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At least 1,711 records · Page 95

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NASA NTRS2021

Design and Commissioning of an In-Air Coronagraph Testbed in the HCIT facility at NASA’s Jet Propulsion Laboratory

After completing its duty in the vacuum chamber at the High Contrast Imaging Testbed (HCIT) facility at NASA’s Jet Propulsion Laboratory, the General Purpose Coronagraph Testbed (GPCT) has been retrofitted as the In-Air Coronagraph Testbed (IACT), with the purpose of verification of Boston Micromachines (BMC) 50x50 MEMS deformable mirrors (MEMS DM) performance by contrast comparison before and after random vibration testing. The testbed is configured as a vortex coronagraph, with one MEMS DM in the pupil plane to create a half dark hole in monochromatic light. High wavefront stability is achieved using an environmentally isolating enclosure, based on the enclosure design previously used on Caltech’s High Contrast Spectroscopy Testbed (HCST). Further, a smaller enclosure has been designed which will enforce humidity conditions necessary for the MEMS DM to operate. We expect this testbed to achieve 1e-8 contrast, and will use this contrast level as a baseline to assess survival or failure of MEMS DMs during vibration testing. In this presentation, we will present an overview of the design of the IACT, commissioning results, and plans for upcoming DM tests in preparation for launch on future space telescopes with coronagraph instruments.

Mejia-Prada, Camilo↗

NASA NTRS2021

3D Shape Reconstruction of Small Bodies from Sparse Features

The autonomous approach of spacecraft to a small body (comet or asteroid) relies on using all available information at each phase of the approach. This paper presents new algorithms for global shape reconstructions from sparse tracked surface points. These methods leverage estimates from earlier phases, such as rotation pole, as well as a priori knowledge, such as a genus-0 body (i.e. without boundaries or topological holes). A mapping algorithm is proposed, which performs faithful reconstructions while enforcing genus-0 output through spherical parameterization. To estimate the shape of permanently shadowed regions of the body, a symmetry reconstruction method is added to the reconstruction algorithms. This method is shown to substantially increase the reconstruction accuracy but is subject to the symmetry of the body perpendicular to the rotation pole. The proposed mapping algorithm is compared to stateof- the-practice surface reconstruction algorithms, assessing their accuracy and ability to correctly generate genus-0 shape models for 2400 datasets and three small bodies. The proposed spherical parameterization algorithm performed consistently with the state-of-the-practice while being the only algorithm to always produce genus-0 shape models.

Nesnas, Issa↗

NASA NTRSDate not supplied

Modern Scientific Data Governance Framework

Science has entered the era of Big Data with new challenges related to data governance, stewardship, and management. The existing data governance practices must catch up to ensure proper data management. Existing data governance policies and stewardship best practices tend to be disconnected from operational data management practices and enforcement and mainly exist in well-meaning documents or reports. These governance policies are, at best, partially implemented and rarely monitored or audited. In addition, existing governance policies keep adding additional data management steps that require a human, ‘a data steward’, in the loop, and the cost of data management can no longer scale proportionately with the current and future increased data volume and complexity. The goal for developing an updated data governance framework is to modernize scientific data governance to the reality of Big data and align it with the current technology trends such as cloud computing and AI. The goals of this framework are two folds. One is to ensure thoroughness that the governance adequately covers the entire data life cycle. Two, provide a practical approach that offers a consistent and repeatable process for different projects. Three core principles ground this framework. First, focus on just enough governance and prevent data governance from becoming a roadblock toward the scientific process. Remove any unnecessary processes and steps. Second, automate data management steps where possible. Actively remove steps that require ‘human in the loop’ within the management process to be efficient and scale with increasing data. Third, all the processes should continually be optimized using quantified metrics to streamline the monitoring and auditing workflows.

