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At least 1,333 records · Page 74

Two self-test methods applied to an inertial system problem

The paper describes two self-test procedures applied to the problem of estimating the biases in accelerometers and gyroscopes on an inertial platform. The first technique is the weighted sum-squared residual (WSSR) test, with which accelerator bias jumps are easily isolated, but gyro bias jumps are difficult to isolate. The WSSR method does not take full advantage of the knowledge of system dynamics. The other technique is a multiple hypothesis method developed by Buxbaum and Haddad (1969). It has the advantage of directly providing jump isolation information, but suffers from computational problems. It might be possible to use the WSSR to detect state jumps and then switch to the BH system for jump isolation and estimate compensation.

Willsky, A. S.↗

EOS ground data and operations support

The Earth Observing System (EOS) is planned as a space-based measurement system, earth-science research program, and data and information system (EOSDIS). It will consist of several observatories with multiple earth sensing instruments to provide investigators with a thorough, long-term view of the earth's environment. Providing the data handling and flight operations support for EOS will be the EOSDIS Core System (ECS). The ECS will command and control the observatories consisting of core service platforms and science instruments, and it will transport, process, and store the EOS data, provide access to the data for years, and support researchers. EOS and EOSDIS are briefly described to provide a context for a description of the ECS.

Smith, Gene↗

Recovering from On-orbit Anomalies on the Astrobee Free Flyers and its Systems

Since 2019, NASA has been operating three Astrobee free flying robots on board the International Space Station (ISS) providing an autonomous and flexible research platform for national and international payload developers in microgravity and serving as a robotic assistant for astronauts on the ISS. During its use on the ISS, in particular with over 750 hours of free-flyer operation as of March 2022, Astrobee and its Docking Station have encountered multiple software and hardware anomalies. These anomalies were either resolved remotely via software and firmware updates, or, where not possible, with hardware replacements on orbit or by the return of the faulty unit to NASA’s ground facilities for its repair. Despite being inherently designed to be repaired or replaced on orbit, Astrobee and its systems can still suffer anomalies that would be complex enough to disassemble, cause risks of hardware damage, or use excessive crew time to perform the repair in orbit. That was the case for the anomaly the Astrobee unit ‘Honey’ encountered, reason why it needed to be down-massed for repair. One of the most common points of failure was found to be the SD card, which is used for the different Astrobee processors and for the Dock Station. Other comparable SD card anomalies were found also on the Astrobee ground units, which provided useful data in the effort of upgrading their systems. This presentation will focus on 1) The overview of the different faults and anomalies on Astrobee and its systems on orbit and on the ground 2) The processes and procedures implemented to resolve the anomalies 3) The implementation of software updates and hardware upgrades in order to reduce the risk on returning anomalies 4) The lessons learned in increasing Astrobee’s robustness and resilience to such anomalies.

International Space Station↗

Characterizing Wildfires in Western US.: A Cloud-based Case Study for Interdisciplinary Research using NASA Resources

This presentation will demonstrate a case study of interdisciplinary research done in the Amazon Web Services (AWS) cloud platform, in addition to in the local machine. We conduct data analysis next to data by leveraging various cloud-based data in NASA Earthdata Cloud, which are distributed by different missions/NASA Distributed Active Archive Centers (DAACs), and cloud computing resources at NASA. For instance, we directly access multiple datasets stored in the AWS Simple Storage Service (S3) buckets using a Python Jupyter notebook through a JupyterHub interface hosted in AWS (without having to download data), and conduct data analysis next to data in the cloud. We will also show how to share the research results following Open Source policy. This case study characterizes the change in wildfire events in the western United States during the past 20 years. In particular, we focus on the wildfires in California in 2021, one of the most severe wildfire years occurring in the most recent 20 years in California. We will analyze the possible causes of wildfires, such as drought conditions and climate variability, and examine the impacts of wildfires on air quality and atmospheric composition, and on land cover. We will examine the data distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), including aerosols and meteorological data from the NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), precipitation from the Global Precipitation Measurement (GPM) and Global Precipitation Climate Project (GPCP), and aerosol index from Ozone Monitoring Instrument (OMI). We also utilize the data distributed by the Physical Oceanography (PO) DAAC, such as Sea Surface Temperature (SST) data from the Group for High Resolution Sea Surface Temperature (GHRSST), and the data distributed by Land Processes (LP) DAAC, such as Normalized Difference Vegetation Index (NDVI).

