Results for “risk mitigation” — Page 31

NASA NTRSDate not supplied

Evaluating the Relationships Between Supine Propriorception Assessments With Upright Functional Mobility and Balance Tests

- Sensorimotor adaptations during spaceflight can result in impaired posture and locomotion upon return to Earth. - In-flight sensorimotor countermeasures and assessment tools are needed to mitigate risks associated with mission-critical task performance upon return to Earth or arrival to Mars. - The tilt board (Fig. 1) is proposed as an inflight proprioceptive countermeasure and will be tested in an upcoming bed rest study. - Proprioceptive assessments on the tilt board may also help predict post-flight and post-bedrest functional task performance.

Rachel F. Bellisle↗

NASA NTRSDate not supplied

Space Launch System: Core Stage Thrust Vector Control Systems Engineering Challenges in Reusing Heritage Hardware

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of 8 mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. The Space Shuttle heritage hardware directly reused on SLS includes the Orbiter TVC hydraulic servo-actuators (with two slight design modifications), the Orbiter hydraulic circulation pumps, the Orbiter gimbal block/bearing, and the Solid Rocket Booster hydraulic pumps. The Core Auxiliary Power Unit (CAPU) is derived from the Orbiter Auxiliary Power Unit (APU). The Orbiter and Solid Rocket Booster APU turbines are powered by hot gas produced by catalyzed hydrazine decomposition. On the SLS Core Stage, the CAPU turbine is spun using cold gas tapped-off from the RS-25 to CS liquid hydrogen autogenous pressurization line. While direct reuse or slight modification of existing hardware may seem to be a triple-win for a program in cost, schedule, and technical risk mitigation, those benefits can only be realized when its degree of application in a new system is carefully and thoughtfully managed. The heritage hardware reuse should be prescribed within the heritage design capability and reuse environments must lie within the envelope of heritage qualification testing. Despite the significant test and flight experience of the Shuttle heritage hardware components, successful integration with the newly designed CS TVC components and incorporation into the stage design proved to be a challenge which required re-qualification of the heritage hardware as well as thorough integrated testing to support flight certification. Examples of the challenges that were overcome include: re-qualifying heritage hardware to survive new shock and vibration environments, certifying performance of extensively modified heritage hardware, regenerating design insight due to lack of available heritage vendor data, showing compliance to modern structural design standards, translation of heritage requirements for analog avionics to modern digital avionics, and interfacing heritage mechanical hardware with newly designed avionics. This paper is the second installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. This paper will discuss several engineering challenges encountered during the development process for SLS CS TVC and how they were successfully overcome to reach flight readiness.

Thrust Vector Control↗

NASA NTRSDate not supplied

Ground Test Technology Demonstration for Nuclear Thermal Propulsion Engines

Nuclear Thermal Propulsion (NTP) engines have been deemed a key technology to enable human missions to Mars due to their high efficiency, also known as specific impulse (Isp). Ground testing the NTP engine is critical in maturing the technology and increasing the design’s Technology Readiness Level (TRL), thus mitigating risk from NTP engine performance/operations. NTP engine development began with open-air ground testing through the Rover/NERVA program back in the 1960s when regulatory requirements were not as stringent as they are today. Due to the formation of regulatory bodies, increase in oversight and environmental requirements, the exhaust gas released from NTP engines must be captured or processed to gain approval in the case that the exhaust gas contains fission products from the nuclear fuel elements within the reactor. Ground test campaigns following Rover/NERVA focused on the certification of a full scale NTP engine, which led to exhaust processing systems such as the Rocket Exhaust Capture System (RECS) and Real Time (RT) exhaust processing. These systems were deemed favorable for regulatory compliance but have a high initial investment cost. Reassurance on the feasibility of ground testing and the NTP engine technology likely need to be achieved before NASA invests in these systems. Recently the objectives for NTP engine ground testing have shifted from certification testing of a full scale engine to demonstration testing of a subscale engine. The shift to demonstration testing allows for a shorter testing duration and a lower operational thrust (for demo testing purposes only) to demonstrate the NTP engine (5k-12.5k lbf). Due to these factors, the infrastructure, consumables, total footprint, and exhaust system complexity are able to be drastically reduced, thus reducing cost significantly. The High-pressure Exhaust Capture System (HECS) concept was designed for a NTP engine ground test demonstration. The HECS concept greatly reduces cost compared to previous concepts and suggests favorable regulatory acceptance due to its ability to capture all of the exhaust gas from the NTP engine.

