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Predictive Model for Workload in Remote Operators During sUAS Contingency Scenarios
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Effect of Carbon Dioxide Exposure on Physical and Cognitive Performance in a Simulated Spaceflight Contingency Scenario: “Co2 Walk Back”
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Development of Space Shuttle Rescue and Recovery Operations
As the first Space Shuttle launch was still in our future, many from NASA, the Department of Defense (DoD) and NASA contractors were busy planning for not only a nominal launch and return, but contingency operations at the launch pad and landing sites. Prior to the first launch, detailed coordination, planning and simulations were conducted at all three locations and internal rescue procedures were taught at Kennedy Space Center (KSC). Later in the Program, the Transoceanic Abort Landing (TAL) sites were added in Europe and Africa. For the 51L mission a new TAL site was brought on line in Morocco. However, upon launch, the Shuttle Program experienced it's first lost. During the following months a complete review of all contingency operations (launch and landing) was completed. Many enhancements were made based on the reviews following. A Mode VIII water rescue was developed for NASA by the DoD before the STS-26 launch. Different concepts were explored and being debated by NASA. Training of the contingency forces was required before final decisions were made forcing the teaching of two different sets of procedures. To assist with training, a video was developed for the fire/crash/rescue personnel. This accompanied the detailed extraction procedures that were developed by a combination of KSC and DoD firemen. Training for the fire/crash/rescue personnel at Vandenberg AFB was also being planned before the accident happen. The fire/crash/rescue mockup that was being built at Chanute AFB was diverted to Edwards AFB. Educational Objectives: With the emphasis on Commercial Crew Programs for Space flight it is important that all involved understand what is required to prepare for contingencies. Cost effective means of being prepared for contingencies are needed. Questions: 1. When should planning for nominal and contingency operations begin? 2. What type of training aids are needed for contingency operations? 3. Who were the major contributors to Shuttle contingency operations?
Next-Generation Evaporative Cooling Systems for the Advanced Extravehicular Mobility Unit Portable Life Support System
The development of the Advanced Extravehicular Mobility Unit (AEMU) Portable Life Support System (PLSS) is currently underway at NASA Johnson Space Center. The AEMU PLSS features two new evaporative cooling systems, the Reduced Volume Prototype Spacesuit Water Membrane Evaporator (RVP SWME), and the Auxiliary Cooling Loop (ACL). The RVP SWME is the third generation of hollow fiber SWME hardware, and like its predecessors, RVP SWME provides nominal crewmember and electronics cooling by flowing water through porous hollow fibers. Water vapor escapes through the hollow fiber pores, thereby cooling the liquid water that remains inside of the fibers. This cooled water is then recirculated to remove heat from the crewmember and PLSS electronics. Major design improvements, including a 36% reduction in volume, reduced weight, and more flight like back-pressure valve, facilitate the packaging of RVP SWME in the AEMU PLSS envelope. In addition to the RVP SWME, the Auxiliary Cooling Loop (ACL), was developed for contingency crewmember cooling. The ACL is a completely redundant, independent cooling system that consists of a small evaporative cooler--the Mini Membrane Evaporator (Mini-ME), independent pump, independent feed-water assembly and independent Liquid Cooling Garment (LCG). The Mini-ME utilizes the same hollow fiber technology featured in the RVP SWME, but is only 25% of the size of RVP SWME, providing only the necessary crewmember cooling in a contingency situation. The ACL provides a number of benefits when compared with the current EMU PLSS contingency cooling technology; contingency crewmember cooling can be provided for a longer period of time, more contingency situations can be accounted for, no reliance on a Secondary Oxygen Vessel (SOV) for contingency cooling--thereby allowing a SOV reduction in size and pressure, and the ACL can be recharged-allowing the AEMU PLSS to be reused, even after a contingency event. The development of these evaporative cooling systems will contribute to a more robust and comprehensive AEMU PLSS.
Streamlining Tactical Operator Handoffs During Multi-Vehicle Applications
Increased automation has shifted the operator control paradigm from a single operator controlling a single vehicle, to multiple operators collaborating to control multiple vehicles; this paradigm is known as m:N. Many questions remain unanswered in this new operational paradigm about the division of assets as workload for individual operators varies overtime. This paper explores the management of workload by enabling operators to temporarily handoff vehicles among each other. A study was conducted to explore both a manual and assisted method for performing handoffs during manipulated contingency scenarios. The assisted handoff method allowed subjects to easily choose and group nominal and/or contingency vehicles. The number of contingencies was also manipulated to determine the effect workload had on how pilots utilized the ability to handoff vehicles. Results show subjects performed handoffs more often when there were more contingencies and when the assisted handoff tool was available. In addition, the assisted tool make subjects feel more comfortable, enabling them to feel like they could take longer to resolve contingency situations. Lastly, even during contingencies, subjects were able to successfully complete secondary tasks.