Xiaohua Pan↗

Multi-sensor fusion for robust autonomous flight in indoor and outdoor environments with a rotorcraft micro-aerial vehicle (MAV)

The subject matter described herein includes a modular and extensible approach to integrate noisy measurements from multiple heterogeneous sensors that yield either absolute or relative observations at different and varying time intervals, and to provide smooth and globally consistent estimates of position in real time for autonomous flight. We describe the development of the algorithms and software architecture for a new 1.9 kg MAV platform equipped with an IMU, laser scanner, stereo cameras, pressure altimeter, magnetometer, and a GPS receiver, in which the state estimation and control are performed onboard on an Intel NUC 3rd generation i3 processor. We illustrate the robustness of our framework in large-scale, indoor-outdoor autonomous aerial navigation experiments involving traversals of over 440 meters at average speeds of 1.5 m/s with winds around 10 mph while entering and exiting buildings.

42 ENGINEERING↗

Simulation of Attitude and Trajectory Dynamics and Control of Multiple Spacecraft

Agora software is a simulation of spacecraft attitude and orbit dynamics. It supports spacecraft models composed of multiple rigid bodies or flexible structural models. Agora simulates multiple spacecraft simultaneously, supporting rendezvous, proximity operations, and precision formation flying studies. The Agora environment includes ephemerides for all planets and major moons in the solar system, supporting design studies for deep space as well as geocentric missions. The environment also contains standard models for gravity, atmospheric density, and magnetic fields. Disturbance force and torque models include aerodynamic, gravity-gradient, solar radiation pressure, and third-body gravitation. In addition to the dynamic and environmental models, Agora supports geometrical visualization through an OpenGL interface. Prototype models are provided for common sensors, actuators, and control laws. A clean interface accommodates linking in actual flight code in place of the prototype control laws. The same simulation may be used for rapid feasibility studies, and then used for flight software validation as the design matures. Agora is open-source and portable across computing platforms, making it customizable and extensible. It is written to support the entire GNC (guidance, navigation, and control) design cycle, from rapid prototyping and design analysis, to high-fidelity flight code verification. As a top-down design, Agora is intended to accommodate a large range of missions, anywhere in the solar system. Both two-body and three-body flight regimes are supported, as well as seamless transition between them. Multiple spacecraft may be simultaneously simulated, enabling simulation of rendezvous scenarios, as well as formation flying. Built-in reference frames and orbit perturbation dynamics provide accurate modeling of precision formation control.

Stoneking, Eric T.↗

Object and Gas Source Detection with Robotic Platforms in Perceptually-Degraded Environments

In exploration-oriented robotic missions for disaster relief in unknown subterranean environments, it is of prime importance for a human supervisor to rapidly gain situational awareness of salient objects within the environment. In this paper we present an automated object detection pipeline that is adaptable to heterogeneous robots with arbitrary sensor configurations. It has been deployed in time-critical scenarios with multiple collaborative robots in a variety of demanding underground environments. For visually observable objects, detections are made in both the visible and thermal spectra using a state-of-the-art machine learning framework for object detection and classification. Our pipeline can be rapidly adapted to a specific task by using a small, structured dataset to fine-tune a pre-trained convolutional neural network (CNN). Relative localization is separated from the CNN for speed of operation. A robust architecture for localization is used with outlier rejection and a hierarchy of fall-back distance measurement methods. Point-source objects such as gas and WiFi hotspots can also be detected, by tracking signal strength over time and presenting an intuitive visualization on a map. Observations of each object types are presented to the operator in ranked confidence order for final evaluation.

Agha-mohammadi, Ali-akbar↗

Magnetic Field-Stabilized Wigner Crystal States in a Graphene Moiré Superlattice

ABC-stacked trilayer graphene on boron nitride (ABC-TLG/hBN) moiré superlattices provides a tunable platform for exploring Wigner crystal states in which the electron correlation can be controlled by electric and magnetic fields. Here, in this work, we report the observation of magnetic field-stabilized Wigner crystal states in a ABC-TLG/hBN. We show that correlated insulating states emerge at multiple fractional and integer fillings corresponding to ν = 1/3, 2/3, 1, 4/3, 5/3, and 2 electrons per moiré lattice site under a magnetic field. These correlated insulating states can be attributed to generalized Mott states for the integer fillings and generalized Wigner crystal states for the fractional fillings. The generalized Wigner crystal states are stabilized by a vertical magnetic field and are strongest at one magnetic flux quantum per three moiré superlattices. The ν = 2 insulating state persists up to 30 T, which can be described by a Mott–Hofstadter transition at a high magnetic field.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Automated Controller Hardware-In-The-Loop Testbed for EV Charger Resilience Analysis

This paper focuses on the development of a tool that includes an automated testbed with controls, protection, and communications integrated into a real-time system to provide a platform to generate data sets for failure modes and effects analysis. This tool establishes a value for automation of data generation for different scenarios and addresses the gap of nonexistent field data for different applications and use cases. The features of this tool can further be expanded to include multiple power electronics models, communication protocols, and scaled system architectures. This general framework was evaluated for a DC fast charger system use case to provide quantitative solution for resiliency.