Nuclear Thermal Propulsion↗

NASA NTRSDate not supplied

Sustaining NASA-Invented Thermal Protection System Materials for Future Missions

TPS is needed for NASA and many emerging commercial space missions and is dependent on an industrial base for future availability. Supply chains are dynamic and global. Change to constituent availability, after the fact, can impact missions. In addition to external vendor capability, NASA needs to maintain the in-house expertise and use SMEs to engage industry to assess the risk of atrophy on a constant basis and propose risk mitigation options to the Leadership as needed.

Matt Gasch↗

NASA NTRSDate not supplied

Nuclear Thermal Propulsion Engine Technology Demonstration Testing

Nuclear Thermal Propulsion (NTP) engines have been deemed a key technology to enable human missions to Mars due to their high efficiency, also known as specific impulse (Isp). Ground testing the NTP engine is critical in maturing the technology and increasing the design’s Technology Readiness Level (TRL), thus mitigating risk from NTP engine performance/operations. NTP engine development began with open-air ground testing through the Rover/NERVA program back in the 1960s when regulatory requirements were not as stringent as they are today. Due to the formation of regulatory bodies, increase in oversight and environmental requirements, the exhaust gas released from NTP engines must be captured or processed to gain approval in the case that the exhaust gas contains fission products from the nuclear fuel elements within the reactor. Ground test campaigns following Rover/NERVA focused on the certification of a full scale NTP engine, which led to exhaust processing systems such as the Rocket Exhaust Capture System (RECS) and Real Time (RT) exhaust processing. These systems were deemed favorable for regulatory compliance but have a high initial investment cost. Reassurance on the feasibility of ground testing and the NTP engine technology likely need to be achieved before NASA invests in these systems. Recently the objectives for NTP engine ground testing have shifted from certification testing of a full scale engine to demonstration testing of a subscale engine. The shift to demonstration testing allows for a shorter testing duration and a lower operational thrust (for demo testing purposes only) to demonstrate the NTP engine (5k-12.5k lbf). Due to these factors, the infrastructure, consumables, total footprint, and exhaust system complexity are able to be drastically reduced, thus reducing cost significantly. The High-pressure Exhaust Capture System (HECS) concept was designed for a NTP engine ground test demonstration. The HECS concept greatly reduces cost compared to previous concepts and suggests favorable regulatory acceptance due to its ability to capture all of the exhaust gas from the NTP engine.

Nuclear Thermal Propulsion↗

NASA NTRS2023

An In-time Aviation Safety Management System (IASMS) Concept of Operations for Vertiport Design and Operations

The National Airspace System is foreseen to undergo revolutionary change with Urban Air Mobility (UAM) and its use of vertiports to transport passengers and cargo. To assure safety with UAM and more broadly with Advanced Air Mobility (AAM), the National Academies recommended an In-time Aviation Safety Management System (IASMS) that is extensible to the design and operation of vertiports. Vertiport designs will scale in several dimensions including physical size and infrastructure depending upon location and in the Services, Functions, and Capabilities required for assuring safety with increasingly complex vertiport designs and operations. These operations will be enabled by evolving technologies including electric vertical takeoff and landing (eVTOL) aircraft for passenger-and cargo-carrying commercial transportation. Within this construct, safety hazards and risk mitigations involving predictive data analytics and modeling will be used. Use cases and future challenges are examined to guide maturation of the IASMS ConOps for vertiports.

K Ellis↗

NASA NTRSDate not supplied

Active Swarm Resiliency in the HelioSwarm Mission

Designed to observe plasma turbulence dynamics in solar wind over a distributed volume of space, the HelioSwarm mission comprises a primary chief spacecraft and eight smaller deputy satellites in uniquely assigned “loops” of periodic relative motion in a P/2 lunar resonant orbit. If one or more deputies fail, this multi-satellite architecture facilitates resiliency for science goals through repositioning of satellites to contingency loops. This strategy of Active Swarm Resiliency mitigates risk by modeling quantitative results ahead of time for mission operators to make informed decisions. Responsive actions meet minimum science objectives based on past and predicted system performance, an approach with applications to future missions with similar architecture and requirements.