Streamlining Tactical Operator Handoffs During Multi-Vehicle Operations
Increased automation has shifted the operator control paradigm from a single operator controlling a single vehicle, to multiple operators collaborating to control multiple vehicles; this paradigm is known as m:N. Many questions remain unanswered in this new operational paradigm about the division of assets as workload for individual operators varies over time. This paper explores the management of workload by enabling operators to temporarily handoff vehicles among each other. A study was conducted to explore both a manual and assisted method for performing handoffs during manipulated contingency scenarios. The assisted handoff method allowed subjects to easily choose and group nominal and/or contingency vehicles. The number of contingencies was also manipulated to determine the effect workload had on how pilots utilized the ability to handoff vehicles. Results show subjects performed handoffs more often when there were more contingencies and when the assisted handoff tool was available. In addition, the assisted tool made subjects feel more comfortable, enabling them to feel like they could take longer to resolve contingency situations. Lastly, even during contingencies, subjects were able to successfully complete secondary tasks.
Safety Assessment of Conformance Monitoring for Situational Awareness in UTM Operations
This report presents a systematic approach to evaluating the safety benefit of utilizing strategic deconfliction and Conformance Monitoring for Situational Awareness to manage the traffic that is comprised of both conforming aircraft and contingent aircraft. First, we developed a Monte-Carlo-based simulation platform that generates a range of nominal flight paths, a set of flight paths associated with contingent aircraft, encounters between conforming and contingent aircraft, and simulates aircraft's reported positions within conformance bounds. Next, we derived the mathematical equations for quantifying the level of safety, represented by the probability of mid-air collision per flight hour, using the flight data from the simulation platform. Finally, we compared the safety benefit of CMSA services in scenarios generated at different traffic densities and rates of contingent aircraft. This study suggests that strategic deconfliction and CMSA services can collaboratively handle traffic mixed with conforming and contingent aircraft more safely than strategic deconfliction alone.
An Onboard ISS Virtual Reality Trainer
Prior to the retirement of the Space Shuttle, many exterior repairs on the International Space Station (ISS) were carried out by shuttle astronauts, trained on the ground and flown to the station to perform these repairs. After the retirement of the shuttle, this is no longer an available option. As such, the need for the ISS crew members to review scenarios while on flight, either for tasks they already trained or for contingency operations has become a very critical subject. In many situations, the time between the last session of Neutral Buoyancy Laboratory (NBL) training and an Extravehicular Activity (EVA) task might be 6 to 8 months. In order to help with training for contingency repairs and to maintain EVA proficiency while on flight, the Johnson Space Center Virtual Reality Lab (VRLab) designed an onboard immersive ISS Virtual Reality Trainer (VRT), incorporating a unique optical system and making use of the already successful Dynamic Onboard Ubiquitous Graphical (DOUG) graphics software, to assist crew members with current procedures and contingency EVAs while on flight. The VRT provides an immersive environment similar to the one experienced at the VRLab crew training facility at NASA Johnson Space Center. EVA tasks are critical for a mission since as time passes the crew members may lose proficiency on previously trained tasks. In addition, there is an increased need for unplanned contingency repairs to fix problems arising as the ISS ages. The need to train and re-train crew members for EVAs and contingency scenarios is crucial and extremely demanding. ISS crew members are now asked to perform EVA tasks for which they have not been trained and potentially have never seen before.
An Onboard ISS Virtual Reality Trainer
Prior to the retirement of the Space Shuttle, many exterior repairs on the International Space Station (ISS) were carried out by shuttle astronauts, trained on the ground and flown to the Station to perform these specific repairs. With the retirement of the shuttle, this is no longer an available option. As such, the need for ISS crew members to review scenarios while on flight, either for tasks they already trained for on the ground or for contingency operations has become a very critical issue. NASA astronauts prepare for Extra-Vehicular Activities (EVA) or Spacewalks through numerous training media, such as: self-study, part task training, underwater training in the Neutral Buoyancy Laboratory (NBL), hands-on hardware reviews and training at the Virtual Reality Laboratory (VRLab). In many situations, the time between the last session of a training and an EVA task might be 6 to 8 months. EVA tasks are critical for a mission and as time passes the crew members may lose proficiency on previously trained tasks and their options to refresh or learn a new skill while on flight are limited to reading training materials and watching videos. In addition, there is an increased need for unplanned contingency repairs to fix problems arising as the Station ages. In order to help the ISS crew members maintain EVA proficiency or train for contingency repairs during their mission, the Johnson Space Center's VRLab designed an immersive ISS Virtual Reality Trainer (VRT). The VRT incorporates a unique optical system that makes use of the already successful Dynamic On-board Ubiquitous Graphics (DOUG) software to assist crew members with procedure reviews and contingency EVAs while on board the Station. The need to train and re-train crew members for EVAs and contingency scenarios is crucial and extremely demanding. ISS crew members are now asked to perform EVA tasks for which they have not been trained and potentially have never seen before. The Virtual Reality Trainer (VRT) provides an immersive 3D environment similar to the one experienced at the VRLab crew training facility at the NASA Johnson Space Center. VRT bridges the gap by allowing crew members to experience an interactive, 3D environment to reinforce skills already learned and to explore new work sites and repair procedures outside the Station.
