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NASA NTRS2022

Making or Breaking a Rover: System Engineering Parameters On-Board the Mars 2020 Perseverance Rover

On February 18, 2021, Perseverance, NASA’s Jet Propulsion Laboratory’s (JPL’s) Mars 2020 Rover, successfully landed on Mars with all systems nominal, despite the risk surrounding the over 200,000 internal flight parameters that had to be properly configured. The Perseverance team defines these parameters as software variables that are configurable, commandable and retrievable from Earth. In 2015, the Mars 2020 project leaders focused on improving systems engineering of parameters based on their experiences from parameter management on previous Mars rovers (Curiosity, Opportunity, Spirit, and Pathfinder) and parameter failures of past missions, such as the mission-ending parameter of the Mars Climate Orbiter. The new rigorous development process allowed for efficient certification and effective implementation of the parameters, allowing the rover to approach and land on the red planet (the most challenging phase of the mission) with zero parameter issues. Although successful, the Perseverance team learned many lessons for how to better manage parameters for the continued surface operations of the Mars 2020 mission and future missions. This paper will discuss eight parameter-management topics for the Perseverance Mission. The first is parameter definition: how we define parameters on our mission, where they are physically located on the vehicle, and why we have so many of them. The second topic is the updated parameter flight software module from Curiosity, including details on the 99% reduction in parameter commands, new bulk configuration capabilities, and improved parameter traceability. The third topic is parameter selection for different mission phases; this includes improving and tweaking our preferred parameter settings until they become certification candidates and managing parameter configurations based on test venue throughout the mission life cycle. The fourth topic is our flight certification process; this includes certification of flight values for four different epochs in the mission: Launch, Entry Decent and Landing (EDL) - 6days, Landing + 5 Sols (Martian Days, still on Cruise Flight Software), and once are on Surface Flight Software (FSW). The fifth topic covers in-flight command implementation, along with details on testing, validation, and verification of those commands. In the sixth section, we will explain our use of open-source management tools, including how we used GitHub for version control and management approvals. The seventh topic will describe the ground tools used in operations, including capabilities of the in-house built tool called Parasol. The eighth and final topic will dig into lessons learned for improving parameter management in the future of this mission and others.

Roth, Brian↗

NASA NTRS2022

Making or Breaking a Rover- Systems Engineering Parameters On-Board the Mars 2020 Perseverance Rover

Roth, Brian↗

NASA NTRS2020

EDL Simulation Results for the Mars 2020 Landing Site Safety Assessment

The Mars 2020 rover is NASA’s next flagship mission, set to explore Mars in search of scientific evidence of past microbial life. Importantly, the rover will also, for the first time, have the ability to collect and cache rock and soil samples for retrieval and return to laboratories here on Earth. A key step in the development of the Mars 2020 mission is the selection of a suitable landing site with the largest likelihood of meeting scientific goals. This decision is a complex and critical one that requires close interaction between the scientific and engineering communities. The chosen landing site must be both scientifically interesting — providing the project with the greatest possible chance of gathering credible and defendable scientific evidence — and also safe enough to attempt a landing in the first place. Thus, arguably one of the most important undertakings of the Entry, Descent, and Landing (EDL) team, is to effectively enumerate, quantify, and communicate the landing risks to all of the stakeholders. The culmination of this effort is the Landing Site Safety Assessment, which is a review commissioned by the project, presided over by the EDL Standing Review Board, and attended by management and science stakeholders, in which the EDL team communicates their assessment of the associated landing risks and the statistical probability of a successful landing at each of the final candidate landing sites. This paper summarizes the results of high-fidelity computer simulations of the Mars 2020 EDL sequence used in this assessment. From an EDL performance perspective, all four candidates offer similar level of robustness, which is in-family with Mars Science Laboratory (MSL). However, two new features of the Mars 2020 EDL sequence – range trigger and Terrain-Relative Navigation (TRN) – dramatically enhance the capability of the EDL system to safely land at landing sites with much more rugged terrain than ever before considered. This has allowed the landing site selection for Mars 2020 to proceed in a manner that has been unprecedentedly weighted more heavily toward scientific interest and less heavily on engineering constraints. With TRN, the overall probability of success is predicted to be approximately 99% for all of the candidates.

