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NASA NTRS2021

Modeling the Radiative Effect on Microphysics in Cirrus Clouds Against Satellite Observations

The radiative effect on microphysics (REM) plays an important role in the dew/frost formation near the surface. How REM impacts cirrus clouds is investigated in this study, using bin microphysical model simulations and coincident data of the CloudSat and Global Precipitation Measurement (GPM) satellites. REM affects ice crystal spectrum with two types: radiative cooling and warming. Radiative cooling, as predicted by the bin-model simulations, favors the formation of horizontally oriented ice crystals (HOICs), but radiative warming does not. Hence, a test of REM can be transformed to a test of HOICs, because HOICs can be measured by the microwave polarization observations of the GPM Microwave Imager (GMI) at 166 GHz. To analyze the GMI data for their HOIC distribution, clouds are sorted into four groups with different optical depth and altitude, based on the radiative cooling/warming ratio (or eta) computed with satellite-retrieved ice water content. Their HOIC distributions (e.g., the midlevel thick clouds have more HOICs than the high-level ones) agree well with those predicted by the bin-model simulations. The general agreement between the GMI observations and bin-model simulations suggests that REM is common in cirrus clouds and impacts cirrus clouds significantly.

clouds↗

NASA NTRS2021

StrayCats: A Catalog of NuSTAR Stray Light Observations

We present StrayCats, a catalog of NuSTAR stray light observations of X-ray sources. Stray light observations arise for sources 1°–4°away from the telescope pointing direction. At this off-axis angle, X-rays pass through agap between the optics and aperture stop and so do not interact with the X-ray optics; instead, they directly illuminate the NuSTAR focal plane. We have systematically identified and examined over 1400 potential observations resulting in a catalog of 436 telescope fields and 78 stray light sources that have been identified. The sources identified include historically known persistently bright X-ray sources, X-ray binaries in outburst, pulsars, and type I X-ray bursters. In this paper, we present an overview of the catalog, how we identified the StrayCats sources, and the analysis techniques required to produce high-level science products. Finally, we present a few brief examples of the science quality of these unique data.

Brian W. Grefenstette↗

NASA NTRSDate not supplied

Sensitivity of Hybrid NEP-Chemical Vehicle Mass to Assumptions for Crewed Opposition-Class Mars Missions

This research illustrates the impact of different technology choices and their associated performance on overall sizing for a hybrid Nuclear Electric Propulsion (NEP) and chemical crewed Mars transportation vehicle. A set of models for the trajectory and vehicle mass, power system specific mass(α), and power conversion performance enable the analysis. Vehicle mass required to close the mission is calculated as a function of α and specific impulse (Isp) for multiple choices of high-level assumptions including system alpha vs. power scaling and electric thruster type. System alpha is built up and compared for multiple cases of technology assumptions. A Brayton cycle model is used to illustrate the alpha sensitivities to assumptions in cycle design such as peak operating temperature and component performance. The analysis illustrates how technology performance sensitivities affect the alpha and thus vehicle sizing for a range of mission and technology assumptions.

Matthew Duchek↗

NASA NTRS2021

STEReO AIAA 2021

STEReO brings together several technologies in Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Autonomy, Communications, Human Factors, and Domain Expertise & Tools, aimed at providing scalability and flexibility, as well as operational resiliency to dynamic changes during a disaster event. Some of the concepts STEReO explores are: collaborative tools to ingest remote sensing information and distribute a common mission data set, apply ad-hoc communication networks to facilitate timely information sharing and communication of changes, vehicle-to-vehicle and onboard autonomy technologies ensure the safety and resiliency of operations, and apply NASA’s UAS traffic management system (UTM) as a public safety UAS Service Supplier (USS) to access and coordinate use of the airspace by both manned and unmanned operations. The potential benefits of STEReO include: standardized, cross-platform communication means increased interoperability and ease of cooperation/collaboration, increased situation awareness to assist in earlier detection and decision making, and scalable to size and complexity of environment, operations, and mission objectives. This presentation gives a high-level overview of the STEReO concept, what we have done so far, and a preview of what's to come.

UAS vehicles↗

NASA NTRSDate not supplied

Gateway - A Communications Platform for Lunar Exploration

As stated by a NASA administrator, “NASA, International Partners, and commercial partner are going forward to the moon. With Artemis, we will be exploring more of the Moon than ever before, and this time we are planning to stay. We will be demonstrating new technologies, capabilities, and business approaches needed for future exploration of Mars.” To support the complex, Artemis exploration campaign envisioned, the Gateway program is developing a communication network orbiting the Moon. Gateway will provide relay communication paths and radiometric tracking between crewed and robotic systems on the lunar surface or in cis-lunar space to mission control on the Earth. This paper is a high-level description of Gateway’s communication and ranging capabilities, the motivation and use of internationally developed interoperability standards, potential upgrade opportunities, and challenges as Gateway enables technology to support future Mars exploration.

