergency. For each assessment, a team developed probability distributions for hazard scenarios to address statistical uncertainty, resulting in survivability plots over time. The first assessment developed a mathematical model of probabilistic survivability versus time to reach a safe location using an ideal Emergency Egress System at Launch Complex 39B (LC-39B); the second used the first model to evaluate and compare various egress systems under consideration at LC-39B. The third used a modified LC-39B model to determine if a specific hazard decreased survivability more rapidly than other events during flight hardware processing in Kennedy's Vehicle Assembly Building.

Operational Hazards↗

Promoting Collaborative Open Science through the Stakeholder Engagement Program

Since 2016, the Satellite Needs Working Group (SNWG), an initiative of the U.S. Group on Earth Observations (USGEO), has surveyed federal agencies biennially to identify their satellite Earth observation needs. Coordinating with the agencies, NASA-led assessment teams work to identify solutions for each expressed need. Solutions to a need can involve existing data products or even the formation of new data products and technologies, such as the Harmonized Landsat Sentinel-2 (HLS) product and the Catalog of Archived Sub-Orbital Earth Science Investigations (CASEI). To enhance community engagement with these new data products and technologies, the SNWG Management Office’s Stakeholder Engagement Program (SEP) was established. The SEP within NASA’s Interagency Implementation and Advanced Concepts Team (IMPACT) at Marshall Space Flight Center has three goals: to increase awareness of the SNWG survey and its outcomes, to ensure training coordination and outreach efforts supporting integration and use of SNWG solutions, and to enhance coordination among solution development teams, NASA’s Distributed Active Archive Centers (DAACs), SNWG stakeholders, and end user communities. These goals align with NASA Earth Science Data System’s (ESDS) Open Science initiative by establishing a collaborative community focused on enhancing scientific research at diverse levels of understanding. This presentation will highlight SEP’s facilitation of these open science goals through its support in SNWG’s past and current survey cycles as well as its plans for future involvement.

Jenny Wood↗

An Overview of Distributed Spacecraft Autonomy at NASA Ames

Autonomous decision-making significantly increases mission effectiveness by mitigating the effects of communication constraints, like latency and bandwidth, and mission complexity on multi-spacecraft operations. To advance the state of the art in autonomous Distributed Space Systems (DSS), the Distributed Spacecraft Autonomy (DSA) team at NASA's Ames Research Center is developing within five relevant technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. DSA is maturing these technologies - critical for future large autonomous DSS - from concept to launch via simulation studies and orbital deployments. A 100-node heterogenous Processor-in-the-Loop (PiL) testbed aids distributed autonomy capability development and verification of multi-spacecraft missions. The DSA software payload deployed to the D-Orbit SCV-004 spacecraft demonstrates multi-agent reconfigurability and reliability as part of an ESA-sponsored in-orbit technology demonstration. Finally, DSA's primary flight mission showcases collaborative resource allocation for multipoint science data collection with four small spacecraft as a payload on NASA's Starling 1.0 satellites.

Caleb Ashmore Adams↗

A Human Factors Approach to Bridging Systems and Introducing New Technologies

The application of human factors in aviation has grown to cover a wide range of disciplines and methods capable of assessing human-systems integration at many levels. For example, at the individual level, pilot workload may be studied while at the team level, coordinated workload distribution may be the focal point. At the organizational level, the way in which individuals and teams are supported by training and standards, policies and procedures may introduce additional, relevant topics. A consideration of human factors at each level contributes to our understanding of successes and failures in pilot performance, but this system focused on the flight deck alone -- is only one part of the airspace system. In the FAA's NextGen plan to overhaul the National Airspace System (NAS), new capabilities will enhance flightdeck systems (pilots), flight operations centers (dispatchers) and air traffic control systems (controllers and air traffic managers). At a minimum, the current roles and responsibilities of these three systems are likely to change. Since increased automation will be central to many of the enhancements, the role of automation is also likely to change. Using NextGen examples, a human factors approach for bridging complex airspace systems will be the main focus of this presentation. It is still crucial to consider the human factors within each system, but the successful implementation of new technologies in the NAS requires an understanding of the collaborations that occur when these systems intersect. This human factors approach to studying collaborative systems begins with detailed task descriptions within each system to establish a baseline of the current operations. The collaborative content and context are delineated through the review of regulatory and advisory materials, letters of agreement, policies, procedures and documented practices. Field observations and interviews also help to fill out the picture. Key collaborative functions across systems are identified and placed on a phase-of-flight timeline including information requirements, decision authority and use of automation, as well as level of frequency and criticality.

