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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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At least 73 records · Page 4

Mid-Lift-to-Drag Ratio Rigid Vehicle Control System Design and Simulation for Human Mars Entry

The Mid-Lift-to-Drag Ratio Rigid Vehicle (MRV) is a proposed candidate in the NASA Evolvable Mars Campaign's (EMC) Pathfinder Entry, Descent, and Landing (EDL) architecture study. The purpose of the study is to design a mission and vehicle capable of transporting a 20mt payload to the surface of Mars. The MRV is unique in its rigid, asymmetrical lifting-body shape which enables a higher lift-to-drag ratio (L/D) than the typical robotic Mars entry capsule vehicles that carry much less mass. This paper presents the formulation and six-degree-of-freedom (6DOF) performance of the MRV's control system, which uses both aerosurfaces and a propulsive reaction control system (RCS) to affect longitudinal and lateral directional behavior.

mars↗

Multidisciplinary Optimization of Urban-Air-Mobility Class Aircraft Trajectories with Acoustic Constraints

The design and analysis of on-demand mobility class vehicles will require thorough acoustic analysis to ensure that more numerous aircraft can operate in densely populated areas without causing excessive levels of noise. This work is a step towards a comprehensive ODM vehicle analysis capability. The authors use 6DOF equations of motion to model the electric quad-rotor concept developed by NASA's Revolutionary Vertical Lift Technologies program. As a first step towards acoustic analysis, this trajectory is coupled to an acoustic model that tracks the sound pressure level perceived by an acoustic observer on the ground. The results show that the approach is successful in finding trajectories that minimize total propulsive impulse while obeying limits imposed on the sound pressure level. Future work will involve adding acoustic analysis of increasing fidelity and tying the resulting trajectories to the performance of the electric propulsion system.

electric aircraft↗

Dynamics and Control of Quadcopter in Uncertain Environment

We consider problem of dynamics, control, and uncertainty quantification for quadcopter. We use the 6DOF model of quadcopter dynamics, linear quadratic regulator and linear quadratic Gaussian control of quadcopter in the presence of dynamical disturbances, measurement noise, hidden dynamical variables, dashing GPS signal, and wind gusts to predict quadcopter trajectory. We identify key sources of uncertainties and report on progress in development of a system that estimates the probability of safety-critical events using a set of algorithms based on the trajectory predictions.

uncertainty quantification↗

Mid-Lift-to-Drag Ratio Rigid Vehicle 6-DOF EDL Performance Using Tunable Apollo Powered Guidance

The Mid-Lift-to-Drag ratio Rigid Vehicle (MRV) is a candidate in the NASA multi-center effort to determine the most cost effective vehicle to deliver a large-mass payload to the surface of Mars for a human mission. Products of this effort include six-degree-of-freedom (6DoF) entry-to-descent trajectory performance studies for each candidate vehicle. These high fidelity analyses help determine the best guidance and control (G&C) strategies for a feasible, robust trajectory. This paper presents an analysis of the MRV's G&C design by applying common entry and descent associated uncertainties using a Fully Numerical Predictor-corrector Entry Guidance (FNPEG) and tunable Apollo powered descent guidance.

human↗

Simulation and Testing of the Range of Motion of a Six Degree of Freedom Docking System

The soft capture system of the NASA Docking System (NDS) is a mechanism with six-degrees of freedom (6DOF). Although the nominal motion of the system is simple and largely in a single degree of freedom, complex movement is permissible within the requirements for docking. As such it is critical in the design, test, and verification of the docking system to fully understand the range of possible movement of the mechanism. This range of motion (ROM) must be large enough to accommodate all permitted docking sequences without internal collisions. This paper will discuss the methods used to perform these analysis for the NDS. Additionally, the testing sequences derived from this analysis will be presented, as illustrated in Figure 1. Finally, lessons learned from the analysis and test program will be discussed.