Starke, Michael↗

Virus-induced gene editing of stomatal regulators in Nicotiana benthamiana enables rapid functional genomics

Virus-induced gene editing (VIGE) holds promise as a rapid and scalable approach for functional genomics in plants. Here, we apply a tobacco rattle virus (TRV)-based single-guide RNA (sgRNA) delivery system to target key regulators of stomatal development in Nicotiana benthamiana using transgenic Cas9-expressing lines. sgRNAs fused to a mobile RNA element and co-delivered with TRV enabled both somatic and heritable genome editing across orthologs of STOMAGEN, EPF2, YODA, and SPEECHLESS. Somatic editing frequencies reached up to 95%, and heritable tetra-allelic mutations were recovered in multiple target genes. Mutants exhibited significant, gene-specific changes in stomatal density, with corresponding effects on leaf temperature indicative of altered evaporative cooling. Additionally, sgRNAs fused to an AmCyan reporter enabled visualization of virus-infected tissues, allowing stomatal phenotyping in edited M0 sectors. This TRV-based platform facilitates functional assessment of genes influencing stomatal patterning and offers a powerful tool for dissecting gene function in a developmentally and physiologically relevant context.

60 APPLIED LIFE SCIENCES↗

Nickel-incorporated Oxide Composites for Fiber-Optic Based Gas Sensing

Numerous high-value applications within the energy sector involve environmental conditions that are incompatible with traditional sensor technology due to degradation of electrical interconnects, packaging, or the sensors themselves. These can include chemically harsh conditions, high temperature operation, or the presence of electromagnetic interference due to high voltage. The fiber optic platform, constructed of robust, electrically insulating glass or single crystal oxides, offers a versatile and often low cost per node solution to this problem, especially with the integration of distributed sensing techniques such as optical time-domain and frequency-domain reflectometry (OTDR, OFDR). A major challenge of gas and chemical sensing on the optical fiber platform is the fabrication of robust and stable sensing materials that interact quickly and reversibly to the presence of the target analytes. In this work, we discuss the utilization of nickel-incorporated oxides on evanescent-field optical fiber sensors for gas sensing under harsh conditions relevant to multiple energy infrastructure applications. This paper will discuss a Ni/GDC (Ni / Gd-doped ceria) based sensing layer targeting conditions relevant for high-temperature (up to at least 800 oC) hydrogen sensing applications (e.g., for operation within a solid oxide fuel cell or electrolyzer). The impact of hydrogen at elevated temperatures on the optical properties of Ni/GDC will be shown and the material mechanisms for the optical response will be discussed.

gas sensors↗

Design criteria for a multiple input land use system

A design is presented that proposes the use of digital image processing techniques to interface existing geocoded data sets and information management systems with thematic maps and remote sensed imagery. The basic premise is that geocoded data sets can be referenced to a raster scan that is equivalent to a grid cell data set, and that images taken of thematic maps or from remote sensing platforms can be converted to a raster scan. A major advantage of the raster format is that x, y coordinates are implicitly recognized by their position in the scan, and z values can be treated as Boolean layers in a three-dimensional data space. Such a system permits the rapid incorporation of data sets, rapid comparison of data sets, and adaptation to variable scales by resampling the raster scans.

Billingsley, F. C.↗

Object Based Numerical Zooming Between the NPSS Version 1 and a 1-Dimensional Meanline High Pressure Compressor Design Analysis Code