Kanki, Barbara G.↗

Advancing Autonomy in Distributed Space Systems: Insights From on-Orbit Testing with the Starling 1.0 Mission

Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.

Caleb Ashmore Adams↗

SISO Space Reference FOM - Tools and Testing

The Simulation Interoperability Standards Organization (SISO) Space Reference Federation Object Model (SpaceFOM) version 1.0 is nearing completion. Earlier papers have described the use of the High Level Architecture (HLA) in Space simulation as well as technical aspects of the SpaceFOM. This paper takes a look at different SpaceFOM tools and how they were used during the development and testing of the standard.The first organizations to develop SpaceFOM-compliant federates for SpaceFOM development and testing were NASA's Johnson Space Center (JSC), the University of Calabria (UNICAL), and Pitch Technologies.JSC is one of NASA's lead centers for human space flight. Much of the core distributed simulation technology development, specifically associated with the SpaceFOM, is done by the NASA Exploration Systems Simulations (NExSyS) team. One of NASA's principal simulation development tools is the Trick Simulation Environment. NASA's NExSyS team has been modifying and using Trick and TrickHLA to help develop and test the SpaceFOM.The System Modeling And Simulation Hub Laboratory (SMASH-Lab) at UNICAL has developed the Simulation Exploration Experience (SEE) HLA Starter kit, that has been used by most SEE teams involved in the distributed simulation of a Moon base. It is particularly useful for the development of federates that are compatible with the SpaceFOM. The HLA Starter Kit is a Java based tool that provides a well-structured framework to simplify the formulation, generation, and execution of SpaceFOM-compliant federates.Pitch Technologies, a company specializing in distributed simulation, is utilizing a number of their existing HLA tools to support development and testing of the SpaceFOM. In addition to the existing tools, Pitch has developed a few SpaceFOM specific federates: Space Master for managing the initialization, execution and pacing of any SpaceFOM federation; EarthEnvironment, a simple Root Reference Publisher; and Space Monitor, a graphical tool for monitoring reference frames and physical entities.Early testing of the SpaceFOM was carried out in the SEE university outreach program, initiated in SISO. Students were given a subset of the FOM, that was later extended. Sample federates were developed and frameworks were developed or adapted to the early FOM versions.As drafts of the standard matured, testing was performed using federates from government, industry, and academia. By mixing federates developed by different teams the standard could be tested with respect to functional correctness, robustness and clarity.These frameworks and federates have been useful when testing and verifying the design of the standard. In addition to this, they have since formed a starting point for developing SpaceFOM-compliant federations in several projects, for example for NASA, ESA as well as SEE.

Möller, Björn↗

Bhutan Agriculture II: Creating a Graphical User Interface, Crop Mask, and Data Collection Protocol for Analysis of Rice Crop in Bhutan Using Remotely Sensed Data

Agriculture is an important sector in Bhutan, accounting for 19.63% of Bhutan’s GDP in 2020 (World Bank) while also providing livelihoods for approximately 57% of the population (World Bank, 2017). The Department of Agriculture (DoA) in Bhutan still relies on in-field reporting for crop monitoring, which is time-consuming and labour intensive. To promote efficiency in these efforts, the team partnered with the DoA, the Bhutan Foundation, and the Ugyen Wangchuck Institute of Conservation and Environmental Research (UWICER). The team, with the help of the science advisors from NASA SERVIR, expanded the crop mask created in the previous term to the whole country of Bhutan and streamlined the sampling protocols for applicability to any available crop data. The team also created a graphical user interface (GUI) which provided a visual representation of current trends and rice distribution across Bhutan. The team utilized NASA Earth observations, including Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), and Shuttle Radar Topography Mission (SRTM), as well as other Earth observations including Sentinel-1 C-band Synthetic Aperture Radar (C-SAR). This project refined the previous term’s methodology to help supplement crop monitoring and increase the frequency of data collected to aid decision-making processes with the use of remote sensing data.