David Way↗

NASA NTRS2017

Mars Molniya Orbit Atmospheric Resource Mining

This NASA Innovative Advanced Concepts (NIAC) Phase I study examined the revolutionary concept of performing resource collection and utilization during Mars orbital operations in order to enable the landing of large payloads. An exploration architecture was developed, out of which several mission alternatives were developed. Concepts of operations were then developed for each mission alternative, followed by concepts for spacecraft systems, which were traded to assess their feasibility. A novel architecture using Mars Molniya Orbit Atmospheric Resource Mining is feasible to enable an Earth-independent and pioneering, permanent human presence on Mars by providing a reusable, single-stage-to-orbit transportation system. This will allow cargo and crew to be routinely delivered to and from Mars without transporting propellants from Earth.In Phase I, our study explored how electrical energy could be harnessed from the kinetic energy of the incoming spacecraft and then be used to produce the oxygen necessary for landing. This concept of operations is revolutionary in that its focus is on using in situ resources in complementary and varied forms: the upper atmosphere of Mars is used for aerocapture, which is followed by aerobraking, the kinetic energy of the spacecraft is transformed into usable electrical energy during aerobraking, and the atmospheric composition is the source of oxidizer for a landing under supersonic retropropulsion. This NASA Innovative Advanced Concepts (NIAC) Phase I study explores a novel mission architecture to establish routine, Earth-independent transfer of large mass payloads between Earth and the Mars surface and back to Mars orbit. The first stage of routine mission operations involves an atmospheric resource mining aerobraking campaign following aerocapture into a highly elliptical Mars orbit. During each pass through the atmosphere, the vehicle ingests the atmospheric oxidizer and stores it onboard, using solid oxide electrolysis to convert the primarily CO2 atmosphere into usable O2 for propellant. Power is made available through the use of magnetohydrodynamic energy generation, which converts the motion of the plasma in the shock later into usable electrical energy. Upon termination of the aerobraking sequence, the descent vehicle detaches from the orbit stack, deorbits, and executes the entry, descent, and landing sequence. Hypersonic deceleration is achieved via a deployable heat shield to lower the vehicle ballistic coefficient, and supersonic and subsonic deceleration are achieved via retropropulsion. Mars surface operations involve resource mining of the Martian regolith to produce CH4 and O2 propellant to be used for the subsequent MDAV ascent back to high Mars orbit (HMO) providing an apoapsis raise maneuver to initialize the aerobraking sequence, in addition to providing fuel from the Mars surface for EDL propulsive descent. The Resource Collector Vehicle (RCV), which is used for the orbital mining operations, is raised back to HMO via onboard deployable augmented solar electric propulsion. Concepts of operations were developed for each mission alternative, to evaluate between them and assess feasibility.

Mining↗

NASA NTRS2024

Plasma-Based Elemental Analyzer for Crewed Transit and Planetary Habitation

As NASA continues to perform research on the ISS and move towards the Moon and Mars, it is important for astronauts to have a technology capable of determining the composition of solid, liquid, and gas samples. Currently, samples are transported back to Earth for analysis, which may impact results due to the time delay of samples waiting to be returned to Earth as well as potential sample contamination from re-entry, change in environment, and various personnel handling. Therefore, researchers at the Applied Chemistry Lab at KSC have developed a proof-of-concept “Plasma-Based Elemental Analyzer,” which has the capability of testing solid, liquid, and gas samples for identification. Currently, the analysis is only qualitative, with quantitative identification left for future work. This technology is similar to ICP-OES, but differs in instrument size and sample preparation. Both technologies use plasma to ionize samples for light emission. The plasma elemental analyzer aims to be portable and lightweight, require only electrical power, and analyze solid, liquid, and gas samples. It does not use acid digestion or a nebulizer, requires less power than ICP-OES, and is able to operate with minimal to no usage of argon gas. Furthermore, the plasma elemental analyzer operates within low power constraints, which makes it feasible for usage on future missions with higher power constraints. The technology was tested at atmospheric pressure using mostly room air as the carrier gas for plasma production in the proof-of-concept study. The results showed the peak signals of the elements with an associated arbitrary signal intensity that allowed for qualitative identification. Solid samples that were tested included inedible biomass from the Golden Heirloom Cherry Tomato plant and Lunar Highlands Simulants (LHS-1). The liquid samples included elements of interest for the space crop production community. This work showed that a system smaller than the traditional ICP-OES equipment is able to be designed and implemented in future use cases, although it requires further development.

