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At least 541 records · Page 30

Plant Atrium System for Food Production in NASA's Deep Space Habitat Tests

In preparation for future human exploration missions to space, NASA evaluates habitat concepts to assess integration issues, power requirements, crew operations, technology, and system performance. The concept of a Food Production System utilizes fresh foods, such as vegetables and small fruits, harvested on a continuous basis, to improve the crew's diet and quality of life. The system would need to fit conveniently into the habitat and not interfere with other components or operations. To test this concept, a plant growing "atrium" was designed to surround the lift between the lower and upper modules of the Deep Space Habitat and deployed at NASA Desert Research and Technology Studies (DRATS) test site in 2011 and at NASA Johnson Space Center in 2012. With this approach, no-utilized volume provided an area for vegetable growth. For the 2011 test, mizuna, lettuce, basil, radish and sweetpotato plants were grown in trays using commercially available red I blue LED light fixtures. Seedlings were transplanted into the atrium and cared for by the. crew. Plants were then harvested two weeks later following completion of the test. In 2012, mizuna, lettuce, and radish plants were grown similarly but under flat panel banks of white LEDs. In 2012, the crew went through plant harvesting, including sanitizing tlie leafy greens and radishes, which were then consumed. Each test demonstrated successful production of vegetables within a functional hab module. The round red I blue LEDs for the 2011 test lighting cast a purple light in the hab, and were less uniformly distributed over the plant trays. The white LED panels provided broad spectrum light with more uniform distribution. Post-test questionnaires showed that the crew enjoyed tending and consuming the plants and that the white LED light in 2012 provided welcome extra light for the main HAB AREA.

Massa, Gioia D.↗

KINEROS2-AGWA: Model Use, Calibration, and Validation

KINEROS (KINematic runoff and EROSion) originated in the 1960s as a distributed event-based model that conceptualizes a watershed as a cascade of overland flow model elements that flow into trapezoidal channel model elements. KINEROS was one of the first widely available watershed models that interactively coupled a finite difference approximation of the kinematic overland flow equations to a physically based infiltration model. Development and improvement of KINEROS continued from the 1960s on a variety of projects for a range of purposes, which has resulted in a suite of KINEROS-based modeling tools. This article focuses on KINEROS2 (K2), a spatially distributed, event-based watershed rainfall-runoff and erosion model, and the companion ArcGIS-based Automated Geospatial Watershed Assessment (AGWA) tool. AGWA automates the time-consuming tasks of watershed delineation into distributed model elements and initial parameterization of these elements using commonly available, national GIS data layers. A variety of approaches have been used to calibrate and validate K2 successfully across a relatively broad range of applications (e.g., urbanization, pre- and post-fire, hillslope erosion, erosion from roads, runoff and recharge, and manure transport). The case studies presented in this article (1) compare lumped to stepwise calibration and validation of runoff and sediment at plot, hillslope, and small watershed scales; and (2) demonstrate an uncalibrated application to address relative change in watershed response to wildfire.

Erosion↗

Structural Pain Compensating Flight Control

The problem of control command and maneuver induced structural loads is an important aspect of any control system design. Designers must design the aircraft structure and the control architecture to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to build the structure with high margins, restrict control surface commands to known good combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage.

