Neha Sajja and Owen Swischuk Exit Presentation SF3 – Summer 2020
A project overview and walkthrough of the Deep Space Science Vessel (DSSV).
Moon↗
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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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Generation-based Evolutionary Tool for the Optimization of Constellations (GenETOC)
With the rapid growth in the capabilities of smaller satellites, satellite architectures that replace a single, extremely capable spacecraft with multiple, cheaper ones are gaining in popularity. Unfortunately, the orbit design process for constellations can be significantly more involved, especiallywhen the relative placement of the individual spacecraft within the constellation is not constrained by mission and/or science objectives. Optimizing a satellite constellation in the presence of multiple, competing objectives is a highly complex problem to which many traditional mathematical optimization methods cannot be applied and few tools exist to help mission designers search for promising candidate mission designs. The Generation-based Evolutionary Tool for the Optimization of Constellations (GenETOC) has been created to search for near-optimal constellation design options. GenETOC combines a modified version of the Non-dominated Sorting Genetic Algorithm II (NSGA II) with STK Components libraries (a 3rdparty .NET package created by Analytical Graphics Inc.) to create a framework that enables a mission designer to generate a simulation that models the design problem and obtain a family of potential, near-optimal solutions that can be investigated more in detail. GenETOC was developed in C# using the .NET framework with Windows Presentation Foundation (WPF) serving as the framework from which to create the graphical user interface (GUI). GenETOC user inputs can be categorized into three major data components: definition of the problem (areas of interest, satellite decision parameters, and sensor configurations), definition of performance objectives, and specification of the genetic algorithm (GA) parameters. In the problem definition component, the user is prompted to define the areas of interest against which the performance metrics will be computed, define the sensor parameters and attach them to specific spacecraft, select which satellite orbital parameters will be added to the decision space of the GA, and specify the range of desired values for each optimization parameter. For performance objectives, the user is presented with a list of available coverage and revisit performance based calculation options from which two metrics are chosen to serve as the objective functions that the GA will use to evaluate solutions during the optimization process. Finally, the definition of the GA parameters provides user control over the number of generations (number of optimization iterations), the population size (number of candidate constellations created in each generation), and the adaptive mutation and crossover threshold values (control parameters for how frequently each process occurs during the optimization). GenETOC has been extensively tested to verify the individual components of the optimization process. The GA has been tested against a suite of GA test problems to confirm convergence to the known two and three-dimensional Pareto fronts. The coverage and revisit performance metrics obtained in GenETOC are compared with STK desktop scenarios, confirming the constellations are being appropriately modeled within GenETOC simulations. A walkthrough of a simple, example problem is provided to illustrate the workings of GenETOC and to demonstrate the output available to the mission designer.
mission design↗
Europa Clipper Thermal Control Design
This paper details the design developments of the Europa Clipper spacecraft thermal control system and its primary element the Heat Redistribution System (HRS). The Europa Clipper spacecraft will launch in the early 2020s and will have multiple flybys of Jupiter’s icy moon, Europa. The HRS, which utilizes a Mechanically Pumped Fluid Loop (MPFL) to reclaim waste heat from an avionics vault module and redistribute it to the propulsion module and radiator, has become an integral part of the spacecraft architecture both in terms of mechanical configuration and spacecraft operations capability. A walkthrough on the planned implementation of the HRS on the primary spacecraft modules is provided along with a description on thermal control of spacecraft hardware not located on the HRS vault, where thermal isolation and tolerance to extreme thermal environment drives the hardware designs.