HydraGNN_OPF_GFM_2026 - Ensemble of predictive graph foundation models for power grid applications
This dataset supports research on graph foundation models for optimal power flow (OPF) on electric grids using HydraGNN. It contains heterogeneous graph representations of PGLib-OPF cases spanning systems from 14 to 13,659 buses, together with packed HDF5 datasets for pretraining, feasibility classification, and N-1 contingency analysis. The release includes OPF solution data, downstream fine-tuning datasets, pretrained HeteroSAGE and HeteroHEAT model checkpoints, hyperparameter-optimization summaries across multiple heterogeneous GNN architectures, and aggregated fine-tuning results for sample-efficiency studies. The dataset is designed to enable scalable training, evaluation, and transfer-learning studies for OPF surrogate modeling, including node-level AC-OPF solution prediction, graph-level prediction, feasibility classification, operating-condition generalization, and contingency-response tasks.
The Earth Science Afternoon Constellation: Preparing for Autonomous but Coordinated Operations
This paper describes how the challenges of coordinating the autonomous operations of geographically dispersed mission control centers for several small and large satellites are being overcome. The Earth Science Afternoon Constellation, also referred to as the "A-Train", is an international grouping of five NASA satellites (two major NASA EOS missions and three NASA/Earth System Science Pathfinder missions) and one French satellite orbiting in close proximity. This grouping of satellites provides scientists with the opportunity to perform coincident observations using data from two or more instruments on various satellites with measurements taken at approximately the same time. Three of the six missions are currently on-orbit, with the two missions expected to join the constellation later this year and one mission in 2007. The operational challenges are daunting for several reasons. There are several Mission Control Centers (widely separated on two continents), operating autonomously under tight budget constraints. All of the Mission Control Centers have reasons to be concerned about safety while flying in close proximity to other satellites, but most Centers did not have the resources or the desire to address this concern alone - the interfaces are too numerous and anticipated operations too costly. Clearly, an efficient approach was needed. This paper describes the steps taken to make this Earth science constellation a reality. Agreements were forged to allow the Mission Control Centers to maintain their autonomy, while ensuring their satellite's safety. Each member mission in the constellation operates independently in accordance with its own mission requirements, but the member missions have agreed to coordinate their operations, i.e., orbital positions and control to ensure the safety of the entire constellation. A centralized system was developed at NASA Goddard Space Flight Center to collect, analyze, and distribute ephemeris data used by each of the mission teams to determine the positions of the satellites in the constellation. The system issues warnings regarding possible dangerous configurations, eliminating the need for redundant capabilities at each Mission Control Center. On-orbit contingency situations were identified and analyzed; agreements were reached in advance of contingency operations to ensure that coordination between the Mission Control Centers can be handled expeditiously and fairly. In this manner, recovery from anomalous situations can be more quickly realized, thereby increasing the science return and reducing costs. The process used to develop these contingency procedures and the systems used to facilitate the contingency resolution are described as well.