advanced autonomy↗

External Influences on Modeled and Observed Cloud Trends

Understanding the cloud response to external forcing is a major challenge for climate science. This crucial goal is complicated by intermodel differences in simulating present and future cloud cover and by observational uncertainty. This is the first formal detection and attribution study of cloud changes over the satellite era. Presented herein are CMIP5 (Coupled Model Intercomparison Project - Phase 5) model-derived fingerprints of externally forced changes to three cloud properties: the latitudes at which the zonally averaged total cloud fraction (CLT) is maximized or minimized, the zonal average CLT at these latitudes, and the height of high clouds at these latitudes. By considering simultaneous changes in all three properties, the authors define a coherent multivariate fingerprint of cloud response to external forcing and use models from phase 5 of CMIP (CMIP5) to calculate the average time to detect these changes. It is found that given perfect satellite cloud observations beginning in 1983, the models indicate that a detectable multivariate signal should have already emerged. A search is then made for signals of external forcing in two observational datasets: ISCCP (International Satellite Cloud Climatology Project) and PATMOS-x (Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres - Extended). The datasets are both found to show a poleward migration of the zonal CLT pattern that is incompatible with forced CMIP5 models. Nevertheless, a detectable multivariate signal is predicted by models over the PATMOS-x time period and is indeed present in the dataset. Despite persistent observational uncertainties, these results present a strong case for continued efforts to improve these existing satellite observations, in addition to planning for new missions.

clouds (meteorology)↗

Managing a Safe and Successful Multi-User Spaceport

Encouraged by the creation of the Office of Commercial Space Transportation within the U.S. Federal Aviation Administration (FAA) in 1984 and the Commercial Space Act of 1998, the National Aeronautics and Space Administration (NASA) now relies on an extensive network of support from commercial companies and organizations. At NASA's Kennedy Space Center (KSC), this collaboration opens competitive opportunities for launch providers, including repurposing underutilized Shuttle Program resources, constructing new facilities, and utilizing center services and laboratories. The resulting multi-user spaceport fosters diverse activity, though it engenders risk from hazards associated with various spaceflight processing activities. The KSC Safety & Mission Assurance (S&MA) Directorate, in coordination with the center's Spaceport Integration and Center Planning & Development organizations, has developed a novel approach to protect NASA's workforce, critical assets, and the public from hazardous, space-related activity associated with KSC's multi-user spaceport. For NASA KSC S&MA, the transformation to a multi-user spaceport required implementing methods to foster safe and successful commercial activity while resolving challenges involving: Retirement of the Space Shuttle program; Co-location of multiple NASA programs; Relationships between the NASA programs; Complex relationships between NASA programs and commercial partner operations in exclusive-use facilities; Complex relationships between NASA programs and commercial partner operations in shared-use facilities. NASA KSC S&MA challenges were met with long-term planning and solutions involving cooperation with the Spaceport Integration and Services Directorate. This directorate is responsible for managing active commercial partnerships with customer advocacy and services management, providing a dedicated and consistent level of support to a wide array of commercial operations. This paper explores these solutions, their relevance to the current commercial space industry, and the challenges that continue to drive improvement with a focus on areas of safety management and risk assessment that have been crucial in KSC's evolution into a multi-user spaceport. These solutions may be useful to government entities and private companies looking to partner with the commercial space industry.

Range↗

Viscoplastic Characterization of Ti-6-4: Experiments

As part of a continued effort to improve the understanding of material time-dependent response, a series of mechanical tests have been conducted on the titanium alloy, Ti-6Al-4V. Tensile, creep, and stress relaxation tests were performed over a wide range of temperatures and strain rates to engage various amounts of time-dependent behavior. Additional tests were conducted that involved loading steps, overloads, dwell periods, and block loading segments to characterize the interaction between plasticity and time-dependent behavior. These data will be used to characterize a recently developed, viscoelastoplastic constitutive model with a goal toward better estimates of aerospace component behavior, resulting in improved safety.