Docking System↗

Mid Lift-to-Drag Ratio Rigid Vehicle 6-DoF Performance for Human Mars Entry, Descent, and Landing: A Fractional Polynomial Powered Descent Guidance Approach

Defining a feasible vehicle design and mission architecture capable of reliably delivering apayload of 20 metric tons (mt) or more is a great challenge for landing humans on Mars. TheMid Lift-to-Drag Rigid Vehicle (MRV), a rigid decelerator studied in NASA’s Entry, Descent,and Landing Architecture Study (EDLAS), has shown to be a viable vehicle candidate forfuture human Mars missions. As the vehicle concept matures, models of increasing fidelity areadded to the six-degree-of-freedom (6DoF) EDL simulation. This paper presents 6DoFsimulation results using model updates for vehicle mass properties, fineness ratio, andaerodynamic-propulsive interactions. Additionally, an assessment of the Fractional-Polynomial Powered Descent Guidance (FP2DG) performance is presented, and the vehicleperformance is compared with the Tunable Apollo Powered Descent Guidance (TAPDG).Finally, Monte Carlo results of the vehicle design trades are presented.

Johnson, Breanna J.↗

Mid-Lift-To-Drag Ratio Rigid Vehicle 6-DOF EDL Performance Using Tunable Apollo Powered Guidance

The Mid-Lift-to-Drag ratio Rigid Vehicle (MRV) is a candidate in the NASA multi-center effort to determine the most cost effective vehicle to deliver a large-mass payload to the surface of Mars for a human mission. Products of this effort include six-degree-of-freedom (6DoF) entry-to-landing trajectory performance studies for each candidate vehicle. These high fidelity analyses help determine the best guidance and control (G&C) strategies for a feasible, robust trajectory. This paper presents an analysis of the MRV's G&C design by applying common entry and descent associated uncertainties using a Fully Numerical Predictor-corrector Entry Guidance (FNPEG) and tunable Apollo powered descent guidance.

Johnson, Breanna J.↗

Guidance and Navigation Challenges for a Mars Ascent Vehicle

This work presents studies and analysis in support of a Mars Ascent Vehicle as part of a Martian Sample Return campaign. The vehicle design has been ongoing, with rapid development of a 6 Degree of Freedom simulation to capture full vehicle dispersions and integrated performance of vehicle, guidance, navigation and control. The maturation of this simulation is presented to provide an overview of its capabilities added over the past year of effort. The results describe in detail guidance algorithm development to increase the system’s robustness to thrust sensitivities. Navigation performance and sensitivity analysis are included to describe the capabilities of the current design as well as identify primary drivers of insertion performance. Lastly, integrated vehicle 6DOF statistical results are presented to provide insight into the nominal performance of the current vehicle and insight into system-level drivers. Future work is described to outline the continuing maturation and development of the MSR MAV ascent vehicle.

Anzalone, Evan↗

Development of a Trajectory-Centric CFD-RBD Framework for Advanced Multidisciplinary/Multiphysics Simulation

The desire to model increasingly complex unsteady flow phenomena drives coupling of physics-based disciplinary analysis tools, such as coupled aerodynamics-rigid body dynamics simulations. This paper documents the creation of a framework linking the six-degree-of-freedom trajectory propagator POST2 with NASA’s FUN3D computational fluid dynamics flow solver. Cross-code verification between the framework and a CFD-centric 6DOF code is performed using the Army-Navy Finner projectile experiencing unsteady accelerating flow. Free-flight simulations of an entry vehicle ballistic range test are validated against physical and computational experiments.

Zachary J Ernst↗

Development of a Trajectory-Centric CFD-RBD Framework for Advanced Multidisciplinary/Multiphysics Simulation

The desire to model increasingly complex unsteady flow phenomena drives coupling of physics-based disciplinary analysis tools, such as coupled aerodynamics-rigid body dynamics simulations. This paper documents the creation of a framework linking the six-degree-of-freedom trajectory propagator POST2 with NASA’s FUN3D computational fluid dynamics flow solver. Cross-code verification between the framework and a CFD-centric 6DOF code is performed using the Army-Navy Finner projectile experiencing unsteady accelerating flow. Free-flight simulations of an entry vehicle ballistic range test are validated against physical and computational experiments.

