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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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DOE OSTI2020

Automated, Unmanned Detection and Quantification of Fugitive Methane Emissions

Compressor stations used to move natural gas are one of the largest sources of fugitive methane emissions in the midstream sector, accounting for approximately 50% of all fugitive emissions (Zimmerle et al., 2015). This problem is most widespread at reciprocating compressors (Subramanian et al., 2015) where faulty seals are a key contributor to methane emissions (Johnson et al., 2015). As such, there is a significant need for a robust technology that could provide an early indication of an unexpected emission. Equally important, the technology needs to be able to account for biogenic versus anthropogenic sources of methane. One means of indirectly making this determination, is to leverage optical technologies that can autonomously pinpoint the source of such leaks. This presentation discusses recent work funded by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), focused on the development of an innovative remote sensing technology that can reliably and autonomously detect fugitive methane emissions in near real-time, using computer vision and deep learning. The technology called the Smart Methane Leak Detection (SLED/M) system was initially developed to monitor facilities such as compressor stations in a stationary, pan-tilt-zoom configuration. The system has recently been adapted to monitor facilities from an unmanned aerial system (UAS). The speed and maneuverability of UAS platforms are attractive to leak detection and repair program operators, but introduce several challenges. Many existing methane detection algorithms rely on mostly static backgrounds becoming unusable with motion. In addition, top-down views of fugitive methane emissions present differently in Optical Gas Imagers (OGI) compared to looking across the plume. Our work has focused on overcoming these challenges, enhancing the operators ability to detect methane emissions, and pinpoint their sources. Another recent adaptation to SLED/M is the ability to quantify methane emissions using passive sensors (OGI, thermal camera), environmental conditions, plume modeling, and deep learning. SLED/M advances the state-of-the-art for methane emission detection and quantification by focusing on three key critical criteria for effective methane emission mitigation: (1) autonomy (no need for a human to be in the loop), (2) high reliability (low false alarm rates), and (3) real-time performance. Results from this work will be presented.

03 NATURAL GAS↗

DOE OSTI2025

Autonomous Flow Electrochemistry for Accelerated Catalyst Discovery

Our objective is to develop an Autonomous Chemical Experimentation (ACE) platform that accelerates discovery of new catalytic transformations and other energy-relevant chemical reactions and processes. We intentionally designed ACE to be highly modular, both with respect to its rapid deployment to different chemistries and experimental workflows as well as incorporation of a wide range of different AI algorithms. In addition to the development of the core software architecture, initial efforts were made to incorporate Large Language Models to provide human-interpretable reasoning of the optimizer’s actions, and to develop a user-friendly graphical interface for experimental researchers. ACE was demonstrated using a flow electrocatalysis platform containing an inline FTIR spectrometer for real-time analysis and quantification of the reaction outcome. Human-in-the-loop experiments were performed in which a human researcher conducted an experiment using electrode potentials suggested by ACE, then fed the spectral data back to ACE for decision making. After confirming the successful function of the optimizer, efforts were next directed to automation of the hardware and performed full autonomy tests using three reactions: catalytic oxidation of formate, catalytic oxidation of cyclohexanol, and oxidation of hydroquinone. These studies confirm that ACE can close the loop between reaction execution, analysis, and optimization. They also reveal that more improved product detection methods will be essential for ACE to make well-informed decisions for reactions with low conversions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1993

Space Life Support Engineering Program

This report covers the second year of research relating to the development of closed-loop long-term life support systems. Emphasis was directed toward concentrating on the development of dynamic simulation techniques and software and on performing a thermodynamic systems analysis in an effort to begin optimizing the system needed for water purification. Four appendices are attached. The first covers the ASPEN modeling of the closed loop Environmental Control Life Support System (ECLSS) and its thermodynamic analysis. The second is a report on the dynamic model development for water regulation in humans. The third regards the development of an interactive computer-based model for determining exercise limitations. The fourth attachment is an estimate of the second law thermodynamic efficiency of the various units comprising an ECLSS.