Rahul Ramachandran↗

NASA NTRS2022

Flight Rule Design, Implementation, Verification, and Validation for the Psyche Mission

NASA Jet Propulsion Lab (JPL)’s upcoming mission Psyche will begin its journey to the asteroid (16) Psyche in late 2022 in an effort to better understand its origins and, in turn, better understand our own. Operating the spacecraft safely will require the dedicated efforts of a small team that understands the spacecraft’s operational constraints, as well as a set of powerful spacecraft models designed to catch command errors that can pose risks to mission success. One of the responsibilities of the operations team is to ensure adherence to a set of Flight Rules written by spacecraft and instrument experts that are designed to mitigate these risks. Psyche’s innovations in Flight Rule design principles and advancements in the tools and processes used to implement and check Flight Rules are discussed. A comparison of Psyche’s approach to Flight Rules to other JPL missions will provide lessons learned for future missions that must perform constraint checking during operations. Flight Rule development faces several major challenges. First, flight rule developers must work with Subject Matter Experts (SME) to write the rules in a way that captures the intent of the constraint in a straightforward, enforceable manner. Second, software implementers must correctly interpret flight rules into code so that it meets the original intent of the SME. Finally, a means must be provided for SMEs to validate flight rule implementations without requiring them to understand the underlying software. Innovative processes intended to efficiently close the loop between stakeholders and software developers are described, such as the use of test-driven development to provide stakeholders with easy-to-review implementations. New guidelines for flight rule writing, designed to address these challenges, are described for future missions to adopt and build upon. Psyche Mission System has a variety of new and heritage tools that improve in the Flight Rule validation and checking process. Psyche developed a powerful, new tool called RandSEQ and made significant improvements to Octopusjam, two valuable tools that aid the development of Flight Rule unit tests. Advancements in the models and processes for performing sequence validation with SEQuence GENerator (SEQGEN), the primary, high-heritage tool used for automated flight rule checks on Psyche, are described. The development of new software and the advancements to existing software put Psyche at the forefront of Flight Rule technology. All missions must perform detailed constraint checking, so a comparison of Psyche’s approach to some of these items to the approaches taken by other missions such as Dawn, M2020, and Europa Clipper is done, specifically to examine SME-developer communication, tools used, and development process. Lessons learned from this comparison will be provided.

Weise, Tim↗

NASA NTRSDate not supplied

Where IMERG Goes Next: Version 08 and Beyond

With the Version 07 (V07) Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm finalized and production initiated, the focus turns to enhancements for Version 08. These include innovations not included in V07 due to time constraints, plus issues revealed by the initial V07 products. One high priority is to evaluate and revise the schemes in V07 that rectify temporal artifacts caused by the time interpolation that fills the gaps between the various passive microwave (PMW) sensor overpasses. A second priority is to improve the homogeneity between the TRMM and GPM eras by characterizing differences between the two eras, determining the causes of these differences, and applying corrections as feasible, perhaps by enforcing spatial scale consistency (an overarching issue). Certainly, we must account for GPROF and the Combined Radar-Radiometer Algorithm converting to Machine Learning schemes in V08. Other priority topics include additional automated quality control for artifacts in the IR brightness temperatures and PMW precipitation fields, revisions to the specification algorithm for the probability of liquid precipitation, and accommodating new PMW sensors, which include the next generation of small-sats. We also consider the post-V08 landscape; the final GPM reprocessing will be restricted to fixing known code or algorithmic errors. Nonetheless, there are several data sources on the horizon to consider, including more small-sat PMW radiometers, AVHRR-based precipitation estimates (most useful in high latitudes), and the ISCCP-Next Generation and GEO-Ring projects that could provide easy access to multiple geosynchronous satellite channels and enable significantly improved algorithms compared to GEO-IR alone.

George J. Huffman↗

NASA NTRS2023

Towards Streamlining Auditing for Compliance With Requirements in Open-Source Software at NASA