Fault Management↗

NASA NTRSDate not supplied

Jettison and Disposal from Near Rectilinear Halo Orbits, Part 1: Theory

The proposed Gateway spacecraft in a Near Rectilinear Halo Orbit (NRHO) will be a human outpost in cislunar space. The baseline mission may experience the deployment of visiting vehicles, cubesats, and on-orbit debris. Departure from the NRHO and cislunar space is nontrivial due to the complex gravitational environment that persists in and around Gateway. Long-term disposal orbits in heliocentric space offer safe destinations for deployed objects. To mitigate risks associated with conjunctions between Gateway and deployed objects, strategies to identify risk-avoidant paths to heliocentric space are necessary for Gateway mission operations.

Stephen T. Scheuerle↗

NASA NTRSDate not supplied

Active Swarm Resiliency in the HelioSwarm Mission

Designed to observe plasma turbulence dynamics in solar wind over a distributed volume of space, the HelioSwarm mission comprises a primary chief spacecraft and eight smaller deputy satellites in uniquely assigned “loops” of periodic relative motion in a P/2 lunar resonant orbit. If one or more deputies fail, this multi-satellite architecture facilitates resiliency for science goals through repositioning of satellites to contingency loops. This strategy of Active Swarm Resiliency mitigates risk by modeling quantitative results ahead of time for mission operators to make informed decisions. Responsive actions meet minimum science objectives based on past and predicted system performance, an approach with applications to future missions with similar architecture and requirements.

Fault Management↗

NASA NTRSDate not supplied

Advanced Supersonic Parachute Inflation Research and Experiment-2 (ASPIRE2) Flight Mechanics Modeling and Simulation

Introduction: The Advanced Supersonic Para-chute Inflation Research Experiment-2 (ASPIRE2) program is a sounding rocket flight test to be conducted at Wallops Island, VA in early 2025. This program is a risk mitigation exercise for the Mars Sample Retrieval Lander (MSRL) program and builds upon the success of the 2017 & 2018 ASPIRE program, [1,2]. While the ASPIRE program certified the strengthened 21.5 m diameter disk-gap-band (DGB) deployed at Mach 1.7, ASPIRE2 will certify a 24 m diameter DGB deployed at Mach 2.1. The need to certify this increased parachute performance is driven the increased lander mass for MSRL; over 50% increase in comparison to M2020. Modeling: Like its predecessor, ASPIRE2 is developing a multi-body flight dynamics simulation to predict parachute dynamics and aide in designing the flight test that will target Mars-relevant flight conditions, as shown in Figure 1. This work de-scribes the parachute modeling, flight mechanics simulations (from payload separation to splash-down), and design trades used to prepare for the 2025 ASPIRE2 flight. Discussed herein are comparisons between ASPIRE and ASPIRE2, noting key differences in the parachute modeling and vehicle configuration. A study on the attitude control system performance impacts with respect to payload section design will also be presented. This work will quantify the pre-flight parachute performance in the presence of uncertainties, such as those associated with the separation from the sounding rocket, atmosphere, the parachute system, and vehicle mass. The pre-flight predictions will include Monte Carlo analyses, powered by the flight mechanics simulations to show the ASPIRE2 vehicle performance in meeting program requirements on parachute deployment conditions (Mach & dynamic pressure), parachute loads, vehicle attitude at key milestones, and the vehicle splashdown conditions.

Entry Descent and Landing↗

NASA NTRS2022

Flood Monitoring Using Enhanced Resolution Passive Microwave Data: A Test Case Over Bangladesh

Monitoring floods is a major issue in water resources management and risk mitigation, especially in the Global South. Optical and radar observations, even providing a fine spatial resolution, are still limited by cloud cover interaction or insufficient temporal resolution. On the other hand, passive microwave (PMW) sensors collect information on a daily frequency with minor cloud cover interaction, but they have been historically limited in terms of spatial resolution. Here, we evaluate the capability of an enhanced spatial resolution PMW dataset (3.125 km) in monitoring spatio-temporal evolution of flood events, focusing on a major flood event that occurred in October 2005 in Bangladesh. We apply an algorithm aimed to remove the seasonal variability of surface temperature from the PMW timeseries, exploiting the difference in emissivity between dry and water-covered pixels. We assess the capability of the algorithm in capturing flood evolution and extension through the comparison with quantities obtained from optical data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and water level measurements. We also compare the enhanced product with the historical coarser resolution dataset by means of a variogram-based analysis to evaluate the improvements in terms of spatial representation. Finally, we evaluate the possibility to extract the water fraction within a single pixel by using an Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) emissivity dataset and compare the estimates with MODIS-derived water fractions. Our results show that the enhanced PMW product outperforms the coarser one when compared to flood mapped from optical data based on information content, indicating that it is possible to integrate such a product into the mapping of floods at a global scale on a daily basis.