Bhandari, Pradeep↗
Rapid Assessment of a Lunar Surface Laboratory Module
Johnson Space Center is piloting an innovation team known as the Forge to perform rapid turnaround, concurrent engineering studies. The Forge is intended to be able to pull together a team of strategically selected domain experts to innovatively solve a specified problem within a short period of time. The Forge’s inaugural project being the development of a Lunar Surface Laboratory Module concept. The lab module is intended as an option for the Artemis program’s Lunar Architecture Team. The lab module may allow for increased science productivity and return on investment than a surface architecture with only the habitat. This paper will discuss the configuration of the Lunar Laboratory module, including the pressure vessel, its placement relative to the Surface Habitat and Pressurized Rover, and internal architecture. In order to determine the suitability of such a design, a human factors evaluation is conducted. Historically, a human factors evaluation of a habitable volume could require a month or longer, including time needed to prepare a test plan, conduct the evaluation, compile the data, and produce a report. The entire Forge effort will only last for five weeks, forcing the creation of a rapid assessment process. This rapid assessment includes three evaluation studies, all conducted and processed in the space of a single day, to determine the acceptability of the resulting design. The first evaluation is a card sort evaluation of the laboratory instruments. A brief discussion of the card sort evaluation is provided. This card sort is focused on the relative positioning of the laboratory instruments, determining whether a given instrument should be adjacent to, or separated from, another. It will use human factors personnel and both life and physical scientists as subject matter experts. The second evaluation is a science productivity tabletop evaluation. This evaluation focuses on the selection of instruments and the number of instruments, attempting to assess the amount of work the crew will be able to use the facility to do. It uses life and physical science personnel as subject matter experts. The third evaluation is a CAD or Virtual Reality human factors walkthrough evaluation. This evaluation focuses on the layout of the lab module and its connectivity to the basecamp’s pressurized elements. If possible, astronauts will be used as subject matter experts. Each of these evaluations will focus primarily on objective data with limited subjective comments, reducing the time required for processing responses. The results of each evaluation and their implications will be discussed. Based on the evaluation data, an overall acceptability of the Lunar Surface Laboratory Module produced by the Forge study can be determined. Lessons learned and recommendations for future use of the human factors rapid assessment process in early design trades will also be provided.
Lunar Laboratory↗
Initial Exploration of STEReO (Scalable Traffic management for Emergency Response Operations) system user requirements for safe integration of small UAS
Environment-based disasters, such as wildfire, can cause substantial loss of life and loss of property and are costing billions of dollars annually. Existing disaster response operations are complex, with many challenges. The aim of the Scalable Traffic management for Emergency Response Operations (STEReO) system is to demonstrate the application of technologies that will enable small, low-altitude Unmanned Aerial System operations to safely take place in the airspace above a disaster event, increasing the effectiveness of the response. As a first step, the project aims to build a small prototype to demonstrate and test the core functions of this system based on user needs and requirements that were gathered from experts in the field during discussions and walkthroughs.
STEReO↗
Developing an Unmanned Aircraft System Pilot (UASP-kit) for Wildland Fire UAS Operators
The use of unmanned aircraft systems (UAS) to support disaster management is becoming more widespread. Uninhibited by many of the operational constraints imposed on crewed aircraft, UAS have the potential to augment the aerial response in a number of ways, including supporting situation awareness, thereby accelerating disaster management efforts. The intent of the Scalable Traffic management for Emergency Response Operations (STEReO) activity is to build an ecosystem that will allow small UAS (sUAS) operations to fly safely in the airspace during disaster management events. The first step toward this goal is to develop a small, single-user tool (the UASP-kit) that will enhance an sUAS pilot’s situation awareness of the airspace. User needs for the functions and features of this tool were collected during a walkthrough over multiple days with subject matter experts from the US Forest Service. A prototype of the UASP-kit was then taken on an extended demonstration to multiple users, who were able to interact with it. User feedback was largely positive and users discussed the information they needed to support situation awareness in context. The demonstration also highlighted features that were unintuitive to use, and functions that need to be modified to make the kit more user-friendly and robust.
STEReO↗
Developing an Unmanned Aircraft System Pilot Kit (UASP-kit) for Wildland Fire UAS Operators
The use of unmanned aircraft systems (UAS) to support disaster management is becoming more widespread. Uninhibited by many of the operational constraints imposed on crewed aircraft, UAS have the potential to augment the aerial response in a number of ways, including supporting situation awareness, thereby accelerating disaster management efforts. The intent of the Scalable Traffic management for Emergency Response Operations (STEReO) activity is to build an ecosystem that will allow small UAS (sUAS) operations to fly safely in the airspace during disaster management events. The first step toward this goal is to develop a small, single-user tool (the UASP-kit) that will enhance an sUAS pilot’s situation awareness of the airspace. User needs for the functions and features of this tool were collected during a walkthrough over multiple days with subject matter experts from the US Forest Service. A prototype of the UASP-kit was then taken on an extended demonstration to multiple users, who were able to interact with it. User feedback was largely positive and users discussed the information they needed to support situation awareness in context. The demonstration also highlighted features that were unintuitive to use, and functions that need to be modified to make the kit more user-friendly and robust.