Artemis↗

NASA NTRSDate not supplied

TESS Science Processing Operations Center Pipeline Status and Updates

The past eighteen months have seen a number of important changes for the TESS Science Processing Operations Center (SPOC) and our archival data products as TESS embarked upon its first extended mission. First, the SPOC developed and deployed a new 20-sec cadence pipeline, promising to unveil exciting new astrophysics at these short timescales for up to 1000 targets per observing sector. We also developed an FFI light curve pipeline that creates light curves and associated data products for up to 160,000 targets in each sector and archive these as High-Level Science Products (HLSP) at the Mikulski Archive for Space Telescopes (MAST). Soon we plan to perform transiting planet searches on these light curves and to release Data Validation reports and associated data products to the MAST. We also present results from the first multi-year transiting planet search of sectors 1 through 36. Finally, we discuss major changes to the SPOC pipeline that motivated the reprocessing of the first year of data, including the application of target-and cadence-specific scattered light flags, and an update to the sky background correction algorithm to mitigate bias in the original algorithm for dim and/or severely crowded stars.

TESS↗

NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of how much mass is in the drums, this type of high-level planning is not possible. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All take in system states, such as arm/drum positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums.1) A neural network model that takes a vector of normalized system states; 2) A model that uses the integrated power consumption of an arm-raise (normalized by velocity); 3) A model that uses average drum current over a variable length interval of the drum disengaged from the surface; and 4) A real-time estimation model that aggregates excavation drum current. The developed models run in real time, outputting predictions for the front and rear drums, timestamp of the last prediction, and total mass in RASSOR’s drums. Further testing is required to validate the arm-raise model (2), though initial tests indicate reasonable performance (<10% mean error) on the hardware. The linear fit of average drum-current model (3) had a front value of r^2=0.99 and a rear value of r^2=0.98 on the validation dataset. This model currently has the best performance on unseen data. The real time model (4) is still in development, though initial results on a small subset of the training data show that it has high accuracy in predicting the increase in mass during excavation. Though work remains to be done with deploying a high-fidelity model to the physical system that makes predictions with error below the desired threshold, the modular architecture for model development allows quick adjustment of parameters to increase model fidelity. This architecture can also be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results are promising as it has been shown that models can be developed that accurately estimate excavated regolith mass.

rassor↗

NASA NTRSDate not supplied

Visualizing UPSP Data with Python

The Unsteady Pressure-Sensitive Paint (uPSP) projects uses Pressure-Sensitive paint applied over aerospace models during wind tunnel testing to collect pressure data with high spatial and temporal resolution in order to inform unsteady aerodynamics studies. For each of the 800+ experimental runs, four cameras generate up to 50 GB of video data, which must then be processed, analyzed, and visualized on the NASA Advanced Supercomputing system (NAS) to assess the result. One of the final data analysis products is the dynamic modal decomposition (DMD) results, which decomposes the pressure reading signals by their frequency component. The goal of this project is to visualize the DMD results over a 3D rendering of the model, using efficient and parallelized python routines. The software uses the pytecplot library, a high-level API that connects python scripting to a Tecplot 360 engine. Tecplot is an industry standard high-performance visualization tool that can handle large datasets and workflow. Various animation, rendering, and image-combination techniques were investigated to generate the final videos using OpenCV on the NAS. The final result is a software tool that takes in data products from the uPSP processing chain and generates high resolution visualization videos in parallel for every data file, allowing researchers to view their results efficiently and at an unprecedentedly detailed level.

Emma Dolores McMillian↗

NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a mobile robotic bucket-drum excavator platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for estimating the quantity of regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete In-Situ Resource Utilization (ISRU) missions. To teleoperate or run autonomously, it is crucial for the amount of regolith mass ingested to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of the total mass in the drums, this type of high-level planning is not possible. Three distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR, none of which require modification to the hardware. All take in system states, such as arm/drum motor positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums. The developed models run in real-time, outputting predictions for the front drum mass, rear drum mass, timestamp of the last prediction, and total drum mass (sum of front and rear) in RASSOR’s drums. Models deployed to the hardware have low error (<7.5% mean error over the mass range, and <2.6% mean error when drums are more than half full) when making predictions in real-time. Our modeling approach can be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results of this work are promising and show that models can be developed to accurately estimate excavated regolith mass.