Zachary J Ernst↗

Attitude Profile Reference for the Earth Orbit Raising Phase of NASA Gateway’s Co-Manifested Vehicle

As part of NASAs lunar exploration Artemis program, the agency is designing a Gateway to orbit8near the moon and provide long term support of a sustained lunar presence at the moon’s south pole.9The first element launched for the Gateway is the Co-Manifested Vehicle (CMV), comprised of the10Power and Propulsion Element (PPE) and Habitation and Lunar Outpost (HALO). The PPE Mission11Design team of McGuire & et. al (2021) has developed a Design Reference Mission (DRM) trajectory12for CMV’s Earth Orbit Raising (EOR) mission phase, which provides the vehicle’s 3 degrees of freedom13(DoF) trajectory information during the approximately yearlong spiral out from low Earth orbit and14into the lunar near-rectilinear halo orbit (NRHO). In tandem, the PPE GN&C team is developing a15high-fidelity and fine temporal resolution 6DoF model of the CMV spacecrafts GN&C performance16for delivery to the Gateway team; this work acts to bridge the gap between Mission Designs 3DoF17reference and detailed GN&Cs attitude simulation.

Guidance Navigation and Control↗

Convex Optimization Guidance for Precision Landing on Titan

Precision landing is an anticipated technology for future interplanetary missions. Autonomous spacecraft Entry, Descent and Landing (EDL) on the surface of a planetary body with a degree of precision in the order of meters is highly challenging. In this paper, a successive convexification guidance algorithm is utilized to simulate autonomous precision landing sequences on Saturn’s moon Titan. Due to its unique geophysical features, studying the science of matter within Titan’s atmosphere and beneath its surface is one of NASA’s most important planetary science objectives. As part of the Space Exploration Technology Directorate, a parafoil is proposed for landing on Titan due to its cost effectiveness, ease of deployment, low mass compared to the prospective payload and capabilities of precise autonomous delivery. This paper focuses on path optimization and guidance law development for high-fidelity dynamics parafoil tuning in the dense and adverse wind atmosphere of Titan, defined as a nonlinear and nonconvex optimal control problem. The powerful successive convexification method is used to solve the problem accordingly. The algorithm is designed such that the converged solution adheres to the nonlinear dynamics and kinematics in accordance with the original formulation, while respecting the state and control constraints. The six-degree-of-freedom (6DoF) simulations results show that this robust method is suitable for autonomous interplanetary applications.

Mooij, Edwin↗

Robust Vision-based Multi-spacecraft Guidance Navigation and Control using CNN-based Pose Estimation

In this paper, we present an end-to-end simulation framework for tracking an uncooperative Target spacecraft in Low Earth Orbit using a CubeSat-class Ego spacecraft outfitted with a camera. Currently, capturing high-fidelity realistic images in space for this scenario is difficult and exorbitantly expensive. Therefore, we developed a framework to simulate the spacecraft orbits in Basilisk software and generate high-fidelity realistic images of spacecraft in Unreal Engine, including the effects from Sun, Earth, Moon and stars. The Ego spacecraft uses cameras to capture images of the uncooperative Target and estimates its position and attitude using a CNN based 6DOF pose estimation pipeline, eliminating need for large SWAP-C(Size, Weight, Power and Cost) sensors like LIDAR or reliance on inter-spacecraft communication, This CNN, which is motivated by ESA’s Pose Estimation challenge of 2019, is trained using simulated data from our end-to-end simulation framework. We compare the performance of two distinct CNNbased algorithms for pose estimation along a nominal trajectory. In presence of non-Gaussian modeling uncertainties, the statedependent estimation error is characterized with a quadratic upper-bound. The quadratically-bounded error can be used by a robust controller to maneuver