Kenneth Engeling↗

NASA NTRS2010

Orion Entry Performance-Based Center-of-Gravity Box

The Orion capsule is designed both for Low Earth Orbit missions to the ISS and for missions to the moon. For ISS class missions, the capsule will use an Apollo-style direct entry. For lunar return missions, depending on the timing of the mission, the capsule could perform a direct entry or a skip entry of up to 4800 n.mi. in order to land in the coastal waters of California. The physics of atmospheric re-entry determine the capability of the Orion vehicle. For a given vehicle mass and shape, physics tells us that the driving parameters for an entry vehicle are the hypersonic lift-to-drag ratio (L/D) and the flight path angle at entry interface (gamma(sub EI)). The design of the Orion atmospheric re-entry must meet constraints during both nominal and dispersed flight conditions on landing accuracy, heating rate, total heat load, sensed acceleration, and proper disposal of the Service Module. These constraints define an entry corridor in the space of L/D-gamma(sub EI); if the vehicle falls within this corridor, then all constraints are met. The gamma(sub EI) dimension of the corridor can be further constrained by the gloads experienced during emergency entries. Thus, the entry performance for the Orion vehicle can be described completely by the L/D. Bounds on the hypersonic L/D necessary to achieve all the mission requirements can be defined for the given entry corridor. Landing accuracy performance drives the lower limit on L/D. In order to achieve the desired landing accuracy, a minimum L/D must be ensured. The design of the Thermal Protection System (TPS) drives the upper limit on L/D. A higher L/D can drive mass into the design of the TPS. Conversely, once the TPS is designed, the L/D must be ensured to stay below a certain limit in order for the TPS to stay within its design envelop. The L/D must stay within its upper and lower bounds during dispersed flight conditions. L/D is a function of both the aerodynamics and the center-of-gravity (CG) of the vehicle. The aerodynamics of the vehicle are determined by Computational Fluid Mechanics (CFD) and wind tunnel tests. However, the aerodynamics are not known precisely. Instead, an aerodynamic database has been developed where the aerodynamic coefficients are known to fall within a probabilistic band defined by upper and lower bounds. It is expected that the probabilistic band will shrink after the first missions are flown and real-world data is collected. Until that time, the Orion must be designed to the current aerodynamic database. Thus, for a given aerodynamic database with given uncertainties, the allowable range in L/D can be mapped to an allowable box for the CG location. The CG box is used to set requirements on the dispersions allowed for vehicle packaging and cargo storage. As the aerodynamic uncertainties decrease, the size of the CG box can increase. This paper discusses the technique used to map the minimum and maximum L/D bounds set by the entry performance requirements to the allowable dispersions in CG while accounting for aerodynamic uncertainties. The L/D is defined as the ratio of the lift force to the drag force. It is equivalent to the ratio of lift coefficient (C(sub L)) over drag coefficient (C(sub D)). C(sub L) and C(sub D) are functions of Mach number (M) and angle of attack (alpha). A Mach number of 25 is used as a measuring point of the hypersonic L/D. Variations in C(sub L), C(sub D) and alpha cause variations in L/D. Equation (1) shows the three contributions to the variation in L/D.

Rea, Jeremy R.↗

NASA NTRS2020

Aerocapture as an Option for Ice Giants Mission

Aerocapture is an atmospheric maneuver where the aerodynamic forces of the vehicle (lift and drag) are used to provide the 𝞓V needed to slow down from the approach hyperbolic trajectory to achieve the desired captured orbit around the target planet. The aeroassist capture provides a large savings in propulsion needed to change the velocity of the vehicle, since aerodynamic forces rather than propulsive systems provide the change in velocity. Aerocapture requires an integrated system level design, including thermal protection systems, actuator systems for aerodynamic modulation, and guidance and control systems that can autonomously command the change in the aeroassist forces. Although aerocapture has been proposed for many situations in the past, including Mars, Venus, Titan, Saturn, Uranus, and Neptune orbiters as well as for Earth demonstration missions, it has not been attempted on any missions. However, many studies in the past three decades that have considered aerocapture as a design option have concluded that there are large mass savings that come from using aeroassist forces rather than propulsive forces to put a spacecraft into a captured orbit. The benefits are destination dependent, but some of the largest mass savings occur for the Ice Giants planets. Due to the large hyperbolic velocities of interplanetary trajectories approaching Uranus and Neptune, large amount of propulsion must be used to put a spacecraft in science orbits around these planets. Aerocapture can reduce the propulsion needs by dissipating energy in the sizable atmospheres of Uranus and Neptune. NASA commissioned a detailed study analysis to quantify the benefits, if any, for use at Neptune. The study found that even having to provide a heat shield aerocapture could deliver 40% more payload than an all-propulsive vehicle, and also provides for a 3–4-year reduction in trip time. Mass savings are expected also at Uranus with an aerocapture mission. Additionally, more recent advances in thermal protection systems and guidance and control systems show a path to increase capabilities beyond those results. This paper will discuss the merits of including aerocapture as an option for an Ice Giants mission. The discussion will focus on the cost and mass savings of using aerocapture instead of propulsive burns for Ice Giants orbiter mission scenarios while also detailing a potential concept of operations and entry vehicle design. Finally, the talk will discuss more recent work that shows aerocapture design is possible without the development of any novel entry vehicle. Thus, aerocapture can significantly improve science capabilities for an Ice Giants mission.

Soumyo Dutta↗

NASA NTRS2011

Methodology and Results of the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS)