The Interaction of the Space Shuttle Launch and Entry Suits and Sustained Weightless on Astronaut Egress Locomotion
The purpose of this study was to determine the consequences of extended periods of weightlessness during space missions on astronauts f ability to perform a simulated contingency egress while wearing either of the Launch and Entry suits immediately after space flight. In our previous lab-based study of simulated contingency egress, we found only 4 of 12 non-astronauts wearing the Launch and Entry Suit (LES) successfully completed the simulated egress. However, 4 of 4 of the previous failures (when tested wearing the LES), were then successful in completing the test wearing the Advanced Crew Escape Suit (ACES). Therefore, this study tested 21 Astronaut Volunteers wearing either the LES or ACES while performing a simulated egress on a treadmill (TM) onboard the Crew Transportation Vehicle immediately after space flight at either the Kennedy Space Center or Edwards AFB. Astronauts walked for 400 meters at 1.6m/sec with g-suit inflation level set to preflight testing levels, visor down, breathing from the suit emergency O2 supply. Metabolic, heartrate, and perceived exertion data were collected during these post-flight tests. Exactly the same preflight simulated egress tests on a TM were performed in the lab at NASA/JSC by each crewmember at L-60. Preflight testing found 2 of the 21 crewmembers were unable to complete the simulated contingency egress. Postflight, 9 crew (8 ACES, 1 LES) completed the simulated contingency egress of 400 meters at 1.6m/sec. and 12 failed to meet that standard (7 ACES, 5 LES). Preflight physiological response tests failed to identify crew capable of performing the egress vs. those who failed. However, 18 of the 21 crew did make at least 2.67 minutes into the postflight egress testing. At that point in time, heartrate was higher (P <=.20) for the failures compared to the finishers. These findings indicate that NASA fs switch to the ACES for space flight crews should be expedited.
Analysis Method for Non-Nominal First Acquisition
First this paper describes a method how the trajectory of the launcher can be modelled for the contingency analysis without having much information about the launch vehicle itself. From a dense sequence of state vectors a velocity profile is derived which is sufficiently accurate to enable the Flight Dynamics Team to integrate parts of the launcher trajectory on its own and to simulate contingency cases by modifying the velocity profile. Then the paper focuses on the thorough visibility analysis which has to follow the contingency case or burn performance simulations. In the ideal case it is possible to identify a ground station which is able to acquire the satellite independent from the burn performance. The correlations between the burn performance and the pointing at subsequent ground stations are derived with the aim of establishing simple guidelines which can be applied quickly and which significantly improve the chance of acquisition at subsequent ground stations. In the paper the method is applied to the Soyuz/Fregat launch with the MetOp satellite. Overall the paper shows that the launcher trajectory modelling with the simulation of contingency cases in connection with a ground station visibility analysis leads to a proper selection of ground stations and acquisition methods. In the MetOp case this ensured successful contact of all ground stations during the first hour after separation without having to rely on any early orbit determination result or state vector update.
Adaptive Planning: Understanding Organizational Workload to Capability/ Capacity through Modeling and Simulation
In August 2003, the Secretary of Defense (SECDEF) established the Adaptive Planning (AP) initiative [1] with an objective of reducing the time necessary to develop and revise Combatant Commander (COCOM) contingency plans and increase SECDEF plan visibility. In addition to reducing the traditional plan development timeline from twenty-four months to less than twelve months (with a goal of six months)[2], AP increased plan visibility to Department of Defense (DoD) leadership through In-Progress Reviews (IPRs). The IPR process, as well as the increased number of campaign and contingency plans COCOMs had to develop, increased the workload while the number of planners remained fixed. Several efforts from collaborative planning tools to streamlined processes were initiated to compensate for the increased workload enabling COCOMS to better meet shorter planning timelines. This paper examines the Joint Strategic Capabilities Plan (JSCP) directed contingency planning and staffing requirements assigned to a combatant commander staff through the lens of modeling and simulation. The dynamics of developing a COCOM plan are captured with an ExtendSim [3] simulation. The resulting analysis provides a quantifiable means by which to measure a combatant commander staffs workload associated with development and staffing JSCP [4] directed contingency plans with COCOM capability/capacity. Modeling and simulation bring significant opportunities in measuring the sensitivity of key variables in the assessment of workload to capability/capacity analysis. Gaining an understanding of the relationship between plan complexity, number of plans, planning processes, and number of planners with time required for plan development provides valuable information to DoD leadership. Through modeling and simulation AP leadership can gain greater insight in making key decisions on knowing where to best allocate scarce resources in an effort to meet DoD planning objectives.