Rahmani, Amir↗

Assessments of Physiology and Cognition in Hybrid-Reality Environments (APACHE) – A VR “Sandbox” for Planetary Spacewalk Research

NASA is planning to return to the Moon in the mid-2020s as a steppingstone to Mars missions in the 2030s. Spacewalks, or extravehicular activities (EVAs), performed on the Moon and Mars will differ in a variety of ways from those that have been performed in decades past. NASA has identified multiple risks to human health and performance associated with a crewed mission to Mars, especially those associated with exploration EVAs which are expected to be a primary mission activity. Crew may be expected to conduct up to 24 hours of EVA per person per week, where the likelihood of injury and/or mental mistakes are increased compared to ground-based training or current microgravity EVAs and the consequences of which can be catastrophic. Current test environments for exploration EVA research and technology development are large, costly facilities that are limited in their availability or capabilities. Spacesuit testing in a reduced gravity environment such as NASA’s Neutral Buoyancy Laboratory, while a good representation of the crew’s physical workload during exploration EVAs, typically has small datasets and is difficult to integrate physiological sensors or other types of crew performance measures. Meanwhile, scientific field-based testing such as NASA’s Desert Research and Technology Studies offers an operationally relevant environment for exploration EVAs, particularly for cognitive workload, but is also limited by small datasets, lack of a pressurized spacesuit, and obtrusive measures. The limitations of current analogs for exploration EVAs identify a need for a new test environment that can approximate both the physical and cognitive demands associated with exploration EVAs to enable rapid, controlled, and repeatable evaluations of human health and performance risks of exploration missions. In response, the Human Physiology, Performance, Protection, and Operations Laboratory (H-3PO) at NASA Johnson Space Center has developed a hybrid reality exploration EVA analog named the Assessments of Physiology And Cognition in Hybrid-reality Environments (APACHE)[ to address these limitations using a combination of virtual, physical, and hybrid reality techniques. The APACHE facility resides at NASA Johnson Space Center and serves as a large “sandbox” for EVA research and simulation. At its center is a roughly 15x20ft space surrounded by a 14” tall sandbox partially filled with lunar regolith simulant to emulate the physical feeling of walking on a planetary surface and to allow for simulated geology operations. Nearby, a curved passive treadmill (Skillmill Connect, Technogym, Fairfield, NJ) and an omnidirectional treadmill (Infinadeck, Infinadeck, Rocklin, CA) are included to enable exploration of these large virtual environments while also imposing the physical demands, representative timelines, and cognitive burdens required to navigate and traverse these distances during exploration EVA. A 6DOF motion platform is used to simulate rover operations and supports various human performance evaluations and associated risks. Lastly, APACHE can support two extravehicular (EV) crewmembers working in tandem. A computer workstation is located nearby and also supports an intravehicular (IV) crewmember as part of a full mission simulation. The IV crewmember has direct video and audio communication with the EV crew in VR to provide operational and procedural support.

Human Performance↗

Assessments of Physiology and Cognition in Hybrid-Reality Environments (APACHE)