mechanical properties↗

A Comparison of the SOCIT and DebriSat Experiments

This paper explores the differences between, and shares the lessons learned from, two hypervelocity impact experiments critical to the update of orbital debris environment models. The procedures and processes of the fourth Satellite Orbital Debris Characterization Impact Test (SOCIT) were analyzed and related to the ongoing DebriSat experiment. SOCIT was the first hypervelocity impact test designed specifically for satellites in Low Earth Orbit (LEO). It targeted a 1960's U.S. Navy satellite, from which data was obtained to update pre-existing NASA and DOD breakup models. DebriSat is a comprehensive update to these satellite breakup models- necessary since the material composition and design of satellites have evolved from the time of SOCIT. Specifically, DebriSat utilized carbon fiber, a composite not commonly used in satellites during the construction of the US Navy Transit satellite used in SOCIT. Although DebriSat is an ongoing activity, multiple points of difference are drawn between the two projects. Significantly, the hypervelocity tests were conducted with two distinct satellite models and test configurations, including projectile and chamber layout. While both hypervelocity tests utilized soft catch systems to minimize fragment damage to its post-impact shape, SOCIT only covered 65% of the projected area surrounding the satellite, whereas, DebriSat was completely surrounded cross-range and downrange by the foam panels to more completely collect fragments. Furthermore, utilizing lessons learned from SOCIT, DebriSat's post-impact processing varies in methodology (i.e., fragment collection, measurement, and characterization). For example, fragment sizes were manually determined during the SOCIT experiment, while DebriSat utilizes automated imaging systems for measuring fragments, maximizing repeatability while minimizing the potential for human error. In addition to exploring these variations in methodologies and processes, this paper also presents the challenges DebriSat has encountered thus far and how they were addressed. Accomplishing DebriSat's goal of collecting 90% of the debris, which constitutes well over 100,000 fragments, required addressing many challenges stemming from the very large number of fragments. One of these challenges arose in identifying the foam-embedded fragments. DebriSat addressed this by X-raying all of the panels once the loose debris were removed, and applying a detection algorithm developed in-house to automate the embedded fragment identification process. It is easy to see how the amount of data being compiled would be outstanding. Creating an efficient way to catalog each fragment, as well as archiving the data for reproducibility also posed a great challenge for DebriSat. Barcodes to label each fragment were introduced with the foresight that once the characterization process began, the datasheet for each fragment would have to be accessed again quickly and efficiently. The DebriSat experiment has benefited significantly by leveraging lessons learned from the SOCIT experiment along with the technological advancements that have occurred during the time between the experiments. The two experiments represent two ages of satellite technology and, together, demonstrate the continuous efforts to improve the experimental techniques for fragmentation debris characterization.

Ausay, Erick↗

Lessons Learned While Exploring Cloud-Native Architectures for NASA EOSDIS Applications and Systems

NASA's Earth Observing System (EOS) is a coordinated series of satellites for long term global observations. NASA's Earth Observing System Data and Information System (EOSDIS) is a multi-petabyte-scale archive of environmental data that supports global climate change research by providing end-to-end services from EOS instrument data collection to science data processing to full access to EOS and other earth science data. On a daily basis, the EOSDIS ingests, processes, archives and distributes over 3 terabytes of data from NASA's Earth Science missions representing over 6000 data products ranging from various types of science disciplines. EOSDIS has continually evolved to improve the discoverability, accessibility, and usability of high-impact NASA data spanning the multi-petabyte-scale archive of Earth science data products. Reviewed and approved by Chris Lynnes.

Cumulus↗

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression, Experiment Development

The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads. The subject of this paper is the design of the optimal control architecture, and provides the reader with some techniques for tailoring the architecture, along with detailed simulation results.

controls↗

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression, Flight-Test Performance

The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads to specified values. This technique has been implemented and flown on the National Aeronautics and Space Administration Full-scale Advanced Systems Testbed aircraft. The flight tests illustrate that the approach achieves the desired performance and show promising potential benefits. The flights also uncovered some important issues that will need to be addressed for production application.

cFOSS↗

Recent Developments in X-Ray Diagnostics for Cryogenic and Optically Dense Coaxial Rocket Sprays