A Crew and Logistics Lander for the Common Habitat Architecture
The Common Habitat Architecture is a conceptual study that explores the use of a large habitat derived from the Space Launch System (SLS) liquid oxygen tank as a core habitation element that can be used for crew missions or training in 0g, 1/6g, 3/8g, and 1g. This is not part of current NASA Artemis mission planning, but instead represents an architecture that could potentially follow after the Artemis missions and initial human Mars landings. This architecture leverages Starship-derived vehicles for crew landing on and ascent from the Moon and Mars in support of long-duration surface missions with pressurized crew transfer baselined as a nominal capability. This is not the Human Landing System variant of Starship but represents a number of modifications to enable long-duration surface missions with an eight-person crew size. A rapid brainstorming study was conducted in February of 2021, using only public data, to identify options to deliver the 90-ton Common Habitat to the surface and emplace it at the intended habitation site. This study compared three lunar lander concepts and three Mars lander concepts before ultimately selecting the SpaceX Starship as the most viable lander. The Common Habitat Architecture assumes that this Starship variant can further be modified for crew and cargo delivery, assuming that the use of a common system will lead to cost benefits. It is assumed that the Starship will expend too much propellant in landing crew and logistics to be able to launch, given the assumed absence of surface propellant production. Consequently, a separable ascent stage is used for crew ascent. The pressurized elements of this modified Starship are discussed: Starship Ascent Module, Airlock, Transfer Tunnel, Pressurized Crew Transfer Module, and Logistics Modules. For each element, a description, dimensions, rough mass estimates, core capabilities, and design features are presented. Key mechanisms and internal structures of the starship are also discussed. This will include flame diverters for the ascend module, the orbital docking hatch, Pressurized Crew Transfer Module Garage door, Starship Ascent Module fairing, flame diverter blow-out panels, Pressurized Crew Transfer Module lift system, logistics module lift system, contingency crew ascent via the logistics module lift system, internal catwalks, and structural interfaces. Concept of Operations will be discussed for both Moon and Mars. This will include in-space crew rendezvous and transfer, crewed landing, shirtsleeve crew transfer, crew departure, contingency surface operations, and final element disposition. Key differences for Mars will be discussed, such as the Martian atmosphere, dust storms, the absence of crew handover, and Deep Space Exploration Vehicle rendezvous. Contingency microgravity maintenance access will also be discussed. This work will demonstrate viable pressurized crew transfer with a Starship-based lander architecture. Forward work includes Garage lighting and camera systems, Starship Ascent Module propulsion system and docking port trades, contingency habitation trades, and mass/power equipment estimation. Finally, forward work includes developing a heavy cargo return system derived from the Crew and Logistics Starship. The goal of this system is the return of at least 10,000 kg payloads from the surfaces of the Moon and Mars.
A Hybrid Dynamic/Steady-State Tool With Protection Simulation for Cascading-Outage Analysis of Extreme Events in Power Systems
The bulk electric power grid is subject to vulnerabilities from component outages, which in certain combinations (extreme events) might lead to cascading outages. Some of these outages can be severe enough to trigger brownouts and blackouts. Much is known about mitigating the first few failures near the beginning of a cascade, but there are few established methods and tools for directly analyzing the risks of cascading component outages over a longer time scale. Current power system tools have limited ability to perform detailed and accurate cascading-outage analysis, which could be computationally intensive. The Dynamic Contingency Analysis Tool (DCAT) enables power system planning engineers to more realistically assess the consequences of extreme contingencies and potential cascading events across their systems and interconnections. DCAT has several unique features: (i) detailed hybrid dynamic and steady-state analysis of power systems to mimic real-world cascading outages, (ii) detailed modeling of protection systems embedded in the dynamic simulation, (iii) simulation of corrective action after transients, (iv) simulation of islanding , and (v) high-performance computing capability to simulate a large number of contingencies in a reasonable time. DCAT outputs will help find technically sound solutions to reduce the risk of cascading outages. This paper provides details of DCAT methodology and shows its capabilities with extreme events on real-world cases.
Harnessing distributed GPU computing for generalizable graph convolutional networks in power grid reliability assessments
Although machine learning (ML) has emerged as a powerful tool for rapidly assessing grid contingencies, prior studies have largely considered a static grid topology in their analyses. This limits their application, since they need to be re-trained for every new topology. Here, this paper explores the development of generalizable graph convolutional network (GCN) models by pre-training them across a range of grid topologies and contingency types. We found that a GCN model with auto-regressive moving average (ARMA) layers with a line graph representation of the grid offered the best predictive performance in predicting voltage magnitudes (VM) and voltage angles (VA). We introduced the concept of phantom nodes to consider disparate grid topologies with a varying number of nodes and lines. For pre-training the GCN ARMA model across a variety of topologies, distributed graphics processing unit (GPU) computing afforded us significant training scalability. The predictive performance of this model on grid topologies that were part of the training data is substantially better than the direct current (DC) approximation. Although direct application of the pre-trained model to topologies that are not part of the grid is not particularly satisfactory, fine-tuning with small amounts of data from a specific topology of interest significantly improves predictive performance. In general, this paper highlights the feasibility of training large-scale GNN models to assess the reliability of power grids by considering a wide variety of grid topologies and contingency types. With the advent of foundational models in ML and the exponential increase in GPU computing clusters, generalizable ML models will significantly enhance how utilities manage power systems and make decisions in real-time or near-real-time.