NASA is planning to return to the Moon in the mid-2020s as a stepping stone to Mars missions in the 2030s. Spacewalks, or extravehicular activities (EVAs), performed on the Moon and Mars will differ in a variety of ways from those that have been performed in decades past. NASA has identified multiple risks to human health and performance associated with a crewed mission to Mars, especially those associated with exploration EVAs which are expected to be a primary mission activity. Crew may be expected to conduct up to 24 hours of EVA per person per week, where the likelihood of injury and/or mental mistakes are increased compared to ground-based training or current microgravity EVAs and the consequences of which can be catastrophic. Current test environments for exploration EVA research and technology development are large, costly facilities that are limited in their availability or capabilities. Spacesuit testing in a reduced gravity environment such as NASA’s Neutral Buoyancy Laboratory, while a good representation of the crew’s physical workload during exploration EVAs, typically has small datasets and is difficult to integrate physiological sensors or other types of crew performance measures. Meanwhile, scientific field-based testing such as NASA’s Desert Research and Technology Studies offers an operationally relevant environment for exploration EVAs, particularly for cognitive workload, but is also limited by small datasets, lack of a pressurized spacesuit, and obtrusive measures. The limitations of current analogs for exploration EVAs identify a need for a new test environment that can approximate both the physical and cognitive demands associated with exploration EVAs to enable rapid, controlled, and repeatable evaluations of human health and performance risks of exploration missions. In response, the Human Physiology, Performance, Protection, and Operations Laboratory (H-3PO) at NASA Johnson Space Center has developed a hybrid reality exploration EVA analog named the Assessments of Physiology And Cognition in Hybrid-reality Environments (APACHE) to address these limitations using a combination of virtual, physical, and hybrid reality techniques. The APACHE facility resides at NASA Johnson Space Center and serves as a large “sandbox” for EVA research and simulation. At its center is a roughly 15x20ft space surrounded by a 14” tall sandbox partially filled with lunar regolith simulant to emulate the physical feeling of walking on a planetary surface and to allow for simulated geology operations. Nearby, a curved passive treadmill (Skillmill Connect, Technogym, Fairfield, NJ) and an omnidirectional treadmill (Infinadeck, Infinadeck, Rocklin, CA) are included to enable exploration of these large virtual environments while also imposing the physical demands, representative timelines, and cognitive burdens required to navigate and traverse these distances during exploration EVA. A 6DOF motion platform is used to simulate rover operations and supports various human performance evaluations and associated risks. Lastly, APACHE can support two extravehicular (EV) crewmembers working in tandem. A computer workstation is located nearby and also supports an intravehicular (IV) crewmember as part of a full mission simulation. The IV crewmember has direct video and audio communication with the EV crew in VR to provide operational and procedural support. The software used in APACHE was created by the JSC Engineering Directorate, in partnership with Buendea, powered by a custom Unreal Engine 5 (UE5.3, Epic Games) project. APACHE currently utilizes the HTC Vive Pro Eye in a wireless configuration for VR simulations. There are two virtual environments that subjects can explore within APACHE, a Lunar and Martian surface. The virtual Lunar surface was created from LIDAR data of the Lunar South Pole to create roughly 16 sq km of explorable terrain. The virtual Martian surface contains roughly 400 sq km of explorable terrain derived from Mars Reconnaissance Orbiter LIDAR data of the Jezero Crater. The immersion and related cognitive burdens of conducting a planetary EVA is simulated through a series of EVA-relevant tasks performed in the VR environment, using these high-fidelity visual representations. Additionally, APACHE includes biosensor driven informatics, such as real-time heart rate monitoring and/or derived values from model simulations, for active monitoring by the EV crew and added cognitive demand. A “Wizard of Oz” control panel enables test operators to activate contingency events such as simulated spacesuit malfunctions, loss of communications, and/or limited visibility. Embedded performance measures such as accuracy, completeness, and execution time have been developed for various exploration tasks to objectively quantify crew performance during an EVA and compare impacts to performance when different environmental stressors, both physical and cognitive, are added to or removed from the simulation. Additionally, validated cognitive and operational performance measures such as the Digit Symbol Substitution Task have been recreated and embedded in VR for direct and relatively unobtrusive measurement of motor perception. The APACHE environment currently supports multiple research studies at NASA. Examples include the CHAPEA project, a series of simulated year-long missions on Mars by a 4-person crew; and the CO2 Contingency Walk Back Study, an investigation of elevated CO2 exposure on crew performance during a contingency EVA scenario. APACHE also provides a test environment to support the development of the Crew State and Risk Model, which is a collection of individualized, mathematical models of crew physical and cognitive state; and the Personalized EVA Informatics and Decision Support system, an operational tool for flight controllers, and eventually a self-reliant Martian crew, to make biomedically-informed decisions in real-time to optimize the EVA planning and execution with respect to crew health and performance. Some technical challenges associated with developing the APACHE environment, as well as current limitations, include VR limitless natural walking with a hybrid spacesuit simulator, optimizing performance for wireless PC VR streaming while maintaining a high degree of visual fidelity, and the integration of various physiological (metabolic masks) and psychometric (eye tracking) sensors with the VR headset.