Seagrave, Richard C.↗

NASA NTRS1995

Adaptation to Space: An Introduction

The cardiovascular and musculoskeletal systems are normally exposed to gradients of blood pressure and weight on Earth. These gradients increase blood pressure and tissue weight in dependent tissues of the body. Exposure to actual and simulated microgravity causes blood and tissue fluid to shift from the legs to the head. Studies of humans in space have documented facial edema, space motion sickness, decreased plasma volume, muscle atrophy, and loss of bone strength. Return of astronauts to Earth is accompanied by orthostatic intolerance, decreased neuromuscular coordination, and reduced exercise capacity. These factors decrease performance during descent from orbit and increase risk during emergency egress from the spacecraft. Models of simulated microgravity include 6 deg head-down tilt, immersion, and prolonged horizontal bedrest. Head-down tilt is the most accepted model and studies using this model of up to one year have been performed in Russia. Animal models which offer clear insights into the role of gravity on vertebrates include the developing giraffe and snakes from various habitats. Finally, possible countermeasures to speed readaptation of astronauts to gravity after prolonged space flight will be discussed.

Hargens, Alan R.↗

NASA NTRS2017

Human Factors Virtual Analysis Techniques for NASA's Space Launch System Ground Support using MSFC's Virtual Environments Lab (VEL)

Using virtual environments to assess complex large scale human tasks provides timely and cost effective results to evaluate designs and to reduce operational risks during assembly and integration of the Space Launch System (SLS). NASA's Marshall Space Flight Center (MSFC) uses a suite of tools to conduct integrated virtual analysis during the design phase of the SLS Program. Siemens Jack is a simulation tool that allows engineers to analyze human interaction with CAD designs by placing a digital human model into the environment to test different scenarios and assess the design's compliance to human factors requirements. Engineers at MSFC are using Jack in conjunction with motion capture and virtual reality systems in MSFC's Virtual Environments Lab (VEL). The VEL provides additional capability beyond standalone Jack to record and analyze a person performing a planned task to assemble the SLS at Kennedy Space Center (KSC). The VEL integrates Vicon Blade motion capture system, Siemens Jack, Oculus Rift, and other virtual tools to perform human factors assessments. By using motion capture and virtual reality, a more accurate breakdown and understanding of how an operator will perform a task can be gained. By virtual analysis, engineers are able to determine if a specific task is capable of being safely performed by both a 5% (approx. 5ft) female and a 95% (approx. 6'1) male. In addition, the analysis will help identify any tools or other accommodations that may to help complete the task. These assessments are critical for the safety of ground support engineers and keeping launch operations on schedule. Motion capture allows engineers to save and examine human movements on a frame by frame basis, while virtual reality gives the actor (person performing a task in the VEL) an immersive view of the task environment. This presentation will discuss the need of human factors for SLS and the benefits of analyzing tasks in NASA MSFC's VEL.

Searcy, Brittani↗

NASA NTRSDate not supplied

Autonomous Spacecraft Inspection with Free-Flying Drones

This paper describes a proof-of-concept mission demonstrating a multi-agent system performing visual inspection of damage sustained by a spacecraft. Free-flying satellites, simulated by unmanned aerial vehicles (UAVs), autonomously fly around a mock space module maximizing the search space for damage detection. The free-flyers are responsible for independently coordinating their flights to avoid collision with the space module and each other, while executing mission tasks. Damage analysis on the surface of the mock space module is performed in real-time using video from each free-flyer. Three-dimensional modeling is deployed offline to supplement and improve damage detection. This approach demonstrates the feasibility of deploying real space systems for damage detection, where 2D analysis can quickly determine region of interest and 3D visualization can produce a human-navigable virtual environment with depth perspective for further investigation.

unmanned aerial vehicle (UAV)↗

NASA NTRSDate not supplied

Design Considerations for LTV HITL Testing of Pressurized Suited Crew on a Motion-Based Platform

The upcoming NASA Lunar Terrain Vehicle (LTV) will succeed the Apollo Lunar Roving Vehicle, performing both surface exploration and logistics transfer in NASA’s return to the Moon. Human-in-the-Loop (HITL) testing will play a key role in refining the design of the LTV, ensuring its usability and ability to accommodate the astronaut population. A motion-based platform and a lunar terrain and lighting model can simulate the conditions of the lunar south pole region. It can be used by NASA to conduct HITL testing in concert with HITL testing of the drivable Ground Reference Unit (GTU) concept vehicle. The dynamic motion of the platform combined with the mobility restrictions of pressurized suits could help improve NASA understanding of vehicle-suit-astronaut interfaces. NASA human factors practitioners have proposed multiple HITL test series to use the motion-based platform in conjunction with testing of the GTU in hopes that lessons learned can be applied to help select a commercial partner to develop the Artemis LTV.