The mixing and atomization of propellants is often characterized by optically dense flow fields and complex breakup dynamics. In the development of propulsion systems, the complexity of relevant physics and the range of spatio-temporal scales often makes computational simulation impractical for full scale injector elements; consequently, continued research into improved systems for experimental flow diagnostics is ongoing. One area of non-invasive flow diagnostics which has seen widespread growth is using synchrotron based x-ray diagostics. Over the past 3 years, a series of water and cryogenic based experiments were performed at the Advanced Photon Source, Argonne National Lab, on a NASA in-house designed swirl co-axial rocket injector, designed for operation using liquid oxygen and liquid methane in support of Project Morpheus. A range of techniques, such as x-ray fluorescence and time-averaged radiography were performed providing qualitative and quantitative mass and phase distributions, and were complemented by investigations using time-resolved radiography and white beam imaging, which provided information on breakup and mixing dynamics. Results of these investigations are presented, and conclusions regarding the viability of x-ray based diagnostics are discussed.

Radke, Christopher D.↗

Finite Element Modeling and Analysis of Mars Entry Aeroshell Baseline Concept

The structure that is developed and analyzed in this project must be able to survive all the various load conditions that it will encounter along its course to Mars with the minimal amount of weight and material. At this stage, the goal is to study the capability of the structure using a finite element model (FEM). This FEM is created using a python script, and is numerically solved in Nastran. The purpose of the model is to achieve an optimization of mass given specific constraints on launch and entry. The generation and analysis of the baseline Rigid Mid-Range Lift to Drag Ratio Aeroshell model is a continuation and an improvement on previous work done for the FEM. The model is generated using Python programming with the axisymmetric placement of nodes for beam and shell elements. The shells are assigned a honeycomb sandwich material with an aluminum honeycomb core and composite face sheets, and the beams are assigned the same material as the shell face sheets. There are two load cases assigned to the model: Earth launch and Mars entry. The Earth launch case consists of pressure, gravity, and vibration loads, and the Mars entry case consists of just pressure and gravity loads. The Earth launch case was determined to be the driving case, though the analyses are performed for both cases to ensure the constraints are satisfied. The types of analysis performed with the model are design optimization, statics, buckling, normal modes, and frequency response, the last of which is only for the Earth launch load case. The final results indicated that all of the requirements are satisfied except the thermal limits, which could not yet be tested, and the normal modes for the Mars entry. However, the frequency limits during Mars entry are expected to be much higher than the lower frequency limits set for the analysis. In addition, there are still improvements that can be made in order to reduce the weight while still meeting all requirements.

Ahmed, Samee W.↗

Drawbar Pull (DP) Procedures for Off-Road Vehicle Testing

As NASA strives to explore the surface of the Moon and Mars, there is a continued need for improved tire and vehicle development. When tires or vehicles are being designed for off-road conditions where significant thrust generation is required, such as climbing out of craters on the Moon, it is important to use a standard test method for evaluating their tractive performance. The drawbar pull (DP) test is a way of measuring the net thrust generated by tires or a vehicle with respect to performance metrics such as travel reduction, sinkage, or power efficiency. DP testing may be done using a single tire on a traction rig, or with a set of tires on a vehicle; this report focuses on vehicle DP tests. Though vehicle DP tests have been used for decades, there are no standard procedures that apply to exploration vehicles. This report summarizes previous methods employed, shows the sensitivity of certain test parameters, and provides a body of knowledge for developing standard testing procedures. The focus of this work is on lunar applications, but these test methods can be applied to terrestrial and planetary conditions as well. Section 1.0 of this report discusses the utility of DP testing for off-road vehicle evaluation and the metrics used. Section 2.0 focuses on test-terrain preparation, using the example case of lunar terrain. There is a review of lunar terrain analogs implemented in the past and a discussion on the lunar terrain conditions created at the NASA Glenn Research Center, including methods of evaluating the terrain strength variation and consistency from test to test. Section 3.0 provides details of the vehicle test procedures. These consist of a review of past methods, a comprehensive study on the sensitivity of test parameters, and a summary of the procedures used for DP testing at Glenn.

wheel↗

Characteristics of Total Column CO2 Retrievals from the OCO Missions: Biases, Information Content and Implications for Flux Inversions