Bucket Drum Excavators↗

NASA NTRSDate not supplied

The System Complexity Metric (SCM) Explains Systems Design and is Correlated with Cost and Failure Rate

The human short term memory span and working capacity is limited to three to five items, especially if they are organized complex “chunks” of information. The impression of complexity occurs when a system is simply difficult to understand, where there is no apparent pattern to predict its behavior. Hierarchical systems design can reduce perceived complexity and increase the amount of information that can be managed. The SCM was developed to measure complexity and help compare proposed overall system architectures before detailed design information is available. The SCM is defined as the sum of the number of major nodes, N, in the system block diagram plus the number of one-way interactions, I, between the nodes. SCM = N + I. SCM’s are easily determined by direct inspection of high-level block diagrams of life support systems. Axiomatic design develops a hierarchy of subsystem requirements and designs together in a top-down, back-and-forth process. A coupling matrix is used to control the relationships between the subsystem functions and design concepts. Axiomatic design can improve system design by decoupling requirements and designs. Axiomatic design was applied to the planning of a closed life support system, similar to that used on the International Space Station. A materially open as opposed to a closed system design was created by removing the interconnections required to close the system. The open system had the same number of designed subsystems as the closed system, but it had many fewer interconnections and its SCM was lower by about half. The costs were estimated and the MTBF (Mean Time Before Failure) tabulated for open and closed space life support systems. The estimated costs were linearly proportional to SCM for the wide variations of SCM in life support, but small differences may not be significant. The flight and preflight MTBF’s both declined exponentially with increasing MTBF, faster than MTBF-2, even though the preflight estimated MTBF’s were about ten times higher than the flight MTBF’s.

System Complexity Metric (SCM)↗

NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

bucket drum excavators↗

NASA NTRSDate not supplied

Overview of the Volatiles Investigating Polar Exploration Rover (VIPER)

General overview of the Volatiles Investigating Polar Exploration Rover (VIPER) rover system, including a high-level description of the rover's hardware and software.

planetary rover↗

NASA NTRSDate not supplied

DIP Architecture and Data Integration Services

This workshop will cover DIP architecture and data integration services. Participants will get a look at how the DIP architecture is set-up as well as how data integration services are planned to be hosted on the platform. The DIP architecture review is intended to cover how DIP was envisioned and how DIP is being developed to address data needs across the industry. Participants will have a chance to provide feedback on the DIP architecture and gain insight into how one might interface with the DIP to send or receive data. The data integration services portion is intended to cover DIP’s technical approach to data integration. As an example implementation, there will be a first look at possible data fusion on the platform, including utilizing NASA’s Fuser, and tailoring for industry data consumers. Descriptions, at a high-level, of input to and output of the Fuser will also be discussed.

ATM-X↗

NASA NTRS2020

Demonstrating Assurance of Model-Based Fault Diagnosis Systems on an Operational Mission

Developers of robotic scientific and commercial spacecraft are trending towards use of onboard autonomous capabilities for responding quickly to dynamic environments and rapidly changing situations. These capabilities need to know the state of the spacecraft’s health. Model-based fault diagnosis (MBFD) is an approach to estimating health by continuously verifying accurate behavior and diagnosing off-nominal behavior. Proper functioning of MBFD depends on 1) the quality of the diagnostic system model that is analyzed and compared to commands and onboard measurements to estimate a system’s health state, and 2) the correct functionality of the diagnosis engine interrogating the model and comparing its analyses to observed system behavior. Our goal is to develop Verification and Validation (V&V) techniques for MBFD to provide future missions sufficient confidence in its functionality and performance to deploy it on the systems they develop. Our work has been focused on infusing the techniques we developed earlier to an operational mission. First, we are constructing diagnostic models of a spacecraft attitude control system and updating our diagnostic engine so they can be demonstrated aboard the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, an operational spacecraft for which experiments in autonomy are being planned and executed, using the V&V techniques we have previously developed to assure they are both correct and complete. Since it is nearing the end of its life, ASTERIA provides a unique opportunity to demonstrate MBFD since the monitored components are expected to fail. Our demonstration will give system developers additional confidence to make timely, informed MBFD deployment decisions. Second, we will be completing performance assessments of the diagnostic engine/diagnostic model ensemble both on the flight system and ground-based testbeds to gain confidence in MBFD’s ability to run successfully in a spacecraft’s resource-constrained environment without adversely affecting other on-board activities. Finally, we are capturing our experience in preparing this demonstration in a set of checklists and guidance documents. Current practice includes high-level institutional guidance documents and standards, but at a high level of abstraction that does not necessarily address specific MBFD concerns. The purpose of the new checklists is to provide future mission developers clear, unambiguous, procedure-oriented guidance on assuring MBFD. This paper describes our work in these areas. For the first area, we describe the diagnostic models and updated diagnostic engine that will be used for the on-board demonstration. We describe how the V&V techniques we developed earlier are used to assure model and engine correctness and completeness. For the second area, we identify the performance measurement and assessment techniques used to characterize the diagnostic engine and diagnostic models, and discuss the effect of measured performance on overall mission operation. Finally, we present the checklist and guidance documents and describe how they meet the goals of providing system developers with clear, unambiguous, procedure-oriented guidance on MBFD assurance. We show how the techniques we have developed map into those artifacts.