flood detection↗

NASA NTRSDate not supplied

Artemis IV Docking in Radiation Belt Charging Environment

NASA’s Artemis IV mission is planned to deliver the International Habitation Module (I-Hab) to the Gateway space station in lunar orbit. The I-Hab will be launched aboard the Space Launch System (SLS) vehicle as a co-manifested payload with the Orion spacecraft. After translunar injection begins, the Orion spacecraft will separate from the SLS Exploration Upper Stage (EUS) and then dock with the I-Hab to extract it from the EUS. Because of the altitude, orientation, and time for this to occur, the vehicle-to-vehicle potential between the I-Hab/EUS vehicle and Orion spacecraft could exceed several thousand volts. The docking of these two spacecrafts with such large differential potentials presents a challenge for the vehicles. This presentation describes the space environments at the docking altitude, the calculated vehicle-to-vehicle potential, and the possible impacts of the resulting voltage and current transients occurring at first contact. Additionally, possible risk mitigation tests to demonstrate compatibility with the transient current and voltages will be presented.

Matthew Mccollum↗

NASA NTRSDate not supplied

Manual Crew Override of Vehicle Landings Following G-Transitions

BACKGROUND Manual control during exploration spaceflight consists of both planned automated supervisory control and unplanned crew override. This crew override capability is critical to enable overall mission success during landing contingencies. However, the introduction of manual override capabilities must be implemented to enable crews to mitigate risks introduced by human error. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. While training and landing aids enable successful landing through disorientation, these adaptive changes may increase cognitive demand that needs to be accounted for in the manual control strategy. It is important to characterize these effects as soon as possible following the G-transition to develop appropriate countermeasures. METHODS In this study, we will examine operational piloting tasks following International Space Station (ISS) missions in a simulated lunar landing using a six-degree-of-freedom (6DOF) motion base. The motion-based simulation will be implemented in our laboratory at the Johnson Space Center (JSC) and will be available within hours following the return from commercial crew landings. The primary goals of this study are (1) to understand the impact of spaceflight on crew ability to perform manual crew override tasks, (2) to examine how adaptive changes in vestibular and cognitive function relate to changes in manual crew override proficiency, and (3) compare performance during late “just-in-time” on-board training with early post-flight crew performance. The impact of spaceflight on piloting capability will be assessed from pre- versus post-flight changes in crewmembers assigned to either short duration (< 30 day) or long duration (~6- month) missions to the International Space Station (ISS). Individual differences in post-flight vestibular and cognitive changes include motion sickness reports, measures of tilt motion perception accuracy and precision, and dual-task tracking. During the 6DOF lunar simulation, the crew will manually takeover attitude and rate-of-descent to the nominal or re-designated landing aim point during the approach phase. The outcome measures for the lunar crew override tasks will be the percent time maintaining actual vehicle states, e.g., attitude and rate-of-descent, within recommended guidance during the landing approach, number and maximum deviation outside limits, and root mean square error (RMSE). Given that “just-in-time” (JIT) training is an operational expectation for the Human Landing System (HLS) program, all participants will perform late inflight JIT training for each manual crew override task in which they will participate. Crew proficiency will be captured inflight during JIT training that will be implemented on a laptop with hand controllers to allow the crewmember to practice the landing task procedures like the approach implemented for JIT training with Shuttle landing and ISS telerobotic tasks. COUNTERMEASURE UPDATES The lunar lander simulation has been implemented onto a two-laptop display system where subjects select from alternative landing points, based upon avoiding hazards that the on-board system identifies during the landing. The subject makes inputs using a rotational hand controller (i.e., joystick) and a translational hand controller, which are processed by simulated vehicle dynamics to update the vehicle attitude and rate of descent. Subjects will utilize a combination of flight, situation, and status displays to monitor the state of the simulated vehicle. The simulation exports tilt and translation movements to a 6DOF motion base synced to visual movements and provides representative vestibular cues to the subject while performing the task inside an enclosed cabin featuring a simulated lunar out-the-window view and a heads-down lander cockpit view. RELEVANCE This project will deliver an operational demonstration of crew override capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew override performance will help better characterize the manual control risks associated with sensorimotor alterations. The inclusion of “just-in-time” on-board training will ensure we are characterizing changes in override proficiency with this expected countermeasure in place. ACKNOWLEDGEMENTS: The authors acknowledge contributions from Draper, HLS Joint Test Panel, Crew HLS Interfaces for Piloting Working Group, and Dynamic Skills Trainer (DST) Lab toward the development of the lunar landing simulation. This project is funded by the Human Health Countermeasures Element.