The Orbiting Carbon Observatory-2 and Orbiting Carbon Observatory-3, launched in 2015 and 2019, respectively, are intended to collect and deliver high-resolution observations of CO2 with unprecedented space and time coverage. Observations of CO2 from these remote-sensing missions (also known as XCO2, or column-based average, dry air mole fraction of CO2) are then used by the global carbon cycle community to answer a wide range of science questions, from the distribution and quantification of global and regional CO2 source-sink patterns to quantification of anthropogenic sources at urban scales. Even though we have had the OCO-2 mission flying for a few years now, the retrieval algorithms are continuously evolving and improving to deliver XCO2 retrievals with very high precision and high accuracy (or low biases). In this presentation, we will discuss a simple yet effective quantitative framework that has been developed by the OCO-2 flux team to evaluate the information content of these XCO2 retrievals as soon as they are released, i.e., with lower latency than full-scale flux inversions. This framework serves as a precursor to advanced inverse modeling frameworks and is intended to provide an early but accurate assessment of the signal present in the satellite retrievals, the robustness of that signal, and the ability of these retrievals to resolve patterns in CO2 surface fluxes that cannot be resolved by our current network of surface sites. Specific results will tackle a tiered set of questions that are being addressed using this framework: (a) what are the distribution of retrievals in the different modes of operation and how do they vary in space and time? (b) what is the information that is being given to the inverse modeling frameworks from the space-based data, information above and beyond what is provided by the in-situ data? and (c) how do these factors influence our choices for doing flux inversions with the satellite retrievals? While the primary focus of the results will be on application of this technique to mature OCO-2 retrievals, we will show early results for a couple of months of OCO-3 retrievals. For the time-period that the retrievals from the two missions overlap, we will highlight how this framework allows us to effortlessly put the information from OCO-3 and OCO-2 on an equal footing, thus enabling easy comparison between the two pioneering missions.

Chatterjee, Abhishek↗

Keeping Up With the Time(s): Advancing NASA’s Worldview to Facilitate Quick Access to Global Near Real-Time Imagery

Striving to keep up with the constantly changing environment, whether physical or computing, NASA Worldview’s interactive web mapping application continues to make improvements to ensure that avenues to near-real time imagery are quick, easy and accessible. This poster will explore recent additions to NASA Worldview and the Global Imagery Browse Services (GIBS) of near real-time imagery and imagery visualizations - from geostationary to flood mapping visualizations; improvements to access to imagery - from granule swath visualizations to vector interactions with fires and other types of vectors; and improvements to imagery discovery - from enhancements to the timeline to providing more ways to locate relevant imagery in the layer picker.

Min Minnie Wong↗

On-demand Command and Control of ASTERIA with Cloud-based Ground Station Services

ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a 6-unit CubeSat technology demonstration mission that deployed from the International Space Station on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations to mature technology both in space and on the ground. One of the technologies was a completely cloud-based ground system leveraging Amazon Web Services (AWS) Ground Station service.Announced in December 2018 and launched in May 2019, AWS Ground Station is a fully managed ground station service that aims to reduce the overhead associated with developing and maintaining ground system infrastructure throughout the mission lifecycle. AWS Ground Station makes available the suite of features required for any ground system in support of low-Earth orbit (LEO) and medium-Earth Orbit (MEO) satellite operations on-demand and without setting up or maintaining long-term contracts. Charges are incurred on a per-minute basis for antenna usage during scheduled tracks. Support is available for S-band uplink and downlink, along with X-band narrowband and wideband downlink. Missions that use the service may reserve tracks with any licensed AWS Ground Station antennas located across each service region and have direct access to any AWS services in support of mission operations.The cloud-based architecture built around the AWS Ground Station service greatly enhanced ASTERIA mission operations by enabling end-to-end pass automation, on-demand contact scheduling and contingency planning, along with more efficient data downlink through station availability and station-to-station handovers. It incorporated open-source software, particularly NASA's AMMOS Instrument Toolkit (AIT) and Open Mission Control Technologies (OpenMCT), along with the AWS application programming interfaces (API) to the Ground Station, Elastic Compute Cloud (EC2) and Simple Storage Service (S3) services. After showcasing operability in August 2019, the team continued using and improving this novel ground system architecture until the end of mission in December 2019. This paper describes the cloud-based ground system, how it was designed, tested, and evaluated with an in-orbit spacecraft, the operational capabilities that it enabled, along with lessons learned and recommendations for future missions.