Wangdrak Dorji​↗

De-Energized Line Testing Interface (DELTI) Report

To guarantee the safety of power system operations, it is crucial to understand a de-energized power line’s status before restoring power. It is hypothesized that the Grid Resonance Probe (GRP) and De-Energized Line Testing Interface (DELTI) can be utilized to identify a faulted distribution line. Therefore, the project team is targeting development of a methodology to identify faulted distribution lines by using the DELTI system. In this R&D task, two field tests on Plum Island have been conducted, including DELTI tests with multiple configurations and fault scenarios. This report provides the analysis results of distribution line fault identification from the two field tests. In the remainder of this report, Section 1 is the introduction of the DELTI system, Section 2 provides the analyses of the two field tests in June and October of 2021, respectively, Section 3 discusses the existing line fault detection devices on market and how they compare to DELTI and Section 4 includes the lessons learned and recommendations for future work.

24 POWER TRANSMISSION AND DISTRIBUTION↗

U.S. Department of Energy Solar District Cup Collegiate Design Competition

The Solar District Cup is a multidisciplinary collegiate competition that challenges student teams to design and model standalone solar and solar-plus-storage systems for multiple buildings on a local electrical distribution network, such as a college campus, across a development, or in a district. Students learn cross-cutting skills that prepare them to become part of the next generation of the distributed energy workforce. Student teams act as renewable energy developers proposing to solar and solar-plus-storage system requests. Students, faculty, and prospective employers can benefit from knowing about this program and what students learn--either immediately as participants, mentors, or judges, or as potential employers of Solar District Cup alumni. RE+ is also one of our competition partners.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

CARA Devolution ESMO Pilot Program

Information regarding the current effort ongoing with CARA to determine the steps needed to have a mission move away from being supported by CARA, otherwise referred to as Devolving/Devolution. Information regarding the working group established to undertake this effort, documents agreed that needed to be written and plans for a parallel operations period. The communication between ESMO and CARA during the Parallel Operations period will be as the following: – A daily email will be sent from ESMO to CARA describing each HIE that is being actively planned and worked, and the action that ESMO is planning on taking – A weekly email will be sent from ESMO to CARA listing the progress toward achieving the parallel operations success criteria – The CARA team will remain on distribution for ESMO HIE communications and CAM invitations associated with DAMs/RMMs during the parallel operations period – At a minimum, 2 members of the CARA team will be in attendance at all ESMO planning and review discussions – A monthly email will be sent from ESMO to CARA with the HIE metrics • During parallel operations, ESMO will contact NASA Headquarters to report any redDevolution Working Group laid out and completed all steps needed to begin parallel operations • Parallel Ops for ESMO began on 11/26 (CARA in shadow mode only) • Any lessons learned from parallel ops will be folded back into documents/templates • Hope to achieve all success criteria < 6 months • Decision for permanent devolution will be based on completion of parallel ops and other future documentation creation (CARA Standard and Handbook, etc) and reviews (ORR) event which is less than 2 days from TCA, including the proposed remediation, on an as-needed daily basis flow using SpaceTrack to send and receive data

ESMO pilot devolution program↗

Progress in Scheduling Algorithms for a Collaborative Distributed System for Flight Planning

This Technical Memorandum describes four contributions made by the authors to a larger team effort toward developing a distributed system for scheduling commercial flights at navigation fixes and/or airport runways. These contributions are as follows: (1) a proof of correctness for a scheduling algorithm published previously by Meyn, (2) an improvement of Meyn's algorithm from quadratic to linear time, (3) two independent implementations of the algorithm with test results identical to those published, and (4) an extension of Meyn's algorithm to support minimum usable time intervals.

arrival scheduling↗

The cleanroom case study in the Software Engineering Laboratory: Project description and early analysis