STEReO↗
Human-Autonomy Teaming Research in Support of m:N Operations
Since 2019, the NASA and industry partners have been involved in research focused on a novel paradigm for operations of remotely piloted aircraft. This paradigm involves multiple people sharing a fleet of multiple vehicles between them. Referred to as m:N (pronounced “em-to-en”), this configuration describes a ratio where m is the number of operators and N is the number of vehicles. Through force and asset multiplication, the m:N concept seeks to enable a scalable and resilient operation of remotely crewed vehicles. The primary means of obtaining such a robust operation is through allowing a flexible crew of variable size to dynamically attend to the needs of assets in while performing real-time operator workload management. It is in that sense that assets are shared between operators: as needed (such as in events of elevated workload) an operator in an m:N context can “handoff” the responsibility for some amount of assets, nh < N, to be absorbed by the m – 1 crew members on staff. At some time later, these nh assets could be returned to their original owner or they may be further distributed to other crew if called for by the mission. During this panel, I will elaborate on the research activity undertaken by the Human-Autonomy Teaming (HAT) Laboratory at NASA Ames Research Center over the previous three years. The studies conducted by the HAT Lab range from interviews with subject matter experts, a cognitive walkthrough, a task analysis, and two simulation experiments to-date. During experimentation, pilots made use of an advanced Ground Control Station developed by the HAT Lab and industry partners to simulate m:N operations in two large, metropolitan areas of Southern California: Los Angeles and San Diego. Further experimentation planned over the next few years. Results from our research to-date indicates that pilots of a moderately sized fleet of about a dozen remotely crewed aircraft adequately maintained safety performance and situation awareness of their aircraft, even when presented with unexpected situations of heightened workload.
multi-vehicle control↗
Roadmap to Cooperative Operating Practices for Strategic Conflict Detection and Resolution in the Upper Class-E Traffic Management Concept
As the governing body of flight operations in the highly anticipated emergent area of Upper Class E airspace (60,000 ft and above), the Federal Aviation Administration (FAA) has recognized the potential for a possible extensible traffic management system for new entrants into this domain. Following the successes with Unmanned Aircraft Systems (UAS) Traffic Management (UTM) and Advanced / Urban Air Mobility (AAM / UAM) Traffic Management programs, FAA put forth an initial concept of operations for supporting the start of the Upper Class E Traffic Management (ETM) concept. Like UTM and AAM / UAM, ETM is envisioned to also be a community-based, industry driven cooperative management concept. However, tailoring it to be adaptable to the atmospheric communication, navigation, and surveillance deficits, as well as the diverse vehicle and mission profiles operating in the ETM environment will be the challenge. As such, the National Aeronautics and Space Administration (NASA) Ames Research Center has been investigating several technologies that will help enable industry in the development of this new type of cooperative operating environment. These technologies are being prototyped and will be tested in a collaborative evaluation of an initial ETM system in late 2023. The evaluation will concentrate on building out ETM system technologies that will inform the participants regarding operational intent sharing, strategic conflict detection, and the resultant deconfliction process. In addition to the technical aspects, key roles and responsibilities will need to be defined. This will be done through exploring community-agreed upon Cooperative Operating Practices (COPs) that include procedures and capabilities to aid in timely, strategic conflict identification and resolution to be developed during the evaluation. As an initial step to the evaluation, the ETM research team at NASA Ames solicited industry feedback on various aspects of ETM operations from subject matter experts. A virtual tabletop walkthrough session was held over a two-day period to follow a roadmap through the functional steps needed to build COPs, focusing on strategic conflict detection and resolution. Overall, the ETM tabletop provided insights into how the community wanted to instantiate the generation and sharing of operational intent, detect strategic conflicts and resolve those conflicts using a preliminary set of procedural community-agreed upon COPs.
Upper Class-E Traffic Management (ETM)↗
Roadmap to Cooperative Operating Practices for Strategic Conflict Detection and Resolution in the Upper Class E Traffic Management Concept
As the governing body of flight operations in the highly anticipated emergent area of Upper Class E airspace (60,000 ft and above), the Federal Aviation Administration (FAA) has recognized the potential for a possible extensible traffic management system for new entrants into this domain. Following the successes with Unmanned Aircraft Systems (UAS) Traffic Management (UTM) and Advanced / Urban Air Mobility (AAM / UAM) Traffic Management programs, FAA put forth an initial concept of operations for supporting the start of the Upper Class E Traffic Management (ETM) concept. Like UTM and AAM / UAM, ETM is envisioned to also be a community-based, industry driven cooperative management concept. However, tailoring it to be adaptable to the atmospheric communication, navigation, and surveillance deficits, as well as the diverse vehicle and mission profiles operating in the ETM environment will be the challenge. As such, the National Aeronautics and Space Administration (NASA) Ames Research Center has been investigating several technologies that will help enable industry in the development of this new type of cooperative operating environment. These technologies are being prototyped and will be tested in a collaborative evaluation of an initial ETM system in late 2023. The evaluation will concentrate on building out ETM system technologies that will inform the participants regarding operational intent sharing, strategic conflict detection, and the resultant deconfliction process. In addition to the technical aspects, key roles and responsibilities will need to be defined. This will be done through exploring community-agreed upon Cooperative Operating Practices (COPs) that include procedures and capabilities to aid in timely, strategic conflict identification and resolution to be developed during the evaluation. As an initial step to the evaluation, the ETM research team at NASA Ames solicited industry feedback on various aspects of ETM operations from subject matter experts. A virtual tabletop walkthrough session was held over a two-day period to follow a roadmap through the functional steps needed to build COPs, focusing on strategic conflict detection and resolution.