LTV↗

NASA NTRS2016

Computational Study of Flow Interactions in Coaxial Rotors

Although the first idea of coaxial rotors appeared more than 150 years ago, most helicopters have used single main-rotor/tail-rotor combination. Since reactive moments of coaxial rotors are canceled by contra-rotation, no tail rotor is required to counter the torque generated by the main rotor. Unlike the single main rotor design that distributes power to both main and tail rotors, all of the power for coaxial rotors is used for vertical thrust. Thus, no power is wasted for anti-torque or directional control. The saved power helps coaxial rotors reach a higher hover ceiling than single rotor helicopters. Another advantage of coaxial rotors is that the overall rotor diameter can be reduced for a given vehicle gross weight because each rotor provides a maximum contribution to vertical thrust to overcome vehicle weight. However, increased mechanical complexity of the hub has been one of the challenges for manufacturing coaxial rotorcraft. Only the Kamov Design Bureau of Russia had been notably successful in production of coaxial helicopters until Sikorsky built X2, an experimental compound helicopter. Recent developments in unmanned aircraft systems and high-speed rotorcraft have renewed interest in the coaxial configuration. Multi-rotors are frequently used for small electric unmanned rotorcraft partly due to mechanical simplicity. The use of multiple motors provides redundancy as well as cost-efficiency. The multi-rotor concept has rarely been used until recently because of its inherent stability and control problems. However, advances in inexpensive electronic flight control systems have opened the floodgates for small drones using multirotors. Coaxial rotors have started to appear in some multi-rotor configurations. Small coaxial rotors have often been designed using a hundred year old approach that is "sketch, build, fly, and iterate." In that approach, there is no systematic way to explore trade-offs or determine logical next steps. It is neither possible to account for multiple real-world constraints up front in design nor possible to know what performance is possible with a given design. Since unmanned vehicles are sized and optimized for the particular mission, a modern low-fidelity conceptual design and sizing tool that has been used for the design of large helicopters can be used for design of small coaxial rotorcraft. However, unlike most helicopters with single main rotor, the interactions between the upper and lower rotors emerge as an important factor to consider in design because an increase in performance of a multi-rotor system is not proportional to the number of rotors. Interference losses and differences in thrusts between the upper and lower rotors were investigated by theoretical methods as well as a computational fluid dynamics (CFD) method using the Reynolds-Averaged Navier-Stokes (RANS) equations. In this work, hybrid turbulence models are used to investigate the physics of interactions between coaxial rotors and a fuselage that are not well understood. Present study covers not only small-scale drones but also large-scale coaxial rotors for heavy-lifting missions. Considering the recently proposed FAA drone rules that require the flight only in visual line-of-sight, a large multirotor might be used as an airborne carrier for launch and recovery of unmanned aircraft systems with a human operator onboard. For applications to civil operations, their aerodynamic performance and noise levels need to be assessed. Noise is one of the largest limiting factors to rotorcraft operations in urban area. Since the high-frequency noise of multi-rotors may increase the annoyance, noise may turn out to be a key issue that must be addressed for market acceptability. One of the objectives of the present work is to study the effects of inter-rotor spacing and collectives on the performance, efficiency, and acoustics of coaxial rotor systems.

Study↗

NASA NTRS1995

Managing Complexity in Multidisciplinary Visualization

As high performance computing technology progresses, computational simulations are becoming more advanced in their capabilities. In the computational aerosciences domain, single discipline steady-state simulations computed on a single grid are far from the state-of-the-art. In their place are complex, time-dependent multidisciplinary simulations that attempt to model a given geometry more realistically. The product of these multidisciplinary simulations is a massive amount of data stored in different formats, grid topologies, units of measure, etc., as a result of the differences in the simulated physical domains. In addition to the challenges posed by setting up and performing the simulation, additional challenges exist in analyzing computational results. Visualization plays an important role in the advancement of multidisciplinary simulations. To date, visualization has been used to aid in the interpretation of large amounts of simulation data. Because the human visual system is effective in digesting a large amount of information presented graphically, visualization has helped simulation scientists to understand complex simulation results. As these simulations become even more complex, integrating several different physical domains, visualization will be critical to digest the massive amount of information. Another important role for visualization is to provide a common communication medium from which the domain scientists can use to develop, debug, and analyze their work. Multidisciplinary analyses are the next step in simulation technology, not only in computational aerosciences, but in many other areas such as global climate modeling. Visualization researchers must understand and work towards the challenges posed by multidisciplinary simulation scenarios. This paper addresses some of these challenges, describing technologies that must be investigated to create a useful visualization analysis tool for domain scientists.