Near-Earth Asteroids (NEAs) have been identified by the current administration as potential destinations for human explorers during the mid-2020s. While the close proximity of these objects' orbits to Earth's orbit creates a risk of highly damaging or catastrophic impacts, it also makes some of these objects particularly accessible to spacecraft departing Earth, and this presents unique opportunities for solar system science and humanity's first ventures beyond cislunar space. Planning such ambitious missions first requires the selection of potentially accessible targets from the growing population of nearly 7,800 NEAs. To accomplish this, NASA is conducting the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS). Phase I of the NHATS was executed during September of 2010, and Phase II was completed by early March of 2011. The study is ongoing because previously undetected NEAs are being discovered constantly, which has motivated an effort to automate the analysis algorithms in order to provide continuous monitoring of NEA accessibility. The NHATS analysis process consists of a trajectory filter and a minimum maximum estimated size criterion. The trajectory filter employs the method of embedded trajectory grids to compute all possible ballistic round-trip mission trajectories to every NEA in the Jet Propulsion Laboratory (JPL) Small-Body Database (SBDB) and stores all solutions that satisfy the trajectory filter criteria. An NEA must offer at least one qualifying trajectory solution to pass the trajectory filter. The Phase II NHATS filter criteria were purposely chosen to be highly inclusive, requiring Earth departure date between January 1st, 2015 and December 31st, 2040, total round-trip flight time <= 450 days, stay time at the NEA >= 8 days, Earth departure C(sub 3) energy <= 60 km(exp 2)/s(exp 2), total mission delta-v <= 12 km/s (including an Earth departure maneuver from a 400 km altitude circular parking orbit), and a maximum atmospheric re-entry speed of 12 km/s. After determining which NEAs offer at least one trajectory solution meeting the criteria, the estimated size constraint is then imposed whereby those NEAs may only be considered NHATS- qualifying NEAs if their maximum estimated size is >= 30 m. This corresponds to an absolute magnitude H <= 26.5 with an assumed albedo p = 0:05. The following is a brief high-level summary of the Phase II study results. Of the 7,665 NEAs in the SBDB as of February 3rd, 2011, 765 NEAs passed the trajectory filter and yielded a total of 79,157,604 trajectory solutions. The trajectory solutions for each NEA are post-processed into Pork Chop Contour (PCC) plots which show total mission delta-v as a function of Earth departure date and total mission duration. Although the PCC plots necessarily compress a very multi-dimensional design space into a two-dimensional plot, they permit rapid assessment of the breadth and quality of an NEA's available Earth departure season and clearly indicate the regions of the trajectory design space which warrant further analysis and optimization. The PCC plot for the NEA with the greatest number of NHATS-qualifying trajectory solutions, 2000 SG-344, is shown. Of the 765 NEAs which passed the Phase II trajectory filter, a total of 590 NEAs also satisfied the further constraint of maximum estimated size >= 30 m. The distributions of osculating heliocentric orbital semi-major axis (a), eccentricity (e), and inclination (i), for those 590 NEAs are shown. Note that the semi-latus rectum used is equal to alpha (1-e(exp 2)). To further our understanding of round-trip trajectory accessibility dynamics, it is instructive to examine the distribution of the NHATS-Qualifying NEAs according to orbit classification. NEAs are grouped into four orbit families: Atiras (aphelion < 0.983 AU), Atens (aphelion > 0.983 AU, alpha < 1.0 AU), Apollos (perihelion < 1.017 AU, alpha > 1.0 AU), and Amors (1.017 < perihelion < 1.3 AU). Of the 765 NEAhich satisfied the NHATS trajectory criteria, none are Atiras, 193 are Atens (31% of known Atens), 456 are Apollos (11% of known Apollos), and 116 are Amors (4% of known Amors). While Apollos comprise 60% of the NEAs which pass the NHATS trajectory filter and Atens comprise only 25%, the percentages according to orbit family are perhaps more relevant. Note that only 11% of known Apollos passed the trajectory filter while 31% of known Atens passed. These simple statistics alone strongly suggest that Aten orbits possess features which tend to enhance their round-trip trajectory accessibility as compared to Apollos or Amors. This is significant because Atens' orbits cause them to spend considerable time in Earth's daytime sky, making them difficult to discover and track using ground-based observing assets. In this paper we will detail the NHATS analysis algorithms, present and analyze all NHATS results to date, and discuss aspects of HSF mission architecture design for future NEA missions.

Barbee, Brent↗

NASA NTRS2000

Biological removal of gaseous ammonia in biofilters: space travel and earth-based applications

Gaseous NH3 removal was studied in laboratory-scale biofilters (14-L reactor volume) containing perlite inoculated with a nitrifying enrichment culture. These biofilters received 6 L/min of airflow with inlet NH3 concentrations of 20 or 50 ppm, and removed more than 99.99% of the NH3 for the period of operation (101, 102 days). Comparison between an active reactor and an autoclaved control indicated that NH3 removal resulted from nitrification directly, as well as from enhanced absorption resulting from acidity produced by nitrification. Spatial distribution studies (20 ppm only) after 8 days of operation showed that nearly 95% of the NH3 could be accounted for in the lower 25% of the biofilter matrix, proximate to the port of entry. Periodic analysis of the biofilter material (20 and 50 ppm) showed accumulation of the nitrification product NO3- early in the operation, but later both NO2- and NO3- accumulated. Additionally, the N-mass balance accountability dropped from near 100% early in the experiments to approximately 95 and 75% for the 20- and 50-ppm biofilters, respectively. A partial contributing factor to this drop in mass balance accountability was the production of NO and N2O, which were detected in the biofilter exhaust.