Within NASA's High Performance Computing and Communication (HPCC) program, NASA Glenn Research Center is developing an environment for the analysis/design of propulsion systems for aircraft and space vehicles called the Numerical Propulsion System Simulation (NPSS). The NPSS focuses on the integration of multiple disciplines such as aerodynamics, structures, and heat transfer, along with the concept of numerical zooming between 0- Dimensional to 1-, 2-, and 3-dimensional component engine codes. The vision for NPSS is to create a "numerical test cell" enabling full engine simulations overnight on cost-effective computing platforms. Current "state-of-the-art" engine simulations are 0-dimensional in that there is there is no axial, radial or circumferential resolution within a given component (e.g. a compressor or turbine has no internal station designations). In these 0-dimensional cycle simulations the individual component performance characteristics typically come from a table look-up (map) with adjustments for off-design effects such as variable geometry, Reynolds effects, and clearances. Zooming one or more of the engine components to a higher order, physics-based analysis means a higher order code is executed and the results from this analysis are used to adjust the 0-dimensional component performance characteristics within the system simulation. By drawing on the results from more predictive, physics based higher order analysis codes, "cycle" simulations are refined to closely model and predict the complex physical processes inherent to engines. As part of the overall development of the NPSS, NASA and industry began the process of defining and implementing an object class structure that enables Numerical Zooming between the NPSS Version I (0-dimension) and higher order 1-, 2- and 3-dimensional analysis codes. The NPSS Version I preserves the historical cycle engineering practices but also extends these classical practices into the area of numerical zooming for use within a companies' design system. What follows here is a description of successfully zooming I-dimensional (row-by-row) high pressure compressor results back to a NPSS engine 0-dimension simulation and a discussion of the results illustrated using an advanced data visualization tool. This type of high fidelity system-level analysis, made possible by the zooming capability of the NPSS, will greatly improve the fidelity of the engine system simulation and enable the engine system to be "pre-validated" prior to commitment to engine hardware.

Follen, G.↗

Fundamental Biological Research on the International Space Station

The fundamental Biology Program of NASA's Life Sciences Division is chartered with enabling and sponsoring research on the International Space Station (ISS) in order to understand the effects of the space flight environment, particularly microgravity, on living systems. To accomplish this goal, NASA Ames Research Center (ARC) has been tasked with managing the development of a number of biological habitats, along with their support systems infrastructure. This integrated suite of habitats and support systems is being designed to support research requirements identified by the scientific community. As such, it will support investigations using cells and tissues, avian eggs, insects, plants, aquatic organisms and rodents. Studies following organisms through complete life cycles and over multiple generations will eventually be possible. As an adjunct to the development of these basic habitats, specific analytical and monitoring technologies are being targeted for maturation to complete the research cycle by transferring existing or emerging analytical techniques, sensors, and processes from the laboratory bench to the ISS research platform.

Souza, K. A.↗

Cost-Effective Icy Bodies Exploration using Small Satellite Missions

It has long been known that Saturn's moon Enceladus is expelling water-rich plumes into space, providing passing spacecraft with a window into what is hidden underneath its frozen crust. Recent discoveries indicate that similar events could also occur on other bodies in the solar system, such as Jupiter's moon Europa and the dwarf planet Ceres in the asteroid belt. These plumes provide a possible giant leap forward in the search for organics and assessing habitability beyond Earth, stepping stones toward the long-term goal of finding extraterrestrial life. The United States Congress recently requested mission designs to Europa, to fit within a cost cap of $1B, much less than previous mission designs' estimates. Here, innovative cost-effective small spacecraft designs for the deep-space exploration of these icy worlds, using new and emerging enabling technologies, and how to explore the outer solar system on a budget below the cost horizon of a flagship mission, are investigated. Science requirements, instruments selection, rendezvous trajectories, and spacecraft designs are some topics detailed. The mission concepts revolve around a comparably small-sized and low-cost Plume Chaser spacecraft, instrumented to characterize the vapor constituents encountered on its trajectory. In the event that a plume is not encountered, an ejecta plume can be artificially created by a companion spacecraft, the Plume Maker, on the target body at a location timed with the passage of the Plume Chaser spacecraft. Especially in the case of Ceres, such a mission could be a great complimentary mission to Dawn, as well as a possible future Europa Clipper mission. The comparably small volume of the spacecraft enables a launch to GTO as a secondary payload, providing multiple launch opportunities per year. Plume Maker's design is nearly identical to the Plume Chaser, and fits within the constraints for a secondary payload launch. The cost-effectiveness of small spacecraft missions enables the exploration of multiple solar system bodies in reasonable timeframes despite budgetary constraints, with only minor adaptations. The work presented here is a summary of concepts targeting icy bodies, such as Europa and Ceres, which have been developed over the last year at NASA Ames Research Center's Mission Design Division. The platforms detailed in this work are also applicable to the cost-effective exploration of many other small icy bodies in the solar system.