This case study analyzes the application of the cleanroom software development methodology to the development of production software at the NASA/Goddard Space Flight Center. The cleanroom methodology emphasizes human discipline in program verification to produce reliable software products that are right the first time. Preliminary analysis of the cleanroom case study shows that the method can be applied successfully in the FDD environment and may increase staff productivity and product quality. Compared to typical Software Engineering Laboratory (SEL) activities, there is evidence of lower failure rates, a more complete and consistent set of inline code documentation, a different distribution of phase effort activity, and a different growth profile in terms of lines of code developed. The major goals of the study were to: (1) assess the process used in the SEL cleanroom model with respect to team structure, team activities, and effort distribution; (2) analyze the products of the SEL cleanroom model and determine the impact on measures of interest, including reliability, productivity, overall life-cycle cost, and software quality; and (3) analyze the residual products in the application of the SEL cleanroom model, such as fault distribution, error characteristics, system growth, and computer usage.

Green, Scott↗

Autonomous Mission Operations Roadmap

As light time delays increase, the number of such situations in which crew autonomy is the best way to conduct the mission is expected to increase. However, there are significant open questions regarding which functions to allocate to ground and crew as the time delays increase. In situations where the ideal solution is to allocate responsibility to the crew and the vehicle, a second question arises: should the activity be the responsibility of the crew or an automated vehicle function? More specifically, we must answer the following questions: What aspects of mission operation responsibilities (Plan, Train, Fly) should be allocated to ground based or vehicle based planning, monitoring, and control in the presence of significant light-time delay between the vehicle and the Earth?How should the allocated ground based planning, monitoring, and control be distributed across the flight control team and ground system automation? How should the allocated vehicle based planning, monitoring, and control be distributed between the flight crew and onboard system automation?When during the mission should responsibility shift from flight control team to crew or from crew to vehicle, and what should the process of shifting responsibility be as the mission progresses? NASA is developing a roadmap of capabilities for Autonomous Mission Operations for human spaceflight. This presentation will describe the current state of development of this roadmap, with specific attention to in-space inspection tasks that crews might perform with minimum assistance from the ground.

Mission Operations↗

InfraSys (Infrastructure Systems) [SWR-24-42]

This package implements a data store for components and time series in support of Python-based modeling packages. While it is designed to support teams modeling transmission and distribution systems for electrical grids, it can be used by any package that needs to store components (e.g., generators and buses) that have quantities (e.g., power and voltage) which may vary over time. The package was inspired by InfrastructureSystems.jl (https://github.com/NREL-Sienna/InfrastructureSystems.jl).

Thom, Daniel↗

MCNP6.3 Code and Nuclear Data Installation Guide [Slides]

This presentation discusses the MCNP6.3 release package and examines how it offers more MCNP6-specific executables and options available than ever before. It also discusses the installer and that it streamlines the MCNP6.3 installation and automatically downloads all production nuclear data and generates xsdir files for the user. Additionally, the nd_manager is also discussed regarding how it allows the LANL Nuclear Data and Monte Carlo teams to work and distribute their products independently. It also allows updates, fixes (errata), and newly released data to be made available in a much faster timescale than ever before.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Water ingress testing of Pressure Cooker 1006027150 REVAB-021

The requirements of this water ingress test are defined in PA-RD-01009, TA-55 Criticality Safety Requirements. “The container design should be capable of preventing the entry of more than 50 ml water when subjected to water spray at a flow of up to 2 inches water per hour for 2 hours or when immersed in water up to a depth of 6 inches above the top of the container for the same period of time.” The six allen screw fasters on the lid of the container were torqued to approximately 45 inch-pounds with a calibrated torque wrench in a crisscross pattern to ensure equal force distribution. The container management team of ORI-2 has developed a standard practice of gathering 5 data points to increase the statistical confidence in the data. This method has been demonstrated in previous LA-URs and approved official memorandums as follows: LANL Memo, SPE-2: 19-016 dated August 22, 2019; LANL Memo, SPE-2:19-020 dated September 24, 2019; and LA-UR-19-28268, Water Ingress Testing of Commercially Available Containers for the TA-55 Criticality Safety Program.

42 ENGINEERING↗