Austin M Bollinger↗

NASA NTRSDate not supplied

Human-Autonomy Teaming Assistant to Support Small Uncrewed Aircraft Systems for Wildland Firefighting Operations

An exploratory human-in-the-loop simulation was conducted to investigate and characterize a Human-Autonomy Teaming (HAT) Assistant to support a remote operator of multiple small Uncrewed Aircraft Systems (sUAS) using a ground control station (GCS) in the context of a wildland fire surveillance mission. Operator performance using the GCS with the HAT Assistant (Assisted Mode) was compared to operator performance using the GCS without the HAT Assistant (Unassisted Mode) during two types of contingency-event scenarios (Low and High Complexity). In the Assisted Mode, the HAT Assistant provided updates to the level of risk to the mission along with recommendations for risk mitigation, which were not provided in the Unassisted Mode. No significant differences in objective performance and subjective ratings of workload, situation awareness, and trust in automation between the Assisted and Unassisted Modes were detected, however there were indications that participants preferred the Assisted GCS over the Unassisted GCS and directions for further development were explored. Additional work is necessary to further refine the HAT Assistant and better characterize its effects on remote operator performance while managing multiple sUAS assets. Future work is recommended to optimize the implementation of an assistant to support operator performance during different missions and across vehicle classes.

Human-Autonomy Teaming↗

NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗

NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben Phillips↗

NASA NTRSDate not supplied

Setting the Bar for the Replacement of the Probability of Collision Metric

Recent research in satellite conjunction risk assessment has levelled a number of criticisms at the probability of collision (Pc) parameter as a durable statement of satellite collision likelihood, and a number of different alternatives to this calculation have been proposed. Many of these proposals, however, stop at the outlining of the theory and do not discuss the additional philosophical and practical issues that must be confronted in evaluating such proposals for adoption. The present work seeks to outline some of these philosophical and practical considerations, and therefore the kinds of analyses and profiling that will be needed before the Pc, which is at present nearly universally adopted in the conjunction risk mitigation community, can be replaced with a new (and superior) paradigm and associated metric.

conjunction assessment↗

NASA NTRSDate not supplied

Green Propulsion : A NASA GSFC Assessment

In the ever-changing paradigm of efficient and capable spacecraft design, scientific missions continue pushing spacecraft subsystems to deliver effective solutions to meet challenging new mission/spacecraft applications. From an in-space storable liquid chemical propulsion perspective, monopropellant hydrazine is a dependable propellant. Bi-propellant architectures offer even superior performance, but add the complexity of a hypergolic fuel (hydrazine/ mono-methyl hydrazine) and oxidizer (Nitrogen Tetroxide/ mixed oxides of nitrogen) dual tank combination. These propulsion system designs (mono-propellant and bi-propellant) have high heritage, high propellant throughput qualified engines, widely tested material compatibility, qualified fluid delivery commercial-off-the-shelf components, known handling practices, and repeatable performance in successfully delivering on mission requirements. NASA and the broader propulsion community have historically selected hypergolic propellants for most mission applications. The space propulsion community has learned to successfully handle these highly toxic and hazardous materials, navigate the regulated use and the associated safety protocols, personnel protective equipment, and unique training standards – all requisite for loading spacecraft propulsion systems with hypergolic propellants. The question now arises as to what is next for in-space chemical propulsion? Is there an alternative, or even replacement, to the reliable hypergolic fluids, or propellant alternatives that promise increased mission benefits? With the evolution and proven advancements in innovative in-space green propellant technologies capable of delivering benefits to scientific missions, concern over the reliability and infusibility of this higher performing and safer to handle class of propellants is waning. As NASA science missions move forward with the potential flight infusion of green propulsion, NASA and the broader propulsion community are working to address remaining gaps in hardware development, reliability, performance, unique operational considerations, and risk mitigations for high value scientific assets.

Henry W. Mulkey↗