Human Performance↗

Space Launch System Liftoff and Separation Dynamics Analysis Tool Chain

A flexible, hierarchical tool chain that is being applied to NASA’s Space Launch System (SLS) for critical dynamics phenomena is described. This tool chain, called CLVTOPS, is used to investigate lateral liftoff movement of the vehicle as it departs and clears the mobile launch tower and separation of the two solid rocket boosters without collision with the core stage and payload. The toolset’s architecture was configured to take advantage of a modern software-engineering approach for maximum flexibility and utilization of open-source simulations and associated tools. As opposed to a “monolithic” approach, scripting languages were used to “bind” together a tool chain to configure and organize input data, execute and produce analysis results, and post-process these results to facilitate a rapid iterative analysis process to quickly address issues and pursue alternatives with emphasis on analysis automation. Key capabilities in the tool chain include processing and mining of very large data sets, a wide range of graphical depictions, and high-fidelity, physics-based simulations. The paper begins with a problem description and the motivation for liftoff and separation dynamics analysis followed by a historical survey of dynamics analyses for previous NASA human-rated launch vehicles. Details of the tool chain and its components are then introduced divided, first, into description of the scripting language architecture used to “bind” the simulation tools, programs, and scripts together and, second, the physics models and simulations. Representative analyses and data products are shown for liftoff and booster separation dynamics that provide in-depth insight to the tool chain’s capabilities. Supporting activities such as simulation tool chain verification, version archiving and data management, and training are addressed. The paper concludes with case examples on how the tool chain can be tailored to related aerospace dynamics analyses, both large and small. These patterns and techniques for SLS dynamics tool construction can be applied for other aerospace simulations.

6DOF↗

Space Launch System Liftoff and Separation Dynamics Analysis Tool Chain

A flexible, hierarchical tool chain that is being applied to NASA’s Space Launch System (SLS) for critical dynamics phenomena is described. This tool chain, called CLVTOPS, is used to investigate lateral liftoff movement of the vehicle as it departs and clears the mobile launch tower and separation of the two solid rocket boosters without collision with the core stage and payload. The toolset’s architecture was configured to take advantage of a modern software engineering approach for maximum flexibility and utilization of open-source simulations and associated tools. As opposed to a “monolithic” approach, scripting languages were used to “bind” together a tool chain to configure and organize input data, execute and produce analysis results, and post-process these results to facilitate a rapid, iterative analysis process to quickly address issues and pursue alternatives with emphasis on analysis automation. Key capabilities in the tool chain include processing and mining of very large data sets, a wide range of graphical depictions, and high-fidelity, physics-based simulations. The paper begins with a problem description and the motivation for liftoff and separation dynamics analysis followed by a historical survey of dynamics analyses for previous NASA human-rated launch vehicles. Details of the tool chain and its components are then introduced and divided, first, into description of the scripting language architecture used to “bind” the simulation tools, programs, and scripts together and, second, the physics models and simulations. Representative analyses and data products for liftoff and booster separation dynamics are shown in order to provide in-depth insight into the tool chain’s capabilities. Supporting activities such as simulation tool chain verification, version archiving and data management, and training are addressed. The paper concludes with case examples on how the tool chain can be tailored to related aerospace dynamics analyses, both large and small. The flexibility and versatility of this tool chain in supporting analyses of such a diverse range of aerospace applications demonstrates the feasibility of applying these patterns and techniques for tool construction to other aerospace simulations.

6DOF↗