NASA Discipline Life Support Systems↗

DOE OSTI2021

A multi-dimensional parametric study of variability in multi-phase flow dynamics during geologic CO 2 sequestration accelerated with machine learning

Successful geologic CO 2 storage projects depend on numerical simulations to predict reservoir performance during site selection, injection verification, and post-injection monitoring phases of the project. These numerical simulations solve non-linear sets of coupled partial differential equations, while accounting for multi-phase fluid dynamics on the basis of constitutive equations that are embedded into the solution scheme. As a consequence, individual simulations often require tens to hundreds of hours to complete on high-performance computing clusters. Moreover, laboratory experiments reveal that parametric functions for capillary pressure and relative permeability exhibit substantial variability, even within the same rock type. This combination of computational expense and wide-ranging parametric variability means that there remains substantial uncertainty in the behavior of multi-phase CO 2 -water systems, particularly in the context of feedbacks between relative permeability and capillary pressure. To bridge this knowledge gap, here we develop a novel workflow that utilizes physics-based numerical simulation to train an artificial neural network (ANN) emulator for interrogating the multivariate parameter space that governs both capillary pressure and relative permeability. With this approach, the ANN is trained to emulate both fluid pressure distribution and CO 2 saturation, which are then interrogated quantitatively to generate parametric response surface mappings with high-fidelity resolution. Results from this study initially show that capillary entry pressure is the dominant control on both CO 2 plume geometry and fluid pressure propagation when considering the combined effects of capillary pressure and relative permeability, particularly when phase interference is low and residual CO 2 saturation is high. Moreover, the ANN emulator provides tremendous computational speed-up by computing 2691 individual simulations in several minutes; whereas, the same simulation ensemble would have required ~3 years of simulation time using only physics-based simulation methods (25,000 times speed up).

58 GEOSCIENCES↗

NASA NTRS2019

Implementing CubeSat Avionics Components to Full-Scale Capsule Return Missions

Returning samples from Low Earth Orbit (LEO) is no simple task. Whether the samples are scientific experiments or surveillance footage, engineers must overcome many challenges to achieve mission success. In August of 1960 the first payload recovered from LEO, the Corona capsule, carried “more photographic coverage of the Soviet Union than all previous U-2 missions”. The Corona program proved that re-turning surveillance footage from LEO is possible, the program is still referenced today when designing new sample return missions. Although there are many crucial subsystems that make up a sample return capsule, the avionics subsystem demands the most attention. This paper will discuss how current CubeSat avionics components can be applied to large sample return missions. One advantage of using CubeSat avionics components is that they can fit into a 1.5 U (10x10x15 cm) compartment, leaving more room for the payload. This paper is broken down as follows. First, the reader is introduced to the history of sample return projects. The major design strengths of previous projects are analyzed and applied to the current capsule design. Next, the typical trajectory of a capsule is presented along with mission requirements and operations. During the re-entry phase, the avionics subsystem is responsible for commanding the deployment of the parachute, back shell, and the heat shield. Next, the power subsystem is discussed in detail including a trade study on batteries and voltage regulators. Next, the interface between the Ground Support Equipment (GSE) and the avionics components is discussed. It is important that the capsule is able to provide avionics system state of health to ensure proper functionality before the capsule is launched. Next, an in-depth analysis of current TechEdSat avionics components, with proven flight history, are presented. The various avionics components including the radios, GPS, IMU, temperature sensors, altitude sensors, and ejectors are discussed. The application of cur-rent avionics components to a sample return projects are analyzed. After, the wiring diagram is presented along with a discussion of the design. Next, a summary of how the avionics components are tested and validated is pro-vided. Finally, this article will present current sample return missions TechEdSat avionics components are being applied to. CubeSat Avionics can be applied to almost all sample return missions due to their compact configuration and proven space flight heritage. The TechEdSat team is currently making great progress in returning samples from the International Space Station (ISS) and is excited to present how their avionics components can be applied to a full-scale sample return mission.

Hughes, Z. M.↗

NASA NTRSDate not supplied

Evolution of Hardware and Philosophy of Emergency Response Actions on the International Space Station and Future Spacecrafts

Human spaceflight is dangerous for numerous reasons. This ranges from the dynamic environment of launching on a rocket, flying in space among the thousands and thousands pieces of space debris, to the hazards of re-entry & landing, as well as being surrounded by vehicle systems containing hazardous materials or gasses. In-flight emergencies fall into four categories: Rapid Depressurization, Fire, Toxic Spill, and Medical emergency. This paper will address the first three, which fall under the responsibility of the Environmental Control and Life Support (ECLS) Systems flight control and engineering teams. It will review the evolution of the International Space Station’s emergency response philosophy, procedures, training, and equipment changes over the years. The International Space Station (ISS) emergency equipment has evolved over the last two decades of operations in many ways, but in some it has remained the same. The core actions the flight crew takes to ensure team safety, personal safety, vehicle safety, and equipment safety has not changed. However, the equipment and capabilities provided to them have. From early days of minimal capability when the ISS consisted of a few modules, to today’s 30,000 ft^3 vehicle with over a dozen isolatable segments. From use of positive pressure O2 masks, to the development of respirators. From a lack of procedures for a deadly ammonia leak scenario to a memorized response utilizing numerous atmosphere measurement systems. This paper will review all these various areas that fall under the umbrella of “on-board emergencies”. In addition, the comparison to the planned emergency operations on the Orion vehicle will be reviewed. The Orion vehicle differs from the ISS in that it has no isolatable volume, being approximately 2% the size of ISS, as well as not having a quick return to earth capability.