Context: NASA requires all software to meet several requirements (NPR 7150.2) depending on software criticality. The instantiation of these requirements may vary per project; however, once decided upon, projects must undergo audits to evaluate compliance with these requirements. Aim: We propose that audit effort can be reduced when requirements are realized by leveraging commonly used open-source infrastructure for version control, issue tracking and continuous integration, and the generated records are analyzed using a repository mining software tool to quantify process compliance. Method: We perform a case study in the NASA-funded Copilot project, utilizing Kaiaulu, a repository mining software tool. We define four software compliance metrics based on the Copilot’s requirements, and analyze their impact on source code quality. Results: Our work demonstrates how it is possible to leverage existing open source tools and platforms to facilitate software certification and qualification, and to streamline the auditing process required even when stringent requirements must be enforced. Conclusion: Together, both project and tool can be utilized to visualize project compliance, and metrics can be defined to more easily identify process irregularities to minimize auditing efforts. Project Repository: github.com/Copilot-Language/copilot Tool Repository: github.com/sailuh/kaiaulu

code-quality↗

NASA NTRS2023

Summer Atmospheric Circulation Over Greenland in Response to Arctic Amplification and Diminished Spring Snow Cover

The exceptional atmospheric conditions that have accelerated Greenland Ice Sheet mass loss in recent decades have been repeatedly recognized as a possible dynamical response to Arctic amplification. Here, we present evidence of two potentially synergistic mechanisms linking high-latitude warming to the observed increase in Greenland blocking. Consistent with a prominent hypothesis associating Arctic amplification and persistent weather extremes, we show that the summer atmospheric circulation over the North Atlantic has become wavier and link this wavier flow to more prevalent Greenland blocking. While a concomitant decline in terrestrial snow cover has likely contributed to this mechanism by further amplifying warming at high latitudes, we also show that there is a direct stationary Rossby wave response to low spring North American snow cover that enforces an anomalous anticyclone over Greenland, thus helping to anchor the ridge over Greenland in this wavier atmospheric state.

Atmospheric dynamics↗

NASA NTRS2023

Establishing a Pathway to Greener Aviation

The burning and production of jet fuel in both commercial and regional planes at a high volume releases extreme levels of carbon emission as of its current state. This paper analyzes the implementation and benefits of three sustainable alternatives to traditional jet fuel: sustainable aviation fuel (SAF), hydrogen fuel cells, and electric batteries. A roadmap to show progress in reducing the carbon footprint of aviation is then proposed. The first phase of the roadmap involves the evolution of technology, validation, and testing of SAF-powered planes and the preliminary development of hydrogen production and propulsion and battery technology and the development of electric propulsion technologies. The second phase illustrates the widespread implementation of all three fuel sources where electric aviation will be enforced in short-range travel (30 min-3 hrs), medium-range aircraft (3-6 hrs) will use hydrogen fuel cells, and long-range (6+ hrs) airliners will utilize SAF. The third and final phase will enact the use of SAF and electric batteries for long-range applications while hydrogen fuel cells will dominate short- and medium-range aircraft. This roadmap, in combination with proper legislative action and corporate cooperation paired with public awareness, can help eliminate the usage of jet fuel in the aviation industry and replace it with three more sustainable and clean fuel sources.

green aviation↗

NASA NTRS2023

San Joaquin Valley Health & Air Quality: Evaluating the Overlap of Social Vulnerabilities and Air Quality in the San Joaquin Valley Air Pollution Control District

Little Manila Rising (LMR) is a nonprofit in Stockton, California that has been increasingly concerned by the air pollution in their city and the neighboring San Joaquin Valley (SJV). Geographical factors, climate conditions, and anthropogenic activities, such as agriculture burning and vehicle emissions, contribute to the high levels of air pollution in this region. To visualize the distribution of air pollution and social disparities across the SJV, LMR partnered with NASA DEVELOP. The DEVELOP team used Terra and Aqua MODIS, Sentinel-5P TROPOMI, and CALIPSO CALIOP to observe Aerosol Optical Depth (AOD), Nitrogen Dioxide (NO 2 ), and the vertical distribution of pollutants at varying pollution levels, respectively. Additionally, Suomi-NPP VIIRS provided active fire data. By leveraging NASA Earth observations along with sociodemographic and public health data, the DEVELOP team created maps identifying the areas experiencing the highest vulnerabilities and disparities in pollution exposure. The team found that AOD was slightly higher in agricultural regions, while NO 2 was consistently higher along transportation corridors and urban areas. Wildfires dominated the type of detected active fires, and there was high correlation (R 2 = 0.6924) between active fires and burn permits in agricultural tracts. Furthermore, the team identified both high AOD vulnerability and high NO 2 vulnerability in census tracts in South Stockton, an area that has been historically redlined and disinvested in, and where LMR resides. There was also a moderate correlation between air quality reported from the satellites and in-situ ground monitors. These results will support LMR’s organizing strategies for stricter enforcement of air pollution regulations and increased public health equity for community members.