Upper Class E Traffic Management (ETM)↗
Freddie Software Security Patching
Software applications become more complicated over time as they depend on many third-party, open-source libraries. The Freddie Platform Services team actively improves software security by addressing software bugs and vulnerabilities that negatively impact software applications, especially those providing real-time operations and services for the federal partners and industries. In order to detect bugs and patch vulnerabilities in software development and maintenance cycles, an automated and systematic approach is needed. This document describes what bugs and vulnerabilities are, and how they can be detected by using static code analyzers and software composition analysis tools. Once vulnerabilities are detected, the patching approaches, such as upgrading direct and transitive dependencies and loading custom classes first, are presented together with their strengths and weaknesses. In addition, patching walkthrough, example code, lessons learned throughout the vulnerability patching process and the recommended practices are discussed.
Chok Fung Lai↗
Introduction to the Glenn Icing Computational Environment (GlennICE)
The NASA John H. Glenn Research Center at Lewis Field is developing the Glenn Icing Computational Environment (GlennICE) tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This short course will walk through some of the underlying physics involved with GlennICE and how we achieve efficient 3D ice accretion predictions. After an introduction of GlennICE, an analysis of the Common Research Model High-Lift will be demonstrated to showcase the typical workflow for an aircraft icing analysis. Within this walkthrough, capabilities will be highlighted with future planned capabilities being discussed. Finally, we will showcase the impact GlennICE is having on NASA’s icing portfolio and how it is advancing aircraft icing research and safety.
Icing↗
Supervisory Control with Dual Tasking in Post G-Transition Vehicle Landings
BACKGROUND Landing during exploration spaceflight may consist of both planned automated supervisory control and unplanned crew override. Supervisory control, particularly when performed under cognitive load with additional monitoring tasks, is essential for ensuring overall mission success during landing contingencies. Evaluating performance in a relevant Human Landing System (HLS) supervisory landing task after long-duration microgravity exposure can help identify potential risks from human error and sensorimotor alterations. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. Although training and landing aids facilitate successful landings despite disorientation, these adaptive changes may heighten cognitive demand, which must be considered in the landing strategy. It is important to characterize these effects as soon as possible following the G-transition while the sensorimotor system remains in a state of adaptive flux to inform appropriate countermeasures. METHODS A Multi-attribute Lunar Table Battery (MALTB) task was developed for an iOS tablet device to provide flexible crew testing and training capabilities in-flight and on the ground. Elements of the tablet task were derived from the Multi-Attribute Task Battery (MATB, Cegarra et al. 2020). The task requires crew members to study a map of a planned landing site and memorizing the terrain and surface landmarks to inform potential divert maneuvers during landing. The user will oversee a series of approaches through touchdown simulations on the tablet with an external camera view of the Lunar surface. The primary responsibility of the crew member will be to execute a divert if the guidance recommended site is erroneous (e.g., the guidance projected landing target is not within 10m of the planned landing site center), or the projected landing site is no longer suitable due to surface obstacles. Considering vehicle maneuverability and fuel reserves, the divert capabilities will diminish as the task progresses. In cases where a divert is initiated, a new landing target will need to be designated by the user and will be evaluated for the proximity to the original pre-planned site. A secondary operational monitoring task will challenge the user's cognitive reserve by requiring the user to maintain several gauges within acceptable limits and respond to a visual indicator while completing the landing approach. Outcome measures include distance from the planned landing site to the user-initiate divert landing location, ground slope at the new landing site, time to divert, the ability to accomplish the secondary monitoring tasks, and perceived workload. The tablet task is being evaluated in a ground-based study to determine the learning effect of first-time users. The tablet task will be utilized in a flight study to test performance multiple times postflight. Future potential testing in-flight have been identified for capsules with iOS tablet devices. Multi-attribute Lunar Table Battery Task MALTB comprises video footage of thirty distinct landing conditions. The landing scenarios feature various landing sites (n = 3), hazardous object sizes (n = 6), sun azimuth degrees (n = 4), camera modes (i.e., fixed or gimbaled), and navigation