Fesq, Lorraine↗

A Generalized Approach to Aircraft Trajectory Prediction via Supervised Deep Learning

As research advances diverse forms and missions of aircraft, the National Airspace System (NAS) will become increasingly crowded, limiting current communications resources to accommodate aviation operations. Ongoing research proposes a paradigm of airspace communications, such that resources are autonomously and dynamically allocated via intelligent agents; this allocation requires accurate representations of the NAS, including the predicted positions of aircraft. State-of-the-art research emphasizes the importance of a hybrid-recurrent framework for trajectory prediction and compares the impact of commonly considered weather data on prediction accuracy. However, current research has been limited in its scope of efforts, frequently utilizing a unique flight route, architecture, set of weather data, and date range. This article considers the challenges of generalizing hybrid-recurrent predictive models for flight trajectories. Results illustrate an increase in error variance when identical models are trained over a generalized set of flights; this may be mitigated with careful tuning of hyperparameters, both in the network structure and optimization algorithms. Even so, an irreducible vertical error was identified, resulting from the complex takeoff and landing procedures which can not be correlated to functions of weather or additional assumptions of aircraft behavior. Finally, the use of a test route indicates that generalized models still do not possess sufficient knowledge for general aircraft predictions, with mean error increases ranging from 70-500%. These results illustrate the need for continued efforts on improving model versatility, as well as potential limitations for spectrum allocation near airports and other centers.

Nathan Schimpf↗

On-demand Command and Control of ASTERIA with Cloud-based Ground Station Services

ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a 6-unit CubeSat technology demonstration mission that deployed from the International Space Station on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations to mature technology both in space and on the ground. One of the technologies was a completely cloud-based ground system leveraging Amazon Web Services (AWS) Ground Station service. Announced in December 2018 and launched in May 2019, AWS Ground Station is a fully managed ground station service that aims to reduce the overhead associated with developing and maintaining ground system infrastructure throughout the mission lifecycle. AWS Ground Station makes available the suite of features required for any ground system in support of low-Earth orbit (LEO) and medium-Earth Orbit (MEO) satellite operations on-demand and without setting up or maintaining long-term contracts. Charges are incurred on a per-minute basis for antenna usage during scheduled tracks. Support is available for S-band uplink and downlink, along with X-band narrowband and wideband downlink. Missions that use the service may reserve tracks with any licensed AWS Ground Station antennas located across each service region and have direct access to any AWS services in support of mission operations. The cloud-based architecture built around the AWS Ground Station service greatly enhanced ASTERIA mission operations by enabling end-to-end pass automation, on-demand contact scheduling and contingency planning, along with more efficient data downlink through station availability and station-tostation handovers. It incorporated open-source software, particularly NASA's AMMOS Instrument Toolkit (AIT) and Open Mission Control Technologies (OpenMCT), along with the AWS application programming interfaces (API) to the Ground Station, Elastic Compute Cloud (EC2) and Simple Storage Service (S3) services. After showcasing operability in August 2019, the team continued using and improving this novel ground system architecture until the end of mission in December 2019. This paper describes the cloud-based ground system, how it was designed, tested, and evaluated with an inorbit spacecraft, the operational capabilities that it enabled, along with lessons learned and recommendations for future missions.

Fesq, Lorraine↗