Miceli, Kristina D.↗

NASA NTRS2016

Utilizing the ISS Mission as a Testbed to Develop Cognitive Communications Systems

The ISS provides an excellent opportunity for pioneering artificial intelligence software to meet the challenges of real-time communications (comm) link management. This opportunity empowers the ISS Program to forge a testbed for developing cognitive communications systems for the benefit of the ISS mission, manned Low Earth Orbit (LEO) science programs and future planetary exploration programs. In November, 1998, the Flight Operations Directorate (FOD) started the ISS Antenna Manager (IAM) project to develop a single processor supporting multiple comm satellite tracking for two different antenna systems. Further, the processor was developed to be highly adaptable as it supported the ISS mission through all assembly stages. The ISS mission mandated communications specialists with complete knowledge of when the ISS was about to lose or gain comm link service. The current specialty mandated cognizance of large sun-tracking solar arrays and thermal management panels in addition to the highly-dynamic satellite service schedules and rise/set tables. This mission requirement makes the ISS the ideal communications management analogue for future LEO space station and long-duration planetary exploration missions. Future missions, with their precision-pointed, dynamic, laser-based comm links, require complete autonomy for managing high-data rate communications systems. Development of cognitive communications management systems that permit any crew member or payload science specialist, regardless of experience level, to control communications is one of the greater benefits the ISS can offer new space exploration programs. The IAM project met a new mission requirement never previously levied against US space-born communications systems management: process and display the orientation of large solar arrays and thermal control panels based on real-time joint angle telemetry. However, IAM leaves the actual communications availability assessment to human judgment, which introduces unwanted variability because each specialist has a different core of experience with comm link performance. Because the ISS utilizes two different frequency bands, dynamic structure can be occasionally translucent at one frequency while it can completely interdict service at the other frequency. The impact of articulating structure on the comm link can depend on its orientation at the time it impinges on the link. It can become easy for a human specialist to cross-associate experience at one frequency with experience at the other frequency. Additionally, the specialist's experience is incremental, occurring one nine-hour shift at a time. Only the IAM processor experiences the complete 24x7x365 communications link performance for both communications links but, it has no "learning capability." If the IAM processor could be endowed with a cognitive ability to remember past structure-induced comm link outages, based on its knowledge of the ISS position, attitude, communications gear, array joint angles and tracking accuracy, it could convey such experience to the human operator. It could also use its learned communications link behaviors to accurately convey the availability of future communications sessions. Further, the tool could remember how accurately or inaccurately it predicted availability and correct future predictions based on past performance. The IAM tool could learn frequency-specific impacts due to spacecraft structures and pass that information along as "experience." Such development would provide a single artificial intelligence processor that could provide two different experience bases. If it also "knew" the satellite service schedule, it could distinguish structure blockage from schedule or planet blockage and then quickly switch to another satellite. Alternatively, just as a human operator could judge, a cognizant comm system based on the IAM model could "know" that the blockage is not going to last very long and continue tracking a comm satellite, waiting for it to track away from structure. Ultimately, once this capability was fully developed and tested in the Mission Control Center, it could be transferred on-orbit to support development of operations concepts that include more advanced cognitive communications systems. Future applications of this capability are easily foreseen because even more dynamic satellite constellations with more nodes and greater capability are coming. Currently, the ISS fully employs a 300 million bit-per-second (Mbps) return link for harvesting payload science. In the coming eighteen months, it will step up to 600 Mbps. Already there is talk of a 1.2 billion bit-per-second (Gbps) upgrade for the ISS and laser comm links have already been tested from the ISS. Every data rate upgrade mandates more complicated and sensitive communications equipment which implies greater expertise invested in the human operator. Future on-orbit cognizant comm systems will be needed to meet greater performance demands aboard larger, far more complicated spacecraft. In the LEO environment, the old-style one-satellite-per-spacecraft operations concept will give way to a new concept of a single customer spacecraft simultaneously using multiple comm satellites. Much more highly-dynamic manned LEO missions with decades of crew members potentially increase the demand for communications link performance. A cognizant on-board communications system will meet advanced communications demands from future LEO missions and future planetary missions. The ISS has fledgling components of future exploration programs, both LEO and planetary. Further, the Flight Operations Directorate, through the IAM project, has already begun to develop a communications management system that attempts to solve advanced problems ideally represented by dynamic structure impacting scheduled satellite service. With an earnest project to integrate artificial intelligence into the IAM processor, the ISS Program could develop a cognizant communications system that could be adapted and transferred to future on-orbit avionics designs.