Agricultural Fires↗

NASA NTRSDate not supplied

Performance Analysis of A Dual Quaternion Guidance Algorithm Applicable During Lunar Approach With A Hazard Avoidance Maneuver

There is currently a need for advanced guidance and targeting algorithms that can provide real-time trajectories in the presence of state and vehicle constraints during powered descent. The Safe & Precise Landing Integrated Capabilities Evolution (SPLICE) program aims to mature Hazard Detection (HD) technology along with advanced navigation and guidance algorithms. This paper will report the overall performance of the SPLICE Dual Quaternion Guidance (DQG) algorithm which is a 6-Degree-of-Freedom (6-DOF) convex optimization-based guidance algorithm that can enforce multiple vehicle and state constraints required for Hazard Detection Lidar (HDL) scans during the approach phase. DQG was tested in a closed-loop lunar descent simulation with realistic HDL sensing constraints in a Monte Carlo assessment of 1000 dispersed runs.

Guidance↗

NASA NTRS2023

A Finite Element Approach for Simplified 2D Nonlinear Dynamic Contact/Impact Analysis

In this paper, a simplified numerical approach for finite element dynamic analysis of an inelastic solid structure subjected to solid object impact is presented. The approach approximates the impacting solid as the selected multiple nodes, for which mass of the impactor is distributed. The node-to-segment contact formulation with the penalty constraint technique incorporated is employed to impose contact conditions between the nodes and the surface of the receiver structure. The node-to-segment algorithm is integrated into Newton–Raphson time integration scheme and the Lagrange multiplier technique is applied to enforce the identical displacements for the selected nodes throughout the analysis process. The approach is verified using two-dimensional plane strain models considering elastic-perfectly-plastic material behavior. The results obtained using the proposed approach are in a good agreement with those simulated using a commercial finite element code, ABAQUS dynamic/implicit, in terms of displacements and stress distribution fields. The proposed approach is shown to be computationally superior to general finite element method-based contact/impact analysis without significantly sacrificing the accuracy.

Seungwook Seok↗

NASA NTRSDate not supplied

Gradient-Based Optimization of the Common Research Model Wing Subject to CFD-Based Gust and Flutter Constraints

The linearized frequency-domain method was recently implemented in the stabilized finite element solver in NASA’s FUN3D code. Previous work by the authors used this method for enforcing flutter constraints during gradient-based optimizations. More recently, the solver was expanded to account for continuous (also known as stochastic) gust responses. This paper expands on recent Common Research Model wing optimization work, which demonstrated gradient-based optimization with flutter and stochastic gust constraints, among others. While that work utilized FUN3D for static aeroelastic solutions but relied on doublet lattice aerodynamics for gust and flutter responses, the present work replaces these unsteady aerodynamic analyses with those of FUN3D’s linearized frequency-domain solver. With analytic derivatives available, gradient-based optimization is performed through the use of the OpenMDAO/MPhys libraries with over 700 shape, structural, and aerodynamic design variables and over 10 nonlinear constraints. Comparisons of analysis results and optimized designs are made between doublet lattice and linearized frequency-domain solutions.

aeroelasticity↗

NASA NTRSDate not supplied

A Web-Based Negotiation Tool for Conflict Resolution in Upper Class E Traffic Management