bias (i.e., true or false). Each seventy second trial uses a sixty-degree constant glideslope trajectory. The application architecture and layout include user identification setup and data storing, a guided walkthrough of the task and interface components, practice mode for task familiarization, and a modified Bedford workload scale administered following task completion. The time-based dependent measures are saved locally to the iOS Files application and post-processing scripts have been developed to evaluate the remaining measures of performance. RELEVANCE This project will deliver an operational demonstration of crew monitoring capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew performance will help better characterize the landing risks associated with sensorimotor alterations. ACKNOWLEDGEMENTS: This project is funded by NASA’s Human Research Program Human Health Countermeasures Element. REFERENCES Cegarra J, Valery B, Avril E, Calmettes C, Navarro J (2020) OpenMATB: A Multi-Attribute Task Battery promoting task customization, software extensibility and experiment replicability. Behav Res Methods 52:1980-1990 doi: 10.3758/s13428-020-01364-w
Matthew McDonnell↗
Interface Consistency: Phase I Results & Phase II Status
Future exploration missions will rely on designing and developing vehicles and complex systems from within NASA and through multiple external commercial partners to meet mission goals. Despite existing consistency-related agency requirements, NASA’s approach to commercial spaceflight development encourages providers’ flexibility and innovation. This strategy is resulting in significant design diversity across Artemis vehicles. Design best practices and guidelines champion interface consistency to promote mental model development and knowledge transfer. However, research investigating the benefits of consistency is mixed, and little is known about its role in complex systems. Determining the level of risk that system diversity presents is difficult, as there is no established method for quantifying the degree of consistency within and across interfaces, nor is there information about the differential impacts of different types of inconsistency. Phase I of this project (Characterization and Measurement) served as a starting point to better understand the construct of consistency, its application, and the range of studies and methods for measuring it. The project team created a taxonomy of consistency to apply to interfaces as a framework to guide the development of tools to assess intersystem consistency. Checklist and cognitive walkthrough methods were developed for use by human factors (HF) and human-computer interaction (HCI) experts. The Intersystem Consistency Scale (ICS) was developed for interface evaluations with crew. A pilot study evaluated the methods’ ability to distinguish differences between Artemis-like prototype pairs exhibiting either high or low design consistency. In addition, click errors and time on task were collected within the ICS (crew-like) group. Results from our exploratory analysis and lessons learned from the pilot study will be discussed. The project team will also present the status of Phase II (Risk Assessment, Standards and Guidelines). This includes incorporating feedback to redesign the assessment tools, and inputs from displays and training Subject Matter Experts to update tasks and prototype designs. The team will present the risk assessment study design to identify the types and levels of inconsistency that pose the greatest risk to performance. Plans to apply these results toward agency standards and guideline recommendations will also be discussed.
Human-Computer Interaction↗
Thermal Analysis on Large Format Lithium-Ion Batteries in Thermal Runaway
Lithium-ion (Li-ion) batteries can deliver electrical power across a large range of applications, and large format versions of these batteries are common in aerospace for their low mass and energy dense properties. Li-ion cells usage has increased as they are more power dense than fuel cells and have overall higher performance over lead-acid/NiCd batteries. However, Li-ion cells can experience Thermal Runaway (TR) via electro-chemical, mechanical, or thermal abuse. TR is a phenomenon where the stored energy in a cell is rapidly released along with vented gases and other effluents. A cell is generally determined to be in TR if its internal heat generation has surpassed its ability to dissipate that heat. If a Li-ion cell enters TR, propagation within the battery may occur. Propagation is the chain reaction that can occur to nearby cells due to a cell that has entered TR initially. Understanding a battery’s susceptiveness to propagation is necessary to evaluate risks associated with TR phenomenon. To determine if a battery is designed in a sufficient manner to prevent battery propagation if single cell TR occurs, testing and thermal analysis of the battery must be conducted. The presentation for TFAWS 2026 will cover considerations for battery TR thermal analysis, such as: testing methods, influences on the cells, failure mechanisms, and TR parameters. This presentation will include a walkthrough of an example battery TR thermal analysis, and the results thereof.
Lithium Ion Batteries↗