Nikora, Allen↗

NASA NTRS2020

A Visual Analytics Approach to Debugging Cooperative, Autonomous Multi-Robot Systems’ Worldviews

Autonomous multi-robot systems, where a team of robots shares information to perform tasks that are beyond an individual robot’s abilities, hold great promise for a number of applications, such as planetary exploration missions. Each robot in a multi- robot system autonomously schedules which robots should perform a given task and when, using its worldview–the robot’s internal representation of its belief about the environment and other robots’ states. A key problem for operators is that robots’ worldviews can fall out of sync (often due to weak communication links), leading to desynchronization of the robots’ scheduling decisions and inconsistent emergent behavior (e.g., tasks not performed, or performed by multiple robots). Operators face the time-consuming and difficult task of making sense of the robots’ scheduling decisions, detecting de-synchronizations, and pinpointing their cause by comparing every robot’s worldview. To address these challenges, we introduce MOSAIC Viewer, a visual analytics system that helps operators (i) make sense of the robots’ schedules and (ii) detect and conduct a root cause analysis of the robots’ desynchronized worldviews. Over a year-long partnership with roboticists at the NASA Jet Propulsion Laboratory, a formative study was performed to identify the necessary system design requirements, which supports the design of the system. A qualitative study with 12 roboticists reveals that MOSAIC Viewer is faster- and easier-to-use than the users’ current approaches, and it allows them to stitch low-level details to formulate a high-level understanding of the robots’ schedules and detect and pin-point the cause of desynchronized worldviews.

Ma, Kwan-Liu↗

NASA NTRS2020

Partially Observable Games for Secure Autonomy

Technology development efforts in autonomy and cyber-defense have been evolving independently of each other, over the past decade. In this paper, we report our ongoing effort to integrate these two presently distinct areas into a single framework. To this end, we propose the two-player partially observable stochastic game formalism to capture both high-level autonomous mission planning under uncertainty and adversarial decision making subject to imperfect information. We show that synthesizing sub-optimal strategies for such games is possible under finite-memory assumptions for both the autonomous decision maker and the cyber-adversary. We then describe an experimental testbed to evaluate the efficacy of the proposed framework.

Ames, Aaron D.↗

NASA NTRS2021

InSight Mars Lander Instrument Deployment Arm Flight Software

The Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) lander landed on Mars on November 26, 2018 and continues to investigate the internal structure of the planet two years later. The Instrument Deployment Arm (IDA), a robotic arm on the lander, was used to deploy the science instrument payloads from the lander deck to the surface of Mars and to take images of the lander and the surrounding environment. This was the first precision deployment and release by a robotic arm on another planet. After deploying the instruments, the IDA has been used for instrument commissioning, scientific data gathering, and to assist with troubleshooting one of the science instruments. This paper provides a high-level summary of the flight software that controls the IDA. The paper provides an overview of the IDA software interfaces, task structure, command handling strategy, motion specification, motion planning, motor control, grapple control, fault protection, and telemetry.

Ali, Khaled S.↗

NASA NTRS2020

A Flight Rule Checker for the LADEE Lunar Spacecraft

As part of the design of a space mission, an important part is the design of so-called flight rules. Flight rules express constraints on various parts and processes of the mission, that if followed, will reduce the risk of failure. One such set of flight rules constrain the format of command sequences regularly (e.g. daily) sent to the spacecraft to con- trol its next near term behavior. We present a high-level view of the automated flight rule checker Frc for checking command sequences sent to NASA’s LADEE Lunar mission spacecraft, used throughout its entire mission. A command sequence is in this case essentially a program (a sequence of commands) with no loops or conditionals, and it can there- fore be verified with a trace analysis tool. Frc is implemented using the TraceContract runtime verification tool, an internal Scala DSL for checking event sequences against “formal specifications”. The paper illustrates this untraditional use of runtime verification in a real con- text, with strong demands on the expressiveness and flexibility of the specification language, illustrating the advantages of an internal DSL.

Kurklu, Elif↗