Barry Tobias↗

NASA NTRSDate not supplied

Evolution of Hardware and Philosophy of Emergency Response Actions on the International Space Station and Future Spacecrafts

Human spaceflight is dangerous for numerous reasons. This ranges from the dynamic environment of launching on a rocket, flying in space among the thousands and thousands pieces of space debris, to the hazards of re-entry & landing, as well as being surrounded by vehicle systems containing hazardous materials or gasses. In-flight emergencies fall into four categories: Rapid Depressurization, Fire, Toxic Spill, and Medical emergency. This paper will address the first three, which fall under the responsibility of the Environmental Control and Life Support (ECLS) Systems flight control and engineering teams. It will review the evolution of the International Space Station’s emergency response philosophy, procedures, training, and equipment changes over the years. The ISS emergency equipment has evolved over the last two decades of operations in many ways, but in some it has remained the same. The core actions the flight crew takes to ensure team safety, personal safety, vehicle safety, and equipment safety has not changed. However, the equipment and capabilities provided to them have. From early days of minimal capability when the ISS consisted of a few modules, to today’s 30,000 ft^3 vehicle with over a dozen isolatable segments. From use of Russian gas masks to positive pressure O2 masks, to the development of respirators. From a lack of procedures for a deadly ammonia leak scenario to a memorized response utilizing numerous atmosphere measurement systems. This paper will review all these various areas that fall under the umbrella of “on-board emergencies”. In addition, the comparison to the planned emergency operations on the Orion vehicle will be reviewed. The Orion vehicle differs from the ISS in that it has no isolatable volume, being approximately 2% the size of ISS, as well as not having a quick return to earth capability.

Emergency↗

NASA NTRS2024

Crew Health and Performance Integrated Data Architecture (CHP-IDA) Project

BACKGROUND: Future Human Exploration missions introduce a new paradigm as crews move further from the resupply and near real-time ground support typical of Low Earth Orbit missions today. Without immediate support from ground-based personnel, exploration crews will be more reliant on inflight data and technology to respond to emergencies and anomalies. A data architecture to support a new generation of technologies, employing advanced analytical and predictive modeling techniques, is needed to enable crew autonomy. OVERVIEW: The Crew Health and Performance Integrated Data Architecture (CHP-IDA) project funded by NASA’s Exploration Medical Integrated Product Team (XMIPT) is laying a foundation for future in-flight informatics by providing a back-end architecture for collecting, storing, and integrating multiple sources of data generated by and around the crew. CHP-IDA provides a platform for common data models and Application Programming Interfaces to access, integrate, process, and display CHP data (e.g., environmental, exercise, medical, sleep, performance, etc.). This will facilitate the increased situation awareness and decision support required by the crew and remote support of exploration missions. This presentation will describe the currently ongoing effort to develop and evaluate a path-to-flight concept of the CHP-IDA software and its core capabilities. Current integrations will be discussed, including analytics for Extravehicular Activity metabolic rate and data ingestion from a multi-functional integrated medical device. The presentation will also provide examples of scenarios used to demonstrate the CHP-IDA through human-in-the-loop test bed activities as well as examples of appropriate system performance metrics. DISCUSSION: Today, in-flight data is often siloed, unsynchronized, and largely inaccessible in real time. Many data sets require manual entry and/or data transfer between vehicles and the ground. These issues contribute to risks in supporting exploration medical capabilities. The CHP-IDA is a back-end data system providing core capabilities needed for timely and meaningful data insights across CHP domains to crew and remote personnel to enable increased crew autonomy. Future work includes collaboration with additional CHP domains, new technology integrations, and further demonstrations of the IDA within different vehicle and communication latency contexts. LEARNING OBJECTIVES 1. The audience will understand that the CHP-IDA is a back-end system, providing a platform to facilitate access, promote decision tools, and provide meaningful insights to crew and to remote stakeholders during exploration missions. 2. The audience will gain insight into human-centered research and activities used to discover CHP domain data needs and pain points and how this information is used to guide development of the IDA.