Jackson, Dan↗

DOE OSTI2021

Machine Intelligence to Detect, Characterise, and Defend against Influence Operations in the Information Environment

Social media has enabled a new era of manipulation in the information and cognitive domains. Deceptive content—misleading, falsified, and fabricated—is routinely created and spread in the modern social media environment with the intent to create confusion and widen political and social divides, and exploit the societal conflict exacerbated by these divides in the real-world (aka physical domain). Such disinformation campaigns demonstrate a threat to the integrity of economic, political, cultural, public health, and national security institutions around the world. In this work we overview our artificial intelligence (AI) capabilities to detect, describe, and defend against information operations on Twitter as an example social platform to understand the influence of misleading and falsified content diffusion and better enable those charged with defending against such manipulation to enable responsive parties to counter it. We first present novel linguistically-informed deep learning (DL) models for misinformation and disinformation detection, and present an in-depth linguistic analysis of psycho-linguistic markers across broad deception categories. We then demonstrate how our models perform in the multilingual and multimodal setting and categorize falsified and misleading content based on the intent to deceive. We also provide a large-scale analysis to describe user behavior and spread patterns while engaging with deceptive content and report novel findings about the immediate diffusion of deceptive content by characterizing the vulnerable sub-populations and their demographics, and explicitly measuring speed and scale of deception spread to uncover who shares deceptive content, how quickly, how much, and how evenly. In addition, we measure audience reactions to misinformation and disinformation at scale, distinguishing the reactions of users identified as bots versus humans. Finally, we take advantage of deep translation and generation models to create unique solutions for real-time defense against digital deception and discuss how to apply causal inference to prescribe and intervene into strategic communications jointly across information, cognitive, and physical domains.

artificial intelligence, deep learning, neural lan↗

NASA NTRSDate not supplied

Towards a Characterization of Scheduling Task Complexity

Future long-duration missions will require astronauts to act more autonomously, manage their schedules, and replan timelines as anomalies and discoveries occur. Astronauts are not professional planners, however, and the complexity of schedules that novice planners can complete successfully is not fully understood. To identify the primary factors which contribute to scheduling task complexity, we conducted a human-in-the-loop study and developed planning algorithms to investigate how the type and amount of constraints affect the difficulty of scheduling and rescheduling. We created rankings of difficulty using a combination of human performance metrics from experimental planning tasks and metrics describing the final plans that participants scheduled. Using the results of our scheduling and rescheduling algorithm algorithms, we created a similar ranking with which to compare. We created rankings which compared well between the experimental and algorithm results for the scheduling task, but the rescheduling task proved more difficult to estimate.

scheduling↗

NASA NTRSDate not supplied

Towards a Characterization of Scheduling Task Complexity

scheduling↗

NASA NTRS1996

Life and Microgravity Sciences Spacelab Mission: Human Research Pilot Study

The Life Sciences, Microgravity Science and Spacelab Mission contains a number of human experiments directed toward identifying the functional, metabolic and neurological characteristics of muscle weakness and atrophy during space flight. To ensure the successful completion of the flight experiments, a ground-based pilot study, designed to mimic the flight protocols as closely as possible, was carried out in the head-down tilt bed rest model. This report records the rationales, procedures, preliminary results and estimated value of the pilot study, the first of its kind, for 12 of the 13 planned experiments in human research. The bed rest study was conducted in the Human Research Facility at Ames Research Center from July 11 - August 28, 1995. Eight healthy male volunteers performed the experiments before, during and after 17 days bed rest. The immediate purposes of this simulation were to integrate the experiments, provide data in a large enough sample for publication of results, enable investigators to review individual experiments in the framework of a multi-disciplinary study and relay the experience of the pilot study to the mission specialists prior to launch.