In Upper Class E airspace 60,000 feet (or Flight level / FL600), vehicles such as High Altitude Long Endurance (HALE) balloons and slow fixed-wing gliders have diverse vehicle characteristics and limited maneuverability. Due to these unique characteristics of high-altitude operations, a new type of strategic negotiation-based conflict resolution method has been proposed to avoid potential conflict between vehicles in Upper Class E airspace, well in advance of the conflict point and with ample time for bilateral negotiation. This paper introduces the first real-time web-based negotiation tool for high-altitude operations. To facilitate negotiation, this tool incorporates a bilateral negotiation model with an algorithm to assess conflict risks and generate new flight trajectories with a given flight path deviation. This tool allows users to make decisions during negotiation manually and automatically while enforcing the needed constraints for negotiation to be successful. Operators can make decisions at every step while they interact with each other on separate devices. To conduct sensitivity analysis, a mechanism that automates human inputs to the user interface is also developed for this web-based negotiation tool, such that fast-time simulations can be constructed and used to explore various scenarios to gain insights into this web-based negotiation model. Using this tool, a study was conducted to evaluate the impact of different negotiation strategies, vehicle types, vehicle crossing angles, and operator response times during the negotiations on metrics such as total negotiation completion time, number of negotiation rounds, and extra flight distance to avoid the conflict due to negotiation, compared to ones without negotiation. The results suggest that operators benefit from using negotiated flight paths with quick response times, across various crossing angles and vehicle types. Various Negotiation Strategies are investigated to simulate the behaviors associated with different types of negotiations. The findings demonstrate that, in comparison to the conventional method where a single operator assumes full responsibility, negotiation-based strategic deconfliction reduces the total extra flight distance by an average of 24% - 27%. On an individual basis, each operator may be able to save an average of 65% of their extra flight distance.

Upper Class E Traffic Management (ETM)↗

NASA NTRS2024

Intrastep, Stage-Value Predictors for Diagonally-Implicit Runge-Kutta Methods

To better identify the necessary attributes of good stage-value predictors (SVPs), numerous SVPs are designed for an existing: ESDIRK4(3)7L[2]SA [26] and a new: ESDIRK4(3)8L[2]SA scheme.1 Both are stifflyaccurate, stage-order two, explicit, singly-diagonally implicit Runge–Kutta (ESDIRK) schemes. Tradeoffs are studied in the parameter spaces enforcing the constraints on accuracy, linear stability, nonlinear stability and coefficient size to determine which objectives correlate with effective predictors. The SVPs are tested on three challenging external aerodynamics problems [107 − 108 degrees of freedom (DoFs)], each with a different level of stiffness. The problems include two 3D airfoils simulations and one canonical turbulence simulation. All simulations use the compressible Navier-Stokes equations (CNSE). An entropy stable spectral collocation formulation is used for discretizing the spatial terms in the equations. Simulations are performed at a wide variety of temporal error tolerances. Problems that are sufficiently stiff (e.g., lax temporal error tolerances) benefit from SVPs designed with second-order accuracy and stability properties: A-stability, and L-stability, rather than high accuracy constraints. Simulations with modest stiffness (e.g., strict error tolerances) are better suited for SVPs designed using high accuracy constraints. Designing SVPs with enhanced stability properties is tedious but worthwhile. Simulation times are reduced with optimal SVPs by as much as 100% on some stages, with combined stepwise improvements of between 50 − 100% for both methods. A comparative study is performed with the two aforementioned methods as well as four other ESDIRKs. The newly designed ESDIRK4(3)8L[2]SA with γ ≈ 1/10, proves to be the most efficient of the six tested ESDIRK schemes simulating the CNSE.

Diagonally-Implicit Runge-Kutta↗

NASA NTRS2024

Thermal Actuator Identification and Control for Thermomechanical Real-Time Cyber–Physical Testing

Thermomechanical cyber–physical testing enables two-way thermal coupling between a numerical and an experimental subsystem. The interactions between the numerical model and the physical specimen occur through transfer systems, which enforce interface conditions. Thus, efficient control methodologies are necessary to achieve the desired interface interaction through thermal actuators with minimal error. This study introduces a novel thermal transfer system that imposes distributed cooling (or heating) thermal loads on a physical subsystem. First, the thermal actuator is identified considering switching-mode continuous dynamics for heating and cooling conditions. A switching-mode estimation algorithm is adopted to estimate the operating thermal cycle of the actuator in real-time. A control system is developed to experimentally impose the desired temperature and reduce tracking error (i.e., the error between the desired and actual temperature) under different thermal cycles. The identification and control of the thermal transfer system are then validated through a set of experiments considering different temperature rates of change. The developed control system is found to effectively minimize tracking errors in real-time cyber–physical experiments.