Exploration↗

NASA NTRS2007

A Comparison of Two Skip Entry Guidance Algorithms

The Orion capsule vehicle will have a Lift-to-Drag ratio (L/D) of 0.3-0.35. For an Apollo-like direct entry into the Earth's atmosphere from a lunar return trajectory, this L/D will give the vehicle a maximum range of about 2500 nm and a maximum crossrange of 216 nm. In order to y longer ranges, the vehicle lift must be used to loft the trajectory such that the aerodynamic forces are decreased. A Skip-Trajectory results if the vehicle leaves the sensible atmosphere and a second entry occurs downrange of the atmospheric exit point. The Orion capsule is required to have landing site access (either on land or in water) inside the Continental United States (CONUS) for lunar returns anytime during the lunar month. This requirement means the vehicle must be capable of flying ranges of at least 5500 nm. For the L/D of the vehicle, this is only possible with the use of a guided Skip-Trajectory. A skip entry guidance algorithm is necessary to achieve this requirement. Two skip entry guidance algorithms have been developed: the Numerical Skip Entry Guidance (NSEG) algorithm was developed at NASA/JSC and PredGuid was developed at Draper Laboratory. A comparison of these two algorithms will be presented in this paper. Each algorithm has been implemented in a high-fidelity, 6 degree-of-freedom simulation called the Advanced NASA Technology Architecture for Exploration Studies (ANTARES). NASA and Draper engineers have completed several monte carlo analyses in order to compare the performance of each algorithm in various stress states. Each algorithm has been tested for entry-to-target ranges to include direct entries and skip entries of varying length. Dispersions have been included on the initial entry interface state, vehicle mass properties, vehicle aerodynamics, atmosphere, and Reaction Control System (RCS). Performance criteria include miss distance to the target, RCS fuel usage, maximum g-loads and heat rates for the first and second entry, total heat load, and control system saturation. The comparison of the performance criteria has led to a down select and guidance merger that will take the best ideas from each algorithm to create one skip entry guidance algorithm for the Orion vehicle.

Rea, Jeremy R.↗

NASA NTRS2007

Integrating Human Factors into Crew Exploration Vehicle Design

With NASA's new Vision for Exploration to send humans beyond Earth orbit, it is critical to consider the human as a system that demands early and continuous user involvement, and an iterative prototype/test/redesign process. Addressing human-system interface issues early on can be very cost effective even cost reducing when performed early in the design and development cycle. To achieve this goal within Crew Exploration Vehicle (CEV) Project Office, human engineering (HE) team is formed. Key tasks are to apply HE requirements and guidelines to hardware/software, and provide HE design, analysis and evaluation of crew interfaces. Initial activities included many practice-orientated evaluations using low-fidelity CEV mock-ups. What follows is a description of such evaluations that focused on a HE requirement regarding Net Habitable Volume (NHV). NHV is defined as the total remaining pressurized volume available to on-orbit crew after accounting for the loss of volume due to deployed hardware and structural inefficiencies which decrease functional volume. The goal of the NHV evaluations was to develop requirements providing sufficient CEV NHV for crewmembers to live and perform tasks in support of mission goals. Efforts included development of a standard NHV calculation method using computer models and physical mockups, and crew/ stakeholder evaluations. Nine stakeholders and ten crewmembers participated in the unsuited evaluations. Six crewmembers also participated in a suited evaluation. The mock-up was outfitted with volumetric representation of sub-systems such as seats, and stowage bags. Thirteen scenarios were developed to represent mission/crew tasks and considered to be primary volume drivers (e.g., suit donning) for the CEV. Unsuited evaluations included a structured walkthrough of these tasks. Suited evaluations included timed donning of the existing launch and entry suit to simulate a contingency scenario followed by doffing/ stowing of the suits. All mockup evaluations were videotaped. Structured questionnaires were used to document user interface issues and volume impacts of layout configuration. Computer model and physical measures of the NHV agreed within 1 percent. This included measurement of the gross habitable volume, subtraction of intrusive volumes, and other non-habitable spaces. Calculation method developed was validated as a standard means of measuring NHV, and was recommended as a verification method for the NHV requirements. Evaluations confirmed that there was adequate volume for unsuited scenarios and suit donning/ doffing activity. Seats, suit design stowage and waste hygiene system noted to be critical volume drivers. The low-fidelity mock-up evaluations along with human modeling analysis generated discussions that will lead to high-level systems requirements and human-centered design decisions. This approach allowed HE requirements and operational concepts to evolve in parallel with engineering system concepts and design requirements. As the CEV design matures, these evaluations will continue and help with design decisions, and assessment, verification and validation of HE requirements.

Whitmore, Mihriban↗

NASA NTRSDate not supplied

NASA’s Moon Trek Portal: New Capabilities Supporting Mission Planning and Engagement