Mission Design↗

Challenges of Operations in a Dynamic Environment: A Three-Year Perspective of SAGE III

The Stratospheric Aerosol and Gas Experiment~III on the International Space Station (SAGE III/ISS) was delivered to the International Space Station (ISS) on 23 February 2017. The SAGE III/ISS payload was robotically installed external to the ISS and began acquiring science measurements on 17 March 2017. The SAGE III/ISS instrument retrieves vertical profiles of atmospheric ozone, multi-wavelength aerosol extinctions, and other gaseous species. This paper will focus on the improvements made to the operations of the SAGE III/ISS payload. A key focus of the operations team following commissioning was to create robust tools that aide in the operations of the payload. A close collaboration with the SAGE III/ISS ground systems team allowed for the development of web-based tools to continuously monitor the health of the instrument. The mission operations team also worked with the SAGE III/ISS science team to gain a better sense of how the instrument works to maximize the quality and quantity of the science data collected. Another unique aspect of the SAGE III/ISS payload, that will be discussed, is the challenges of operating a hosted payload on the ISS; an active platform that has frequent attitude maneuvers, dockings, and EVA's. This active environment increases the need for the SAGE III/ISS operations team command the payload. Through coordination and teamwork, SAGE III/ISS mission has developed an operations team that has successfully managed the instrument around ISS activities and recovered from multiple instrument upsets. This has led the SAGE III/ISS payload to successfully surpass the acquisition metrics set forth prior to launch, allowing for the continued contribution to studying the atmospheric composition of the stratosphere and how it plays a role in earth’s climate.

SAGE III↗

Prediction of Safety Incidents

Crystal Ball is an application being developed that accesses multiple safety databases as a means to improve prediction of safety incidents. Year 1 was data integration, year 2 was predictive modeling, and then year 3(FY20), was the merging of those two prior year efforts into the final application, Crystal Ball (ssc.crystalball.insight.nasa.gov). Crystal Ball sits on the Insight platform (Insight is a NASA platform used to process, manage, integrate, analyze and visualize data at scale, insight.nasa.gov). InFY20, the project focus concentrated on the larger vision of Prediction of Safety Incidents using Crystal Ball as the data source. The Insight platform developer incorporated the predictive modeled data sets, and included a graphical user interface, resulting in a Dashboard for the Crystal Ball application; This application is a one-stop-shop for SMA employees working across data sets and provides a snapshot of current relative risk in different types of locations across the center. The ultimate goal is to have a tool that management can use to aid in decisions that are based on data already being collected. Ideally, the tool would highlight areas of increased risk for any given day. SMA will be conducting case studies to further refine the process of identifying higher areas of risk and potentially strategically direct resources where needed more. Our partners who leveraged funds for this project may consider use at other NASA organizations.

Kamili Shaw↗

A Dynamic PCA and Machine Learning Tool for Automated Identification of Solar Wind Disturbances Impacting Earth’s Magnetosphere

Earth’s magnetosphere is continuously impacted by solar wind and interplanetary magnetic field (IMF) disturbances, such as shocks, discontinuities, magnetic clouds and more. Understanding how such disturbances propagate from the Sun and what is their impact on the different magnetospheric domains is key to understanding and forecasting energy transfer from the solar wind to Earth. The large number of overlapping solar wind and magnetospheric missions carrying magnetometers and the recent advances in communications and data storage technologies have enabled an unprecedented quantity of high-fidelity magnetic field data captured by in-situ spacecraft to be available at the click of a button. However, this massive quantity of available data can prove unwieldy for researchers, limiting the identification of interesting phenomena and disturbances to a relatively small percentage of the total dataset. Several techniques have been previously developed for automated identification of specific types of magnetic anomalies, but these methods are typically mission-specific and can be difficult to generalize. We present initial results for a generic method of automated anomaly detection in magnetic field measurements based on dimensionality reduction and unsupervised clustering via machine learning. The benefit of our technique is its high degree of generalizability and flexibility which make it a most useful data survey tool for a wide range of magnetic field datasets. This method can also be applied simultaneously to other observed time-series properties like plasma density, pressure, and velocity for more accurate event identification. Additionally, the application of this method to data captured by multiple spacecraft enables the simultaneous identification of disturbances and the determination of their propagation characteristics. Initial evaluation of this technique has been performed using data from Magnetospheric MultiScale (MMS) and THEMIS-ARTEMIS missions, providing a testbed scenario for the future Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) platform instruments that will measure solar wind and IMF properties from lunar orbit onboard the Gateway station.

Miguel Martinez-Ledesma↗