Arnaud, Sara B.↗

NASA NTRS1998

Gravity of Living Systems: May the Force Be With You

Gravity, the force which shapes the architecture of organisms from single cells to dinosaurs, has been the most constant environmental factor during the evolution of species on Earth. With long-duration space flight, an understanding of how gravity affects living systems gains greater urgency in order to maintain the health and performance of crews who will explore the solar system. For example, the cardiovascular and musculoskeletal systems are normally exposed to gravitational gradients of blood pressure and weight on Earth. Such gradients increase blood pressure and tissue weight in dependent tissues of the body. Thus, from a physiologic standpoint, these systems are greatly affected by altered gravity. Exposure to actual and simulated microgravity causes blood and tissue fluid to shift from the legs to the head. Studies of humans in space have documented facial edema, space adaptation syndrome, decreased plasma volume, muscle atrophy, and loss of bone strength. Return of astronauts to Earth is accompanied by orthostatic intolerance, decreased neuromuscular coordination, and reduced exercise capacity. These factors decrease performance during descent from orbit and increase risk during emergency egress from the space craft. Models of simulated microgravity include 60 head-down tilt, immersion, and prolonged horizontal bedrest. Head-down tilt and dry immersion are the most accepted models and studies using these models of up to one year have been performed in Russia. Sensitive animal models which offer clear insights into the role of gravity on structure and function include the developing giraffe and snakes from various habitats. Finally, possible countermeasures to speed readaptation of astronauts to gravity after prolonged space flight include exercise, lower body negative pressure, and centrifugation.

Hargens, Alan R.↗

NASA NTRS2009

Implementation of an Adaptive Controller System from Concept to Flight Test

The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) was used for these algorithms. This airplane has been modified by the addition of canards and by changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals included demonstration of revolutionary control approaches that can efficiently optimize aircraft performance for both normal and failure conditions, and to advance neural-network-based flight control technology for new aerospace systems designs. Before the NF-15B IFCS airplane was certified for flight test, however, certain processes needed to be completed. This paper presents an overview of these processes, including a description of the initial adaptive controller concepts followed by a discussion of modeling formulation and performance testing. Upon design finalization, the next steps are: integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness.

Larson, Richard R.↗

NASA NTRS2016

Evidence Report: Risk of Acute and Late Central Nervous System Effects from Radiation Exposure

Possible acute and late risks to the central nervous system (CNS) from galactic cosmic rays (GCR) and solar particle events (SPE) are concerns for human exploration of space. Acute CNS risks may include: altered cognitive function, reduced motor function, and behavioral changes, all of which may affect performance and human health. Late CNS risks may include neurological disorders such as Alzheimer's disease (AD), dementia and premature aging. Although detrimental CNS changes are observed in humans treated with high-dose radiation (e.g., gamma rays and 9 protons) for cancer and are supported by experimental evidence showing neurocognitive and behavioral effects in animal models, the significance of these results on the morbidity to astronauts has not been elucidated. There is a lack of human epidemiology data on which to base CNS risk estimates; therefore, risk projection based on scaling to human data, as done for cancer risk, is not possible for CNS risks. Research specific to the spaceflight environment using animal and cell models must be compiled to quantify the magnitude of CNS changes in order to estimate this risk and to establish validity of the current permissible exposure limits (PELs). In addition, the impact of radiation exposure in combination with individual sensitivity or other space flight factors, as well as assessment of the need for biological/pharmaceutical countermeasures, will be considered after further definition of CNS risk occurs.

Nelson, Gregory A.↗

NASA NTRS2019

Hybrid Transportation System Integrated Trajectory Design and Optimization for Mars Landing Site Accessibility

NASA’s Mars Study Capability Team continues the agency’s efforts to study and refine the nation’s plan to field a sustainable human Mars campaign. One of the primary open issues left unanswered during previous analysis cycles was the uncertainty of the impact to the vehicle performance requirement to deliver crew and cargo to the same landing site across multiple mission opportunities. The Mars Study Capability Team has recently developed an integrated trajectory optimization and system closure model to solve the complex interplanetary trajectory optimization using both low-thrust and high-thrust maneuvers. This paper demonstrates the capability of this new integrated trajectory design and optimization method as it applies to the landing site accessibility problem for the Hybrid transportation architecture. The results showed that the current vehicle is capable of reaching up to +20 degree latitude and down to -20 degree latitude in every mission opportunity from 2033 to 2052. However, reaching latitudes beyond +/- 20 required more propellant than the spacecraft is currently designed to carry for many of the mission opportunities.

Chai, Patrick R.↗