Introduction: NASA’s Moon Trek (https://trek.nasa.gov/moon/) is one of a growing number of interactive, browser-based, online portals for planetary data visualization and analysis produced by NASA’s Solar System Treks Project (SSTP). Moon Trek continues to be enhanced with new data and new capabilities enabling it to facilitate the planning and conducting of upcoming lunar missions by NASA, its commercial partners, and its international partners, as well as advancing its role as a valuable outreach tool. A Comprehensive Online Web Portal: Developed at NASA’s Jet Propulsion Laboratory (JPL) and managed as a project of NASA’s Solar System Exploration Research Virtual Institute (SSERVI) at NASA Ames Research Center, Moon Trek is a browser-based web portal. The portal provides easy-to-use tools for browsing, data layering, data product blending, and feature search among thousands of data products covering topography, mineralogy, elemental abundance, geology, and much more. Visualizations are provided in var-ious map projections, interactive 3D viewing, and in virtual reality. Using an in-house stereo workflow, SSTP is able to produce new NAC-based high-resolution mosaics and DEMs. Diverse Applications for Lunar Exploration: Baseline analytic tools available to all users include dis-tance measurement, elevation profiling, sun angle calculation, and 3D print file generation. More advanced account-level tools allow users to perform more computationally intensive analyses. These include ray-traced lighting analysis for user-specified areas over user-specified time/date ranges and time intervals, electro-static surface potential analysis, subsetting of large data products, slope analysis, and Lunar Laser Ranging geometry calculation. Artificial intelligence (AI) and ma-chine learning (ML) based tools have been implemented for crater detection and hazard analysis, boulder detection and hazard analysis, and rockfall detection. New Tools Facilitating Exploration: Additional, new tools have recently been added and others are in development, offering even greater functionality in con-ducting analyses of potential landing sites and areas of surface operations. The new Line-of-Sight tool facilitates communications planning between locations on the lunar surface, between any given site on the lunar surface and a specified ground station on the Earth, and between a site on the lunar surface and a relay asset in lunar orbit, all taking into account local lunar topography. The new Data Plotter tool provides both tabular and graphical representations of pixel values along a user specified path for a growing number of data products. The new NAC Finder tool will identify and pro-vide access to NAC images that intersect a user-defined path or bounded area. The SSTP development team is looking to leverage the capabilities of its existing AI and ML crater, boulder, and rockfall detection and analysis tools, and extend that technology to a generalized feature detector that can be trained on instances of specific types of landforms and then search the lunar surface for more examples of such features. New traverse planning tools are being developed with use cases in generalized concept studies and specific mission planning in mind. These will facilitate finding optimal traverse paths based on constraints such as slope, lighting, hazard avoidance, and communications. These will be complemented by new traverse visualization capabilities. Users will be able to interactively ride along with a rover, examining 3D views of the terrain while adjusting camera height and viewing angle along with selecting different data layer overlays to drape across the terrain. Engaging the Public: The capabilities being developed for mission planning are being leveraged to further enhance Moon Trek’s proven utility as a valuable public outreach resource. This includes providing multiple lev-els of engagement with different points of entry. At its simplest level, promoting understanding through visualization, media and the public will be able to easily visualize and conduct their own exploration of lunar sites targeted by NASA and its partners. For a more in-depth experience, we are working with our stakeholders to promote understanding through interaction by extend-ing our current landing site and traverse analysis capabilities, making simplified access to these tools available to those who want to explore more deeply key factors in planning a mission through interactive and possibly even gamified experiences. The highest degree of public outreach, focusing on engagement through scientific participation, could be achieved through our work with missions and the NASA Office of the Chief Scientist on Moon Trek’s extension as a tool with specialized capabilities for facilitating citizen science. In such scenarios, participants become members of extended mis-sion science teams, using dedicated and integrated interfaces to analyze mission data to help answer questions key to lunar science and exploration. We are work-ing with NASA’s Office of Communications, museums, planetariums, and the media to help them easily integrate accurate, detailed visualizations of NASA’s lunar destinations and exploration into their content/productions and to engage diverse audiences in diverse venues.

Moon Trek↗

DOE OSTI2025

Analyzing and Exploring Training Recipes for Large-Scale Transformer-Based Weather Prediction

Abstract The rapid rise of deep learning (DL) in numerical weather prediction (NWP) has led to a proliferation of models which forecast atmospheric variables with comparable or superior skill than traditional physics-based NWP. However, among these leading DL models, there is a wide variance in both the training settings and architecture used. Further, the lack of thorough ablation studies makes it hard to discern which components are most critical to success. In this work, we show that it is possible to attain high forecast skill even with relatively off-the-shelf architectures, simple training procedures, and moderate compute budgets. Specifically, we train a minimally modified Swin Transformer V2 (SwinV2) on ERA5 data and find that it attains superior skill in terms of mean-square errors of deterministic forecasts when compared against the European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (IFS). Almost all DL–NWP systems share a core set of hyperparameters and design decisions. To aid and expedite future DL–NWP research, we present an in-depth, systematic exploration of different loss functions, model sizes and depths, patch sizes, and multistep training objectives. We also examine the model performance with metrics beyond the typical accuracy (ACC) and RMSE and investigate how the performance scales with model size. Through our open-source code, scoring pipelines, and models, we share our findings on key aspects of the training pipeline. These ablations reduce the necessity for expensive hyperparameter tuning and lower the barrier to entry for future DL–NWP research. Significance Statement This study investigates the potential of using large-scale transformer-based models for weather prediction, showing that it is possible to achieve high forecast accuracy with simpler, off-the-shelf architectures. By training a minimally modified SwinV2 transformer on ERA5 data, we show that the model achieves competitive forecast skill in terms of mean-square error for key variables, outperforming the European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (IFS) at all lead times. Our findings suggest that effective training strategies, such as multistep fine-tuning and channel-weighted losses, significantly enhance the model’s performance. However, we also highlight that these improvements come with trade-offs in other areas, such as ensemble spread and high-frequency spatial detail. This work highlights the promise of deep learning in improving weather forecasts, which could lead to better preparedness and response to weather events, ultimately benefiting society by providing more reliable weather predictions.

Willard, Jared D. [Lawrence Berkeley National Labo↗