Herta Montoya↗

NASA NTRS2024

Piezoelectric impedance-based high-accuracy damage identification using sparsity conscious multi-objective optimization inverse analysis

Two elements are essential in structural health monitoring utilizing dynamic responses: response measurement with high-frequency contents, i.e., small characteristic wavelengths, that can adequately reflect damage features, and effective inverse identification analysis that is however oftentimes under-determined. The advancement of smart structure integration has led to active interrogation through frequency-sweeping piezoelectric impedance measurement at high frequency range. In this research we develop a multi-objective optimization formulation for the identification of damage location and severity utilizing piezoelectric impedance. While one optimization objective is to match the response measurement with finite element model prediction in the damage parametric space, the other is the number of locations of damage, i.e., the sparsity of damage index as the solution vector, since damage usually occurs within a small number of locations. This multi-objective formulation fits well the under-determined nature of damage identification, as it naturally provides multiple solutions as basis for further elucidation. The challenge remaining is how to find a small solution set that can include the actual damage scenario. Here we develop a novel inverse identification framework utilizing the intelligent swarm optimizer which possesses flexibility for enhancement. We first embed a sparsity enforcement process into the population generation of the optimizer, which yields a solution repository intrinsically possessing sparsity. We then apply reinforcement learning so the agents can adaptively opt for local strategies with the aim of enriching the searching patterns to diversify the solutions. Through the incorporation of a Q-table, searching toward more promising directions will be rewarded. Our case analyses employing experimental data indicate that this sparsity-conscious multi-objective particle swarm optimization technique can lead to a small solution set which generally encompasses the true damage scenario. This effectively solves the structural damage identification problem with piezoelectric impedance measurement.

Yang Zhang↗

NASA NTRS2024

Real-Time Temperature Field State Observer and Digital Replica to Support Cyber-Physical Testing

Cyber-physical testing is a class of experimental methods in which a system is partitioned into physical and numerical components to study its overall behavior. Transfer systems are typically needed to capture relevant interactions by enforcing appropriate interface conditions between the physical and numerical portions. While cyber-physical testing is often performed using lumped-parameter systems, thermomechanical cyber-physical testing requires the use of thermal actuators as transfer systems to apply a thermal condition over a spatially distributed region or surface. Thus, the interactions between the numerical and physical components are of a distributed nature, i.e., a field rather than point values. In this paper, we develop and experimentally validate a state observer for temperature fields to enable thermomechanical cyber-physical testing. The state observer provides continuous estimates of temperature over a surface of the thermal actuator using only temperature measurements at discrete locations. The estimated temperature field is then leveraged to account for localized mechanical defects in the interface condition. The method consists of building a digital replica of one portion of the control plant. By imposing defects in the digital replica it is used to generate and output the response of a thermal load pattern that represents that of a physical system with mechanical defects.

Manuel Salmeron↗

NASA NTRS2026

Deep RL for Fast Long-Horizon Operations Scheduling on NASA's Carruthers Geocorona Observatory Mission

Spacecraft operations scheduling is a highly constrained, long-horizon combinatorial optimization problem that traditionally relies on heuristics, constraint programming, or manual planning. We present a scalable deep reinforcement learning framework developed and deployed for NASA’s Carruthers Geocorona Observatory mission. Our framework introduces a macro-action abstraction known as activity blocks coupled with dynamic action-masking to navigate the intractably large search space and strictly enforce complex power, thermal, and instrument constraints. The resulting architecture generates globally feasible schedules with overwhelming probability, establishes operational trust, and executes a full training cycle in under six hours, circumventing the need for policy robustness by enabling rapid, on-demand retraining. Further, resulting schedules outperform baseline heuristics in scheduled science quality. The deep reinforcement learning framework was deployed as the default operational scheduler for the Carruthers Geocorona Observatory mission from the outset of the mission, demonstrating that deep reinforcement learning can be trusted for real spacecraft operations under complex, evolving constraints.

Geocorona↗